Big Data Analytics for Cyber-Physical System in Smart City

In the 20th century, the United Kingdom first implemented waste sorting and recycling, placing sorting barrels on the streets and recycling available resources. This method has also become popular worldwide. With the proposal of “smart city”, people have higher and higher requirements on quality of life, and the intelligentization of sorting buckets has become an inevitable trend. In order to respond to the call for garbage classification, this article has designed a set of intelligent garbage classification system based on STM32F103 Single-chip microcomputer, image processing technology and sensor technology. This article gives a more detailed and systematic description of the software framework and hardware design of the entire project. The design mainly uses the SSD algorithm and the Open MV module to identify and classify the types of garbage. The system controls the rotation of the steering gear baffle and the barrel in the garbage bin through the STM32F103 single-chip microcomputer, thereby performing accurate garbage classification. The intelligent trash can designed in this paper can realize the intelligent identification of garbage types and automatically complete the classification processing of garbage. In the future of the popularization of artificial intelligence, the design has certain innovative value, practical value and scientific research value.

The railway building is easily deformed during the long-time operation. In order to ensure the safety of the railway building, it is necessary to monitor the deformation of the railway building. A deformation monitoring method of railway buildings is proposed based on 3D laser scanning technology.

In order to improve the real-time transmission ability of motion video data, it is necessary to compress video data. A real-time compression method for motion video data based on wavelet analysis and vector quantization is proposed. The two-dimensional wavelet transform is used to decompose the motion video and transform the time and frequency domain, and the quantization error is used to compensate for the video data. According to the method, the motion video data under the Internet of things are processed by LBG vector quantization, and the method of error compensation coding is used to smooth the noise of the motion video data under the Internet of things. The motion video of the N codebook is coded and combined with the multi-layer wavelet scale decomposition method, the real-time compression of the motion video data under the Internet of things is realized. Simulation results show that the proposed method can achieve better real-time compression and transmission of motion video data, and lower output error rate.

To improve the optimal access and transmission capacity of stored data in cloud storage environment, dynamic task load balancing scheduling is needed. A dynamic task load balancing scheduling method based on adaptive Potter spaced equilibrium control is proposed. The dynamic task transmission channel model under the cloud storage is constructed. The decision multimode blind equalization method is adopted to estimate the impulse response of the dynamic task transmission channel, and the adaptive path forwarding control method is combined. The multipath suppression of the dynamic task information transmission, the phase shift deviation is removed by the phase weighting method, the Doppler shift characteristic of dynamic task transmission under the cloud storage environment is calculated, and the dynamic task load balancing scheduling is implemented by the Potter spacer equilibrium method. The task load balancing scheduling has excellent adaptability and strong resistance to interference, which can reduce the bit error rate of dynamic task transmission.

After more than a decade of rapid growth in the industrial economy, the energy and environmental systems are increasingly hindering the long-term stable development of the economic system, which forces local governments to optimize policy design and promote more coordinated development of the economy-energy-environment system. Based on the theory of system dynamics, this paper constructs the system dynamics model of shandong province’s economy-energy-environment system, and discusses the optimal path for the coordinated development of shandong province’s 3E system by means of Vensim software simulation.

With the rapid development of science and technology, the new generation of aerial photography represented by UAV has been widely used in all walks of life. As an important part of expressway, slope maintenance inspection is always the key and difficult point of road inspection. UAV aerial survey technology has the obvious advantage of high geometric precision and high resolution, and its intervention solves the difficult problems faced by traditional highway survey. In this study, UAV is used for slope maintenance inspection, and the characteristics of UAV, the environment of expressway slope and the problems existing in inspection are analyzed. Based on the current working mode of manual image analysis, the quality of the inspection task is controlled from two aspects of shooting and flight, so as to meet the requirements of the inspectors to interpret the slope state. The research also considers the characteristics of UAV and different types of slope, and selects the algorithm suitable for the slope secondary inspection path planning. The research results of this paper confirm that UAV can effectively solve the problems in image resolution, geometric accuracy of ground objects and flight cost of aerial photogrammetry of large aircraft, and greatly improve the survey efficiency.

With the rapid economic development, the degree of automation of processing machinery is getting higher and higher. People gradually began to attach importance to the level of mechanization and automation of forestry operations to improve the efficiency of forestry operations. However, my country’s forest terrain conditions and operating environment are more complex. The originally developed wheeled or crawler walking robots have many drawbacks. Although crawler walking machines are excellent in terrain adaptability, they have poor obstacle crossing capabilities. Therefore, there is an urgent need to design a new type of walking robot that can adapt to the complex ground environment in the forest to meet market demand. This article combines inertial positioning and visual positioning to reduce the impact of carrier jitter on positioning. Third, the three-dimensional grid map is constructed by using the octree model, which effectively reduces the consumption of storage resources. Finally, a path planning problem based on an improved A* algorithm is studied, including heuristic function design, dynamic weighted evaluation function design, and path smoothing. In this paper, the overall design of the mobile robot is carried out. The principle analysis of the cam damping mechanism is also carried out. The ANSYS finite element analysis and nonlinear calculation of the cam during the movement are carried out. The dangerous area and the deformation displacement of the cam mechanism are obtained. Pedestrian machinery has laid a theoretical foundation for stable walking in the forest. Research shows that the algorithm of this paper increases the length of the path and the number of turns when the scale of the forest map is large, but the search time of the algorithm increases by only 5–11 ms compared with the A* algorithm. The algorithm can take into account both efficiency and path length.

Mineral resources are an important part of natural resources, and a good order of mining activities is an important prerequisite to ensure the safety of mining production, maintain the fairness of mining market, and steadily promote the construction of ecological civilization. Optical remote sensing image is one of the main carriers to reflect the mining activities of open-pit mining area. Deep learning technology is widely used in semantic segmentation of open-pit mining area. However, due to the complex surface environment of mining area, its segmentation accuracy needs to be further improved. In this paper, taking gaofen-2 optical remote sensing image as the data source, the remote sensing image sample set of open-pit mining area is constructed by manual annotation. Based on the sample set, the shallow texture features of the image are constructed, and part of the sample sets are put into the deep neural network for training. Combining the shallow texture features with the deep features of the deep neural network, a semantic segmentation model for pixel level open-pit mining area extraction is proposed by using U-net analysis model, and compared with the other two methods. The experimental results show that the overall accuracy of this method is 89.3%, and the average accuracy is 88.78%, which are better than the other two methods.

As the energy crisis worsens, the new energy industry is developing rapidly, and the electric vehicles are also becoming popular. At the same time, the development of renewable energy raises new challenges for the operation and regulation of the power grid. Charging pile energy storage system can improve the relationship between power supply and demand. Applying the characteristics of energy storage technology to the charging piles of electric vehicles and optimizing them in conjunction with the power grid can achieve the effect of peak-shaving and valley-filling, which can effectively cut costs. These could be compacted as demand response management service participating in grid regulation, binging economic benefits, which in turn promotes the energy transition.

This paper introduced a mechanism and bridge linking the blockchain world to the real world, which named as Oracle. It aims to solve the problem that blockchain and the real world are fragmented. Furthermore, it has listed several fields of application in finance of the Oracle.

The digital resources of academic libraries have been greatly enriched, how to improve the co-construction and sharing (CCS) of digital resources of academic libraries has become a major issue we face. Based on the super-network perspective, this paper studies the resource CCS mechanism of university libraries, in order to better achieve the purpose of constructing university library (UL) information resources CCS. Construction of information resources in various universities in our province, this paper found that 76.74% of the respondents believe that the construction of information resources in university libraries lacks a unified planning and organization, and digital resources are redundantly constructed and inefficient waste; 89.24% think that there is a lack of a unified and authoritative management organization. And put forward corresponding countermeasures and suggestions to improve the level of resource CCS of university libraries and ensure the sustainable development of resource CCS of university libraries.

With the progress of science and technology, the arrival of the era of “big data” brings unprecedented opportunities for the yoga industry; The information and technical support based on big data will help the yoga industry to dig and create more values in China, promote the clustered development of The yoga industry in China, and promote the scientific and systematic development of the yoga industry in China. At the same time, the arrival of the era of big data has also brought a series of challenges to the development of Yoga industry in China. Solutions to these challenges are proposed to accelerate the collaborative innovation of yoga industry and promote the healthy and sustainable development of Yoga industry in China.

With the development of electronic computers and related technologies, a brand new technology is emerging in the world, this is the computer-aided design (CAD) technology. Computer-aided design (CAD) refers to the process that designers use computers and graphics equipment to carry out design work. Computer-aided design is the core technology that transforms the traditional design model. The purpose of this article is to study the inheritance of traditional patterns in the context of computer-aided design. Taking the brocade decoration as the research object, based on the small point of decoration, research and analysis of its artistic form and cultural attribution through the research methods of folk art, hoping to use this to peep into the culture behind traditional folk arts and crafts. The experimental results show that the development of the design system based on the formation principle and structure of the traditional decoration is a basic system that helps designers to complete the traditional decoration design intuitively and efficiently, and can effectively realize the research and development of the inheritance of traditional decoration, and the realization of parametric technology. It also lays a solid foundation for the personalized customization service of the traditional decoration in the future.

In the context of traffic congestion and traffic accidents that seriously threaten people’s safety, vehicle networking, through the connection between vehicles, enables vehicles to effectively obtain traffic environment information, which is considered as an effective way to solve traffic safety problems. However, as a complex network, there are some security risks in the Internet of vehicles. This paper focuses on Sybil attack detection algorithm for Internet of vehicles security, aiming to make full use of vehicle perception data, communication data, user data, etc. in the Internet of vehicles to eliminate specific security risks and curb malicious behaviors. To be specific, first of all, a data-driven security architecture for Internet of vehicles is proposed. Secondly, aiming at the possible Sybil attack in ride-hailing applications, Sybil attacks in Internet of vehicles are divided into three levels according to the different capabilities of attackers, and different detection methods are designed and modeled according to their different characteristics. Finally, a solution based on mobile behavior analysis is proposed.

The current development of artificial intelligence has reached an extremely popular stage, and at the same time it is improving and innovating at a rapid development speed. This article discusses the practical application of artificial intelligence technology in electronic communication, hoping to bring certain promotion and guidance to the application of artificial intelligence in my country’s electronic communication. In this paper, through a questionnaire survey of 13 technology companies in our province, to understand the application of artificial intelligence technology in electronic communications, it is concluded that 75.70% of people believe that in the network intelligent security management, timely detection of existing dangerous and virus data Effective treatment; 80.20% of people believe that artificial intelligence realizes network resource sharing applications in electronic communications; 90.40% of people believe that artificial intelligence is integrated into electronic communication to achieve data collection and integration. The research in this article helps to improve the practical application of artificial intelligence in electronic communication.

With the national attention and development of information technology, computer information technology products have been gradually integrated into and applied to our lives. With the rapid development of medical technology, computer information technology and medical imaging equipment, medical image three-dimensional reconstruction technology is widely used in clinical diagnosis, surgical simulation, anatomy, B-ultrasound and other medical fields. Therefore, three-dimensional reconstruction technology of medical image has important application value and significance in medicine. Based on this, the purpose of this study is to study the application technology of computer-based three-dimensional reconstruction of medical images. In this paper, interpolation method and sift algorithm are used to study the experiment, and the application of medical image 3D reconstruction technology is studied. The experimental results show that the image interpolation method and sift algorithm can improve the brightness continuity and visual effect of the sequence images, so the information in the images can be obtained better when observing the images in the experiment. The computer three-dimensional reconstruction technology has a very important role in the application of auxiliary medical images.

In this paper, the traditional mobile network architecture and softswitch architecture are compared. This paper points out the advantages of the IP based softswitch network architecture and the problems to be solved. Secondly, it introduces three models of IP QoS. Finally, the QoS characteristics supported by media gateway are introduced.

Module division is the key and foundation of modular design. Module division should be based on the basic principle of “strong aggregation within modules and weak coupling between modules”. In product development and design, reasonable and effective module division is of great significance for designers to seek more new functions and new solutions. The rationality of module division largely affects product performance and cost. This article explains the significance of module division in mechanical products, and classifies and summarizes the existing division methods and technologies. According to the characteristics of the product, the method of module division is reviewed from different perspectives such as the product’s function and structure, green design attributes, and different stages of the life cycle. Through the research and analysis of these methods, some prospects are finally made.

Information technology is gradually developing and progressing with the entire society. At the same time, it is also an indispensable part of the education industry. With the advancement of science and technology, multimedia teaching has become common in modern education. While enhancing students’ interest in learning, it creates a broader teaching space. Among them, 3D animation technology is also a cutting-edge technology in the development of information technology. The introduction of animation technology into the classroom plays a very important auxiliary role in improving the quality of teaching, and also greatly improves students’ interest in learning and learning efficiency. The application of 3D animation technology in the current MOOC production can greatly improve the current teaching ability. 3D animation technology can break the limitations of time and space, and make the MOOC production classroom more realistic. In this regard, the purpose of this article is to study the application of 3D animation technology in MOOC production. This article uses a questionnaire survey method to design an experiment with 200 students, and applies the case design to educational practice. The experimental conclusions show that 3D animation technology is very important for MOOC production. In the process of MOOC production, 3D animation technology can be beneficially used to improve teaching methods and classroom efficiency.

It is an important research project that exploring battle example teaching is how to serve the fight and drill preferably. The simulation territory has introduced artificial intelligence, virtual reality and cloud computing at present, the simulation based on these techniques will bring far-reaching influence for battle example teaching. The intelligent simulation technology will remodel analysis factors of battle example, reconstitute research idea of battle example, overturn the research of battle example. The battle example teaching methods based on intelligence confrontation, scene recurrence and fight chess manoeuvre will show itself, and it will help researchers capture victory inspiration from battle example, feel command art in virtual confrontation and excavate defeating mechanism from retrospect research.

Under the background of the continuous promotion of education informatization and the coming out of the 14th five year plan, the construction focus of university informatization is gradually shifting from building digital campus to building smart campus. The construction of smart campus has become one of the hot topics in campus construction. Therefore, this paper analyzes the connotation of smart campus and the basic structure of smart campus from the perspective of hierarchy concept, then discusses the specific construction of smart campus at different levels. Based on that, some practice of a university campus is discussed and a set of experiences are summed up for the construction of smart campus. Smart campus will be the inevitable trend of future.

The purpose of this paper is to study the construction and implementation of an information platform for classroom teaching quality(TQ) evaluation and monitoring based on artificial intelligence(AI) technology. In this paper, the classroom teaching of teachers is taken as the object of TQ evaluation and control for in-depth and detailed research, to find a more reasonable TQ evaluation method, so as to provide accurate feedback information for the improvement of TQ. In this paper, 18 teachers were taken as test objects, and a team of 5 experts made an objective evaluation of each teacher's TQ index at all levels, and the evaluation score was taken as the original data. Through the simulation experiment of the data source, the error of training the TQ evaluation index by using BP neural network is not more than 0.002.

With the expansion of the scale of higher education in my country, the employment situation of college students is becoming increasingly severe. The basic way to improve the employment situation and the quality of employment is to further improve the quality of personnel training. In the context of the era of big data, my country’s college teaching has also made some reforms in response to the current era of big data. The purpose of this article is to study the impact of professional talent training in colleges and universities on student employment and school quality in the era of big data. Therefore, this article takes the university undergraduate talent training model as the comparative research object, and uses literature research, questionnaire method, comparative analysis, mathematical statistics and other methods to grasp the current situation, similarities and differences of the undergraduate talent training model in ordinary universities under the background of big data. The advantages and disadvantages of the current university teaching model under the background of big data, taking the current situation of university professional education reform as the starting point, through the inevitable discussion that the application of modern education technology is inevitable to deepen the university professional education reform, it is proposed to apply modern education technology to deepen the university Several countermeasures and suggestions for professional education reform. Experimental research results show that, in the context of the rapid development of this big data era, the popularization and improvement of college education also needs to open up new ideas to innovate, and it also requires every teacher and student to actively think and challenge.

Under the rapid development of the current era of big data, as an extremely important job, the ideological work of college students has always been the top priority of everyone’s attention, and the development of ideological work related to college students has caused the party Highly valued. In this paper, based on the big data era in Beijing, an in-depth research and discussion on the research of college students’ ideological safety early warning system is the subject. This article first sorts out related concepts such as cyber ideology, cyber ideological security, cyber security early warning system, etc. based on college students in the big data era. Maintain the understanding of the important role played by college students in the process of network security ideology security. Secondly, by investigating the current situation of the security early-warning system of my country’s college students’ network security ideology, find out the problems faced, analyze the reasons, and optimize the security early-warning system of college students’ network security ideology. Through the research on the security early warning system of college students’ network security ideology, we can better maintain the ideological security of our college students. The experimental research results show that. This research is for the current era of big data. It is of great significance to maintain the ideological security of college students and to develop the ideological work of network security in universities. Optimizing the security early warning system of college students’ network security ideology is a long-term process, which requires continuous innovation in practice.

With the development of the times and the progress of society, the development and change of the demand response potential of China’s residents are facing unprecedented challenges. In today’s big data era, the combination of big data technology and the potential analysis of demand response of China’s residential users has become the inevitable demand of the development of the times. Therefore, in order to better make the demand potential of Chinese residents conform to the development trend of the times, this paper deeply studies the business development trend and status quo of the Internet in the demand analysis and response of residents in recent years through the technology of Internet and big data, and analyzes the potential of demand analysis and response of residents in recent years, A large number of information resources about the demand analysis and response of residential users in the new Internet era are sorted out, and the business fields of residents’ demand analysis and response are re classified. The evaluation model of influencing factors of user demand response behavior is established, and the Monte Carlo simulation calculation method is used for research. It is found that time and price is the main factors influencing the demand response behavior of typical industries. Through the analysis, the accuracy rate of the big data analysis method proposed in this paper reaches 97.3% in studying the potential of residents’ demand response.

With the increasingly modern development of industrial manufacturing field, industrial robot has become an indispensable part of modern automatic chemical plant. The intelligent control of robot has become the core content of modern industrial robot research, providing technical support for robot stable work and improving work efficiency. The purpose of this study is to explore the effect of design and implementation of intelligent control program for six axis joint robot.

This paper conducts a methodological research on the academic performance of online learners. This paper applies classification models commonly used in data mining algorithms, such as random forests based on decision trees, support vector machines, neural networks, K nearest neighbor algorithms, etc., combined with data mining tools S software and statistical analysis tools, and analyzes the University of Finance and Economics Tools scores of online learners in the class of 2019. It studies the important factors that affect the academic performance of college students' online learners, and uses these factors to predict students' academic performance. Based on the distance calculation method in mathematics, the article separately studied the application of Euclidean distance correlation analysis algorithm and correlation coefficient correlation algorithm in curriculum relevance, and compared several correlation algorithms. Experimental research results show that in the era of big data, learners will accumulate a large amount of structured and unstructured data during online learning. We can explore the influencing factors of online learners' academic performance through data mining technology, and we can also use machine learning to automatically learn from the data to the academic performance prediction model.

With the continuous development of technology of data and the ‘‘IoT plus’’ the deepening of the action plan, the Internet of things, artificial intelligence and other new technology application in the field of sports, sports were collected through intelligent equipment and mobile terminals, data volume geometric growth, unable to realize the connectivity, a lot of sports data presents the fast expansion of data island state. In order to better study the sports intelligence system under the background of Internet of things and artificial intelligence, this paper takes swimming as the research entry point. Firstly, a swimming posture measurement system is proposed for the daily training of swimmers combined with Internet of things and artificial intelligence technology. Then, this paper chose a professional coach with the system, with butterfly, backstroke, breaststroke and freestyle four commonly used strokes experimental verification, and analyses the actual measuring the movement of information processing, the experimental results show that the system could be used for swimming movement process, the stability of the monitoring accuracy as high as 92.12%.

Artificial intelligence (AI) technology develops rapidly. At present, intelligent technology is still being explored in sports, especially swimming, and there exist some problems such as immature system technology and unclear application. Therefore, it is extremely important to find the combination of AI and swimming, and to optimize intelligent systems. This article about the application of AI to swim at the literature study, video analysis, comparative research and mathematical statistics and other research methods, data of AI in swimming, swimming training the perspectives of the implementation of the way, in order to promote it provides the theory basis for the application of AI in swimming, for AI in the sports training of wider application. At the same time, considering that the development of AI in China is at the stage of perceptual intelligence and machines cannot think and act independently, the research believes that it is necessary to further develop and improve the algorithms related to the collected data of AI.

On the basis of two classical hard and soft threshold processing methods, combined with the improved methods mentioned in the literature, a comprehensive threshold processing method is proposed. The threshold function can not only overcome the defects of discontinuity and constant deviation of the traditional threshold, but also adjust the error between the original wavelet coefficient and the thresholding coefficient by adjusting the parameters. Through the comparison of simulation experiments, it is found that the denoising effect of the new threshold function is significantly improved over the traditional threshold denoising effect in terms of visual effect, mean square error, peak signal-to-noise ratio, etc.

As online product reviews (eWOM) become increasingly important in affecting online consumer decisions, it is critical to develop insights into consumer behavior of using eWOM. This paper examines how eWOM characteristics impact consumers’ use of online product reviews for purchase decisions. We develop a theoretical model drawing on the information adoption model and the information systems success model. We conduct a lab experiment to collect data and carry out our PLS-SEM analysis with Smart PLS. We find that eWOM characteristics influence consumer decisions via diagnosticity and ease of use. This research enhances our understandings on how eWOM characteristics influence consumer decisions. In addition, we apply the information adoption model and the information systems success model to the context of eWOM.

Based on Internet of things ‘‘wisdom city’’ based on the development of emerging information technology industry, such as operation system connected cities of all levels with wisdom, to achieve the production and the life convenient, the wisdom of the new urban development pattern, it can not only bring short-term economic growth, can also bring the progress of the society as a whole and economic all-round development. With the expansion of the construction of smart cities, it becomes very important to study whether the development of smart cities plays a driving role in economic growth. The purpose of this paper is to study the role of smart city development in promoting social and economic growth. This paper first expounds the smart city, and then, based on the empirical analysis of Cobb-Douglas production function, establishes an econometric model to promote economic growth by developing smart city, and obtains the output promoting elasticity index of smart city to economic growth by linear regression. The empirical results show that the construction of smart cities can indeed drive economic growth. This paper obtains that the sum of the coefficients of labor force, capital and smart city for the gross national product is greater than 1.

In the present computer system, the data processing aspect, occupies the enormous processing frequency, approximately has the nearly 50% above CPU processing time is USES in the sort data. It can be seen that the data sorting algorithm has a high requirement on its own execution speed, so it is particularly important to implement a fast and good sorting algorithm. In this paper. The traditional merge sort algorithm uses two-way merge sort, which needs the same size of auxiliary space and data to be sorted, so it is necessary to improve it. The traditional merge sort method and an improved in-situ merge algorithm based on hand method are introduced, which is devoted to providing theoretical basis for improving the traditional data sort method.

As the third wave of information industry after the application of computer technology and Internet, Internet of things technology has been applied to many fields. At the same time, with the acceleration of industrialization process, it has brought environmental pollution and other problems restricting economic development, which has attracted people's attention and attention. It is urgent to monitor and protect the environment. The application of technology in environmental monitoring can not only effectively provide real-time monitoring of the environment, but also provide important data basis for environmental supervision and management through information sharing and auxiliary decision-making. Therefore, this paper first summarizes the relevant contents of environmental monitoring and the Internet of things, and analyzes the current application status of the Internet of things technology in environmental monitoring, then adopts fuzzy comprehensive evaluation algorithm in calculating the data obtained from the monitoring system of the Internet of Things, and finally obtain the parameters of the environment.

The path planning technology of environmental robot is an important research content in the field of robot. In this paper, the global path planning based on environmental model is studied. According to the known environmental information, the intelligent algorithm is applied to plan an optimal path. This paper first introduces the path planning method based on the environment model, and summarizes the common modeling methods of the environment model. Then, according to the characteristics of each model, the grid method is adopted for the environment modeling method, and the grid map path search and generation algorithm considering the robot human model is given. The grid space is used to search the route, and the route range is divided into a series of standard grids. The whole grid area is regarded as a complete binary image, and each cell grid represents a pixel. The practice shows that the accuracy and efficiency of this research in robot path planning are better than other algorithms. Through in-depth study, it can provide reference for the reasonable optimization of robot path planning and design.

There are obvious artificial effects in the constructed art design images such as iterative hard thresholding and other traditional algorithms, especially when the sampling rate is low. These artificial effects not only seriously influence the visual effect of constructed art design images, but also influence the performance of subsequent processing. One-dimensional MFDMA algorithm for art design image in this paper takes the construction results of the traditional construction algorithm as input. One-dimensional MFDMA algorithm is used to extract the features under different scales to achieve the multi scale information mining and fusion of the constructed art design image. Most of the artificial effects have been removed by one-dimensional MFDMA algorithm for image recovered. The subjective visual effect of art design image is improved obviously, and the result is closer to the original art design image.

With the rapid development of modern Internet technology and information technology, the new technology of surveying and mapping also incorporates the elements of modern science and technology in geological exploration engineering, which strengthens the scientificity of surveying and mapping, and realizes the application of data mining technology in geological exploration engineering with larger scope and domain. The application of new surveying and mapping technology using data mining improves the accuracy of the geological exploration engineering projects, enhances the quality, efficiency and safety of geological exploration engineering, and plays an important role in the smooth development of geological exploration engineering. This paper expounds the application of data mining technology in geological exploration engineering, and puts forward the GPS positioning method of new surveying and mapping technology. The simulation results show that this method effectively improves the surveying and mapping method and improves the accuracy of surveying and mapping data by data mining in geological exploration engineering.

In practical application scenarios, XML files are analyzed and understood structurally according to the nested element tags, element attributes, element contents, etc. However, users are not clear about the content published based on XML in advance, so it is difficult to obtain the required content quickly and completely. Especially for large-scale XML files, the analysis time and iteration time are longer, and the time lost due to analysis errors is also longer. In this paper, a fast filtering method of invalid information in XML file is studied. Firstly, the method can establish an index for the XML file to be processed, and then query the case with the highest similarity with the index in the knowledge base, and match the case with the index with the highest similarity in the knowledge base. Then, the preprocess of the XML file is selected from the XML preprocessing process library according to the matching results. Finally, the results of the preliminary processing are transmitted to the receiver for further processing. The practical results show that this method can effectively reduce the length of XML file to be processed, and achieve the beneficial effect of rapid processing on the terminal, and greatly improve the efficiency.

In this paper, based on the SCP algorithm, the current market power alert system alert level is evaluated and studied. The article proposes to establish an evaluation index system for the entire market and network market power in accordance with the structure-behavior-performance (SCP) analysis framework in industrial economics, and then uses a fuzzy hierarchical comprehensive evaluation method to evaluate the market, each blocked area, and each major network market power The alert level is evaluated and monitored in real time, and the corresponding supervisory decision-making mechanism is made according to the evaluation results of the SCP alert level, which can effectively improve the efficiency of supervision. Finally, taking the market data of the actual network market as an example of the algorithm, it is verified that the market power alert and regulatory decision-making mechanism based on SCP and comprehensive evaluation proposed in the article can effectively identify the market power level of each link of the SCP in the market and the strategic quotation of the market at all levels. Behavior. The experimental research results show that in the future, it is necessary to further strengthen the research on higher sensitivity indicators and the identification of complex tacit collusion behaviors between network markets, so as to improve this system structure as soon as possible to ensure the effective competition and healthy development of China's network market.

Biochemistry is an important basic subject in the natural sciences. It is the study of life phenomena and the laws of life activities. The conclusions of biochemistry are all based on experiments. Biochemistry helps cultivate and improve students' scientific literacy, and plays an important role in constructing a professional biochemistry knowledge system and improving students' scientific thinking ability. Modern technology provides new research methods for the application of biochemistry in life sciences. High-tech applications under the influence of the artificial intelligence environment can not only save manpower and resources, but also become more intelligent and environmentally friendly, so as to achieve data. Monitoring. The purpose of this article is to study the application of biochemistry in life sciences based on artificial intelligence. This article starts with artificial intelligence, reforms the traditional manual operation, and uses artificial intelligence as the basis to in-depth research on the application of biochemistry in life sciences. Experimental results show that artificial intelligence can greatly advance the work process and reduce the experimental failure rate.

The traditional over-current relay protection method can not be directly applied to the active distribution network with renewable energy generation. In this paper, a non time domain fault detection method based on voltage signal amplitude spectrum and marginal spectrum is proposed. The fault is set in the distribution network. The voltage data obtained from monitoring points are processed and analyzed to obtain test samples to verify the reliability.

In this paper, the Mallat signal analysis of wavelet transform is used to segment the signal, and then Prony algorithm is used to fit the segmentation algorithm. This method has the advantages of clear section distinction, strong anti-interference, fast calculation response and strong robustness. In the verification stage, the anti-interference robustness of the wavelet is tested by adding noise signals with different signal-to-noise ratio, and the ideal segmentation results are obtained by using wavelet analysis. Prony algorithm can be used to analyze and calculate each sub segment according to the segmentation.

Sentence-level aligned bilingual parallel corpus is an indispensable and valuable resource for machine translation, translation knowledge acquisition, and bilingual dictionary compilation. Based on the Korean-Chinese parallel corpus, this paper uses a Korean-Chinese sentence alignment algorithm based on character length to realize automatic Korean-Chinese sentence alignment, and proposes a sentence alignment evaluation method. Firstly, preprocess and segment the Korean-Chinese corpus; Secondly, calculate the mean and variance of the corpus distribution based on the Korean Chinese corpus, and use the probability score to find the maximum likelihood probability of the sentence under the framework of dynamic programming; Finally, proposed a sentence alignment judgment method, with the help of Hanjaja tool to convert Sino-Korean words in Korean sentences into Chinese words to form Korean sentences containing Chinese words (abbreviated as C-K sentences), then calculate the Jaccard coefficient between the C-K sentence and the Chinese sentence, by determining the appropriate threshold to automatically determine the alignment or not. Experiments show that the length-based sentence alignment method has a good effect on automatic alignment of Korean-Chinese sentences, and the accuracy of sentence alignment reaches 88.61%. The proposed sentence alignment judgment method is simple and effective.

In modern manufacturing environment, multi-source heterogeneous data in the process of workshop processing are collected on a large scale, which reflects the information of processing equipment and workpiece quality. In order predict the workpiece quality by making full use of the collected big data, the SC-GA-RBF model is established. The parameters of RBF neural network are optimized by using SC algorithm and GA algorithm. The four quality prediction algorithms are simulated on the simulation platform, and the experiment result shows that SC-GA-RBF model is the best, BP model is the second, SC-RBF model is the third, and RBF model is the worst in term of RMSE, and the RMSE of SC-GA-RBF model is 0.093. The requirements of quality control can be satisfied by the application of the SC-GA-RBF model.

In the current leaf spring production, side bending is an important issue affecting the quality of leaf spring. Once the leaf spring is bent, the strength of the product will be greatly reduced. Moreover, leaf springs will not be assembled and will be directly assessed as “waste products”. It is common that we will straighten the leaf spring with a punch immediately after blanking. But after the data analysis of the whole production process, we found many meaningful data. In the following processes, such as the spring eye, heating, quenching and shot blasting, there is a high probability that side bending will occur again, which greatly affects the product precision and reduces the production efficiency. After analyzing the collected data, it has been found that the application of the infrared sensitive technology in hot straightening machines can greatly improve the efficiency of the straightening machines. Besides, the transformation and upgrading of the whole production process can be promoted by solving the problem of the side bending of the leaf spring as a breakthrough. Therefore, it is of great significance to combine the infrared sensitive technology with hot straightening machines.

The method of experience and analogy are usually been adopted to design traditional radial drilling machines; however, the structure has not been analyzed and calculated. there are more and more demands for large radial drilling machines; therefore, it is of great significance to make parametric modeling. In this paper, the force of the rocker arm is analyzed systematically, the parameter input interface of each supporting member is designed and the corresponding program module is compiled, the paper attempts to mend the weak parts in order to get different structures, generate the model of bearing parts through the parameterized modeling, make the finite element static analysis on supporting members by means of ANSYS respectively. the support dynamic performance evaluation is given through the analysis of calculation results, and the weak parts are found out.

With the advent of the intelligent age, artificial intelligence has become the mainstream technology in the world, and artificial intelligence technology has established a solid research foundation for digital libraries. This paper discusses the significance and form of artificial intelligence technology in the book library application and the future development trend, in order to provide an important reference for the further development of the establishment of digital libraries. This article starts with the basic theory of text classification, expounds the theory of text classification system and the key technologies and main algorithms of classification, and compares and analyzes the theoretical basis, applicable conditions and scope, advantages and disadvantages of various methods. Aiming at the characteristics of digital library text resources and Chinese language, with the help of rough and good ability to deal with ambiguity and uncertainty and the excellent function approximation ability and fast learning ability of RBF neural network, a digital book based on Rough-RBFNN has been established. The library text automatic classification model is optimized and the neural network is optimized. Based on this, the digital library text automatic classification system is designed and implemented. The experimental research results show that artificial intelligence realizes the intelligentization of machinery and equipment. The library should rationally use artificial intelligence technology and combine the readers’ current reading habits to design reading promotion scenarios that can reflect the characteristics of the collection, so that digital reading promotion has a broader development space, to better play the role of leading reading for all.

With the rapid development of computer information technology, virtual reality technology is a new practical technology developed in the 20th century and has been widely used, which greatly promotes the development of VR animation. VR animation scene as a direct presentation of the audience in front of the screen effect, in order to create excellent VR animation works, this paper discusses the application of Photoshop Image Processing Technology in VR animation. This paper first introduces the content of Photoshop Image processing, then introduces the main functions of Photoshop graphics and image technology, and then introduces the practical application of Photoshop graphics and image technology in VR animation scene, and finally summarizes the application of Photoshop graphics and image technology in VR animation processing.

Big data not only promotes the continuous development and innovation of cloud computing, Internet of things and mobile Internet technology, but also provides technical support and carrier for the development of education informatization. It has become an important driving force of Internet technology and education informatization. Under the background of big data era, technology is constantly reshaping the education and teaching ecology, teaching methods and teaching process, the consciousness of educators and the way of knowledge transmission and acceptance, so intelligent education emerges as the times require. Big data helps to accurately track teaching and learning, so that teachers can master the personalized needs and development characteristics of students. This provides a strong support for the realization of individualized teaching and intelligent teaching. Based on the background of big data era, this paper discusses the asynchronous recording and broadcasting online teaching, the synchronous live online teaching, MOOC (Massive Open Online Courses) and SPOC (Small Private Online Courses), in order to provide help for the development of network education.

In the deep sea mining system, the lifting pipe is a special articulated cantilever pipe, which is prone to large deviations and bending deformations. The finite element plane beam element idea is used to discretize the dynamic differential equation of the lifting pipe, and the vibration balance equation of the lifting pipe affected by internal flow is established. Through the computer simulation software ADINA, the model of lifting pipe and internal flow is established, and the computer simulation process is determined. The computer simulation results show that under different working conditions, the maximum stress of the lifting pipe acts on the top of the lifting pipe, and the maximum offset occurs at the bottom of the lifting pipe. When the internal flow is considered in the lifting pipe, the maximum stress at the top of the pipe increases gradually and the maximum lateral displacement at the bottom of the pipe increases gradually with the increase of the internal flow velocity.

Under the background of the era of big data, the tourism curriculum of higher vocational colleges has ushered in new challenges, and corresponding adjustments have been made in the innovation of education and teaching mode, making the tourism education curriculum model of higher vocational colleges more suitable for the era of big data. Based on the background of big data, this article researches innovative methods suitable for tourism education courses in higher vocational colleges. This article thoroughly explores the reasons that restrict the professional development of teachers’ professional competence in tourism education courses from government organizations, higher vocational colleges and teachers themselves, and on this basis, seeks a way to develop the professional competence of teachers in tourism education courses. Improve the professional competence of tourism education teachers in higher vocational colleges, so as to improve the level of tourism education in higher vocational colleges in China, and ensure the healthy and rapid development of tourism and social economy. With the help of this method, this article collects and categorizes relevant information on the constituent factors, interrelationships and influencing factors of the professional competence of tourism education teachers in higher vocational colleges, and puts forward certain assumptions on the definition, composition and influencing factors of the course shipping industry. Test the hypothesis under different conditions and at different times. The experimental research results show that the reform of the closed traditional education curriculum management model and incentive mechanism provides a platform and conditions for tourism education curriculum teachers to actively improve their professional capabilities, thereby improving the quality of tourism management professional training in higher vocational colleges and providing tourism for China Make greater contributions to vocational education.

In recent years, the development and transmission of traditional Chinese medicine (TCM) has attracted great attention. In the information age, computer technology is closely related to the development of various industries. By collecting the relevant research from CNKI, the essay summarized the current situation of application and progress of computer technology in TCM translation, discussed the role it played, analyzed the problems in the construction of Chinese-English bilingual corpus, TCM term standardization and TCM classics translation, and offered suggestions for the combination of computer technology and TCM translation in the future.

Advertisement is one of the ways merchants attract consumers and enhance their influence. In recent years, under the big picture of smart city and smart life, the advertising business has shown a trend of specialization. It has always been a tough problem for advertisers of how to show potential consumers in real time the advertisements in a precise way. This passage reveals an experiment that alters the logistic regression function model and fits the data logs that users produce in order to forecast the possibility that the user clicks the real-time advertisement designed for him/her. The results of the experiment show that compared to traditional advertising, such altering improves the effectiveness of precise advertising, and has the edge of shorter operating time against other models based on deep learning. An aspect to improve is the comparatively lower accuracy of forecast. Such results indicate an alternative for certain small and medium enterprises to lower their advertising costs.

The recommendation system can calculate the similarity between users and items in the system, which is based on different computational methods, analyzing of calculation results, and then calculates the items that may interest the users and recommend those items to users. Collaborative filtering algorithm is a popular algorithm in academia and industry, but it does have certain shortcomings such as cold start and sparse data. In this paper, a hybrid recommendation algorithm is proposed and applied to an employment service system by using job postings from websites obtained by web crawler as the dataset. The experimental result shows that the hybrid recommendation algorithm is able to the accuracy of employment information recommendation to some extent and meet the personalized needs of job-seeking users.

Nowadays, the rapid development of science and technology has been promoting social development. Internet technology are Applied into all trades and industries. Meanwhile, university teaching should follow the trend of information technology development, integrating information technology closely with the curriculum, in order to innovate and reform the teaching models. Numerous teaching Apps have emerged in the context of information-based teaching, which is beginning to change the traditional teaching methods. This paper analyzed the impacts and issues of teaching Apps on bilingual teaching, also, the Application of Chaoxing teaching Apps in the bilingual lecture of International Accounting as a case study, in order to presenting the effective practice of teaching Apps in bilingual accounting courses.

The so-called prefabricated building is actually a building system that integrates design, production, construction, decoration, supervision and other links, so it always presents a strong integration characteristic. The BIM technology method is the main line that integrates many of the above elements, especially after the organization of simulation activities such as informatization collaborative design, visual assembly, node interactive connection and inspection, it can be more quickly and conveniently integrated, and dynamic supervision and management. The entire industrial chain of prefabricated buildings avoids repeated signs of errors in the design. To apply BIM technology in prefabricated building can effectively improve the effectiveness of prefabricated building design, and it is convenient for engineering designers to discover the deficiencies in prefabricated building design in time and make timely corrections.

In this paper, the distribution of methyl dibenzofuran isomers (MDBFs) in petroleum hydrocarbon samples of different ages and sedimentary environments were analyzed by the GC-MS method and relevant software. Relevant parameters of MDBFs were put into several cross-plots that have been studied and can reflect the origin of petroleum hydrocarbon. The results show that the diagram of pristane/phytane (Pr/Ph) - dibenzothiophene/phenanthrene (DBT/P) and the diagram of Pr/Ph - alkyl dibenzothiophene/alkyl dibenzofuran (ADBT/ADBF) cannot distinguish shale derived from marine and lacustrine shale. Whereas the diagram of Pr/Ph - (1 + 4)-/(2 + 3)-MDBF can effectively distinguish. the sedimentary environments and lithologic characteristics of samples. The results show that the diagram of Pr/Ph versus (vs.) (1 + 4)-/(2 + 3)-MDBF are more suitable to reflect the sedimentary environment and lithologic characteristics of organic matters. The method of big data processing can effectively optimize geochemical information.

With the rapid development of computer teaching technology, it can not only improve the efficiency of classroom teaching and enhance the interaction between teachers and students, but also effectively activate the classroom atmosphere and increase students’ interest in learning. As an important development direction of computer technology in the future, its application prospects in classroom teaching are very broad. By enabling knowledge to be presented in front of students more three-dimensionally, creating a more realistic classroom teaching atmosphere for students, achieving visual and auditory double stimulation, so that students’ learning initiative and learning effects are comprehensively enhanced. This article analyzes the application in computer teaching, and then discusses computer-assisted teaching and cultivating students’ innovative thinking ability.

With the development of mobile Internet, personal mobile phone has become the biggest interference factor in traditional classroom teaching. However, the prohibition of carrying mobile phones in class not only intensifies the contradiction between students and managers, but also contradicts the general trend of the development of mobile Internet. Therefore, it is a better way to use students’ personal mobile phones to assist classroom management and improve teaching effect. In order to reduce the interference of mobile phone to normal classroom order, this paper designs “mobile phone aided class management system”. teachers enter the system through the teacher-end website, they can upload courseware before class, design class questions; on class they can call the roll, ask questions and interact; after class they can input homework results. Through the student-end app into the system, students could carry out classroom activities such as sign in, answer questions, and interact in class. Their mobile phones will be monitored by the system, if they leave the system for more than 6 min, their peacetime results will be automatically deducted, and the points deduction notice will be sended to the student-end app; after class they can download courseware for preview or review, check their usual performance trends whenever and wherever they like. The system aims to enable students to use mobile phones to follow the teacher’s teaching ideas, reduce mind-wandering time, enhance communication and interaction, and create a new classroom model in the mobile Internet environment.

With the rapid development of science and technology and human society in recent years, people’s pace of life is constantly improving, and the demand for fast and convenient high-performance products is constantly increasing. Wearable electronic medical devices are becoming more and more popular, among which the representative is the continuous blood glucose detection system which measures the glucose content in the interstitial fluid. This paper reviews the background and market demand of wearable electronic devices and the applications of CGMS and glucose sensors.

Today machine learning is applied in economy, finance and other aspects. Text information has real-time and high values, and is widely used in the emotion analysis and prediction. This article reviews research papers which analyze machine learning and deep learning, and summarizes the application of text analysis in macroeconomic prediction. Finally, it puts forward the development direction of macroeconomic prediction based on deep learning and text analysis, constructs the overall research framework, and proposes development ideas in the future.

Driven by the technology of network and information, especially the concept of “Internet +”, it has had a great impact on English teaching of college. The traditional classroom-based teaching model cannot meet the social development basic needs at the current stage. Under the “Internet +” background, the “online + offline” college English hybrid teaching model has ushered in new development opportunities. Based on actual teaching experience, the author analyzes the chance and challenges faced in college English teaching at the current stage, and proposes the construction of a “online + offline” hybrid teaching model for college English under the “Internet +” background, in that to improve the effect of English teaching in college positive effects.

By means of computer search and retrieval, this paper is going to analyze the ratio of the pronouns in Homer’s epic The Odyssey and the statistical terms in ancient Chinese descriptive poem Shan Hai Jing (usually translated as Classic of Mountains and Rives). With the help of present computer science search technique, we figure out times of repetition of the target pronouns “he, his, him, I, my, me” in The Odyssey and the maximizing of the alternative frequency of statistical terms “names, figures, pronouns, nouns of position etc.” in Shan Hai Jing. The high repetition frequency of the target pronouns emphasizes “his experience and possession”, reflecting the hero experiencer identity. And then the high alternative frequency of the statistical terms emphasizes “my experience and possession”, suggesting the writer experiencer identity.

Artificial intelligence algorithms rely on big data, which is large enough in quantity and wide enough in scope. But the “big” data is only a relative concept; big data is still incomplete in some specific levels. If the limitation of data is strengthened and amplified by artificial intelligence algorithms, and elevated to the social level, a series of political and ethical issues will occur.

As mankind enters the age of network information, profound changes happened in the working environment and mechanisms faced by college student management. Big data has become an important factor and technical environment for colleges and universities to implement the fundamental task of “building up people by virtue”. How to adapt to the development of the big data era and innovate the education and management of college students has proposed a new era mission. The research on college education management under the trend of “Internet + ” higher education management worldwide, reflects the characteristics of the times, and has the dual meaning of theory and practice. Educational thoughts such as constructivism, humanism, holistic theory, and flattening theory have an impact on higher education. This article analyzes and discusses the problems in China's high education management, and studies the development strategies of higher education management under the “Internet + ” perspective to promote the education management development.

In the process of large-scale machine-to-machine (M2M) communication in the IoT, the Request/Response mode applied by the traditional network system can be no longer applicable due to which high network performance demand and poor expansion ability. With the characteristics of weak coupling and asynchronous communication, Publish/Subscribe mode had become an important platform in the new generation of large distributed application system. This article summarized the research status of publish/subscribe systems. According to the application scenario of data transmission of low-voltage electrical equipment, this paper discusses the realization method of data transmission system based on Message Queuing Telemetry Transport (MQTT) technology. By analyzing the characteristics and simulation of MQTT protocol, it is verified that the subscription publishing model can effectively organize and publish information in the mobile computing environment and has good effectiveness.

In the process of garbage collection, the water flow in residual waste directly affects the process of collecting residual waste. Therefore, detecting the water flow in residual waste at the garbage transfer station is of great guiding significance for garbage disposal. In this paper, the Gaussian-YOLOv3 algorithm with high accuracy and real-time performance is used to identify and detect the water flow during the dumping process of residual waste, and determine the quality of the classification of residual waste according to the recognition situation. The experimental results show that the residual waste quality detection method based on the Gaussian-YOLOv3 algorithm can accurately identify the amount of the water flow during the dumping of the residual waste. At the same time, the back annotation and retraining method significantly reduces the model's impact on similar residual waste in complex environments. The false recognition rate satisfies the actual needs of residual waste water flow identification and improves the efficiency of residual waste classification quality determination.

With China’s accession to the WTO, the rapid development of market economy and the acceleration of global integration, China’s international status continues to improve. Professional English continues to infiltrate professional positions in various industries, and English teaching in higher vocational industries is particularly important. The goal of China’s higher vocational English course is to train students to use the English which they have learned in future professional positions. Based on a questionnaire survey of 324 students from Jilin Engineering Normal University, the article conducted a one-year empirical study on two tourism management classes from the perspective of the EOP Teaching Theory. Through comparative analysis of the data before and after the experiment, it is proved that the career-oriented teaching model is effective in vocational college English teaching.

The power system of five-axis CNC machine tool is designed to determine the maximum machining working space with alloy steel material and maximum overall dimension. Based on the analysis and calculation of machining process parameters, the cutting force, cutting speed, power and torque are checked. From the analysis and calculation of material cutting force to the design of power system, the stability and accuracy of machine tool machining can be improved.

The design of this portable automatic page flipper takes portability and cheapness as the design goal. It uses simple mechanism and control mode to complete the design of this page flipper. Besides meeting the function of the page flipper, it also uses automatic control circuit control. The area covering the pages is very small. The overall design is foldable and can turn pages quickly. It can work either by plug-in mode or by battery power supply mode. The wireless remote control mode is designed to facilitate the user’s long-distance use.

With the development of the times, under the guidance of mobile cloud Internet, computer network and other high-tech technologies, education gradually gets rid of the traditional shackles of teaching mode, and also gets rid of the limitations of traditional teaching mode in space and time, and develops intelligent thinking. In this paper, the author introduces the current situation of physical education (PE) in Colleges and universities (CAU) by using the method of statistics, which is based on the data of compulsory PE in CAU At the same time, it puts forward some suggestions for the improvement of sports CAU in China. The experimental results show that the development trend of PE undergraduate in normal universities in China has been greatly improved, the enthusiasm of students for PE has increased by 13%, and PE is developing towards a better and better direction.

Face recognition technology has attracted attention as people pay more and more attention to facial information, and has become a hot research topic. In this experiment, the training learning rate is set to 0.0004, 64 images are randomly loaded in a single loop, and then noise is added to start training. The cyclic process can be described as: First, the generator G generates output, and then the discriminator D performs the discrimination, and the generation loss and the discrimination loss are calculated by the output of the generator G and the discriminator D. Experimental data shows that a face database is formed through feature extraction and training of the face database. Then, randomly extract images for detection and recognition, and finally match the features in the feature library. The experimental results show that the accuracy of face recognition is 88.11% when the original data is used for 1000 iterations. The data filled with samples generated by GAN is used for training, and the accuracy of face recognition is 93.76%. There is a significant increase. At present, face verification and recognition still have difficulties in the application of computer science, and the generative confrontation network has made certain breakthroughs in the description of image generation.

The Yugur nationality is one of the ethnic groups with a small population in China, and the Yugur nationality has its own language. In the course of development, the Yugur language is divided into two types: Eastern Yugur and Western Yugur. The native language has been lost. Yugur language currently has a very small population and is an endangered language, and the special attributes displayed in the evolution of the language make Yugur language research of great value. This article will start from the design of the voice database, with the purpose of protecting and preserving the existing Yugur language, taking the western Yugur language voice database design as an example, introduce the design of the western Yugur language voice database, and propose the western Yugur language signals and parameters Set standards.

In order to solve the problems of insufficient bicycle parking space, random parking and low safety factor, this paper designs an intelligent three-dimensional bicycle garage based on the Internet of Things. The bicycle garage adopts a revolving three-dimensional structure, and the motor drives the gear chain structure to realize the three-dimensional parking function of the bicycle. The control system adopts STM32F103 single-chip microcomputer, and realizes vehicle detection and frame position positioning through photoelectric sensors. The intelligent garage adopts ZigBee wireless communication module to realize the data transmission between a single garage and the system platform. The test structure shows that the intelligent three-dimensional bicycle garage is fast, convenient, and reliable, and has great commercial value.

In the production process of edible fungi, the quality inspection of each link is a very important link, and the inspection link determines the reliability and intelligence of intelligent equipment. The precision sealing technology of the cotton ball is the last step of the bacteria bag injection, and the quality of the sealing directly affects the bacteria release rate of the bacteria bag. To this end, this paper designs a diagnostic system for the sealing quality of edible fungus bag cotton balls based on image processing technology. In this system, image enhancement, region segmentation and noise filtering are used to preprocess the picture; the combination of convolutional neural network technology and image recognition technology detects the sealing quality of the cotton ball of edible fungus bag, and convolution the neural network uses a three-layer convolution structure. Through a large number of sample training, the accuracy of the identification of the quality of the bacterial envelope is as high as 99.8%.

Through the analysis of literature and literature communication mode, the construction and use of database under the background of big data, the meaning of data intelligence and the construction of historical literature model, this paper expounds that big data and the data intelligence developed on the basis of it have a great promotion effect on the historical research work. Using literature research method, concept analysis method, comparative research method and so on, this paper probes into the way to construct the historical document model under the data intelligent visual fault. Data intelligence emergence enables a historical document to break away from its own single individual, to break the time and space constraints, to connect with similar or similar documents, and then to integrate multiple and dispersed textual information. In particular, data intelligence, through the ability of data acquisition and calculation, can actively screen and compare abstract information in heterogeneous data according to internal logic, can reconstruct the historical original appearance, and can make it be a widely used knowledge, and then can provide research hypothesis and prediction model for research work. This artificial intelligence technology which highlights the subjectivity of literature is marked by deep learning, and further deepens the study of big data.

The anthropological field driven by big data not only brings the sense of scientific research community, but also brings the transformation of logic theory and practice in innovative research theory and methods. As a paradigm shift, Digital Humanities has brought new theories and methods to traditional anthropology; On the one hand, it has realized the “horizon fusion” between horizontal disciplines at the theoretical level. This interactive integration not only brings about the omniscient and wide-angle vision of human, object and image in the space-time field of anthropological research objects, but also constructs a vertical and in-depth repetitive mining of research resources rich context by using research media technology; on the other hand, From open login of big data, related login of big data, to core login of big data in the field of humanities, this process is one of multidimensional coexistence; therefore, in the field of anthropology, this research theory and practical method can realize horizontal and vertical data collection, in-depth research and analysis, and three-dimensional interactive display.

At present, in the process of optimizing distribution network system, economy is taken as the starting point and modern technical means are comprehensively used to realize the reliability and safety of operation mode. The operation of distribution network based on flexible switch is the result of technology development in the new era. In this paper, based on the historical background of modern science and technology development, it analyzes the application of flexible switch synthesis coordination in the economic operation of distribution network. Firstly, it analyzes the current research status of distribution network with the coordination of flexible switches synthesis, and then optimizes the operation mode of traditional distribution network, and again, explores the flexible representation of distribution network in the operation process, optimizes the flexible synthesis of distribution network operation mode, finally completes the verification analysis.

This article starts a research on the development of intra-city clothing distribution under the O2O model. This article mainly analyzes the O2O model and the meaning, status quo and characteristics of intra-city delivery under this model. At the same time, it also focuses on the current situation, characteristics and existing problems of clothing intra-city distribution under the O2O model, combined with existing typical cases to conduct a more comprehensive analysis, and put forward a proposal for intra-city clothing distribution under the O2O model on this basis. Finally, this research focuses on the proposal of intra-city clothing distribution under the O2O model, and mainly develops a relatively new shopping mode and distribution environment from five aspects of supply side, sales side, distribution side, technology side, and service side; while conforming to the O2O trend, it will also achieve healthy economic development.

With the deepening of the reform of higher education management system, more and more attention has been paid to the benefits of running a school, and the economic benefits have become increasingly prominent. However, there are also many problems in resource management and utilization in colleges and universities, such as the mismatch between capital input and output, the inflation of student training cost, the high debt ratio, and the low efficiency of capital utilization. In this case, effective measures must be taken to improve the use efficiency of the existing funds in order to ensure the smooth progress of the work and the completion of the locked targets. Therefore, the budget evaluation system emphasizing the effectiveness of funds begins to attract the attention of colleges and universities. Based on artificial intelligence, this paper constructs a budget evaluation index system for application-oriented undergraduate universities. Firstly, the thesis gives a theoretical overview of the performance budget evaluation system and a brief introduction to the artificial intelligence technology. Secondly, the construction of budget evaluation system of application-oriented undergraduate universities; finally, it puts forward the safeguard measures of applying the budget evaluation system. Budget management is an important work of financial management in colleges and universities, which is of certain significance to the improvement of management level and financial status.

In recent years, with the rapid expansion of urbanization, urban diseases are getting worse. Smart city as a sustainable development solution, has played an increasingly important role. Base on the existing smart city evaluation system, this study has constructed an evaluation index system with 5 dimensions and 14 indicators. The AHP method was introduced to calculate the weight of indicators and their ranking. The results showed that among the five dimensions, smart infrastructure is the most important, followed by smart public services, smart public management, and smart industry economy and finally is the smart security system. This smart city evaluation index system provides a theoretical reference and practical basis for measuring the development level of smart city.

With the continuous progress of social production technology and the continuous increase of car ownership, environmental and energy issues have become increasingly prominent. Electric vehicles can significantly reduce carbon emissions and increase the use of clean energy, which is of great significance to the development of cities. As electric vehicles are a means of replacing traditional fuel vehicles, this paper analyzes the game process between fuel vehicles and electric vehicles after the introduction of electric vehicles based on evolutionary games. Based on the type of consumers choosing to buy a car, the characteristics of electric vehicles and fuel vehicles are analyzed, and the influence of the service level of electric vehicles due to scientific research input factors and government participation in management factors is considered to establish an evolutionary game between electric vehicles and fuel vehicles model. According to the relevant knowledge of dynamics, the parameters of the model are analyzed to obtain the conditions for the stability of each equilibrium point. By analyzing the steady state of system evolution, it provides theoretical support for the green development of electric vehicles and the formulation of related government policies.

The intelligent diagnosis technology of engines is developing towards automation and intelligence. This trend not only puts forward higher requirements for the safety and reliability of engines, but also promotes the progress of online engine operating condition monitoring and fault diagnosis and prediction technology. The paper makes full use of the respective advantages of fuzzy system and neural network, which can better intelligently diagnose engine faults. Finally, simulation analysis proves the effectiveness of the proposed method.

Support vector machine seeks the best compromise between model complexities and learning ability based on limited sample information, in order to obtain the best generalization ability, and has achieved good application effects in demand forecasting. In this paper, a least squares support vector machine is used to classify various factors that affect the consumption of ammunition. Experts will evaluate and score each factor. After preprocessing the data, the projection pursuit method is used to reduce the dimension of the evaluation data. The comprehensive evaluation index is obtained and used as an input item, and the actual consumption is taken as the ideal output to realize the forecast of ammunition demand. The simulation results prove the effectiveness of the method in this paper.

Now, data is in an explosive increase in the “big data (BD) era”. Information technology has greatly promoted the research of ancient literature, mainly in the technology of data collection and data retrieval. Based on big data, this paper uses data mining technology to study the modernity of ancient literature. This paper uses data mining technology to study the modernity of ancient literature through the establishment of mathematical analysis models of ancient literature and the Cholsky decomposition method. This paper conducts data mining on large-scale ancient literary works to find out the potentially valuable information hidden in the literature. Through the analysis of 6359 documents, this paper uses data mining technology to find 659 useful information from 6359 documents. Through experimental research, it is found that BD technology has certain advantages in the study of the modernity of ancient literature, which will promote the common development of ancient literature and modern literature.

As we know that the multithreaded programs are easily to produce data races during the running, and it is really hard for us to locate the position where the mistakes are. After reading the Eraser: A Dynamic Data Race Detector for Multithreaded Programs which introduces “Lockset” algorithm by explaining the shortcomings of the classic “Happens-Before” algorithm [1], and then optimizes the tool Eraser on the basic “Lockset” algorithm, I have summarized the paper and put forward my own views.

With the development and application of software technology, the requirements for software development are constantly improving. The application of software architecture style and quality attributes should be considered while developing software. This system refers to much famous stomatological hospital portal websites in China. In addition to the basic functions of hospital introduction, department doctor introduction, appointment registration and other basic functions, patients can also check their own examination reports, prescriptions, etc., which has strong regional and group characteristics. We should vigorously use Internet technology to build an information platform to better provide oral diagnosis and treatment services for patients. The stomatological hospital information platform is a multi-layer distributed enterprise application program generated by. Net platform. It uses B/s, warehouse, multi-layer, object-oriented and other architecture styles, and adopts corresponding strategies to improve the overall quality of the software in terms of usability, modifiability and other quality attributes.

This paper introduces the design of intelligent classroom system based on Internet of things technology. The intelligent classroom system adopts the Internet of things technology, sensor technology, wireless communication technology and intelligent control technology, which mainly realizes the functions of the statistics of the number of students in the classroom, automatically turn off the lights, automatically switch on and off the air conditioning, detect abnormal doors and windows, and central control, etc. Firstly, this paper analyzes the research background and demand analysis of the intelligent teaching building system, and then designs the functional modules of the system. Finally, according to the required functions and performance requirements, the hardware selection and design are carried out, and the key technologies adopted in the system are analyzed, and the system functions are realized. Through the test, the system runs well, can achieve the expected goal, and has good application value.

The regional economic system lacked accurate calculation of data and reasonable allocation of internal resource requirements in the market operation. For this reason, the design of the regional economic system coupling model based on big data technology was carried out. On the basis of the analysis of regional economic coupling innovation development, the hardware design of regional economic system focused on the standard processing and assignment of coupled raw data to determine the index weight; In the software design, the coupling degree model of the interaction force between several systems was established by comparing the coupling definition in physics and the size of the capacity coupling coefficient. The research proves that from the perspective of time, the coupling fitness of regional economic systems was increasing year by year. However, the overall goal of coupling was small; from a spatial point of view, the coupling fitness had a clear spatial inconsistency distribution.

This paper introduces the design and implementation of international intelligent hospital information system. The Internet and digitization have brought about disruptive changes in many industries, including health care. This project combines to build an international business environment, to promote the construction of smart hospital, to improve the application of information system in the process of hospital diagnosis and treatment, and to provide patients with efficient and high-quality medical services. System through the investigation into the hospital after get the user requirements, and use the core Asp.net MVC framework and the Entity framework Entity framework developed, finally through the system test, for the hospital information management provides a visual management interface, easy to use and manage the basic information of the hospital patients, and on the stages in the medical activities of data acquisition, storage, processing, summarizing, form all sorts of information data processing, the desired goal.

Nowadays, with the rapid development of economy and science and technology, the ecological environment has been greatly affected. In recent years, the concept of sustainable development has been paid more and more attention, and the protection of ecological environment is becoming more and more important. With the advent of the era of big data, ecological data also presents a trend of diversification. The integration of multi ecological big data is conducive to solving more and more serious ecological problems. Therefore, this paper proposes a multi ecological large data fusion method based on rotation forest algorithm for heterogeneous network. In the study, we introduced rotation forest into data fusion, selected an ecological region as the research area, and selected 500 samples from 2000 samples as test sets. In this paper, the proposed method is verified from three aspects of fusion confidence, overall accuracy and computational time efficiency, and is compared with the other two methods. The results show that the highest fusion confidence of method 1 is 0.8, that of method 2 is 0.65, and that of this method is 0.92. In addition, in terms of overall accuracy and computational efficiency, the proposed method based on rotation forest algorithm has more advantages than the other two methods.

From the perspective of the Han-Tibetan cultural exchange, the social and historical backgrounds of the fine collections of Tibetan porcelain produced by Jingdezhen official kiln in the Ming and Qing dynasties integrating the elements of Han-Tibetan cultures are reviewed. The artistic design characteristics of the modeling and color of Tibetan porcelain are analyzed to appreciate the endowment of Tibetan porcelain to the thoughts of Tibetan Buddhism. Through field investigation, consultation of literature, and comparison of real pictures taken, it is concluded in the study that the “Combination of Sanskrit and Han styles” was the main feature of the Tibetan porcelain produced by Jingdezhen official kiln in the Ming and Qing dynasties. It presented a strong religious theme and artistic aesthetic characteristics of deification, forming a unique Sanskrit art style of Tibetan porcelain.

The changes of national traditional sports culture include the changes of ethnic sports and the changes of thinking. According to the development trend of the whole sports culture, the changes tend to progress. This paper presents a method to analyze the cultural changes of traditional national sports based on the structural model of achievement. The method of analyzing the national traditional sports culture adopts the optimal foraging theory to improve the way of sports culture change, analyzes the national traditional sports culture through the structural model of achievement motivation, and learns the national traditional sports culture by using the chaos algorithm and reverse learning algorithm. Realization of the changes of traditional ethnic sports culture experimental results show that the model has good convergence accuracy and computational speed, and is especially suitable for the analysis of traditional sports culture changes.

Computer network security (NS) is the most concerned problem of society and people. With the increasing amount of network information, the computer NS management in the era of Big Data (BD) is very important, and has become the primary topic of NS management. This paper studies the computer NS and preventive measures based on BD technology. In this paper, through the method of literature analysis and questionnaire survey, 150 teachers and students majoring in Computer Science in our school were investigated to understand the current situation of computer NS in China and the solutions. The research results show that the computer NS problems in the era of BD are mainly divided into three aspects: the security problems caused by human factors account for about 30%, the security problems in data transmission account for about 45%, and the security problems of computers themselves account for about 25%. In view of these NS problems, this paper details the NS problems, and proposes corresponding solutions to these problems, so as to effectively improve the level of NS management and promote the efficient development of computer network technology(NT).

In this paper, multivariate data fusion and deep learning artificial intelligence algorithms are introduced into the power grid dispatching business. Combined with dispatching procedures and instruction specifications, the dispatching phone voice is converted into information in text through a voice recognition platform in real time. Key words are extracted through semantic understanding, multivariate data fusion and deep learning for the recognized text to identify and detect business scenarios. The extracted key information is used to verify and prevent errors on the grid operation platform based on the grid real-time status verification and dispatching business scenario rules. Alarms and prompts for irregular and incorrect dispatching instructions is proposed through the voice platform. Through the operation and operation of historical big data, constantly learning and discovering laws, a perfect knowledge map of dispatching business is established, and the accuracy of voice recognition and the accuracy of scene detection is continuously improved, thereby the function of 24-h security supervision of dispatching telephone business are realized. The system realizes full chain intelligent anti-misoperation management and control of the entire process status and power flow, which can solve the problems of wrong dispatching orders and misoperations when the phone is ordered due to inadequate monitoring, irregular orders, and incorrect understanding of scheduling instructions.

As science and technology has developed rapidly, artificial intelligence (AI) has become a trend of the development of modern society, and the development of AI has been concerned by many industries. In the power system, regulation of power grid is an important technology which is equivalent to human brain. The combination of regulation of power grid and AI with the use of information technology can improve the accuracy and efficiency of regulation of power grid to promote the development of power industry in China.

As the society develops, the needs of users have put forward higher requirements for circuit monitoring system. That whether the power grid system can operate normally does not affect the normal living conditions of residents, but it has a great relationship with the accuracy of online monitoring of cable status. According to the requirements of power grid system, this paper designs an online monitoring system for the status of cable based on wireless sensors to effectively solve the problems caused by circuit failures. The design introduces the overall structure of online monitoring system in detail, explains some of the hardware, implements sample monitoring, and realizes accurate monitoring of cable status, indicating that the designed online monitoring system has good advantages. When the circuit fails, it is difficult to find out the fault in a short period of time due to the complication of power grid and limitation of geography and time, which seriously affects the user's electricity experience. With the continuous innovation of wireless sensors, the online monitoring system can detect the status of cable, and the location of cable faults can be quickly checked, so it is practical and significant to design an online monitoring system for the status of cable.

The science and technology and society in China are gradually developing, and the demand for electrical energy is gradually increasing, and there are more and more domestic smart grid constructions. The abnormality of the grid cable has a direct impact on the power supply. In order to better improve the detection capability for abnormal fault of grid cable, the automatic detection technology is performed based on the cable nodes in smart grid. It is an identification based on the abnormal spectrum existing in the current transmission of power grid, and intelligent extraction is carried out, so that the abnormal fault nodes of each cable can be automatically detected, and the fusion of abnormal fault of cable nodes is established. The author first analyzes the faults of cable in smart grid, then analyzes the simulation experiment, and finally applies the automatic detection technology to the abnormal faults of cable nodes in smart grid.

In recent years, with the development of modern wireless communication technology, it has become a new communication technology. Compared with the traditional communication technology, modern wireless communication is relatively combined with more advanced science and technology. When people communicate on wireless communication, they can get more convenience at a faster speed, which has a significant impact on people’s lives and is also recognized by the general public. Modern wireless communication technology makes people’s life and communication more convenient, but how to improve this technology in the future is also the focus of the majority of scholars. In this paper, the author first briefly expounds the modern wireless communication technology, then studies the problems of modern wireless communication technology, and finally expounds its future development trend.

As the rising requirements of volcano analysis of terrestrial planets, researches of volcanic domes become more important in recent years. Analysis on domes helps the researches of extraterrestrial resource development, life detection and planet thermal evolution. Traditionally, domes are normally extracted with naked eye, this is inefficient and cost large amount of resources. In the research, we use some features to detect domes in lunar mare automatically. It contains contour extraction, circular structure detection and dome recognition. Some features are selected to express the basic morphology of domes. We use contour maps to extract circular structures, and then use parameters like roundness, slope, and height-diameter rate to distinguish domes from these structures. We test the method near Hortensius-Milichius area, the recognition accuracy approach 66.67% and some new domes are marked. Detected domes mainly locate near the radially distributed linear structures, the formation is considered as the volcanism caused by strong impacts.

With the development of modern information, the construction of a digital campus is inseparable from the support of campus smart card system which provides a good information sharing environment and provides more comprehensive data collection for the construction of a digital campus. Therefore, the complete integrated digital campus perfects the campus application platform center with richer and unified content, including identity authentication platforms, public data centers, and security information systems. These application platforms will be implemented throughout the entire application system on campus. In addition, the use of the campus card perfects the information management of various departments on campus, and promotes the construction of digital campus.

Based on the perspective of system theory, a composite system evaluation model is established, reveals the process of urbanization quality evolution in Western China from 2000 to 2017. Research shows: (1) The quality of urbanization in Western China is low, but it is gradually improving. (2) There is a big difference between regions. (3) From the perspective of moderate development, coordinated development and inclusive development, uncoordinated and non-inclusive are the main constraints of high-quality urbanization development.

In the daily operation of the power system, stealing electricity often occurs, which makes the power supply enterprises and the country suffer huge economic losses. In view of this series of situations, the power supply enterprises and the state also analyze and study the anti-stealing technology. In this paper, based on the K-means algorithm and LSTM algorithm of electricity theft detection system for the experimental object, the common methods of stealing electricity and stealing electricity characteristics are studied. Secondly, the decision-making model of electricity theft prevention based on data-driven is established. The K-means clustering algorithm is used to cluster the big data of electricity consumption information, and the decision-making model of electricity theft prevention based on K-means is established. The experimental results show that the intelligent detection system based on K-means and LSTM algorithm plays a certain role in preventing power theft between power supply enterprises and people in the future, and its successful application can reduce the loss of a lot of electricity theft and human, material and financial resources.

This paper expounds the development process and future prospect of intelligent proofreading technology. Based on the model training and the research on the composition of knowledge map, the deep learning model is established to reduce the error rate of intelligent proofreading, and the basic proofreading model of intelligent proofreading system is constructed. By perfecting the proofreading model of specific vocabulary and data docking, Chinese fixed terms, sensitive words, etc., a relatively complete proofreading model is formed. Meanwhile, the intelligent proofreading model is encapsulated to form interface service and independent proofreading service.

With the continuous development of the electronic industry, the electronic system is becoming more and more complex. Improving the reliability of electronic products has become an important means to ensure economic growth and social benefits; therefore, the fault diagnosis of electronic system has become the focus of scholars in the field of electronics. In this paper, the general method of data collection for fault diagnosis of electronic products is analyzed based on the data feedback from distributed sensors. In order to fuse the statistical properties of data and the energy properties of data, combining the fusion algorithm of D-S evidence theory, the classification results of LDA feature extraction and wavelet energy spectrum entropy feature vector extraction are fused, compared with the single algorithm, the fusion algorithm has better recognition.

Affected by the outbreak of the novel coronavirus, the beginning of new term is delayed in many places. Most schools are adopted the method of “network teaching” to teach classes, so as to “suspending classes without stopping teaching”. With the development of the times, information-based learning will become a necessary part of normal teaching. With the same time, our educational concept, teaching knowledge and subject content all need to be innovated. This paper takes the “tax law” course as an example, based on the TPACK framework, integrate the blended learning into the curriculum, with the combination of “online” + “offline”, from the curriculum to the contact arrangement all are made corresponding adjustment. To enable students to have a deeper understanding of the learning content, to cultivate students’ financial management ability and professional quality, and to have basic tax processing ability. Finally, to achieve student-centered teaching mode, the optimization of teaching resources, and the high efficiency of teaching quality.

As we all know, energy helps promote China’s social and economic growth and the improvement of people’s living standards. Therefore, the oil and gas industry has obtained important development opportunities. However, oil and gas resources are non-renewable energy sources, and their uses are gradually increasing. Therefore, oil and gas resources are facing a rapid depletion state, which poses a great threat to the future development of society. For this reason, in order to improve the utilization efficiency of oil and gas resources and reduce the pollution to the surrounding environment, China has paid more and more attention to the research on oil and gas recovery, and has gradually increased the intensity of the research. Based on the above background, the purpose of this article is to study the methods of oil and gas detection and recovery in oil and gas storage and transportation based on artificial intelligence technology. This article briefly introduces and summarizes the basic principles and scope of oil and gas recovery technology, and introduces the practical application of oil and gas recovery technology based on artificial intelligence technology, and analyzes the problems of oil and gas recovery technology. Put forward corresponding measures.

To achieve the precise control of the oil supply electrical gear fuel pump of multi-electric aero-engine, the improved BP neural network is applied to establish the equation of the flow characteristics for electric gear fuel pump. The data obtained from the test platform of electric gear pump are processed and then applied to the training and testing of neural network. The simulation time is short with small error, which shows that the improved BP neural network can be used to control the electric gear fuel pump, and the flow model of electric gear fuel pump is drawn.

The complex system often consists of multi-components and components are coupled, in response to this characteristics, the paper analysis the failure behavior between subsystems and components of the system, including components fault time, fault propagation path, system structure, a reliability assessment model for 0–1 binary state multi-components system is established based on the universal generating function method, and the reliability of the system is analyzed. A case study is presented to illustrate the design method is rigorous, scientific, strong usability and versatility, which have very strong promotion value in the field of reliability engineering.

This paper studies how knowledge field activity of industry-university-research alliance affect researcher’s 5G technology innovation performance through promoting alliance’s 5G knowledge flow, and samples 103 researchers from 10 Chinese enterprise or university labs in Shenzhen and Beijing for empirical research. The empirical results found that (1) knowledge field activity of industry-university-research alliance had direct positive affect on 5G knowledge flow containing with both volume of 5G knowledge flow and precision of 5G knowledge flow, and researcher’s 5G technology innovation performance significantly; (2) 5G knowledge flow including both volume of 5G knowledge flow and precision of 5G knowledge flow had direct positive affect on researcher’s 5G technology innovation performance significantly, and meanwhile mediated the direct effect of knowledge field activity of industry-university-research alliance on researcher’s 5G technology innovation performance.

In order to improve translation efficiency, people gradually realized the importance of computers, and a computer-assisted translation model came into being. Applying computer technology to traditional translation work can effectively improve the efficiency of translation work. Mainly explored the innovation and development of computer-aided translation model under the background of big data. The unique “4V” feature of big data will bring new reforms to computer-aided translation, and will play a positive role in promoting the innovation and development of computer-aided translation.

In recent years, the level of physical education in colleges and universities is on the rise as the country attaches great importance to physical education. It is of great practical significance for the reform of physical education in China to seek ways to improve the level of physical education. The purpose of this paper is to study the application of decision tree based classification algorithm in the performance analysis of university physical education teachers. This paper introduces a decision tree data mining algorithm for teacher performance analysis and evaluation. According to the algorithm in the decision tree algorithm, a decision tree model for the analysis and evaluation of physical education teachers’ performance was constructed, and the corresponding rules were extracted. The purpose of this is to obtain the indexes needed to influence the performance of physical education teachers through the decision tree algorithm. The experimental results show that this paper can lay a foundation and provide reference for the improvement of teaching effect. Based on the evaluation of physical education teachers in a school, this paper finds that the teacher evaluation of the school is basically concentrated in the “medium” level, accounting for 70%.

The ZBR algorithm of ZigBee is mainly composed of cluster tree and AODVjr, but the efficiency of cluster tree is low, and the control overhead of AODVjr algorithm is too high. Based on the address allocation algorithm and the route discovery mechanism of AODVjr algorithm, this paper proposes a new route algorithm based on address allocation algorithm, which limits the broadcast direction and the number of broadcast hops in the process of RREQ information transmission. The simulation results show that the performance of the improved algorithm is better than that of the traditional ZBR algorithm in terms of average transmission delay, routing control overhead and residual energy percentage.

Nowadays, new technologies led by artificial intelligence and big data are booming, and have been widely used in many fields such as medical, transportation, military, and industrial. Automobile driving is one of the main application directions of artificial intelligence in the field of transportation. The purpose of this article is to explore the application of artificial intelligence technology in the field of driverless cars, with a view to bringing precision and real-time improvement to pedestrian detection in driverless systems. In this paper, based on the verification model and the pedestrian recognition algorithm based on the recognition model, a new recognition algorithm combining two types of models is proposed. After optimization and testing on the Market1501 pedestrian re-identification data set, it is concluded that the multi-camera test mAP of this algorithm is 72.55%, which greatly improves the detection accuracy compared with other mainstream re-identification algorithms. The research in this paper basically solves the problems of low accuracy, poor real-time performance and discontinuous cross-camera detection, which is beneficial to the successful application of pedestrian detection in unmanned driving.

The O/R mapping technology and object-oriented database technology are compared and analyzed to expound the advantages and disadvantages of these two technologies and the development trend of these two technologies.

With the rapid development of information technology and Internet of things, the traditional classroom check-in mode is no longer applicable. The current commonly used attendance technology and methods are compared, and a check-in system and device based on face recognition technology and distributed thought are introduced, which provides sufficient guarantee for efficient and accurate classroom check-in.

Rural areas are the strategic focus of the development of inclusive finance. With the implementation of strategy for rural revitalization and poverty alleviation, the inclusive financial system has gradually been established in rural China. In the Internet era, the combination of traditional rural finance and Internet technology has provided huge advantages for the implementation of rural inclusive finance. Based on the current supply and demand status and problems of rural inclusive finance, an inclusive financial ecosystem with innovative rural inclusive finance products, should be established and optimizing rural credit reference systems, improving financial laws and regulations could promote the development of inclusive finance in rural areas.

This paper studied the supply and demand congestion problem of tourism industry with big data method. Taking online travel notes about Guilin as sources of big data, we analyzed tourist preference, tourist perception and regional features of tourist routes after data collection, manual encoding and visualization processing. The results showed that tourists prefer to visit Guilin for 2 to 4 days from March to May and from July to October along the tourist route of Guilin—Yangshuo—Long-sheng mainly for fee-charging natural scenery. So, main tourist destinations in China such as Guilin have serious problem of supply and demand congestion. Therefore, in order to improve the supply and demand congestion problem in tourism industry, we should pay more attention to tourist big data collection and analysis for establishing preferences of tourist consumption and accelerate the supply-side reform.

With the continuous occurrence of major emergencies, emergency work input is increasing, major emergencies are increasingly concerned by the society. When major emergencies come, the government has advantages in controlling resources and organizational system, but there are inevitably some limitations. Based on big data analysis technology, this paper studied the mobilization mechanism of young volunteers in major emergencies, in order to put forward reasonable Suggestions for improving the mechanism of volunteer mobilization. Combining vertical system and the system level, this paper put forward the perfect our country major emergency management system of the construction of the digital science and technology policy recommendations, and based on the current domestic COVID - 19 cases, combined with large data analysis techniques for outbreaks in parts of the volunteers mobilize data are analyzed, the results show that whether the work rate or promotional rate, were higher than 89%, above the level of the everyday. This requires us to improve the standard and unified digital epidemic information collection system, so as to facilitate personnel control under major emergencies.

The traditional psychological health education for college students has some shortcomings such as specialization. As a rapidly developing information acquisition technology, big data technology has been gradually applied in various fields of society. The application of big data technology will play an important and positive role in improving and making up for the deficiency in psychological health education for college students. The purpose of this paper is to provide better psychological services for special groups of college students by studying the psychological characteristics of special groups of college students based on artificial intelligence and big data technology. In this paper, with large data and artificial intelligence technology, discusses the significance of college students’ psychological crisis intervention platform construction, objectives and the research status, combined the technology of big data, analysis the performance of the college students’ psychological crisis and the reasons, combined with the application of large data, build a platform for college students’ psychological crisis intervention, the results show that there are more than 82.1% of the students need psychological counseling. The establishment of this platform is of great theoretical and practical significance to guide college students to learn to grow by themselves.

As one of the main lines of the moral education model, the mode of ‘‘three-whole-education’’ includes three aspects: ‘‘whole-staff education, whole-process education and all-round education”. Cultivating compound high-level talents is a systematic project, which needs the implementation of multiple links and the all-round cooperation of all parties. Therefore, it is particularly important to carry out top-level design and overall planning for the mode of ‘‘three complete education’’. The purpose of this paper is to study the moral education model of three complete universities under artificial intelligence technology simulation, so as to provide technical advice to it. Based on ‘‘three education’’ as the research object, comprehensively describes the simulation platform of artificial intelligence, ‘‘three full’’ combined with the era background, the development of the network education platform, practical basis, development process and characteristics of the concept and construction effects, and builds a simulation platform for the study of ‘‘three education’’ model, the results show that for the indicators, the threshold value in 0.4 to 0.6. Finally, based on the experimental results, this paper analyzes the moral education model in colleges and universities and puts forward some Suggestions.

With the development of the Internet and the rapid development of e-commerce, online shopping platforms have become popular. In recent years, driven by the spirit of the state’s advocacy of economizing campuses, many campuses have seen a boom in second-hand commodity trading. It is necessary to make full and reasonable use of second-hand goods, so this article considers that it is necessary to establish a campus second-hand market trading website based on the actual selection of multiple universities. The campus second-hand market transaction system is a typical example of the integration of computer technology and economics technology. Using this system can timely release transaction information and complete online transactions. The system discussed in this article is a combination of C# and SQL, based on the B/S mode of web application software, to achieve the collection and management of student secondary market trading goods related information. This article first analyzes the background and significance of building a campus secondary market trading system, and proposes a website design idea; then introduces the tool technology required to build a campus secondary market trading system, and finally explains the design of each module required by the system Give the overall functional design and database design of the website.

With the rapid development of the Internet of Things technology, the use of sensors to collect data has become a more popular method, but because of the different environment of the sensor, the working state of the sensor must be relatively high, such as in greenhouses such as high temperatures In a high-humidity environment, whether the sensor can work normally; in a continuous working condition of 7 * 24 h, whether the data collected by the sensor can be trusted is a question that must be considered. In the real environment, the environment is complex and changeable. The data collected by the sensor may be inaccurate. In more extreme cases, the sensor may not collect data, that is, there is missing data. In order to deal with the missing data, this article takes a greenhouse as an example, and compares the four dimensions of light intensity, carbon dioxide concentration, temperature, and humidity, and uses multiple interpolation methods to fill in missing sensor data.

The thesis has mainly studied the influence factors of campus express service satisfaction degree. Through investigation, the author has chosen indexes in accordance with the real situation of the campus express service at Jilin Agricultural Science and Technology University. Then the author has transformed the indexes chosen into the questionnaire. The author has carried out the investigation through the questionnaire by taking all college students at Jilin Agricultural Science and Technology University as samples. The author has adopted the factor analysis method and established the factor analysis model by means of SPSS software for the purpose of calculating the factor score and finding out the influence factors influencing the campus express service satisfaction. The author has then concluded that the professional services provided by the express staff, delivery speed and price level have great effect on the campus express services. The author has finally proposed reasonable suggestions on the campus express service from these three aspects in order to enable teachers and students in the university to enjoy the campus express service with higher quality.

Increasing the investment of enterprises in financial management information, can greatly improve the current situation of enterprise capital supervision, improve the utilization rate of funds, reduce the risk that enterprises may face in the process of operation, and can significantly improve the competitive strength of enterprises. In order to provide better Suggestions for the development of enterprises, this paper studies the financial management construction under the informatization. This paper first introduces the connotation, classification, operation mechanism of cloud finance and its influence on the financial management informatization of small and medium-sized enterprises. Secondly, based on the investigation and statistics of the financial management informatization platform of small and medium-sized enterprises in some regions in the information age, the algorithm of the platform was improved, and enterprise A was selected to put it into use and observation. The results showed that the operating efficiency was improved by 21.6%. Finally, the paper discusses the security management of the financial platform under the informationization in detail, and puts forward the way to optimize the financial management construction of small and medium-sized enterprises under the informationization.

With the deepening of economic globalization and China's “One Belt And One Road” initiative, cross-cultural communication among countries is increasingly frequent. Many countries and regions have listed Chinese as a strategic language. The main goal of international Chinese culture teaching in the new century is to cultivate learners' intercultural sensitivity and positive attitude towards different cultures in the world. The purpose of this paper is to provide better analytical Suggestions for cross-cultural communication by studying the cross-cultural communication competence of Hanban teachers based on artificial intelligence and big data. Grind Gui under the framework of narrative inquiry, the quantitative and qualitative combined with hybrid research Gui method, through the form of a questionnaire survey in four countries worked 52 international Chinese teacher, tried to improve them in the real Chinese culture teaching in cross-cultural awareness and cross-cultural teaching empirical research, practice, according to the results in the survey of culture teaching self-scores is around 3.5, still need further training on their intercultural communication ability.

Based on the power hardening model, using the relationship between bending moment and curvature and the formula of springback ratio, the curvature calculation formula after springback compensation of single curvature surface stamping is derived. Based on this, the springback compensation calculation method of complex single curvature surface is constructed. The springback compensation amount of micro plate element after surface discretization is calculated by discretization thought, and then the springback is obtained by interpolation method and difference method Front shape. The finite element analysis and experimental comparison between the interpolation method and the difference method for calculating the springback correction shape are carried out. The simulation results show that the final surface obtained by the two methods is more close to the target surface, which is in good agreement with the target shape, and the error is small. Therefore, compared with the difference method, the interpolation method has better forming accuracy.

Under the background of Traditional Chinese Medicine (TCM) going out to the world, the transmission process of TCM has become faster and faster. Translation of TCM plays a vital role in the “going out” of TCM culture. An electronic (online) dictionary which can quickly and accurately query traditional Chinese medicine vocabulary or terms can provide a convenient tool for TCM translators. This paper focuses on the research and development of TCM Chinese-English electronic dictionaries with hierarchical correspondence technology in order to make contributions to the compilation of TCM electronic dictionary and the development of TCM translation. The application of hierarchical correspondence technology to entry process, the initial establishment of the lexicon has been completed, that is, the basic corpus has been established. And a specialized dictionary software that can be used to query TCM terms has been developed. The work to be done in the future is to perfect the dynamic corpus and combine it with Internet technology to upgrade it to the Internet (online dictionary).

When making spiral submerged arc welded pipes required for transportation of oil and water, how to cut these pipes has always been a difficult problem. To this end, this paper developed a cutting device for the production of spiral submerged arc welded pipe. This device uses PLC as the data processing center of the control system, controls the electronic control components such as cylinder, push rod motor and cutting motor to realize a series of system actions such as feeding, unloading and cutting. The spiral submerged arc welded pipes of different sizes and different diameters are fixed by the cooperation of the upper and lower sets of rollers and springs. Through the touch screen to set the parameters required for each action, to achieve a closed loop system of cutting-detection-then cutting. After experimental verification, the device can fully automatically load and unload steel pipes, and can rotate and cut spiral submerged arc welded pipes of different sizes and different diameters.

The integration of ‘‘Internet plus’’ and cultural industry can stimulate the vitality of Chinese traditional culture and cultivate the cultural self-confidence of the new era. The advent of the ‘‘Internet plus’’ era has broken the traditional culture generation and dissemination mechanism, enabling cultural exchanges to be smoother and more accessible to every public. At present, we need to grasp the development opportunities brought by ‘‘digital communication’’ and ‘‘e-commerce’’ and devote ourselves to cultural co construction and sharing. This website adopts ASP.NET With visual studio 2010 and SQL Server 2005 as the development tools and windows 10 as the operating system, Baoji's bronze ware culture is displayed through the way of information website to realize the functions of cultural exchange, information release and online purchase.

In the era of information and diversification, the basic computer course as a general course plays an important role in improving students’ information literacy and modern skills. In this paper, aiming at the problems existing in the traditional course system, the practical teaching system at different levels is proposed to cultivate students’ application and innovation ability.

China's ‘‘Thirteenth Five-Year Plan’’ also incorporates Informationalized construction into the national strategic development plan through Informationalized construction, unifies offline and offline development space, expands new development areas in all walks of life, and builds an Informationalized road. Technology is the main carrier of economic and social development. With the continuous updating of information technology, the level of Informationalized is also constantly improving. Education is the foundation of talent training. The basis for improving the quality of the people is of great significance to the country and individuals. The core essence of education is to cultivate talents. The cultivation of international talents requires an international talent training system and an Informationalized education model. Under the Informationalized education model, the reform of the talent cultivation system tends to be more international.

A remote intelligent environment monitoring system is designed and implemented. The system can automatically monitor the temperature, temperature, illuminance and other parameters according to the market demand of large indoor feedlot and long-distance constant temperature transportation of fresh products, and transmit the monitored parameters to the Internet of things platform through wireless network. The keepers and transporters can easily log in to the things through web page link and scanning QR code Networking platform, view environmental parameters anytime and anywhere.

In order to accurately detect the concentration of brine, a new sensing technology based on capacitance sensing is adopted. Because the change of salt water concentration will cause the change of capacitance capacity, the circuit is designed to detect the change of capacitance capacity, and then the data is converted into 28 bit binary number and output to the microprocessor STM32. The sampling value is analyzed and processed in the chip, and then the data after the test processing is displayed by high-resolution tft144. At the same time, through the ultrasonic and electronic scale to detect the liquid level and weight, using the method of multi-sensor fusion for comprehensive processing, the accurate brine concentration information is obtained after calculation. Compare the two data and get the test data. The experimental results show the device with an accuracy of 0.1%.

There is a new marketing model which enhances the customers’ preference, motivates customers to make a purchases and ultimately enables the commercial value to be realized through the establishment of trust and emotional support between fans and KOL (Key Opinion Leader). This article elaborates on the main mode and characteristics of KOL marketing, analyzes the realization path of KOL marketing mode, and on this basis, proposes the benign development of KOL marketing mode.

The development of socialist advanced culture in universities is an inevitable requirement for strengthening the mainstream ideology education in universities, and it is also an urgent need to realize the goal of college campus culture education. As the main front for disseminating cultural knowledge, colleges and universities must always adhere to the advanced socialist culture and promote the all-round development of students. This paper aims to use AHP-fuzzy to evaluate the development of advanced socialist culture in universities, and to provide a reliable path for the development of advanced socialist culture in the field according to the weight distribution of fuzzy evaluation results.

This paper mainly uses the reliability test of the scale to test the questionnaire survey. The four factors are the teacher factor scale, the student factor scale, the learning environment factor scale, and the classroom interaction effectiveness measure index scale. Reliability test is performed on the table. If the variable is greater than 0.7, the reliability is good, and the principal component principle is used to evaluate the students’ different learning situations as a whole. In terms of experiments, this paper mainly selects two classes for a school. One for the control class is traditional teaching, and the other is an experimental class, which uses the Internet to integrate traditional education and teach separately. It is mainly discussed in terms of the number of classroom questions, participation in discussions, the number of pre-class previews, online answer scores, homework scores, and overall evaluation scores. The experimental class scores are better than the control class. But in terms of the number of pre-class previews, the control class is higher than the experimental class. Therefore, as far as the integration of the Internet into traditional education and teaching, it may cultivate students’ inertia and test their consciousness. And after the integration of the Internet into traditional teaching, students’ satisfaction with learning is higher than that of traditional teaching, which also greatly promotes the integration of the Internet into traditional teaching.

In the process of complex network modeling training, when the uncertainty relation is used to judge whether the overfitting phenomenon occurs, the overfitting parameters in the discriminant are too large to be determined, which greatly limits the role of the discriminant in guiding the modeling process of complex network. The purpose of this paper is to provide technical advice for rapid network fitting through the research on the method of rapid network fitting based on deep learning (DL). This paper proposes a fast network fitting method based on DL. Simulation results show that the speed of this method is 21.67% higher than that of the traditional algorithm, which proves that this method is feasible.

Financial management consulting is an important method for enterprises to improve the efficiency of financial management and enhance financial service. Therefore, it is necessary to pay enough attention to the financial management consulting work, so as to lay a solid foundation for the effective development of the financial management work of enterprises, so as to ensure the expected effect of financial work. Based on this, this paper studies the basic ideas of enterprise financial management consulting. Through field investigation, this paper understands the current situation of financial management consulting of some enterprises in a certain place in recent years, analyzes its characteristics, and combines the procedures and methods of financial management consulting to analyze the three stages of financial management consulting: preparatory consulting stage, formal consulting stage and scheme implementation stage. Through a comprehensive study, the basic idea of financial management consulting is obtained. First, it is a strategic analysis. Then it starts from the related requirements of consulting and sets the standards to find out the problems. Then it finds out the reasons according to the internal relations of the problems. Finally, it makes a specific financial management consulting plan and optimizes the upgrading.

With the rapid advancement of Internet technology, the operation mode of Internet finance is gradually showing diversified characteristics. The future of the financial sector will be a full possibilities of industry, traditional financial aid will amount Internet showing a trend of Hewlett-Packard, and therefore analyze the nature of the development of different modes of operation and internal issues, and for which the advantages and disadvantages Putting forward sustainable development strategies has certain practical significance.

Compared with the traditional fund-raising model, the Internet gains the following advantages due to the convenience of its platform: low barriers to entry, short capital cycle, and sufficient data and information. This allows small and micro enterprises to quickly and easily obtain the necessary development funds. However, if the Internet financial system has not been strictly controlled by law, it will face the tragic situation that criminals use loopholes to disrupt transactions and cause additional losses. This article strives to reveal the existence or potential problems of small and micro enterprise financing innovation in the context of Internet Finance, and proposes solutions and solutions for improving the financing platform.

The advent of the mobile Internet era has not only brought convenience to people’s lives, but also produced massive amounts of information. As a mobile social tool in the new era, WeChat is not only an important medium for information acquisition, information sharing, interpersonal communication and social participation, but also an important platform for obtaining economic benefits and self-realization. Research on WeChat media user information sharing behavior has become the focus of scholars’ research and Popular topics. Research on information sharing behavior of self-media users is becoming more and more important. This article summarizes the characteristics of social media and the behavior characteristics of media users in a social media environment. This article first selects the two most influential social media platforms in China in recent years-Weibo and WeChat, Multi-dimensional summary of the characteristics of the two platforms Weibo and WeChat. Then the questionnaire method was used to investigate the media users of Weibo and WeChat. The basic characteristics of media users, usage, characteristics of information sharing behavior, factors affecting information sharing behavior, and users’ knowledge of Weibo and WeChat platform were investigated. Data survey. On this basis, suggestions are made on how social media operators can encourage and guide the information sharing behavior of media users and optimize information sharing services. The survey results show that more than 83.18% of Weibo media users and more than 94.70% of WeChat media users have expressed a more acceptable attitude towards marketing information sharing.

[Objective] Video surveillance technology is more and more used in all kinds of scenes, and a large number of surveillance videos are produced every day. In the video, most of the data are normal events, however people focus on only a few abnormal events, how to find individual abnormal events in the massive video is the focus of current research. [Methods] Firstly, the dense optical flow of video is obtained, and the information of optical flow is transformed into the histogram feature of optical flow. Secondly, the space-time cube of video is constructed by using the space-time correlation of video. Finally, sparse representation method is used to model the whole process. [Result] The part in the video with too much reconstruction error is considered as abnormal event. Experiments on the UCSD dataset show that proposed method can effectively detect the abnormal events in the video. [Conclusion] In this paper, a video anomaly event feature and an anomaly detection model are proposed, which provide support for further research.

The intelligent age calls for comprehensively deepening the reform of basic education and teaching, reforming the traditional classroom and improving the students' core quality, which are the key tasks in the informatization construction and application of basic education. This paper proposes to gradually realize the precision education governance service based on big data from the Micro and macro perspectives: curriculum construction, demand-oriented, policy-oriented, multidisciplinary linkage, data governance, platform construction, and model development. The study also provides feasible implementation strategies for institutions of local education governance and management services, theoretical support for applied research and development of “Internet + education” in colleges and universities, and actively explores the difficult issues of promoting education data governance based on privacy protection and open sharing.

Nowadays, the competition in the manufacturing industry is more and more fierce, in order to save costs, improve production efficiency and automation degree, there is an urgent need for enterprises to improve the production line. In this process, the application of machine vision technology is more and more extensive, especially in the industrial production of location detection, development is particularly rapid. The purpose of this paper is to provide technical Suggestions for the optimization of the intelligent control positioning detection system based on machine vision and deep learning. This article is to major scientific research project “mechatronics” the researches on the mechanism of the low voltage circuit breaker intelligent test as the backing, in the research background of low-voltage circuit breaker production testing, using distributed control technology, testing technology and intelligent control technology, machine vision technology, sensor technology and combining with field production experience, research and development of intelligent control orientation detection system based on machine vision technology, the results showed that the rate of each link adaptation remain below the 112 ms. The system improves the existing manual testing method, which can quickly, stably and accurately detect the location, so as to adapt to the increasingly severe competition.

Electrical automation technology is the most effective way for industrial enterprises to improve production efficiency, ensure production and operation safety, and achieve good economic benefits. The purpose of this paper is to study industrial electrical automation control system based on machine vision and deep learning. By studying the latest progress of Scikit-Learn and machine vision, combined with the current development of electrical automation, this paper explores how to combine artificial intelligence with electrical automation. Taking the overall design of industrial electrical automation control system of disc casting unit as the research object, the experimental results show that through traditional electrical automation means and intelligent electrical automation hand In terms of the convergence of fault diagnosis and processing, the section makes rational prediction and statistical analysis. The convergence of deep learning automatic control technology is stable at 0.2 over time, which is superior to the traditional automatic control technology.

Artificial intelligence is also called machine intelligence. It is a comprehensive discipline developed by the penetration of multiple disciplines. Based on artificial intelligence, automatic control science has also gradually emerged and developed, and will become an inevitable trend in the development of industrial control technology. However, NCS itself has problems such as network induced delay, disordered data packet timing, and packet loss. This paper studies two artificial intelligence control algorithms, namely Smith predictive fuzzy PID controller and generalized predictive control based on dynamic BP network error correction, and applies it to network automation control system to reduce the impact of delay on system control performance: Finally An automatic control system for ink color presetting of color newspapers is designed, and fuzzy PID control algorithm is applied to the system to realize the control of the ink output. Aiming at the non-stationarity of the signal to be cancelled, based on the research of traditional nonlinear filtering, we design an artificial neural network as an adaptive processor, relying on its powerful functions similar to the human brain to solve the inherent defects of the conventional filtering mode. The introduction of neural networks has greatly improved the ability of the system to solve complex and highly nonlinear problems. The model designed in this paper has laid a good foundation for solving nonlinear system problems, and the algorithm has a moderate degree of complexity, which has high application value. Experimental research shows that the method is verified by MATILAB experimental simulation to improve the stability of the system and make the system have good dynamic performance and robustness.

Design and technology has become an important driving force for the development of UK building. Data-assisted design is a combination of data, design and technology, which makes British architecture more dynamic. This paper focuses on the current situation of British architecture in the context of energy-saving and emission reduction. With the emergence of some newly designed methods and intelligent technology, it is worthwhile to explore how the design and technology of these can improve climate change in terms of the British building and discuss the relationship between the design, technology and performance of British building. In addition, digital design and modular design will be analyzed in this paper.

Against the background the continuous improvement of modern information technology in China, human society has entered the information era, and big data technology was correspondingly emerged. The industries including auditing were promoted with internet technology and cloud computing technology. The application of big data technology provides the audit industry with new working methods and technologies. In order to achieve sustainable development, the audit industry is required to integrate the development trend of modern society and recognize the importance of big data technology from the perspective of thinking, so as to lay a foundation for the sustainable development of the audit industry. The main content of this paper is to explore the practical application of data technology in audit practice with the aspiration of providing some reference for the development of audit practice in China.

The rapid development of data mining in recent years provides new research ideas and methods for hydrologic time series similarity, which can be used to mine hidden patterns and laws in massive hydrologic data as well as useful information for predicting hydrological processes. By using the hydrologic time series data, through the deep learning and data mining related technology, the hydrologic time series prediction research. In order to better study the hydrological time series similarity based on data mining, this paper use the integral autoregressive moving average model (ARIMA) model for linear autocorrelation is part of the hydrological time series prediction, then use support vector regression (SVR) model to predict nonlinear part, the forecast results together and get the confidence of A confidence interval, which determine the actual value is not in the confidence interval of outliers, the last in α river basin liuhe measured data validation of the test sites, the results show that the similarity detection efficiency of 32.9%.

Conflict matrix is a very frequently used tool in the theory of inventive problem solving (TRIZ). It describes 39 engineering parameters of conflict and 40 principles of invention to establish a corresponding relationship to solve the problem of TRIZ conflict in the design process. The LT table proposed by bartini can get a solution similar to the conflict matrix, in order to make the solution of the conflict problem closer to the Ideal Final Result (IFR), the two methods are combined to search for the key factor X-resources of the Inventive Problem Solving (ARIZ). At the same time, according to the advantages of LT dimension in dimension analysis, the X-resource is further estimated and optimized, which improves the efficiency of X-resource search in ARIZ, and makes the final X-resource characteristics closer to the requirements of ideal solution. Finally, the process of TRIZ conflict X-resource solution based on LT table is summarized. The validity and practicability of the method are verified by the sealing of medical ampoule bottle.

In this paper, by combining the gray system theory and analytic hierarchy process to process product big data and evaluate product quality to determine the standard, through the questionnaire survey and expert interviews to determine 16 product quality indicators. This paper adds the relevant indicators of ecological quality “degree of pollution to the environment and reasonable use of resources” to establish and improve the product quality evaluation system. Taking the refrigerator of Midea as an example, the internal quality, appearance quality, economic quality, market quality and ecology of the product From the perspective of quality, the quality of the selected three models of refrigerators can be evaluated, and the quality of refrigerators under the unified standard evaluation system can be reflected intuitively through quantitative methods.

Economic globalization promotes closer economic ties among countries, and may also lead to a wider spread of economic risks. It is of great significance to study the transmission mechanism of financial risk. In this paper, the multi-scale tail risk transmission mechanism of Chinese and Russian stock market based on spatiotemporal Kriging model is studied. In this paper, the stock market of China and Russia is taken as the research object. Based on the Kriging model of time and space, the variance decomposition is studied. In this paper, we find that the maximum value of Ru share is 2.035% in the results of variance decomposition of SH series and 0.861% in the results of variance decomposition of Ru series. The multi-scale tail risk of Russian stock market has a relatively significant impact on Chinese market, while the multi-scale tail risk of Chinese stock market has a relatively low impact on Russian market.

The paper explores the transformative learning of three college English teachers. The study was conducted to understand how transformative learning contributed to their teaching and researching competences and their ways of thinking. The reflective journals, interviews and classroom observation were used to clarify the phases of their transformative learning and identify the outcomes of their transformative learning.

Since the implementation of the vehicle purchase tax in 2001, car sales have grown rapidly in China, and the sales of small-displacement vehicles have been increasing year by year. Sales of small-displacement vehicles have a positive impact. Due to the rapid development of information technology, big data plays a key role in recording consumer preferences and consumption needs. This article collects car sales data on the Internet platform, uses a double difference model to perform regression analysis on the data, and finally concludes that after the cancellation of the purchase tax preferential policy, the sales of small displacement cars are indeed negatively affected.

Customer service industry is an important part of the national economy. This article studies the service quality of China’s customer service industry in 2019 based on big data from three perspectives: customer satisfaction, customer complaints and service brand building. By investigating eight customer service industries including commercial bank, online shopping, aviation, express delivery, auto insurance, express hotel, online travel and mobile communication, we collect a total sample size of 10800 questionnaires. By analyzing big data, this paper found that customer satisfaction of China’s customer service is at the upper level in global, but there still a huge number of service complaints and few excellent service brands. This paper provides constructive advices on China’s customer service quality construction.

With the advent of the era of big data and the advancement of economic globalization, driven by the “One Belt and One Road” (OBAOR) initiative, China’s cross-border e-commerce (CBEC) has achieved remarkable achievements, and quickly opened up broad foreign markets in the short term. This paper analyzes the development status of CBEC in Yunnan Province and the problems faced by CBEC logistics in the context of the OBAOR in order to provide advice and suggestions for CBEC in Yunnan Province to fully utilize the advantages of the OBAOR and continue its healthy development. This article analyzes the current situation faced by CBEC in Yunnan Province through a questionnaire survey on some CBEC enterprises in Yunnan Province. It was concluded that 88.70% of CBEC enterprises believed that trade and customs clearance took too much time and insufficient convenience; 90.40% of CBEC companies believe that cross-border logistics (CBL) and transportation costs are high and slow. Targeted solutions have been proposed for this purpose, which can provide reference and reference for the development of CBEC in Yunnan Province.

According to the characteristics of central heating system data acquisition, Introduced the composition of remote energy-saving wireless monitoring and control system based on cloud computing and the automatic control of heat exchange station, through the cloud platform to achieve data exchange between the user group and the remote heat exchange station collection site, and then the whole heating system is automatically controlled remotely, It solves the problems such as low intelligent management degree, field data can’t be analyzed and utilized, human resource waste, single control algorithm and so on, and achieves good operation effect.

In the unknown environment, the single image can not obtain the depth information of the landmark, which results in the difficulty of locating the landmark. In view of this, the map initialization method of mobile robot SLAM is studied based on conformal geometric algebra. According to the conformal geometric algebra framework, the landmark initialization model of two phase estimation is established. Due to the mismatch of object imaging features, the non-linearity and the possible larger condition number of observation matrix, combining RANSAC and factor normalization a landmark initialization estimation algorithm is designed. The simulation results verify the effectiveness of the proposed method for the map initialization estimation of mobile robots.

Integrated Marketing Communications (IMC) appeared and was then widely applied to branding and marketing disciplinary in the late twentieth century. IMC spreads “coordinated and consistent messages across various channels of communication” to increase the consistent brand image and reputation globally through the integrated marketing strategies, marketing communications, multiple media and the value of the Internet. This study aims to explore Chinese luxury market situation from Chinese consumer behavior analysis, followed by a SWOT analysis of Stella McCartney. The SWOT and quantitative analysis show that Stella McCartney has low reputation in Chinese market and low consumer awareness, but with the increase of Chinese young consumers attitudes towards on luxury brands, Stella McCartney still have opportunities in Chinese marketplace. It then conducted some strategic recommendations through advertisement, public relations, visual merchandising, and Guerrilla These findings of market research analysis would benefit for the marketer, merchandizer, and fashion retailors.

The country has built a multi-dimensional industrial structure upgrading index. Since 2008, the industrial structure of each city in Guangdong, Hong Kong and Macao Bay area is gradually transforming and upgrading. For the process differences, this paper mainly summarizes the following aspects. We analyze the economic performance brought by the upgrading of industrial structure of each city on the basis of the three upgrading modes of industrial structure: leading, unbalanced and lagging. At present, the Great Bay area of Guangdong, Hong Kong and Macao is transforming and upgrading towards “economic service”, but we need to prevent the trend of “deindustrialization”. In terms of the current transformation of the manufacturing industry, on the one hand, we should establish incentives to appropriately encourage the development of the manufacturing industry. On the other hand, we should guide the cities with low level to accelerate the transformation and upgrading of traditional manufacturing industry, so as to enhance the competitiveness of the whole Dawan District in the field of manufacturing industry. At the same time, considering the producer service industry, reasonably adjust its key development producer service industry, build Guangdong Hong Kong Macao Bay area, so that it has a competitive modern industrial system in the international manufacturing industry.

At present, the economy and society in China has developed, and infrastructure construction in China has been effectively upgraded and developed. Especially in the power industry, power and other facilities and equipment have good development prospects. Based on the background of informatization, power enterprises innovate and create themselves to meet the power demand of all users in our country. By introducing such Internet technologies as big data, power equipment can be effectively improved and upgraded. However, in the context of modern network technology, in the process of power system upgrading and transformations, attention should be paid to the protection and safety of power system to avoid security problems resulting from incompatibility between software system and power system. Therefore, this paper mainly analyzes the current status of security and protection of power system, discusses the problems of software testing system in security and protection of power system based on modern network information technology, and analyzes the application of software testing technology in security and protection of power monitoring system, so as to effectively avoid the loopholes and reduce risks in security and protection of power system.

With the rapid development of science and technology and the rapid development of artificial intelligence, UAV aerial survey technology has also developed rapidly. UAV technology and image fusion and many other technologies, not only to FIG faster, but also a high accuracy mapping, can be applied to a variety of complex terrain. In this paper, a small UAV aerial view of discrete image, change the viewing angle characteristics of the SIFT algorithm has been improved in order to improve image registration rate. In this paper, Harris feature points and SIFT feature vectors are used to extract image features, PCA is used to reduce the dimension of feature vectors, BBF algorithm improves the matching speed, and PROSAC algorithm refines the feature points to achieve automatic image registration. Through the detection of 12 aerial images of unmanned aerial vehicles, the matching rate of the algorithm proposed in this paper reaches 98.55%; A topographic map in a range of plant 1.2 km2 the accuracy of analysis, the method of the large scale topographic map has good effect in complex terrain conditions. The research in this paper effectively improves the overall level of application of UAV aerial survey technology in power surveying and mapping.

After the education reform in China, we pay more attention to the cultivation of quality-oriented education and that of students’ ability to meet the needs of contemporary talents and development. Auto CAD has a wide range of applications and plays an important role in many fields, so there is a great demand for Auto CAD talents with high-quality and high-capacity. Research can be conducted on teaching reform of mechanical drawing and Auto CAD based on task-driven combined with mechanical drawing and the possibility of task-driven development in Auto CAD teaching, which enables people to understand the concept and characteristics of driving in the research process. In the process of teaching reform, we should formulate teaching reform measures based on the current status of mechanical drawing and Auto CAD teaching, optimize mechanical drawing and Auto CAD teaching, so as to cultivate talents with high-quality and high-capacity in mechanical drawing and Auto CAD.

Distribution network feeder fault location based on multi-feature joint judgment is an important content of distribution automation, which has a great impact on improving power supply reliability. Due to the wide distribution of multi-featured distribution networks, it is difficult to achieve effective positioning. Therefore, the research on automatic positioning method of distribution network feeder with multiple features and its realization equipment has important engineering practical significance. In this paper, the K-fault diagnosis method of analog circuit diagnosis is applied to feeder fault location based on the characteristics of multi-featured feeder faults in the distribution network, and its specific implementation scheme in feeder fault location is described. In this paper, based on the characteristics of multi-featured distribution network lines, a wireless sensor network is researched and designed. The sensors installed on the distribution line complete the collection and preprocessing of voltage, current and other information, and the collected synchronization data. The information is transmitted to the monitoring center through the wireless communication network, and the monitoring center analyzes and processes the information. This article realizes the fast determination of the fault location. A 10 kV cable line model was established, and the feasibility of the program was simulated and analyzed using Matlab. The results show that the program can accurately determine the location of the ground fault according to the change of the zero-sequence current amplitude, and solve the traditional fault location technology. Problems such as long time and poor positioning effect have high application value for the fault location of cable lines with multi-features in a large range. The experimental results show that when a small metallic resistance is used for grounding, when a large ground signal flows, the measured signal is 1.5 mA. The same reason and method can gradually reduce the measurement range and finally determine the fault point.

This paper analyzes the fault characteristics of AC and DC side failures under various operation control methods by building a DC distribution network with a typical topology structure. Due to the small fault damping of the DC distribution system and the rapid development of faults, the research on various faults on the DC line has a guiding effect on the reliable protection of the actual system. Through theoretical analysis and simulation, the fault characteristics of various types under various operating modes are theoretically analyzed and verified by simulation.

It is of great significance to establish a set of evaluation index system and related comprehensive evaluation model for auxiliary service market trading mechanism [1]. The index system of three-tier auxiliary service market mechanism is constructed from four aspects: technical assessment, market conditions, market behavior and market performance. Combined with the characteristics of the hierarchy and fuzziness of the system, the fuzzy comprehensive evaluation model of the market mechanism of multi-level auxiliary services is established, and the model is verified by taking PJM FM auxiliary services market as an example [2].

Based on the time-sharing price and the technology of interaction between power grid and electric vehicle, the V2G model of electric vehicle is established. Taking the minimum user cost and load fluctuation as the objective function, the charging and discharging model of electric vehicles, wind power generation, photovoltaic power generation and thermal power generation systems are constructed. When solving the optimal solution of the model, genetic algorithm is used. After the optimal solution is obtained, the optimization model can make use of the random residual power, reduce the abandoned air volume and light volume, and achieve the purpose of restraining the load fluctuation and reducing the user cost.

With the increasingly prominent energy and environmental issues, relevant experts and scholars began to focus on renewable energy. Based on the construction of the boundary conditions of electric vehicle charging and discharging, renewable energy, and petrochemical energy, a coordinated scheduling model of electric vehicles and renewable energy is constructed. The genetic algorithm is used to optimize the multi-source dispatching with the stable operation of power grid, the lowest user cost and the minimum load fluctuation as the objective function, and the example is verified and analyzed.

The purpose of the ship monitoring system based on mobile public network is to improve the safety of ship navigation, and provide guidance and help for the daily management and safety rescue of ships. The system integrates ship dynamic and video monitoring, uses CDMA1X wireless communication technology to transmit GPS dynamic positioning information, and uses multi-channel CDMA1X channel bundling to expand bandwidth technology to transmit ship video information, which not only improves the speed and quality of wireless transmission, but also ensures a lower implementation cost. This paper introduces the structure of the system and the function realization of each part in detail. The actual test on ro-ro passenger ship of Yantai Dalian line in Bohai Bay indicate that: The actual bandwidth of single channel CDMA1X is about 40K, and the image transmission can reach 5 frames per second; the binding bandwidth of four channels CDMA1X is about 150–200k, and the image transmission can reach more than 15–20 frames per second, with good continuity, which fully meets the actual needs of ship monitoring.

The digital clothing mall is the product of the rapid development of 5G virtual reality technology and network technology. It surpasses the existing Internet e-commerce platform and realizes the “human-machine integration” of e-commerce and the immersive three-dimensional effect. The analysis of the differences and similarities between the dynamic VR display of digital clothing display design and traditional animated clothing design provides a theoretical basis for the combination of VR and clothing display system design, which has important theoretical and practical significance. This article analyzes the advantages of 5G virtual reality technology based on the current status of product display on the Internet, attempts to apply the traditional display design concepts to the network-based virtual display system, builds a network-based digital clothing store virtual display system, and creates A new three-dimensional product display method. In this paper, on the Virtools development platform, the user’s autonomous roaming in the scene and the interactive script of the product are designed in detail. Secondly, the principle of the core collision detection technology in 5G virtual reality technology is explained, and a script program for collision detection is added to the interactive function program of the clothing mall to avoid distortion and distortion. In-depth research was conducted on the display and dissemination methods of VR for apparel malls, building a display and dissemination model of apparel malls based on VR technology, and combining design elements of user experience to derive relevant design principles and communication strategies. And through a large number of questionnaires and interviews, the user’s needs were initially obtained and the needs were finally graded using the kano model. Survey research shows that 35% of people understand the dynamic display of clothing VR through the media, and the public’s understanding of the dynamic display of clothing VR has shown an upward trend in recent years.

Consumers pay attention to personalized needs in tourism, and traditional travel methods have been unable to meet the needs of social development. As an innovative model, smart tourism embodies a new tourism development concept and management mechanism. This article aims to analyze the problems existing in the development of smart tourism in the A place to promote the healthy and sustainable development of the tourism industry in the A place. This paper investigates the development of smart tourism in A place and analyzes the satisfaction of tourists. The overall satisfaction of tourists is high, but the satisfaction of transportation and mobile terminals is low. The score ratio is 83.18% and 84.78%. Through interviews, it is found that customers think that waiting in the queue is too long, and the real-time parking situation cannot be intelligent and convenient. On the mobile terminal, customers think that downloading APP is too troublesome. According to the shortcomings and problems in the development of smart tourism, corresponding improvement strategies are proposed to enhance the tourist experience of tourists and promote the balance and sustainable development of smart tourism.

Agricultural data grows geometrically and conform to the characteristics of big data due to agricultural informatization. In addition, given some characteristics of agriculture itself, such as multitudinous types of soil, complex crop varieties, and the relationship and influence between fertilizer, water and climate, the above-mentioned make the database and knowledge base about them are large, multi-dimensional, dynamic, incomplete and uncertain. The use of big data processing method can extract and dig out potential correlation and rule that helps to explore agricultural information. This article designs and realizes the process of building a processing platform of smart agricultural big data based on Hadoop targeted at characteristics of agriculture and data research status of agriculture big data from home and abroad, with the objective of enhancing modern agricultural efficiency in an all-around way.

Based on Baidu Index, 223 pharmaceutical stocks selected from the CSI 300 index from November 1, 2019 to June 8, 2020 were selected as research samples. Fama-French three-factor model and panel regression analysis were adopted to study the impact of investors’ attention to COVID-19 on the pharmaceutical stock market. Based on the three-factor model, this study explained the impact of investors’ increasing concern about the epidemic on the medical stock market from three dependent variables of return rate, trading volume and amplitude. The results show that investors’ attention to COVID-19 has a significant positive impact on the return, volume and amplitude of the pharmaceutical stock market during the same period.

Transportation has achieved rapid development from “bottleneck restriction”, “basic mitigation” to “preliminary adaptation” to “moderate advancement”, and has already possessed the basic conditions of “first lead”. Transportation promotes the logistics industry to reduce costs and increase efficiency is not a unilateral income, but a mutually beneficial interaction process, especially the development of the logistics industry is of great benefit to the comprehensive transportation construction. This paper takes the transportation link of logistics as the research object, analyzes the influencing factors of the transportation industry’s various factors on the cost reduction and efficiency of the logistics industry, and uses the gray correlativity analysis method to analyze the influencing factors.

The article is to explore the relationship of employees’ stress and satisfaction level in a power corporation and the influence of their mental health on job satisfaction in the context of the Internet. 3 assessment scales based on mobile Internet were conducted to measure and analyze the stress level, mental health level and job satisfaction of a sample of 36 employees of a power corporation of southern China. Methods of Chi Square test, correlation analysis and multiple variable regression analysis were used in data analysis. Results indicate that differences exist among different types of work in such aspects as the total score, coercion score, interpersonal sensitivity score, depression score, anxiety score, terror score, bigotry score, and psychotic score. There are bipartite correlations among stress level, mental health and job satisfaction. It is revealed that the effect of stress level on job satisfaction was greater than that of mental Health (P < 0.001). The factors of depression level in mental health significantly affect job satisfaction, sense of responsibility, satisfaction with working conditions and extrinsic reward level. Somatic symptoms and depression symptoms in mental health affect the overall job satisfaction and extrinsic reward level of employees, which can explain the 40.8% variance of the overall job satisfaction. The variance of extrinsic rewards was 33.5%, which indicates that somatic symptoms and depressive symptoms have significant effects on overall job satisfaction and extrinsic rewards.

With the growing development of computer technology and sensor technology, artificial intelligence has been applied to a variety of scenarios, providing solutions to problems in different industries. It is a new dimension in the research of machine vision artificial intelligence to perceive and recognize human biological information, such as physiological state, emotion and biological identity, which contributes to making auxiliary judgment and decision. Based on the extraction of human body-related biological information, this paper aims to review on three aspects which are image-based physiological signal acquisition, sleep information extraction and image-based emotion recognition. With respect to image-based physiological signal acquisition, blind source separation and Eulerian video magnification technology are two more commonly used methods for non-contact video to extract pulse information. Based on the principle of photo plethysmography (PPG), there are also many other methods such as signal weighting analysis and supervised learning algorithm, which are gradually applied to non-contact video acquisition of pulse-related physiological signals. In aspect of sleep information extraction, sleep quality can be analyzed through heart rate and breathing signals. When it comes to image-based emotion recognition, there is still some room for improvement in the accuracy of parameter extraction.

This thesis aims to establish a VR representation system for urban images, using different computer computation methods to change the viewing angle or enhance the experience, enhancing the further dissemination of the city’s image among stratified audiences, and combining real and media reproduction to make. The image of the city is reproduced in the media world to infuse views and construct meaning, so that the audience may understand the city from a particular perspective without even realizing it.

This paper adopts the viewpoint of image copy detection which combines local and global features, gives full play to the matching advantages of different image features, dynamically adjusts the weight of feature fusion according to the expressive ability of different image features and the image content characteristics of different image data sets, calculates the optimal weight allocation value, and proposes the dynamic update weight allocation calculation. This method further improves the accuracy and comprehensiveness of image approximate copy detection.

With the emergence and widespread application of intelligent technologies such as the Internet of Things and big data, many researchers have also begun to combine emerging technologies with food traceability systems. These studies have made innovations in data query and reading platforms or related encryption technologies. However, in traditional food traceability systems, data management information is still scattered, difficult to share, and difficult to trace. The purpose of this article is to study the food safety traceability technology based on blockchain technology. Based on the theoretical basis of blockchain technology, this paper proposes a traceability scheme formed by the combination of reverse search and recursive algorithm. Finally, this paper designs and implements a food safety traceability system. The experimental results show that the scheme proposed in this paper is more efficient than traditional traceability models. And by testing the performance of the system, the test results show that the system can meet the demand. In this paper, through testing the traceability rate of different schemes, the traceability rate of the scheme proposed in this paper is stable at about 1000 ms.

Electric vehicle is one of the typical products of new renewable energy technology. It can be predicted that new energy vehicles will completely replace fuel powered vehicles in the future. In order to speed up the mature process of new energy vehicles, this paper proposes a new concept of data acquisition and transmission system based on remote monitoring system of new energy vehicles. Using the outstanding achievements of human in the electrical field, a complete set of vehicle condition data monitoring system is established, and the performance optimization of new energy vehicles is realized by combining with automatic control technology. At the same time, a large number of effective parameters can be obtained with the support of the monitoring system. Through the analysis, we can find that the research in this paper can accelerate the development of new energy vehicle technology and industry.

The wide application of computer network in various fields has brought opportunities for social development and production technology. At the same time, computer network security has become an important part of the construction of information society, more and more attention has been paid by the whole society. The existing computer network security evaluation methods have many limitations, such as poor usability, limited application scope, easy to be disturbed and so on. Based on the neural network method, the computer network security evaluation method is studied. By analyzing the principle of computer network security assessment and BP neural network learning algorithm, the GA-BP computer network security evaluation model is established by combining genetic algorithm with BP algorithm. In this paper, the input node of the four-layer neural network is set as 268, and the output node is set as 4. The results show that the average error of GA-BP network is obviously smaller than that of BP network, and the running time of GA-BP network is shorter than that of BP network. It overcomes the shortcomings of slow convergence speed and long training time of BP network, and effectively improves the accuracy and efficiency of computer network security assessment.

Due to the advantages of non-tampering, non-forgery and anonymity of blockchain, it is gradually being used in electronic trading systems. However, there is a problem of low efficiency of querying historical information in the traditional blockchain electronic transaction system, which cannot meet the user’s basic query needs. To better solve this problem, we propose an index-based blockchain electric transaction query scheme in this paper. We construct the index directory of the BKV (B-Key-Value) Tree storage structure by modifying the storage of the B-tree, and based on the BKV tree, we store the transaction order number and the corresponding block number in form of key-value pairs by combining the characteristics of the blockchain system. At the same time, we also design the blockchain structure and query algorithm based on the BKV index directory. Theory and experiments show that the index-based blockchain electrical transaction query scheme can reduce the electrical transaction query time, thus effectively improve the efficiency of the electrical transaction query and improve the user’ experience with the blockchain electronic trading system.

We present an algorithm for fitting data points with normal constrains in Computer Aided Geometric Designed. Different from previous methods which interpolate the normal vectors accurately, the purpose of our method is to approximate these normal vectors. We make the normal vectors on the fitting curve are close to the normal constrains with their corresponding parameters. According to approximate the normal vectors constrains, we can control the shape of fitting curve. Our purpose is to minimize the square sum of inner products of normal vectors on fitting curve and normal constrain vectors. In interpolation, we need to minimize the square sum of the inner products and interpolate these data points, so we use Lagrange multiplier method to solve the control points. In approximation, the inner product terms is made as the fair terms, we minimize the weighted sum of the distance term and fair term to get the control points of the fitting curve. Finally, an example of this algorithm is demonstrated.

The rise of “cloud” industry and continuous innovation of network technology, more and more basic network architecture equipment is gradually integrated into the architecture based on the general processor platform, from traditional physical network management to virtual network management, gradually from flat the network structure model evolved into a layered network structure based on SDN. Network construction has become controllable and low cost, able to support the performance requirements of large-scale users or applications and massive data processing. There are many excellent high-performance network data processing frameworks on the market that integrate above technical solutions, such as 6wind, windriver, DPDK, PF_RING, Netmap, etc. This article introduces three common DPDK, PF_RING, Netmap high-performance network packet processing framework compares their advantages and disadvantages, and prospects for future development.

This paper studies the application of virtual reality technology in the field of traditional handicraft, analyzes the value of virtual reality technology in the protection, inheritance and development of traditional handicraft, discusses the integration of virtual reality technology and traditional handicraft, and explores the experiential value and the prospect brought by virtual reality technology to traditional handicraft in future.

In optical 3D measurement, the highlight caused by specular reflection often affects the measurement result, and causes great measurement errors or the inability to complete 3D reconstruction of measured objects. This paper adopts a highlight elimination method based on color spatial conversion and pixel filling theory. It first converts the collected image from RGB to YCbCr, so that the image brightness and chroma are separated. Then, it normalizes the brightness and uses the pixel filling theory to weaken the brightness of its highlight position. The experimental results show that the method can effectively eliminate the specular reflection on the surface of the object within a certain range.

As e-sports games are included in the Asian Games and the Chinese e-sports game team has repeatedly achieved good results in the World Series, domestic people have rethought and positioned e-sports games. With the improvement of the level, the number of domestic game population has risen dramatically in recent years, and the prospects are broad. E-sports games have a positive role in improving team coordination awareness, vision, concentration, spatial sensation, and decision-making ability. They are gradually being used in the field of sports training and have achieved good results.

The aim of considering the issue of order from ethics point of view is to standardize social intercourse and refine network environment. Since the characters of cyberspace has no authority, no center and the character of virtuality; people get greater freedom in acting and expressing, the ethical disorder issue in cyberspace has become more and more serious. Its specific phenomena are the mental anxiety caused by the side-effect of internet technology, the dissimilation of ethical relations due to virtual communication and the ruin of ethical consensus raising by irrational public opinion. Therefore, the basic movement is to attach more importance to the moral reflection for internet technology, then to strengthen the construction of cyber ethics regulatory system and improve the capacity of self-purification for online opinions. Finally, the social capital could grow actively in cyberspace.

With the expand of science and technology, the scale and frequency of internet use are boosting gradually, and the expand of the electronic commerce in the country is rising. As the internet, Big Data has been a crucial resource for the healthy development of the electronic commerce in the country. By studying recent situation and prospect of the development of the electronic commerce in the country, this paper suggests ways to promote the development of the electronic commerce under the background of Big Data: enhance endogenous power of farmers, increase the strength of government guidance, and accumulate a sustainable talent team. These measures are crucial to the development of rural e-commerce in China.

Aiming at the problems of complex organizational structure, large number of participants and wide distribution of equipment involved in the shooting range optical measurement, the structure framework of the simulation training system is proposed based on the DoDAF architecture design concept and the requirement analysis of the simulation training system. The TD-CAP software is used to describe the operational view, system view model and system structure model of the system, and a more comprehensive and intuitive top-level conceptual framework of the shooting range optical measurement simulation training system is given. Through the analysis of architecture verification and evaluation, the integrity and consistency of the architecture are verified. It can provide ideas and reference for the construction of simulation training system and training organization.

This paper proposes a solution for real-time data integration of complex equipment in cloud computing environment, which involves data collection, preprocessing, integration, storage, intelligent analysis services and other life-cycle management. First, it analyzes the development status and serious challenges in the process of existing equipment data integration, puts forward the development direction that data comes from business and will also serve business, then analyzes the advantages of data middle platform in cloud computing data processing, the development prospect of edge computing integrated with intelligent processing, as well as the key technologies of combination of edge computing and data middle platform, finally according to equipment management. According to the application requirements and fusion characteristics of business and data fusion, the design scheme of data middle platform based on edge computing is proposed, and the equipment data integration architecture based on data middle platform is designed.

This paper discusses deep learning oriented PBL teaching design from the aspects of innovation of PBL teaching method, promotion of characteristic courses, integration of interdisciplinary content to form course resource and exerting the advantages of information technology application.

In this article, by using the generalized Riccati transformation and the integral average skill, a class of half-linear neutral delay differential equations are researched. A new oscillation criteria are obtained, which generalize and improve the results of some literatures.

Ancient Chinese machinery is an important part of ancient Chinese civilization. Through reconstruction research, we can better understand the past glory and enhance national self-confidence and pride. However, the traditional restoration research is lack of funds, research talents and unreasonable personnel structure. What’s more, the restoration research results presented in kind are not easy to preserve and display, so they can’t play their due benefits. Through the analysis and practical verification, it is found that virtual reconstruction research with the help of virtual reality and other technologies is an effective way to solve the problems encountered and make it sustainable.

When an electronic transaction occurs, the blockchain system needs to find out whether the accounts of both parties of the transaction exist. However, However, in the existing blockchain account storage solution, account information query efficiency is low, which seriously affects query performance and user experience. To this end, we propose a blockchain-based electronic transaction lookup scheme for grouped accounts. We combine the characteristics of Merkle Patricia Tree, by constructing the Merkle Patricia Tree account storage structure GMPT (Group Merkel Partricia Tree), to reduce the time of querying the accounts of both parties of the transaction during electronic transactions. At the same time, in order to efficiently cluster accounts, we improved the RFM model and K-Means clustering algorithm, and gave out the RFM model based on blockchain accounts and the improved account grouping algorithm AccountGroup. Experiments show that the blockchain electronic transaction query scheme based on account grouping proposed in this paper can effectively reduce the time to query the accounts of both parties in electronic transactions, optimize the query efficiency, and improve the transaction speed of the blockchain system.

Aiming at the reason that traditional face recognition algorithms are greatly affected by factors such as illumination and noise, a feature extraction method based on multi-scale and double-layer MB-LBP operator is proposed. First, extract three MB-LBP features with scales of 1*1, 2*2, and 3*3, respectively. Based on three different scale MB-LBP feature pictures, the MB-LBP features of the second layer are extracted, and then the respective histogram features are counted and all features are combined into a higher dimensional feature. Principal component analysis (PCA) is used to reduce the dimensionality of the fused feature data. Finally, support vector machine (SVM) is used for classification. By testing on ORL and AR face databases respectively, this method has significantly improved the accuracy of face recognition compared to traditional methods, reaching 99.5% and 99.2% respectively. In addition, in order to verify the adaptability of the algorithm to light and noise, through the brightness adjustment and noise addition to the face data set, and then test and verify. while the recognition accuracy of the traditional method has dropped significantly, the recognition accuracy of the algorithm is still more than 98%.

Along With the progress of the times and the rapid development of science and technology, the era of the Internet of Everything has arrived, and the rise of blockchain has opened a new chapter in technology. It has gradually been applied to the fields of finance, the Internet of Things, logistics, and public services, and has also developed rapidly in financial supply chain. With the support of blockchain technology, the digitization of accounts receivable, bills, warehouse receipts and other assets can be realized, and the data is retained to reduce the risk of ticket fraud and repeated pledge, alleviate the problem of information asymmetry, and reflect the blockchain. The smart contract properties of the company ensure the smooth development of supply chain financial services. However, blockchain technology has been widely used in the field of financial technology, but it still faces challenges in business, technology, and risk management. In order to better apply blockchain to the field of supply chain finance (SCF), this article starts from the status quo of SCF. Research and analyze industry pain points in traditional supply chain financing, and propose the application superiority of blockchain in SCF. At the same time, government agencies should actively adjust regulatory strategies to find a regulatory method suitable for the country’s development.

The research on the efficacy of intelligent clothing has been a hot topic at home and abroad. This topic by sifting through a variety of common different underwear fabrics, including cotton, blended and, polyester fabrics, such as, vertical combustion apparatus using cone calorimeter, air permeability tester, moisture permeability test instrument to study the existing fire underwear market in flame retardant, comfortable, such as performance, compare the difference of different fabrics, it can be determined based on the intelligent fire protection clothing of the polyester fabric carrier to make intelligent fire underwear of ecg monitoring function, the flame retardant performance due to the other two, at the same time comfortable properties such as insulation moisture permeability difference. 100% spandex and 15%–18% per square meter of silver plating are selected as electrodes to realize the long-term monitoring of human heart rate and electrocardiogram image by means of machine stitching.

Term recognition is the basic work in the field of natural fishery treatment. Now, the term recognition needs to be realized by machine learning algorithm, which requires a large number of corpus to train the model of the algorithm. At present, most corpus labeling needs manual labeling method, and the quality and speed of corpus labeling are problems to be solved in this field. Therefore, it is urgent to have a platform to assist in the evaluation of corpus labeling quality, so as to make the article labeling more efficient and accurate.

Aim of this study is to explore data ethics of big data technology business application. Using the method of literature research deeply, correctly understand and analyze the problem of data ethics of big data technology. The ethical problems brought by big data technology mainly include information security, privacy disclosure and data gap. The main reason for data ethics is that, from the perspective of data subjects, it is that the awareness of rights of data subjects is not strong; from the perspective of data related enterprises, the main reason is that data collection is driven by interests to infringe other people’s data rights; from the macro level, it is the lag of relevant legislation and weak supervision. The conclusion is that effective measures must be taken to strengthen the construction of data ethics to promote the sustainable development of data business applications. The government should improve the relevant legislation and the supervision of data. The collection and application of data should follow the principle of being informed and harmless. Technological innovation and control should be strengthened. The self-discipline construction of big data industry is strengthened.

Driven by the rise of new technologies such as big data, Internet of Things, and voice recognition, artificial intelligence has accelerated its progress in deep learning and human-machine collaboration. The advance in artificial intelligence has brought significant changes to the society. In the field of translation, the rapid emergence of internet translation tools poses potential challenges to professional translators. Meanwhile, it also brings unprecedented opportunities to the industry. This paper first reviews and summarizes the development of machine translation in China. Then, it analyzes the potential impact of artificial intelligence on the translation industry, and the competition and complementarity between machine translation and human translation. At last, the paper discusses the integration of machine translation with human translation, and visualizes the future prospect of translation technology, hoping to give reference to translators and translation researchers.

Firstly, The upper bound of the infinite norm of the inverse matrix $$ \varvec{A} $$ A for S-SDD matrix is given, Secondly, depending on the upper bound, combined with the newly constructed S-SDD matrix $$ \tilde{\varvec{A}} = \varvec{I} - \varvec{D} + \varvec{DA} $$ A ~ = I - D + DA , the error bound of linear complementarity problem of $$ \varvec{A} $$ A is obtained.

Software defined networking, as a new network architecture, has the advantages of numerical control separation, open interfaces, and network virtualization. However, the new network architecture of SDN still faces the risk of being attacked by DDoS. DDoS attacks not only damage the hosts in the SDN network, but also have a serious impact on the entire SDN. This paper uses PCA to analyze network traffic and detect DDoS attacks. The experimental results show that PCA detection can detect DDoS attacks well.

This paper analyzes the risks related to amphibious vehicle navigation, evaluates the safety risks, and puts forward a feasible solution to the possible risks. Based on Bayesian probability statistics and network reasoning, a quantitative calculation and analysis of the system risk distribution is performed to obtain the maritime navigation safety estimation results of the amphibious vehicle. The results have been verified in the QRA case, which provides beneficial suggestions for its maritime navigation. Traffic accidents related to maritime navigation of amphibious vehicles were estimated by Bayesian learning and Bayesian point estimation in this paper, and an amphibious vehicle maritime navigation traffic system analysis model was established, and its relative risk QRA was obtained through Bayesian networks. The risks related to maritime navigation of amphibious vehicles were evaluated, a safety risk assessment was carried out, and a feasible solution was proposed for possible risks.

This paper introduces a machine learning algorithm to evaluate the risk level of the current P2P online lending platform in my country. This article is divided into two levels: firstly, estimate the risk of online loan platform; secondly, assess the credit risk of borrowers on the platform. Introduce the unsupervised learning algorithm in machine learning dichotomous k-means clustering, classify online lending platforms, analyze the performance of various platforms, determine the level of each category, and give the risk rating results of online lending platforms. Further use the supervised learning algorithm to study the credit risk of the borrower of the online lending platform. This paper uses the K-Means algorithm and related functions in AdaBoost to achieve data crawling of such dynamic web pages. After the end, it was found that there were still missing data on some platforms, and finally a large amount of information on the official website of the P2P online lending platform was manually checked to collect the required data. After collecting the data, the author processed the string by constructing a large number of regular expressions to correct obvious errors and provide data consistency. The experimental research results show that this article sorts the classification results by analyzing the variable values of the online loan platform to obtain different classification levels. In order to better rate the online loan platform, the rating results are more comprehensive and accurate.

Put forward a kind of based on conformal geometric algebra (CGA) vector structure 3D mesh model representation method. In this method, the 3D mesh model with different dimensions is mapped to the corresponding basic element (blade) in geometric algebra, which unifies the representation of multidimensional data without losing the geometric structure. Geometric and topological calculations are also handled in a clear and coordinate free manner. Under CGA framework, the basic geometric, spatial and metric relations are formed by inner and outer operators. A CGA-based 3D mesh model representation method is designed to evaluate the similarity of 3D mesh models. Experiments show that our method surpasses the most advanced similarity evaluation algorithm for 3D mesh models. Under the unified space structure of the method for analysis and application of 3D mesh model provides effective tools.

With the continuous development of the country’s economy, clean and clean advantages widely used, and the construction of small hydropower stations and grid power generation in promoting the green cycle of economic development is playing an increasingly irreplaceable role. Quasi-synchronizing parallel principle in this paper, the generator and the grid conditions are analyzed, and the grid controller design principle, qualitative analysis combined with the actual use of SJ-12d series controller, realize grid generator safely and successfully [1].

As the trend of globalization continues, financial markets around the world are becoming decentralized, making the way currencies are traded more and more open. Of these, digital currency transactions are the most affected of all transactions. This new model of financial transactions usually takes the form of automation, simplifying the process of intermediary and ensuring the security of financial markets by mimicking the mode of transport of the banking industry. Therefore, the global decentralized digital financial market model is feasible and has far-reaching implications in promoting the development of financial markets and optimizing the structure of financial markets. Based on this, this paper will discuss the feasibility of global decentralized digital finance in financial markets and the impact of global decentralized digital finance in financial markets from the concept of decentralized digital finance.

In this paper, an automatic announcer shot detection algorithm is proposed. Based on the statistical law of frequent occurrence of announcer shots, the candidate announcer shots are found out based on the automatic clustering method, and then the candidate announcer shots are confirmed by neural network classifier according to the temporal and spatial characteristics of the announcer shots. The algorithm is one of the important means to automatically analyze the content of TV news programs, and it is essential to establish a video database index. Experimental results show that the method is accurate and fast, and can be effectively applied to video retrieval system.

Artificial intelligence is a science to study the law of human intelligent activities. The application of artificial intelligence technology in College English teaching, combined with the development of auxiliary teaching language system, can effectively solve the problems such as lack of teachers and single teaching mode in the current college English teaching reform, and realize the sharing of teaching resources. It can effectively improve the quality of teaching, reduce the burden of teachers and strengthen students’ autonomous learning ability. This paper introduces the principle, characteristics and application fields of artificial intelligence, analyzes the problems of College English language teaching at present, and puts forward the implementation scheme of College English language assistant teaching system based on artificial intelligence technology. The system consists of two important parts: the expert system module of teacher’s English assisted instruction, which is based on the theory of expert system. It uses the combination of production and framework to express the knowledge in the field of English language, and uses uncertain fuzzy reasoning analysis to make the teacher understand the mastery of students’ knowledge points. In English language teaching, it uses neural network to establish the module of students’ autonomous learning system, Analyze the test situation of students, so that students can diagnose themselves.

With the emergence of cloud computing, a new network technology, the Internet has entered the “cloud” era of resource-based to service-oriented transformation. As an important part of China’s education system structure, modern distance education relies on computer network as the basis, so it will also meet new challenges. Cloud computing brings new ideas to platform construction and resource integration in distance education, and provides greater help for distance education with service as the core concept.

The effectiveness of Ideological and political education in Colleges and universities is related to the prosperity of a country. Practice is an important part of Ideological and political education. Practice base is an important carrier and position of practice. The construction of practice base system will have a significant impact on Ideological and political education in Colleges and universities. Cloud computing is a kind of scalable, virtualized and cheap computing mode through the Internet. The practice base system of Ideological and political education in Colleges and Universities Based on cloud computing technology can save costs, and has the characteristics and advantages of resource pool, cheap, sharing, reliable, agile, expandable, virtual, crossing the boundaries of time and space. Therefore, the author thinks that it is necessary for the state to adopt cloud computing technology to build the practice base system of Ideological and political education in Colleges and universities, and take the hierarchical organic filling construction mode to implement from the top-level design of the state macro level, and make case analysis and Discussion on the micro construction design and practice of colleges and universities.

With the development of AI products and services, the research and application of AI deep learning algorithm has gradually become the basic work in the development of AI. Among them, the modern accounting work is increasingly challenged. Due to the huge workload of accounting, the complex and tedious calculation, it is difficult to meet the needs of modern accounting management by using the traditional accounting models and methods, thus hindering the economic development to a certain extent. At the same time, China’s socialist market economic system has gradually improved, and the economic development has entered the deep-water area. The speed and efficiency of accounting and financial work play an increasingly important role in economic development. In today’s information age, the rapid rise of artificial intelligence in the field of accounting caused a heated discussion, because artificial intelligence can program accounting models and methods, it greatly simplifies the tedious and complex accounting operation process, improves the efficiency of accounting work, and promotes the rapid development of social economy. In essence, the AI deep learning algorithm is actually the AI machine learning algorithm, that is, the intelligent robot processes all kinds of source data collected by the corresponding algorithm, and makes relevant actions according to the final output instructions. It can be seen that the algorithm is the key factor affecting the effect of artificial intelligence. Based on the introduction of several common AI deep learning algorithms, this paper analyzes the application of AI deep learning algorithm to deepen the understanding and research of AI deep learning algorithm.

College students are the precious wealth of the country, the builders and successors of the socialist cause. How to guide college students to establish a correct world outlook, outlook on life and values is very important and of great practical significance. In the teaching practice of guiding college students’ value orientation, multimedia technology has been fully utilized, which is the inevitable trend of the development of higher education. The emergence of multimedia teaching has not only changed the study and thinking habits of college students in the past, but also brought new challenges to the value orientation of college students to a certain extent. Therefore, in order to improve the efficiency of College Students’ value orientation education, it is necessary to study the influence of multimedia teaching on Contemporary College Students’ value orientation education from many aspects. Based on this, this paper analyzes the importance of the value orientation education of contemporary college students, discusses the current situation and existing problems of the value orientation education of contemporary college students, and on this basis discusses the specific impact of multimedia teaching on the value orientation education of contemporary college students, in order to provide some beneficial basis for future research.

With the development of computer network technology and high-quality course recording and playing technology, micro teaching system is also developing in the direction of digitalization, intelligence and networking. On the basis of analyzing the new functions and characteristics of digital microteaching system, this paper puts forward a different strategy from the previous improved algorithm, that is, introducing clustering analysis in the pre-processing stage, so as to improve the association rule algorithm and realize the combination of the two algorithms.

Artificial intelligence is an important direction for the development of computer network technology, and it is also the key to realize the intelligence of information processing. In the era of big data, the rapidly increasing amount of network information and increasingly complex network environments put forward higher requirements for the application and innovation of computer network technology. Based on the intelligent development needs of computer network technology in the era of big data, the author analyzes the basic characteristics of big data, analyzes the advantages of artificial intelligence application, and focuses on the calculation of artificial intelligence in the era of big data The application of computer network technology.

Under the background of quality-oriented education, to promote the growth of students’ physical and mental health, many schools have not only set up psychological culture courses but also set up special institutions for psychological counseling and consultation. Professional psychologists can solve the psychological problems of students and help them to grow out of the “psychological shadow”. Applying data mining to the prevention of College Students’ psychological crisis is a new way of psychological counseling in recent years. Based on this, this paper takes the effective application of data mining in the prevention of College Students’ psychological crisis as the research topic and systematically expounds and studies.

With the acquisition of massive data resources, using big data mining technology to mine and analyze the characteristics of the collected data, making full use of the acquired data, mining the rules of activities, improving the ability of data service system, and providing the basis for the overall benefit of the data. This paper takes the most basic problems of data mining as the starting point, proposes the hot spot temporal and spatial law mining technology based on spectral clustering and the time-series change law mining technology. By further optimizing the data mining process, a data mining and analysis architecture is constructed to complete the mining and analysis of the characteristics between the data, to predict the future trend and behavior of the system, which is a prospective Knowledge-based system optimization decision provides support.

How to cope with novel coronavirus pneumonia is a major task facing school sports. The study holds that novel coronavirus pneumonia is a valuable means to cope with the outbreak of new crown pneumonia: the value of individual level is the material foundation of ensuring students’ life safety; family level value is an important force to activate the development of family sports; social level value is an important cornerstone for maintaining national physical health, and the value of national level is an auxiliary means of scientific prevention and control of the new crown epidemic situation. The application of information technology in college education has been very popular. At present, the construction of the digital campus information system in Colleges and universities mainly focuses on the electronic school affairs system and network teaching system. But in sports, most colleges and universities only use electronic information instead of manual operation to complete the teaching tasks such as course selection and evaluation. The mode of college sports 10 years ago, or even more than 20 years ago is still widely used Many problems are still unsolved. With the development of science and technology in the 21st century, the era of network information has come. The new science and technology provide strong technical support for the reform of physical education in Colleges and universities.

Water is our essential resource, urban water supply, and drainage is the lifeblood of the city, its design and construction directly affect the operation and development of the city. With the development of urbanization, the existing problems in the design of municipal water supply and drainage systems are becoming more and more prominent. The application of the concept of sponge city greatly improves the design quality of municipal road water supply and drainage systems and lays the foundation for the sustainable development of the city.

With the continuous development of educational informationization, cloud computing technology is widely used in Colleges and universities, especially in the development and construction of a teaching resource platform. Taking the music performance major as an example, this paper combs the teaching resource platforms of major domestic famous music colleges and universities, and on this basis, explores the possibility of the construction of a music performance teaching resource service platform based on cloud computing.

With the deepening of higher vocational education and teaching reform, building a shared teaching resource base has become an important embodiment of the development level and connotation of school information. By analyzing the problems existing in the construction, management, and application of the teaching resource base in higher vocational colleges, and introducing the idea of cloud computing technology, this paper expounds the feasibility and application prospect of using cloud computing technology to construct the shared teaching resource base in higher vocational colleges and finally points out the direction for the construction of the shared teaching resource base in higher vocational colleges.

The e-commerce platform in the era of the digital economy has evolved into a data platform ecosystem built around data resources and data technology systems, which greatly reduces transaction costs, improves production efficiency, and optimizes economic structure. This paper first introduces the macro environment of e-commerce development and the concept of e-commerce platform, then analyzes the evolution of the Chinese e-commerce platform and the operation mechanism of the e-commerce platform.

To achieve a comprehensive and accurate dynamic monitoring of sports fitness and avoid sports injury or excessive sports, this paper designs the overall functional framework of sports intelligent self-monitoring mobile device based on the application requirements of sports intelligent monitoring device, introduces the hardware and software design scheme of the device in detail and takes android as the platform support, The mathematical model of motion information is built. The MSP430 single-chip microcomputer is used as the control core. The mpau6050 three-axis acceleration sensor is used to collect, analyze, and process real-time data related to human motion attitude and intensity. GPS is used The positioning technology can track and identify the human body’s motion track. At the same time, the hardware and software design scheme of the device is introduced in detail. Finally, through the test, the device can realize the accurate detection of the motion state and meet the practical application requirements. Students are in an important period of forming long body, long knowledge, and world outlook. The healthy development of the body and mind urgently needs sports activities. The public fitness program has broad space, rich content, diverse forms, good selection performance, and meets the different requirements of students of different ages, genders, interests, and basic levels, This has a positive effect on the development of students’ personality, the improvement of their enthusiasm, independence and creativity in exercise, and the formation of their psychological characteristics. Therefore, it is of practical significance for middle school sports to carry out mass fitness programs.

Based on the analysis of the problems in the process of using the single machine running courseware downloaded through the network, this paper puts forward the significance of the design and development of the web-based courseware synchronous learning support system and introduces the design idea of a web-based English courseware synchronous learning support system in detail, and finally evaluates the system.

With the development and popularization of cloud computing, the fixed cost of the online system is almost reduced to zero. In the past, because of the high cost, electronic file technology, which can not be widely used, has entered people’s vision. This paper first summarizes the main contents of cloud computing and electronic learning files, analyzes the current situation of oral English teaching, and then puts forward the oral English teaching mode based on electronic learning files in the cloud computing environment, and conducts an empirical study. The results are of great significance to promote the research of Cloud Computing Assisted English education and serve the oral English teaching. At the same time, it proves that the oral English teaching mode based on electronic learning files is of great practical significance in the information-based teaching reform of colleges and universities in China.

In view of the absoluteness of judging the merits and demerits in the traditional PE teaching evaluation and the inconsistency of multiple evaluation conclusions, this paper constructs an independent advantage evaluation method that highlights its own advantages. In the evaluation, a probability based random simulation algorithm is used to evaluate the advantages of the evaluation objects by calculating the superiority among the evaluation objects. The effectiveness of the method is verified by examples, The evaluation conclusion with probability information is obtained.

With the rapid development of the Internet of things technology in today’s society, the optimization design and development of intelligent stadium system has become a major trend. Based on the analysis of the requirements of the Internet of things technology for system design, the K-means clustering algorithm of customer classification is used to design an athlete-centered system to improve the service quality of athletes; the system architecture model based on the network is used to realize information interaction and resource sharing among users with different roles. Taking athletes and service management as the core content of the system design and development, the intelligent stadium system is optimized from the system outline structure, system function, Internet of things architecture, and other aspects. The results show that the development and design of the intelligent stadium system under the Internet of things technology is helpful to realize the intelligent management of the stadium, and also can improve the management efficiency of the intelligent stadium, increase 28.0%, and play a positive application benefit. The research results show that under the Internet of things technology, the development and design of an intelligent stadium system can play a positive role and can be applied in practice. The positioning deviation of the original system is corrected.

To study the sterilization and cooling process of orange juice accurately, to ensure the quality of juice, and to reduce the energy consumption and production time, based on the analysis of the killing temperature of common bacteria in juice and the reliability of the model, the high-temperature sterilization and cooling process of canned orange juice was simulated. The results show that the optimal sterilization process is 95 °C, the 1020 s, and the optimal cooling process is 10 °C, 720 s.

In order to realize the sharing of learning resources in distance education and meet the needs of different learners, this paper studies the mode of dynamic transfer of teaching resource base of digital virtual machine in distance education. This paper discusses the mode construction of teaching resource base from three aspects of cloud computing technology, teaching resource base mode and key technology, expounds the logical framework and platform framework of resource base mode, and points out the broad prospect of cloud computing technology in the construction of distance education resource base.

This paper analyzes the types of image enhancement technology, mainly from two aspects of image space domain enhancement technology and frequency domain enhancement technology, explores its application methods and effects and puts forward the shortcomings of this technology, which is a kind of promotion for the further development of image enhancement technology. For example, using IFS system theory and l system theory in fractal geometry, using MATLAB language to generate self-similar and exquisite fractal patterns. It provides a new method for landform description, biological simulation research, art design, and other fields.

BIM Technology is an important method to solve the problem of coordination in the construction process of engineering projects. The construction project construction collaborative management method combined with control computing can be visualized in real-time and can dynamically control the calculation and simulation process. Through the analysis of the important role of the combination of control type calculation and BIM for construction collaborative management, the application of based on BIM theory, engineering collaborative management theory, and multi-objective optimization theory, the multi-objective optimization model based on IFC is established, and the combination scheme of control computing, coevolutionary algorithm, and BIM is designed to realize the calculation of multi-objective optimization model. The collaborative management model of the construction stage is constructed to integrate the multi-objective optimization process and the collaborative workflow of all participants in the construction stage. The construction collaborative model can effectively realize the collaborative work among the participants in the construction stage, the collaborative optimization of multi-objective, and the real-time visualization and real-time control of the process.

Cloud shoulder is an important part of traditional national costume art, and its color has national characteristics and cultural heritage. This paper proposes an inheritance technology for cloud shoulder color. First of all, with the help of MATLAB, the composition proportion of hue, brightness, and purity of the cloud shoulder is analyzed, and the color characteristics of the cloud shoulder are extracted. Then, in the pattern generation algorithm based on processing, the color feature is used to color the pattern, and the color pattern is applied to all kinds of modern design fields. This helps to analyze the digital generation and inheritance application of patterns based on the proportion of color composition and provides a new method of inheritance and innovative application of traditional clothing from the perspective of technology.

This paper focuses on the analysis of the informatization strategy of university education and teaching management in the era of cloud computing and big data. Firstly, it analyzes the current situation of university education and teaching management informatization in the era of cloud computing and big data, analyzes and designs a set of information management system through a collaborative filtering algorithm, realizes parameter setting, and then explains and discusses it from several aspects In the era of cloud computing and big data, the implementation measures of university education and teaching management informatization are designed to provide reference materials for relevant research.

Investment estimation is an important link in the feasibility study stage of residential projects. In this paper, a genetic algorithm is used to improve the BP neural network to estimate the construction and installation cost of residential construction project investment. Taking the project data of a construction company as an example, a genetic BP neural network model is constructed. Through the detection of the actual data, the error is within 10%, which meets the actual investment estimation needs.

The construction and application of task-driven teaching mode, with the periodic task evaluation as a supplement, forms a direct evaluation of the teaching effect of educational psychology in Colleges and universities, and provides objective and reliable effect information. The core of the whole task evaluation is to analyze the results of psychology teaching in Colleges and universities, to effectively establish the influencing factors.

The development and application of an automatic evaluation system in College English writing teaching is conducive to the construction of online courses and the reform of teaching methods and means. This paper designs the framework and function of an automatic evaluation system in College English writing teaching establish the database of the system and finally realizes the automatic evaluation system in College English writing teaching by using asp.net, SQL Server, IIS, CSS, jQuery, and other technologies. The system mainly realizes the upload of teachers' courseware and teaching documents, students; independent learning, after class communication, homework submission, question answering, and testing functions, which can provide a reference for the construction of open teaching platforms in schools.

With the explosive growth of data volume in the field of financial law, how to fully tap the effective value of big data, how to deal with big data computing tasks in a timely and fast manner, to provide users with high-value and high-efficiency services, has become a problem that needs in-depth study. The impact of the legal environment on financial development and their interaction, empirical research, and reference to a large number of financial professional data, the financial legal environment under different legal systems for the actual impact of financial development are described. In the era of big data, the processing model and application technology of financial legal analysis service are facing new challenges. It is urgent to further study the service model, combination method, and big data processing technology to meet the needs of service value and timeliness. This paper first designs the model, processing flow, and system framework of financial big data analysis service, and then studies the combination method of multi-perspective learning and the key technology of task scheduling, On this basis, a big data analysis service system of securities is realized, and the financial supervision, financial law enforcement, judicial and financial legal services are fully used to improve the financial legal environment.

Today, big data, cloud computing, and other technologies are widely used, data resources are being paid more attention by more manufacturing enterprises, and the ability of data mining, transformation, and application will affect the performance of enterprises to a certain extent. As an important person in manufacturing enterprises, accounting workers must learn to adapt to the development of the times, adjust the way of thinking and working methods according to the needs of modern enterprises, enhance their performance ability and innovation ability, to better play the accounting supervision function and realize the transformation of the industry.

Because of the problem of uneven energy consumption in a computer network, the theory of artificial intelligence technology is introduced. Based on the analysis of energy balance computer networks, artificial intelligence technology is applied to the research of energy balance in the computer network. Experiments show that this method enables better cooperation between the nodes of the computer network and maximizes the life cycle of the computer network.

Information technology is the general trend of economic and social development in the world. The integration of information technology and other disciplines has become a new bright spot of school education and teaching reform in the 21st century in China. The design and development of the network learning system have become a hot field of education research, And the “student-centered” adaptive learning system is gradually replacing the “teacher (system) centered” network learning system. Information technology provides a lot of information and various means for art teaching and provides us with deeper and broader potential for the teaching content, teaching methods, and learning methods of art. Therefore, art teachers must combine advanced education ideas and methods with information technology to better achieve the basic purpose of art teaching. In the process of art learning, they use audio, light, electricity, and other visual presentation to stimulate and attract the attention of students and stimulate the students to learn art. Finally, the user model ontology is established, and the user model is improved by data mining technology.

There are not only text images, but also the reality in Lilong. The contrast between memory and reality in Lilong forms a huge tension, which constitutes a lasting debate in the protection and renewal of Lilong. In the text, the neighborhood of Lilong is harmonious, the culture of the marketplace is prosperous and inclusive. The record of the text and the memory of the residents influence each other, which to a certain extent constructs the cultural image of Lilong and becomes Lilong.The carrier of protection. But in reality, Lilong is a low-rise house in a prime location, inhabiting a crowded immigrant community, where old houses coexist with the elderly population. The future of Lilong needs to be solved in memory and reality, and realize the transformation from residential function to cultural function in the way of diversity and sharing.

With the rapid development of Internet technology, distance education has become an important part of education in China, but the development of traditional distance education technology is not perfect, which has become a bottleneck restricting the development of network education. Because of the current situation and existing problems of distance education, this study combines cloud computing technology with a distance education badminton teaching platform and designs a distance education badminton teaching platform based on cloud computing technology. Through simulation test and comparison with traditional distance education platform, it shows that the platform has great advantages in user information security, resource storage and sharing, network service quality, and interaction, and has great research potential.

In this paper, the Apriori association rules mining algorithm is studied in-depth, and the algorithm is realized by MATLAB. To further avoid blind search in the process of mining and improve the efficiency of frequent itemset search, the improved technology of the Apriori algorithm is studied, and the application of the improved Apriori algorithm in teaching management is studied. The proportion of application and research data mining in the teaching management system of colleges and universities is still low, especially in the management of students’ scores, because there are many students, the amount of students’ scores that need to be counted is large.

In this paper, the export volume, real exchange rate, China’s GDP, America’s IPI, and their seasonal variables are used as the determinants. Three methods, BP neural network, ARIMA, and AR-GARCH, are used to model and predict the export volume of China to the United States. Select the error-index, and compare the simulation results and prediction results of the three models with the real values. The results show that the three models are satisfactory. Although there are some differences in simulation and prediction ability, the ARIMA model has obvious advantages. This paper analyzes the causes of the above results and puts forward suggestions for improving China’s export based on the model.

Given the problems of low accuracy and long time delay in the traditional intelligent collaborative processing of tourism information, this paper proposes an intelligent collaborative method of tourism information based on big data analysis. It analyzes the intelligent collaborative system of tourism information under big data, analyzes the non-linear time series of tourism information collaboration according to the analysis results of time-series network data, and fits the results according to big data Based on the analysis of the data law, the characteristics of collaborative tourism, such as tourism characteristics, tourism similarity, tourism filtering and so on, are calculated to improve the timeliness of the system Experiments show that the intelligent collaborative method of tourism information based on big data analysis has strong anti-interference ability and timeliness, and the strategy of studying and judging the massive information of big data analysis is high. It can classify the tourism information quickly and accurately, and extract the tourism products needed by users. The design of the system meets the needs of the tourism system for the processing of big data analysis information.

With the rapid development of scientific research capacity building and the increasing investment in scientific research infrastructure by the state, the fixed assets management mode based on financial management is far from suitable and can not meet the reality in the face of the huge instrument and equipment asset information, function information, use record, and other data and the lack of a unified and timely instrument information sharing platform. This paper proposes an intelligent management platform for scientific research instruments and equipment based on Internet of things technology to improve the sharing degree and resource utilization efficiency of instruments and equipment in the company internal, to effectively improve the fine management level of instruments and equipment and better serve the scientific research management.

Because of the characteristics that the verification device of intelligent electrical energy meter needs regular on-site verification according to the requirements of national verification regulations, we propose a remote automatic value transfer technology for the verification device of intelligent electrical energy meter, to establish and improve the intelligent value transfer traceability system and data analysis means, to reduce the labor cost and effectively improve the working efficiency and the management level of verification device.

The comprehensive economic strength reflects the economic development level of a city. In this paper, the weighted fuzzy clustering algorithm is used to evaluate the comprehensive economic strength of a city, and the algorithm of index weight is improved to avoid the problem that different attributes contribute no difference to the classification. Combined with the weight and fuzzy clustering algorithm, the analysis and evaluation scheme uses the weighted fuzzy clustering algorithm to evaluate the comprehensive economic strength of each city in a province. The results show that it is effective to use the weighted fuzzy clustering algorithm to evaluate the comprehensive economic strength of a city.

With the continuous development of the tourism industry, tourism education has been paid more and more attention. Most of the courses in tourism majors are practical. In the teaching process, to improve the teaching level, we need to make full use of modern education technology to improve the practical ability and comprehensive quality of students. This paper analyzes and discusses the application strategies of modern educational technology in the process of tourism education, aiming to improve the level of tourism education in Colleges and universities.

The evaluation of the development level of tourism resources informatization is a comprehensive evaluation and test of the performance of an MIS system. A good evaluation can promote the realization of the system design objectives and improve investment efficiency. In this paper, a method of using a BP neural network to evaluate is proposed, and AHP and fuzzy evaluation methods are used to evaluate the samples of neural networks. This method makes full use of the fuzzy mathematics theory and neural network method and provides a feasible way for the evaluation of the management information system.

With the rapid development of society and the rapid development of high-tech, modern pace drives people to follow the pace of the times. As a new discipline integrating art, landscape, design, psychology, architecture, human engineering, and other disciplines, environmental design major has to improve the teaching level and formulate the teaching mode and educational objectives to meet the social needs. This paper starts with the cognition of the environmental art design specialty of the project teaching method. Data mining provides a new intelligent way for people to understand data. Based on the brief introduction of the concept, mining process, and common methods of data mining technology, this paper discusses the application of decision tree algorithm in the data resources of environmental art design specialty in Colleges and universities, and the positive signs in the practice teaching of environmental design specialty. Furthermore, the specific practical steps of the application of the project teaching method in environmental art design specialty are proposed.

With the development of Internet technology and information technology, a digital intelligent learning system has brought a lot of convenience for information storage, transmission, and authentication process. However, the existing intelligent learning information system stores the data in the centralized database, which has a weak anti-risk ability for network attacks. The internal personnel of the system can also tamper with the data and erase the operation trace. Given the above problems, this paper applies blockchain technology to the construction of an intelligent learning system and studies the construction of intelligent learning systems under the background of blockchain technology. This paper compares and analyzes the concept of centralized management and decentralized management, points out the defects of the information centralized storage scheme of the intelligent learning system, and analyzes the shortcomings of the existing information system of blockchain intelligent learning system. Using appropriate blockchain technology and web technology, a four-layer blockchain application architecture is designed, which is composed of a blockchain layer, contract layer, data interaction layer, and application layer. We designed and developed the blockchain credit record module and certificate storage and forensics, realized the input and query of relevant information on the blockchain, and ensured the security and reliable traceability of information. The system construction based on the application of blockchain technology in intelligent learning is designed and developed, which takes the characteristics of decentralized blockchain technology and permanent preservation of data traces, records teaching information, and relevant operation records, and has the advantages of safe, reliable and reliable traceability, which makes exploration for the application of blockchain technology in the field of learning.

In view of the fainting situation of modern Chinese students in the process of sports and sports body side, the wearable detection method is realized, and the real-time monitoring of students’ physical quality through cloud computing is realized, and the research and design of students’ physical fitness monitoring system is realized. The sensor, Android system and low-power Bluetooth technology are used to realize the light-weight and portable exercise load detection system. The data is transmitted to cloud computing to realize the sensor data processing, so that the step counting can be carried out, and the precise measurement of the movement energy consumption can be carried out through the linear relationship between the acceleration integral of human body motion and the consumption of motion energy source. Using the combination of exercise energy consumption and step rate, it can effectively meet the needs of students’ sports load detection, and also can provide students with scientific and effective sports standards, so that students can get the best exercise load, and help teachers set reasonable planning for students, and effectively improve the scientific nature of sports. Finally, the system is tested, which shows that the load designed in this paper has a high detection accuracy of sports load, which can fully show the students’ physical state and effectively improve the efficiency of students’ sports training.

In the daily study work, we only fully grasp the advantages of various software, in order to better complete the work, now through the graphic design process example to experience the CorelDRAW and Photoshop software features and mutual relationship.

In today’s era, art colleges and universities inevitably have to intersect with big data, which has both opportunities and challenges. Starting from the introduction of big data, this paper studies and analyzes the current application status and problems of data resources in Colleges and universities, and makes some research and Analysis on the characteristics and shortcomings of art colleges.

To improve the efficiency of tennis forehand stroke, it is necessary to capture the error trajectory of the ball with a high resolution - P algorithm is used to capture the error trajectory of tennis forehand stroke. The linear image of the error trajectory of tennis forehand stroke is collected under the three-dimensional visual model. The wavelet multi-scale decomposition method is used to filter the error trajectory of tennis forehand stroke, and the feature points of linear edge contour of tennis forehand stroke error trajectory are extracted. The gray histogram is used the feature extraction method is used to enhance the gray information of the linear image of the ball hitting error trajectory. Combined with the block feature matching technology, the key action feature points of the tennis forehand stroke error trajectory alignment are located P algorithm realizes the error adjustment and correction in the linear capture of the hitting error trajectory and realizes the correct capture of the trajectory line. The simulation results show that the accuracy of this method is high, the image output signal-to-noise ratio is high, and the action correction ability is strong

Digital-image correlation method (DICM) has been developed in this paper. The initial estimates of both displacement and displacements gradients for Newton-Raphson iteration are studied. The new method of initial estimates, a real-time image subtraction scheme, and a micro-motion compensation mechanism being used to take zero as initial estimates are firstly presented and demonstrated. Some problems in the initial estimates and the convergence of Newton-Raphson iteration have been solved. The fracture behavior of PE composites is studied by using DICM.

Renewable energy refers to the energy that can be regenerated by raw materials, such as hydropower, wind power, solar energy, biological consumption (biogas), and ocean tide energy. This paper introduces the operation conditions and design scheme of the hydraulic driving system of the solar photothermal power collector. With the strengthening of global environmental protection, researchers all over the world are committed to the utilization and research of renewable energy. For China, coal is the main energy production structure for a long time, and the problems of energy shortage and environmental pollution have become increasingly prominent, which have become two major problems restricting the sustainable development of China’s economy. Therefore, it is advocated to optimize the energy structure and vigorously develop renewable energy such as solar energy.

According to the requirement of uniform and stable wire feeding in the welding process, speed and current double closed-loop speed control system is designed. The genetic algorithm is selected as the control strategy and combined with the traditional PID control to realize the on-line tuning of PID control parameters. The simulation results show that the PID tuning based on the genetic algorithm is better than the conventional PID algorithm, and the wire feeding control system meets the requirements of constant speed.

According to the characteristics of large color difference and rich color among interior scene regions, an interior design color transfer algorithm based on topological comprehensive information to guide region matching is proposed. Firstly, the interior design image is segmented, and the topological information of each area is calculated. Then, the regional matching relationship is determined according to the topological structure information to improve the accuracy of color transfer; Secondly, the color transfer is carried out between matched regions, and color adjustment is carried out for the regions without corresponding input color to improve the integrity of color transfer; finally, color harmony algorithm is used to reduce the influence of noise generated in color transfer on color transfer results, The experimental results show that the algorithm can preserve the color richness of the image globally, and obtain better matching relationship and color adjustment results locally, to obtain better color transfer results.

First this paper constructs a public legal service platform suitable for rural residents in Dezhou. This legal service platform is mainly composed of online platform, offline platform and service personnel. The purpose is to popularize legal knowledge to rural residents in various forms. Through the operation of the platform, “law” can be introduced into thousands of households and ordinary families, so that villagers can know the law and understand the law, avoid breaking the law without knowing it, and thus enhance the legal awareness of rural residents. Secondly, a reasonable evaluation system is established to evaluate the operation effect of the service platform, and the service platform is evaluated and improved continuously according to the evaluation results.

With the development of computer network technology, network education has emerged. The traditional physical education has a strong practicality, which is an interactive activity between teachers and students. At the same time, physical education teaching also has a strong demonstration and imitation. Based on these characteristics, the application of multimedia network teaching in physical education is inevitable. The multimedia network teaching has broken through the traditional physical education teaching mode, has supplemented the traditional physical education teaching insufficiency.

The study mainly introduces the comprehensive query platform based on big data technology, including the architecture and components. The architecture is mentioned for displaying the elements and relationship of the platform, such as information resource layer, data query layer and service support layer. The platform consists of query engine and query application, which lists its details and functions. The comprehensive query platform provides unified query accessing interfaces for various queries of heterogeneous data by query engine. In addition, the interface design participates a significant role in the unified query accessing interface to provide a more professional service. Furthermore, the query platform replaces the traditional query method and optimize the process, which can increase the efficiency of management for smart city building.

The visual command and dispatch in the field of public security refers to the comprehensive utilization of existing network technology, computer technology, multimedia technology and other information technologies, based on resource databases, and fusion of business systems such as PGIS application systems [1], emergency resource systems [2], and emergency plan systems [3]. This article starts from the overall architecture of the public security visual command and dispatch system, and designs the system’s resource access module, resource management module, intelligent analysis module, visual display module, and command dispatch module. The system realizes the command and dispatch functions of collecting and analyzing emergency data, organizing, coordinating, and controlling resources, helping public security to carry out business work quickly and efficiently, and has practical application value.

With the continuous advancement of dispatching and control cloud, traditional platform systems and virtualization technologies have been well supported in resource scheduling, flexible scaling, rapid migration deployment, the future availability and maintainability of these business systems will face enormous challenges. The rapid development of Docker container technology has solved the shortcomings of traditional PaaS platform based on virtual machine. In this paper, Docker container technology is used to build PaaS platform services of dispatching and control cloud. Through the analysis and verification of the flexible scaling, resource scheduling, container response and other performance aspects of the container, the experiment shows that the Docker-based PaaS platform has a good effect in the rational scheduling, rapid response and flexible scaling of resources.

With the continuous development of the container technology, the scale of the dispatching and control cloud built by it is expanding continuously. At the same time, the application portability of cloud platform based on virtualization is poor, the man-made operation and maintenance mode of the dispatching and control cloud is inefficient and the error rate is high. It is difficult to guarantee the safe and high-quality operation of power grid and the lean and efficient operation of the dispatching management. Using container technology to containerize cloud platform applications and relying on the Continuous Integration and Continuous Deployment (CI/CD) platform which can achieve efficient and accurate maintenance of the dispatching and control cloud. In this paper, the CI/CD platform which consists of the Jenkins,Kubernetes and Docker is introduced to complete the operation and maintenance tasks of the dispatching and control cloud,such as automatically agile construction, automatic publishing. Finally, through the analysis of the dispatching and control cloud, it is verified that the results show that the platform has a certain effect in automation construction, publishing efficiency, gray publishing update, operation and maintenance quality.

User classification based on sentiment analysis makes it easier for researchers to understand the sentiment behavior characteristic of different groups. Since the current user classification method does not consider the fact of user’s sentiment fluctuation, this paper proposes a user group classification model takes into account the change of user’s sentiment. Firstly, the sentiment analysis of Microblog comments base on the Microblog sentiment dictionary. Calculate the user’s temporal sentiment vector and the user’s sentiment feature vector according to the rules made in this paper. Finally, k-means clustering is used to classify user based on the user’s sentiment feature vector. Experimental results validate the accuracy of the proposed model.

A large number of educational resources are stored in major university databases, resources are not fully shared and resulting in waste of resources. In order to solve the above problem, a method of university education resource sharing based on blockchain and IPFS is proposed in this paper. Using the technology of smart contract and digital signature to authenticate the identity of universities and establish the alliance chain of universities. The design of IPFS storage combined with blockchain technology and university education resources are stored in IPFS distributed storage and the hash addresses and basic information are stored in the blockchain to achieve the protection and sharing of university education resources. The scheme proposed in this paper can not only improve the storage security of information resources, but also enhance the collaborative processing of educational resources among universities, which is conducive to the sharing of university educational resources.

The availability of some specific foods and the nutrients in foods have a great impact on everyone’s life. It goes to the extent of being among the determining factors of an individual’s long-term stay in a foreign country. In this paper, we examine the relationship between the long-term stay of foreigners in China and their food delicacies. For the analysis of data (data from administered questionnaires and interviews), a model was built using python with sklearn in multiple regression, with the coefficient, the intercept, and the adjusted r-square well examined. The research shows a correlation between foreigners living in China and their food delicacies, indicating that though foreigners consider the nutritional and health benefits of cuisine, the taste of the cuisine is prioritized, making their living conditions somewhat difficult when choosing a nutritious cuisine.