Advanced Research on Computer Science and Information Engineering

In this paper the existence of analytic solutions of a functional differential equation with state dependent argument is studied. We obtain results of analytic solutions in the case of

α

at resonance, and the case of

α

near resonance under the Brjuno condition.

A compound biaxial sun tracking system is designed to improve the efficiency of solar panels for power generation. The difference between sensor signals can be judged by the system and the stepper motor can be controlled to drive solar panels to track the sun. At the same time, the system can calculate the elevation angle and azimuth of the sun to drive solar panels to the best location by given information in cloudy circumstances. The advantages of the two track methods are complementary in different situations, thus the efficiency of solar panels for power generation is increased. The battery maintenance is taken into consideration when solar panels do not work normally. The motion characteristics of the system are analyzed to verify the feasibility of the design.

The basic concept of grid is introduced at the beginning of this paper, then Web services and how they benefit for grids are introduced. The architecture of grid is analyzed briefly based on above foundation. Grid’s architecture is related to OGSA and OGSI. OGSA acts as a virtual standards which are used to build grid’s services and applications which are services-oriented and OGSA provides an appropriate infrastructure for grid’s application by using Web services’ technology. OGSA can’t come true correlative services been described by itself, so OGSI are put forward in order to implement the primary services of OGSA according to Web services. At last, an instance of grid’s application is given to demonstrate the use of grid.

Voltage sags constitute 80% of power quality problem, and Dynamic Sag Corrector (DySC) has been considered to be an effective custom power device which mitigates voltage sags. DySC has a concise structure compared with dynamic voltage restorer (DVR). DySC adopts different compensation strategies according to the loads’ sensitivity to voltage amplitude and phase jump. This paper proposes a novel compensation strategy named integrated compensation strategy for DySC. The simulation test for single-phase voltage sag compensation verifies that the proposed strategy can mitigate the phase jump accompanied voltage sags and decrease the amplitude of injecting DySC voltage.

Wavelet analysis has been developed into a new branch for over twenty years. The notion of vector-valued binary wavelets with two-scale dilation factor associated with an orthogonal vector-valued scaling function is introduced. The existence of orthogonal vector-valued wavelets with multi-scale is discussed. A necessary and sufficient condition is presented by means of vector-valued multiresolution analysis and paraunitary vector filter bank theory. An algorithm for constructing a sort of orthogonal vector-valued wave-lets with compact support is proposed, and their properties are investigated.

In the paper, the author has studied the resource management of self -study center based on web. In the paper, all of the studies are finished in self-study center. In the study, different methods of resource management have been proposed by the author Thus she thinks that scientific resource management is necessary and useful for development of students and some effective ways can be used in promoting teaching reform and improving teaching efficiency.

The yield curve of bonds is an instrument that gives us the necessary information for valuing deterministic financial cash flows, measuring the economic market expectations and testing the effectiveness of monetary policy decisions. In the present paper, we focus on fair price calculation and residual analytics of sample bond by different models to find most effective method for china bond interest rate modeling.

Digital watermarking is one of the effective methods which can protect the copyright of multimedia data. This thesis presented a digital watermarking technology based on Arnold and DCT techniques. To improve the robustness of watermark, this thesis adopted the multi-embedded strategy. The DC coefficients in the block of the same location of each color components, are embedded the same robust watermark. The robust watermark is a binary copyright image being transformed by Arnold. The results show that, the proposed watermarking algorithm is an effective way to identify the copyright of image.

Application system integration is an important aspect of industry informatization construction. For scattered, autonomous, heterogeneous application system, this paper puts forward a full set of solution of application system integration based on RIA technology and some open-source frameworks. The scheme realizes the integration of different tech. Web system, J2EE application system, .NET application system, FMS3 streaming media system, different type database systems and Web services. It provides an application platform with rich user experience and friendly user interface. At last, the scheme usability is proved by UPRS.

This paper presents a new methodology for multi-scale texture analysis. The basic idea is that an image texture is viewed as a tessellation of square texels of different sizes and pixel levels. A textural image is decomposed into a set of scale images and each scale image consists of square texels of the same size. The texels in a scale image may have different pixel values. The degree of presence of a texel in a textural image can be measured by the image area occupied by the texel in terms of pixel. The histogram of texel area is shown to be a useful texture feature, and a dominant texture scale derived from the histogram provides a good reference parameter for computing gray-level co-occurrence matrix.

A new illumination invariant feature extraction method for texture classification is proposed. In order to capture the local image texture, texture pattern transform (TPT) in a local neighborhood of a monochrome texture image is introduced. The TPT is robust against any monotonic transformation of the gray scale. The joint distributions of two different TPT, which can be characterized using a pattern co-occurrence matrix (PCM), can be used for texture classification. The PCM technique only requires comparison and counting operations, and thus is highly computationally efficient. The properties of PCM include translation and illuminant invariance, which is highly desirable in real-world applications. Illumination invariant texture classification experimental results show that the texture features derived from PCM achieve good discrimination.

Green index of tree leaves is an important parameter for leaf image segmentation. An innovative method based on color features was presented to automatically extract and split tree leaves from digital image analyses. Based on the features of leaves and its background components, an algorithm was designed to extract the leaves contour, and the corresponding program was developed. This method was simple, and it have a high degree of accuracy as well as a clearly distinguish degree and many other advantages such as good consistency with human visual system. It completely meets the effectiveness and clarity requirements of image segmentation.

This paper analyzes some existing web services description models and services matching methods, puts forward a Web services filtrating mechanism based on latent semantic analysis to solve lower matching efficiency and precision of the available services discovery mechanisms that is short of services filtrating mechanism and matched with keywords. Firstly, this filtrating algorithm describes basic attributes and QoS attributes of Web services using tree structure attributes template. Secondly, the paper builds latent semantic analysis space using certain terms-frequency statistic method and weights method. And then, the paper builds advertising services index database, and filtrates the Web services according to the service request. Experiments results show that this algorithm has higher precision and recall ratio, can improve services matching efficiency largely.

An assembly consists of two or more mating parts. The quality of the assembly is mainly based on the quality of mating parts. The mating parts may be manufactured using different machines and processes with different standard deviations. Therefore, the dimensional distributions of the mating parts are not similar. This results in clearance between the mating parts. To obtain high precision assemblies, clearance variation has to be reduced. Selective assembly helps to reduce this clearance variation. In this paper, appropriate selective group combination for assembling the mating parts is obtained using an ant colony optimization (ACO). The combination obtained has resulted in an appreciable reduction in clearance variations.

Explicit knowledge affects the efficiency and effectiveness of the management in the Enterprise R & D Process (ERDP) directly, yet the classification, evaluation and application of explicit knowledge in this process remain to be studied further. Based on the relevant literature study, the explicit knowledge is classified and the Evaluation System of Explicit Knowledge (ESEK) is constructed in this paper. The empirical study is built on the information from 50 valid questionnaires filled out by the R&D personnel. Empirical analyses have taught us that 6 dimensions (knowledge operation, R&D investment, R&D innovation, R&D accomplishment, R&D potential) of the ESEK are proposed by using Exploratory Factor Analysis (EFA) method. The study suggest that enterprises can evaluate and improve the efficiency and effectiveness of explicit knowledge management through the above 6 dimensions and comes to some new ideas about the classification, evaluation and improvements of explicit knowledge in ERDP.

Different dominant advantages affect supply chain performance. This paper discusses four types of two-stage supply chain model under Stackelberg game by revenue sharing contract, considers a new parameter and enriches supply chain models in theory. Comparisons of reorder quantity, game process, different enterprises’ interests and total profit of supply chain are made, based on the equilibrium and each member’s profit. The result shows that whether the leading enterprise is supplier or retailer, as long as having absolute advantage, can the leader maximize its own profit, while achieving global optimization of the supply chain.

Particle filter has grown to be a standard tool for solving visual tracking problems in real world applications. This paper discusses in detail the application of particle filter in visual tracking, including single object and multiple objects tracking. Choosing a good proposal distribution for the tracking algorithm in particle filtering framework is the main focus of this paper. We also discussed the contributions related to dealing with occlusion, interaction, illumination change using improved particle filters. A conclusion is drawn in section 4.

In this paper we introduce a scalable 3G live streaming system. It has a mobile client which captures and publishes video streams to a media server. Then the server broadcasts and archives received streams simultaneously. Our system uses flash technology in the end-user development and thus we get very wide device support. By applying self-adaptive HTTP and RTMP transmissions, our system can keep working well under mobile network environment with limited time delay. Our experiments showed that even on 3G mobile phones the live streaming time delay was no more than 5 seconds when RTMP transmission was used. As videos contents are very private and sensitive to users, we also built an authorization service in our system to ensure the security of transferred contents.

The paper tried to use visualization and object-based technology to design crop growth system. The method could present the flexibility, easy to manage, code reuse features of object-based technology. The system designed by this method could provide function-expanded interface for the simulation system, also lay the foundation for simulation soybean mass growth state. There would be a great significance in visualization research of virtual crops.

For the last few years, face recognition has attracted much attention. As a part of face recognition, the face detection is significant to computer vision and feature detection. This article is based on massive literature; it has carried on the research summary of face detection methods and classification from pattern recognition’s processing stage. It also a certain supplement to the former classification of face detection methods.

In order to resolve the problems about network curriculum construction and application, this paper gives some advices, such as enhancing publicity of network, training the ability of teacher to drive network technology, guiding teacher to construct network curriculum, strengthening construction of university software and hardware, guiding student to use network curriculum correctly and efficiently, strengthening system construction and regularizing management. Huaiyin Institute of Technology has done as the given advices and got good result about network curriculum construction and application.

Nodes in Ad Hoc network are typically powered by batteries, so how to improve energy efficiency, save energy and prolong the life span of networks are critical problems at all layers of the protocol stack. IEEE802 11 specifies power saving mechanism (PSM) under distributed coordination function (DCF) for energy efficiency. On the basis of an analysis and comparison IEEE802 11PSM, this work proposes an adaptive power saving mechanism (EPSM) EPSM improves PSM model that could only send one package in one BI, dramatically reduces transfer delay, and prolongs the life span of central nodes to save energy using central nodes alternant wake- up The results of simulation show that EPSM has better performance than PSM in decreasing transportation delays, saving energy, and prolonging life span of nodes.

Text categorization is a fundamental methodology of text mining and it is also a hot topic of the research of data mining and web mining in recent years. It plays an important role in building traditional information retrieval, web indexing architecture, Web information retrieval, and so on. This paper presents an improved algorithm of text categorization which combines a feature weighting technique with Naïve Bayesian classification. Experimental results show that using the improved Gini index algorithm to feature weight can improve the performance of Naïve Bayesian classifiers and increase the practical values of the sensitive information system.

With the popularization of Microsoft Office series, it has become one of the compulsory courses for undergraduates of all majors nowadays. Besides, the importance of Office calling and automation has been shown clearly, especially in the computer examination system. This paper provides a good method to achieve Powerpoint calling and automation, the method uses the technology of OLE in development of software with C + + Builder.

This paper is concerned with a functional differential equation. By reducing the equation with the

Schröder

transformation to another functional differential equation, an existence theorem is established for analytic solutions of the original equation. For the constant

α

given in the

Schröder

transformation, we discuss

α

near resonance under the Brjuno condition. Furthermore, we discuss analytic solutions of the differential-difference equation.

For stochastic linear time-delay systems with a given quadratic cost function, the guaranteed cost control problem, by state feedback controllers, was studied by introducing Lyapunov functional, using Ito lemma, Schur complement lemma and stochastic analysis methods. Sufficient conditions for the existence of guaranteed cost controllers are given in terms of linear matrix inequalities. And then the optimal guaranteed cost control law which minimizes the guaranteed cost of the stochastic linear closed-loop time-delay systems is also formulated.

The nuclear and chemical reconnaissance robot, a kind of remote robot, can realize various functions such as nuclear radiation detection, toxic gas detection, solid sampling, and so on. This paper analyzes the functional requirements of the robot, and puts forward the main technical indicators for the robot system. A small-sized nuclear and chemical reconnaissance robot is manufactured according to the requirements, and the overall structure and control system design of the robot is described. Experiment shows that whole system of the robot is reliable to meet the design requirements, and can conduct reconnaissance and detection task in dangerous conditions instead of manual operation.

In order to improve the accuracy of financial achievement prediction and make the prediction effect better, this paper applies neighbourhood rough sets targets optimization in least square support vector machines (LS-SVM) and proposes a LS−SVM financial achievement prediction model which is based on neighborhood rough sets targets optimization. Meanwhile, it gives the algorithm realization procedures of the prediction model. After compared with factor analysis method, classical rough sets targets pretreatment method, this paper verifies that LS−SVM financial achievement prediction model based on neighborhood rough sets targets optimization can improve the model’s prediction accuracy significantly.

The problem of choosing a set of journals to order or to cancel is significant in applications of operations research to library decision making. This paper describes a zero-one interval linear programming approach that can consider all coefficients varied in some interval, and provide a satisficing solution.

Based on the ideas of conflict-free transmission, priority-based service and dynamic load adaptation, this article proposes a scheduling strategy fit for the MAC scheme of WSNs, which has made possible the polling service capable of differentiating the clusters of different priority levels under two kinds of service policy. The scheme has improved the system’s energy efficiency and the instantaneity of multimedia transmissions in wireless system via adjustment of the times of the gated services along with input load change. The theoretical model of this scheme is established through Markov chain and probability generating function. Mathematical analysis is made on the mean queue length and the mean inquiry cyclic time of the common nodes and the key node. It turns out that the findings from theoretical analysis correspond well with those from simulated experiments.

Concept lattice has many applications, e.g., software engineering, knowledge discovery. And isomorphic judgment of concept lattice is important in various fields, for instance, ontology similarity measure. In this paper, we apply the isomorphic judgment algorithm of concept lattice in software engineering to transfer knowledge in different domains after analyzed the foundation of transfer learning. Followed, an example of transfer knowledge in software engineering was introduced, and it shows the efficiency of our method.

The objective of this paper is to investigate the energy saving potentials of increasing the EER of air conditioners. A representative residential building was modelled for building energy simulation with different EERs. The results show that EER increase has a energy saving potential range of 4%-44% depending on the EER ratings, and the heating energy savings is higher than the total and cooling ones. A commonly availabe air conditioner with a 3.16 EER may achieve a total energy savings of about 25%.

Population-based methods are optimization techniques inspired by natural evolution processes. They handle a population of individuals that evolves with the help of information exchange procedures. Each individual may also evolve independently. Periods of cooperation alternatewith periods of self-adaptation. Population-based Learning Algorithm (PBLA), is another population-based method, which can be applied to solve combinatorial optimization problems. PBLA has been inspired by analogies to a social phenomenon rather than to evolutionary processes.Whereas evolutionary algorithms emulate basic features of natural evolution including natural selection, hereditary variations, the survival of the fittest, and production of far more offspring than are necessary to replace current generation.

In order to add custom attribute information to AutoCAD graphic data more flexibly and conveniently, we study the problem of custom extending CAD attribute information which exists in AutoCAD, and implement the custom extending function of AutoCAD attribute information by ObjectARX components in .NET development environment. Respectively, we adopt the XData way and database dictionary way for extending. Finally, we extend GIS attribute data in CAD graphic file and apply to practice. The application results show that this method is convenient, flexible and is worthy to be popularized.

Speech emotion recognition is a new and challenging subject in artificial intelligence field. This paper explores the issues involved in applying support vector machines (SVM) classifier to emotion recognition in speech signals. The performance of SVM on speech emotion recognition task is compared with linear discriminant classifiers (LDC), K-nearest-neighbor (KNN), and radial basis function neutral network (RBFNN). The experimental results on emotional Chinese speech corpus demonstrate that SVM obtains the highest accuracy of 85%, outperforming the other used classification methods.

Wavelet Neural Network (WNN) is a new neural network model based on wavelet analysis theory, which takes advantage of good localization of wavelet transform nature, and combines with neural networks’ self-learning function, thereby, it has strong approximation ability and can approach any nonlinear function. This paper using wavelet neural network constructing the city gas load forecasting of mathematical model, and the model parameters determination, and impact load forecasting of various factors of the in-depth analysis and discussion.

Based on the truth degrees of formulas and the deviations of theories defined by Hausdorff metric, the present paper introduced a new concept of consistency degrees of theories in n-valued Gödel logical system. Sufficient and necessary conditions for theories being consistent or inconsistent are given. The new index provided in the present paper can also be used to grade the consistency degrees of general theories in fuzzy logic systems.

Grain drying process is a complicatedly hysteretic system with multivariate, nonlinearity, time-varying. Traditional control method is difficult to get ideal control effect since there’s coupled relation between temperature and humidity, and it’s difficult to build accurate mathematical models. Therefore, this thesis inducts decoupling ideas as well as fuzzy control method, realizing decoupling control of temperature and humidity of the system, and uses MATLAB to the corresponding simulation analysis, by comparing with the simulation results of PID control algorithm, it indicates that the system with more superior control effect and greatly improve control precision.

In this paper, neural network predictive control method is used to compensate the image forward motion of a certain aerial reconnaissance camera and we have solved several problems that traditional control methods have. Firstly, according to the principle of imaging, we analyzed the reasons for the existence of image forward motion and established the mathematical model. Secondly, we analyzed the theoretically feasibility of the method. At last, simulation, experiments and test are used to validate the practical feasibility. Through what we have done, we conclude that neural network predictive control method can be used to compensate image forward motion for this certain camera and can make a perfect performance.

In the condition of satisfying process requirement, determining the optimum operation schemes of natural gas pipeline network is essential to improve the overall efficiency of network operation. According to the operation parameters of natural gas network, the multi-hierarchy comprehensive evaluation index system is illustrated. This paper presents a multi-hierarchy grey relational analysis method which is suitable for evaluating the multi-hierarchy index system with combining the AHP and grey relational analysis. The comprehensive evaluating mathematic model for natural gas network operation schemes is built based on the method. Ultimately, the practical application shows that multi hierarchy grey relational analysis is effective to evaluate the nature gas pipeline network operation schemes.

In this paper, we propose a novel approach to transfer the designer’s 2D drawings into 3D virtual garment. The designer is required to provide minimum two silhouettes for the front view and the back view of the original design. The silhouettes are triangulated to form a mass-spring system. The virtual sewing of the silhouettes generates the initial shell of the 3D garment. The following drape simulation finalizes the 3D configuration of the original design. Euler integration and Verlet integration are employed for sewing and draping respectively. Various experimental results validate that this method is an effective approach in fast prototyping 3D counterpart of the original design.

This paper proposes an efficient chaos-based image encryption scheme, in which shuffling the positions and changing the grey values of image pixels are combined to confuse the relationship between the cipher-image and the plain-image. Firstly, the Arnold Cat map is employed to shuffle the positions of the image pixels in the spatial domain. Then the discrete output signal of the Lorenz chaotic system is preprocessed to be suitable for the grayscale image encryption, and the shuffled image is encrypted by the preprocessed signal pixel by pixel. The experimental results demonstrate that the key space is large enough to resist the brute force attack and the distribution of grey values of the encrypted image has a random like behavior.

Coasting is frequently used by drivers on level road. So analyzing vehicle’s fuel consumption feature during sliding process has practical significance on realizing reasonable driving and lowering fuel consumption. Taking some light-duty diesel vehicle as experimental object, this paper discussed the fuel economy variation discipline and curves based on various coasting tests, especially analyzed the fuel consumption difference between sliding in neutral and sliding in different gears. The result shows that vehicle’s average fuel consumption rate while sliding in different gears is similar, which is about to 1/50 of sliding in neutral’. While sliding, the vehicle’s fuel consumption rate basically maintains at a low level. But once the coasting speed is too low, the fuel consumption rate increases dramatically. Therefore, aiming at lowing fuel consumption and reducing emission discharge, vehicle sliding in gear should have priority to sliding in neutral and choosing a reasonable coasting speed range is important.

The total assembly work is often implemented at the manufacture, and we propose that the total assembly work and some customization of parts at manufacture should be outsourced to distribution center of 3PL (third party logistics) company to reduce the level of inventory and cost of the whole supply chain, i.e. moving the CODP (customer order decoupling point) to distribution center in the downstream, and then, the advantage and condition of this strategy will be analyzed.

According to the structural similarity theory, the primary function of human visual system (HVS) is to extract the structural information from the view of human being. Therefore the structural information can be taken as an approximation measure of image quality. In this paper, a structural similarity based image authentication watermarking is proposed. The proposed algorithm can chooses the positions in original image where the pixels can be changed but cannot be perceived by human eyes. Experimental results show that the proposed algorithm meets the human visual effectively.

An improved image denoising technique based on the nonlocal means (NL-means) algorithm is investigated in this research. The proposed method not only considers a non-local similarity of the intensity gray level of all pixels in the image, the gradient of pixels in small local windows are also computed to obtain the local structure information for each patch. The proposed algorithm is demonstrated on images corrupted by white Gaussian noise (WGN). The comparative experimental results show that the improved NL-means filter achieves better denoising performance.

This paper first analyzes the current network congestion control technology and presents a new mechanism named backward congestion control mechanism to solve the weakness of current explicit congestion notification mechanism. Finally, we use NS to simulate this mechanism in order to compare with the traditional TCP[1] congestion control mechanism. Experimental results show that the new mechanism has low latency and high congestion notification accuracy of congestion notification, further more the new mechanism can also distinguish between the reasons for the network packet loss and thus can be applied to a hybrid network.

The servo control is widely used in many kinds of fields, and is also a typical teaching case for several engineering disciplines. The aim of the paper is to discuss how to demonstrate the fundamental and detail for the student. After introducing the structure of the servo system, the paper analyzed the correlative curricula. The modeling methods to the key subsystems were discussed. Finally the application level of the simulation was also presented.

The purpose of this paper is to investigate the shape determination of a rigid body located in incompressible fluid flow in two dimensions. This state problem is controlled by the Stokes equations. The derivative of the cost functional is given by an adjiont method. The level set method is successfully utilized as the minimization algorithm. Since the level set method is implemented in an Eulerian framework, the computational cost is moderate. Finally, a numerical example is presented to illustrate the effectiveness and validity of the proposed algorithm.

Oscillation theory of functional partial differential equations has wide applications in mechanics, physics and mathematical biology, economics, automatic control, communications theory etc. In this paper, we consider a class of neutral hyperbolic partial differential equations with continuous distributed deviating arguments and damped term. Some sufficient conditions for oscillation of all solutions with certain boundary value problems are obtained, which are two theorems by integrating directly.

A appraisal model based on the integration of principal component analysis (PCA) and back propagation (BP) neural network is put forward for appraising the real estate project. Firstly, principal component analysis (PCA) is used to reduce the evaluation index dimensions. And then, back propagation (BP) neural network is used to appraise the real estate projects. In order to grasp this appraisal model better, finally, the paper provides a case to demonstrate the application of this model in appraising the real estate project. The case has shown that the model applied to appraise the real estate project is feasible and reliable.

Experiments are commonly used method to help students learn building physics, however the drawback of this method is that it can only measure part of parameters and could not give an accurate evaluation. This paper proposes a computer aided tool in experiments to help students understand the principles of physics in the built environment and improve the design of a building. The results show that it has 7 advantages over conventional manual computation method, and the improved teaching quality in the experiment teaching of building physics evidences its significance.

A condition monitoring method for rolling element bearings based on auto-regressive (AR) model and support vector machine (SVM) is proposed. The AR model of the vibration signal of bearings is established. The auto-regressive parameters and the variances of remnant are used as the feature vectors. Then multi faults classifier is established by support vector machines to identify the condition of bearings. The experimental result shows that the proposed method is effective.

Scheduling for the flexible job-shop problem (FJSP) is very important. However, it is quite difficult to achieve an optimal solution to the FJSP with traditional optimization approaches. This paper examines the development and application of a genetic algorithm (GA) to the FJSP. A algorithm is proposed based on a basic genetic algorithm, an improved chromosome representation is represented, different strategies for crossover and mutation operator are adopted. The algorithm is tested on instances of 7 jobs and 7 machines. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the FJSP.

Technology of online synch record and simulation of motion is a spiry integral technology of mechanics, electrics and hydraulics. Systematical study of it is carried out using a 6-DOF(Degree Of Freedom) synchronous on-line recorder and simulator. The algorithm of the 6-DOF synchronous on-line recorder and simulator is deduced. the adaptive neural network controller is designed accordingly. with the existing hydraulic servo driven 6-DOF simulator, a synchronous on-line recorder and simulator control system is set up, and the experiment proves the algorithm is correct and the controller’s design is fully a success.

In the multi-legged robot research, a challenging task is to manage its walking balance. This paper presents the gait and stability analysis of a simple quadruped robot. First, a quadruped robot which consists of 15 DOFs was built up. To analyze its walking balance, we specified the straight walking gait and the turning gait in every step. A practical obstacle avoidance experiment and further stimulations demonstrate that the proposed gaits can achieve the walking stability of the quadruped robot.

Survivability has been one of the active fields in network security recently. In order to evaluate the survivability of networked system effectively, this paper proposes a method of combining improved TOPSIS and grey relation analysis for quantitative assessment. Firstly, it normalizes indicator matrix according to traditional TOPSIS method and determines the positive and negative ideal solutions. Secondly, it calculates relation degree of every critical service in terms of grey relation analysis, according to which it gets the optimal dependency degree. Then it evaluates the whole survivability of networked system depending on the survivable function. At last a case study is given to show the availability and effectiveness of the method.

Inconsistency has become an important issue in many data-centric applications. Performing query on such data may result in wrong decisions.To obtain query results with high quality, it is necessary to process queries on inconsistent data. The significant limitations of current major methods include the low efficiency and the absence of effective data access mechanism. To process query on inconsistent data efficiently and effectively, in this paper, an index, AIIS (Adaptive Index for Inconsistent String), is presented for string attributes in inconsistent data. With effective graph decomposition and representative selection strategies, this index is an approximately balanced data structure. Extensive experimental results on both real and synthetic data sets demonstrate efficiency and effectiveness.

E-business model innovation is one of the focus e-business research fields and no consensus of e-business model concept hinders the e-business model innovation research. After analyzing the current state of e-business model research, an analytical and hierarchical concept framework of e-business model is proposed, which includes classification, operating and implementation level. From the view of static, e-business model can be regarded as role model, scale model and model organism. From dynamic perspective, e-business model can be regarded as recipe, which guides entrepreneurs to innovate e-business model. This study lays necessary foundations for further research on method of e-business model innovation.

To improve the quality of input data of multivariate calibration model, a new hybrid preprocessing algorithm (WPT-GA-OSC) was proposed, which is the combination of wavelet packet transform (WPT), genetic algorithm (GA) and orthogonal signal correction (OSC) algorithm. At first, WPT algorithm is applied to split the raw spectra into different frequency components. Then, based on the root mean square error of prediction models, the genetic algorithm is employed to select the WPT components related to analyte as the input data of regression model. At last, to further improve the quality of input data, OSC algorithm is applied to each GA-filtered component to eliminate the information irrelevant to analyte information. To validate the WPT-GA-OSC algorithm, it was applied to develop the calibration model for oil concentration measurement of corn. Compared with the conventional preprocessing algorithm, the WPT-GA-OSC algorithm can take full advantages of multiscale property of near infrared (NIR) spectra, and also can significantly decrease the prediction error by up to 48.3%, indicating that it is a promising way for filtering the spectral data to develop the NIR calibration model.

Entity resolution (ER) is to find the data objects referring to the same real-world entity. When ER is performed on relations, the crucial operator is record matching, which is to judge whether two tuples referring to the same real-world entity. Record matching is a longstanding issue. However, with massive and complex data in applications, current methods cannot satisfy the requirements. A Sequence-rule-based record matching (SeReMatching) is presented with the consideration of both the values of the attributes and their importance in record matching. And with the help of the Bloom Filter we changed, the algorithm greatly increases the checking speed and makes the complexity of entity resolution almost O(n). And extensive experiments are performed to evaluate our methods.

With the progress of low-power research on embedded systems, the estimation and analysis of energy consumption of embedded systems becomes a hot topic. Process Algebra is a formal method fit for analyzing the functional properties of embedded software, but it can not analyze the energy consumption properties. This paper proposes a process algebra support for modeling and analyzing energy consumption of embedded software. Priced Timed Communicating Sequential Process (PTCSP) is proposed in this paper can handle it efficiently by extending price information on Timed Communicating Sequential Process (TCSP). In this paper, the power consumption of instructions in embedded systems is mapped into the price of PTCSP, the energy consumption of embedded software can be modeled and optimized by using PTCSP. This formal method improves the accuracy and efficiency of energy calculation, the calculation results can be used to quantitatively analyze and optimize the energy consumption of embedded systems.

The traditional PID controller has structural flaws in the integral process control, a kind of internal feedback particle swarm optimization PID control method is put forward in this paper, which solves the problem of controlling the integral process. The integral time-delay systems in superheated steam temperature system is difficult to be controlled, but by using the method brought in this paper, the simulation results of the steam flow temperature control system have non-overshoot, short adjusting time, which shows the rationality and validity of the PID control based on internal feedback PSO.

Based on the RNG

k

–

ε

turbulence model, numerical simulation was carried out for aerodynamic characteristics of German ICE high-speed railway train under different wind direction angles and different wind angles of attack. In order to verify the accuracy of numerical simulation, the experimental platform of CUMT for the flow field visualization was used to check the result under the same conditions. Further more, the interaction among wind angles of direction, wind angles of attack and pressure coefficient, lift coefficient, overturning moment coefficient were discussed in this paper. The calculation results show that, with the increasing of wind angle of direction and wind angle of attack, the aerodynamic forces and overturning moment of the train increased gradually, which is unfavorable for high-speed railway train.

The reform of teaching in colleges and universities not only requires more for multimedia computer room day by day, but also leads to various sorts of conflicts. Along with continuous development of “cloud computing” and virtual technology, the application of virtual desktop infrastructure (VDI) based on cloud computing provides an effective way which is characterized by lower cost, more reliable data security and more convenient desktop management for construction and management of multimedia computer room in colleges and universities.

The special features of heterogeneous components, frequent user interactions and the system dynamics cause new problems of testing web applications. With a little modification of the server configuration, log files that contain user interactions with a web application can be collected and used for the test purpose. The great issues of user session based software testing are how to effectively select an appropriate set of test data generated from such log files. The paper describes a method of using cluster techniques to partition user session data and to generate test cases for web applications. The key problems of object data types and dissimilarity definition for the special data of user sessions are elaborated. An algorithm of generating test cases from user session data is presented. The experiment with a real web application demonstrated the method’s effectiveness in the code coverage and in the data reduction.

Fault diagnosis of roller bearings is very complex, so it is difficult to use the mathematical model to describe their faults. The fault diagnosis methods of ball bearing based on Wavelet packet transform with entropy features and support vector machine (SVM) are proposed in this paper. Wavelet packets have greater decor relation properties than standard wavelets in that they induce a finer partitioning of the frequency domain of the process generating the data. A two cycles of ball bearing fault current data is processed through wavelet packet transform to obtain wavelet coefficients and then Energy eigenvector of frequency domain are extracted by using Shannon entropy principle. Subsequently, the extracted Energy eigenvector of frequency domain are applied as inputs to SVM for roller bearings from internal fault. Fault state of ball bearing is identified by using radial basis function genetic-support vector machine. The results of the proposed new technique were found to be reliable, fast and accurate in identifying the fault condition.

This paper describes a vehicle heavy identification method, which use of both video vehicle inspection and fiber grating pressure sensor. In this method, firstly, video vehicle inspection system is used to find the target vehicle in the area which fiber grating sensors been buried in. Then the stress testing systems is driven by the recognition results. If there is vehicle in the area, we collect data from fiber grating pressure sensor, analyze the wavelength variation curves, and calculate the weight of the target, which decide what to do at the next step. This method can reduce the fiber grating sensor data collection frequency and effectively avoid false detection of fiber grating sensors.

To solve the problem that the crowd evacuating process model with cellular automata is quite different from the reality crowd evacuating process, the crowd evacuating process model with cellular automata based on safety training is addressed. The crowd evacuating process based on safety training is simulated and predicted, and the result is very close to the reality. Using the vertical way to place the shelves gets both a higher escaping rate and a larger shelf area that the total area is up to 216m

2

, and the average death number is 4.2 by safety training when the fire level being 2.

In order to obtain a safer path in home environment, a modified particle swarm optimization algorithm is first introduced in the paper to get an initial global optimized path. Then an improved A* algorithm is proposed to avoid obstacles based on dynamic danger degree map. The local layer can get multi-mode information of obstacles, and create dynamic danger degree map of the environment. Finally, the head-for-goal strategy is designed to help the mobile robot arrive at the destination with lowest cost. Experiments demonstrate the feasibility and safety of the proposed system.

Reducing inventory levels is a major supply chain management challenge. With the development of information technology new cooperative supply chain contracts emerge such as Vendor-Managed Inventory (VMI). This research aims to look at the literature of information management of VMI and the Internet of Things, then analyzes information flow model of VMI The paper is carried out to make analysis of information flow control of VMI based on the environment of Internet of Things.

Unit commitment problem is traditional mixed variables programming which is difficult to find the optimal solution in mathematics. A quantum genetic algorithm to solve unit commitment problems presented in this paper. The proposed algorithm can solve problems for which the objective function is non-linear, non-convex, non-differentiable, stochastic, or even discontinuous. Quantum genetic algorithm guarantees global convergence and only needs values of objective function and barrier functions consisted by constraint condition while discards the information of their derivative. Simulations are executed on systems of 10-units in 24 hour intervals and the results verify the effectiveness of the proposed algorithm.

Plenty of motion planning methods have been proposed and achieved good performance in static environments. However, motion planning for obstacle avoidance in dynamic and changeable environment is still a challenging task, especially when the tracked object moves freely. This paper presents a practical fuzzy logic based motion planning method for the mobile intelligent security robot with limited sensory information. Vision sensor is used for object tracking, and sonar sensors are used for obstacle avoidance. Fuzzy logic together with three modules: the environment construction module, the reactive planning module, and the action control module are used for obstacle avoidance and navigation. Experimental results show the efficiency and the reliability of this method in the dynamic and uncontrolled environments.

With the characteristic which the control of the multiphase machine is more complex compared with three-phase ac machine, a novel control method is proposed in this paper, namely six-phase motor trapezoidal wave phase current control. By using the trapezoidal phase current waveform, the stator winding is separated into the field winding and the torque winding. The function which is about the field and torque control in directed and separated mode can be realized without the complex Park transformation. The paper carries on the theoretical analysis, the computation of the air gap magnetomotive force(MMF), the electromagnetism torque and MMF decoupling parameter k. And these results are validated by the experiment. It is shown from the theoretical analysis computation and experiment result that it is possible for the control strategy proposed in this paper and it is also of some advantages not only in the control method but also for motor control performance.

This paper presents the UMHexagonS algorithm, reflected in two aspects: In the search process of this algorithm has added the adaptive threshold value and played a role ahead of deadline in the search process, saving the search time; Its has turned into five steps search and increased the step rectangle search, reducing the search time. The results show that the proposed method can not only guarantee the coding effect of UMHexagonS algorithm, improve the speed of motion estimation, but also saving the coding time, and improve the overall coding rate. Simulation results show that the H.264 encoder, using the proposed rate control algorithm, achieves a visual quality improvement up to 0.388 dB, meets better with target bit rates and produces more flat bit-rate curve than that using the H.264 previous rate control method.

The scientific and academic interest for image processing and analysis on autonomous systems for solving problems associated to the artificial vision, such as objects recognition, trajectory planning of robots, etc., has grown in the last years. On the other hand, the reconfigurable logic has attractive features to implement applications of artificial vision on embedded systems. In this context, this paper aims to show the design and implementation of an integral environment for implementing and evaluating algorithms for digital images processing and analysis inside a FPGA.

A new method for the reliable video multicast communication is presented by the study of the communicating technique based on wireless ad hoc networks. In the method, the network layer adopts the on-demand multicast routing protocol, and the application layer combines the Forward Error Correction with Automatic Repeat Request to effectively control errors, so it can provide the reliable data transmission of the wireless video multicast with almost no affecting the system performance. The simulation results show the effectiveness of the method.

In virtualized systems, such as large data centers and cloud computing environments, resources are shared across multiple virtual machines, which results in contentions and conflicting under heavily loaded or consolidated situations. In order to accommodate as many as computing and service capabilities while still delivering performance guarantees, resource utilization and application performance should be tradeoffed such that fewer resources will be utilized for a specific performance requirement. To achieve this goal, in this paper we propose an adaptive resource allocation for tradeoff between resource utilization and upper level application’s performance such as response time and throughput. This approach does not require a highly accurate performance model in a virtualized system where workloads usually change frequently with time in some intervals. Experiments on a Xen based virtualized environment are conducted and evaluated. The results show that the proposed approach utilizes less CPU resources to achieve the same performance goals compared to the fixed over-provisioning of resources.