Advances in Automation and Robotics, Vol. 2

Because of the unique knowledge representation method and natural learning ability, researchers pay more and more attention to the Case-Based Reasoning (CBR). Currently, the most CBR technology just a simple case reuse, it cannot doing the case revise or case revise didn’t have good generality. Aiming at the problem of it, this paper proposed a framework of automatic reasoning technology based on secondary CBR. The framework drive the case reuse by case revise, storing the base case with primary case base, use the secondary difference case base to store the case adjust knowledge, and with the secondary CBR assist the whole automatic reasoning process completely. Practical application shows that the technology has good practicality and generality.

Our daily living environment contains more and more technical systems, which need human control. Modern mobile devices offer functionalities to act as generic control devices for these technical systems. Besides classical user interactions they provide components to process new ways of human-machine interactions like speech and touch inputs. In this article, we describe a software framework to support multimodal inputs for Android based mobile devices. We exploit this framework in a case study to develop adaptable, multimodal user interfaces for two different instances of robot controls. Furthermore, we present some results from evaluating these interfaces with a couple of test persons.

Higher speed will cause more serious Doppler spread, meanwhile change the character of the wireless channel, which breaks suppose that the channel impulse respond (CIR) is a constant during a time slot. In order to overcome this problem, this paper proposed an algorithm which is RS-MAP-PSP (adaptive reduced state maximum a posteriori equalizer based on per-survivor processing) in conjunction with DFE (decision feedback equalizer) for the EDGE system with 8PSK modulation. To reduce the state of the equalizer, a pre-filter is followed by the MAP-PSP to reshape CIR to have approximately a minimum phase property. Our simulation results show that the proposed algorithm can improve the performance of the EDGE system, compared with general receiver algorithm especially for the high coding rate traffic and/or under the high speed environments.

In this paper, human poses which are presented by real 3D points cloud got from Kinect sensor are estimated and tracked by a hierarchical human model in ICP framework. There are several novel points in this paper. First, we compute human models’ nearest points rather than points’ nearest limbs as traditional methods do to make every limb have points. Second, we consider global information while hierarchically do ICP for every local limbs to conserve articulated kinematics chain. Third, by analyzing the four limbs (two legs and two arms) and enforcing joint constraints, we solve several specific problems, such as leg- or arm-crossing, etc. Experimental results including kinds of real human actions verify our method’s effectiveness.

The purpose of this paper is to extend the motion space of a new screwdrive mechanism, termed Double-Screw-Drive (DSD) mechanism, which was developed by the author so far. To this end, the former DSD mechanism was improved so that the degree of freedom of motion of the tip position is extended, and new DSD mechanism is proposed. In order to control bending motion of the new DSD mechanism, inverse kinematics problem is considered. Namely, equations which give the amount of rotations of each linkage are derived. In addition, using the derived equations, the motion space of the tip position is clarified by software analysis.

Machine tools has become an indispensable processing tool in industrial field. Especially the appearance of multi-axis machine tools has changed the traditional processing method. This paper focuses on the research of improving the machine accuracy. Based on the general error model which has been established using multi-body theory, it has given the precise NC instructions of multi-axis machine tools. Taking C-A type machine tool for example, the precise NC instructions of circle angular has been given.

This paper considers the problem of Vehicle Routing Problem with stochastic demands and simultaneous delivery and pickup. An effective algorithm based on cross-entropy is designed to solve the model. The cross-entropy method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. Numerical experiments have been conducted and the results indicate that the method can effectively solve this problem.

According to the shape of screw, the spiral surface equation of screw was established; and through analyzing the relative motion between screw and formed milling cutter, find the contact conditions of screw and cutter, further deduce the meshing conditions of screw and cutter, and the contact line equation was established based on non-instantaneous envelope method. From the axial cross-section shapes which the contact line rotates around the axis of cutter formed rotary surface, the profile equation of formed milling cutter was established. Analyzing the causes of processing error after wear of formed milling cutter, the tooth back curve equation was established, finally got the profile equation of formed milling cutter have constant back edge. By interference checking for profile equation of formed milling cutter, ensure correctness of milling cutter profile.

The inchworm movement principle is studied in this paper firstly, and then by imitating the biological movement of the inchworm, the walking mechanism of inchworm-like micro-robot is studied and designed. The robot can achieve the unique rhythm of the inchworm-1ike movement based on the innovative design of the linkage mechanism. For the inchworm-like micro-robot, both walking gait and rotating gait are studied by the simulation research. The results show that the inchworm-1ike micro-robot walking mechanism is efficient, stable, and easy to be controlled.

Small-size soccer league is a division of the RoboCup (Robot world cup) competitions. Each team uses its own designed hardware and software to compete with othersunder defined rules. There are two kinds of data which the strategy system will receive from the dedicated server, one of them is the referee commands, and the other one is vision data. However, due to the network delay and the vision noise, we have to process the data before we can actually use it. Therefore, a certain mechanism is needed in this case.Instead of using some prevalent and complex algorithms, this paper proposes to solve this problem from simple kinematics and mathematics point of view, which can be implemented effectively by hobbyists and undergraduate students. We divide this problem by the speed status and deal it in three different situations. Testing results show good performance with this algorithm and great potential in filtering vision data thus forecasting actual coordinates of tracking objects.

Separation of coal and gangue is an important procedure in coal production. Present separating technology has such defects as low efficiency, high pollution, high energy consumption, and high cost. Based on the analysis of grey value of digital images, we prompt a new separation method using image segment. Optimizing ordinary illumination, infrared light is used in lighting part. Algorithm is designed in the basis of histogram character of coal and gangue. Automatic recognition is realized to the segment of coal and gangue, which reach the aim of lower energy consumption and reduce pollutant discharge.

Virtual-hand operation techniques which combined virtual reality with kinematics will be used broadly in the future. In this paper, the collision detection theory in virtual scene about virtual-hand, and the rules of virtual-hand stably grasping a virtual object based on those theories are discussed. At last, a series of virtual operations of virtual-hand grasping virtual objects are achieved, using data gloves and motion tracker as input devices and based on Open Inventor.

In the field of aerophotogrammetry and aerial remote sensing, the linear push-broom imager is increasingly applied for getting the imaging information. What the linear push-broom imager captures is a sequence of line images, therefore, it is essential for imaging to collect the POS data of each line image synchronously. In other words, we need a good method to align the POS data and the line images which are captured at the same time. Using GPS time to align data is a traditional method, but sometimes, GPS does not work, so we present a new method to align the POS data and the line images using computer’s high resolution performance counter. What’s more, we have tested this method proposed in this paper by ground-based experiments and flight experiments, the test results show this method is robust.

The architecture is the backbone of Intelligent Robotic System (IRS). Aimed at the current difficulties for designing architecture, on the basis of previous studies, the evaluation methodologies based on comprehensive integration is provided and then the systematical evaluation criterions including nine quality attributes (Modularity, Niche Targetability, Autonomy, Robustness, Portability, Coordinability, Real-time, Security, Cost and resource constraint) are presented in this paper. Finally, a case study has shown these methods combined of qualitative and quantitative are feasible.

For the traditional server cluster system, even when the work load of the system becomes lighter, the scheduling algorithm will load evenly to all servers, which will cause the server is lightly loaded or idling. It will waste power resources and reduce the effective life of the server. This paper proposed and implemented a resource saving-based server cluster scheduling system (RSSCSS). The system according to the severity of the current work load, enable or disable part of server systems dynamically, with the minimal service resources to meet the user’s service requests , so to save the energy consumption of the servers, network equipments and other supporting facilities such as air conditions, lighting and extend the effective life of those equipments.

In servo system, because of the existence of nonlinear friction link, it is very difficult to parameter identification, and the system dynamic and static performance are greatly effected. In order to improve the performance of the control system, the appropriate control method must be adopted to eliminate the influence of friction. Aiming at these problems, PID control based on genetic algorithm friction compensation in servo system is proposed in this paper. The simulation results show that this method is effective.

The cost of construction projects is more and more complicated, and facing cost reform trend to a certain extent. Construction project’s cost estimation model which is based on artificial neural network, can, to some extent, make the auxiliary construction project cost better estimate. It’s a big help in related engineering bid.This article makes a analytical research on it.Meanwhile it also discusses the model and application process.

With the continuous improvement of industrial automation, automated warehouse has been widely used in various industries to improve the production efficiency and Logistics speed to a great extent. As an essential equipment of automated warehouse, stacker’ working efficiency and stable performance will affect the usability of the warehouse directly. This essay studies the tunnel type stacking in machine’ speed control system of an automated warehouse, and analysis its motion curves. Then we combine it with the stacker’s composite material structure to guarantee better motion control accuracy and motion reliability.

Now days, new energy vehicles is more and more popular in our life. It’s very important for us to explore its origin, development, present situation and its prospect. But now we are not sure whether the new energy vehicles have a good development prospect, whether it has difficulty in technology, whether the new energy vehicles can become the main stream of the car industry. All of these are not sure. Through the analysis of the facts, this essay will clear up the development of new energy vehicles, so we can have a good understanding in the prospect of new energy vehicles.

Personal credit system means some intermediary bodies assemble personal credit, reputation and morality together which scattering in different finical institutions and other social organizations. They will process and storage them and form a relevant real personal credit file database. Through e-network transmit, it can provide service to kinds of departments for knowing the personal reputation, asset, tax-payment, morality and so on. The personal credit system construction for our own country is still in a primary level. Therefore we are urging to establish a complete personal credit system and win a positive position for the future competition. This paper will analysis and make a comparison for each country’s personal credit system. According to our national conditions, I try to explore a suitable way to establish personal credit system.

PLC is an industry control computer which applies microprocessor to its core PLC has been applied to the distributed monitor system which is responsible for high speed data collect of the spot, logic operation, count, PID regulate etc. The computer has been used to manage the monitor system. The HostLink communication protocol of OMRON CP series PLC is introduced in this paper. This article introduces the serial communication control VISA provided by the LabVIEW, the command of the programmable operation of PLC, the link method between PC and PLC, the communication parameters setup of PLC.The article also introduces how to use the RS-232 serial communication port to realize the communication between PC and PLC. The method for realizing the communication between PLC and the host computer is presented by means of LabVIEW. The communication procedure and program is also introduced in detail in the paper. This method ensures that the communication is real time and accurate. Through reading and writing of the host computer from or to the PLC, automatic collection of field data is realized, and the device can be monitored and controlled effectively. The serial communication software is proved to be reliable and stable through the successful application in actual project. This article discusses the communication method between PC and PLC and the structure of s oft and hardware, applying the visual program language. The method can make the best of resources and characters of the system and improve communication efficiency.

The time-invariant resistance and inductance of laser plasma are related to the nanosecond currents in laser excitation in initial discharge phase, and can be obtained through measurements of the laser chamber voltage and current using experienced formula and voltage equation. It is found that the plasma resistance and inductance decrease rapidly with time, and is also proved that the time-invariant resistance is dependent on the total charge in the discharge area, the time-invariant inductance is dependent on the electric field in the laser chamber.

In this paper, we define the WLR-normal band, WLR-normal cryptogroup and LR-regular semigroup. We give some equivalent conditions for a completely regular semigroup to be a WLR-normal cryptogroup and give the characterization of LR-regular semigroups.

From the functional requirements of the inspecting and controlling system for the testing platform of CO

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air conditioning, the inspecting and controlling system based on LabVIEW has been designed in this paper. The inspecting and controlling system based on the virtual instrument is composed by the hardware and the computer equipment software system. The hardware includes the data acquisition card, the mass flow sensors, the pressure and temperature sensors, etc. And the computer equipment software system is self-developed, which has taken the LabVIEW software as the platform and that has the virtual panel and testing functions. The inspecting and controlling system can collect, process and store the data of experimental platform as well as control the parameters of air-conditioning testing platform.

In the item of autonomous mobile robots of Robocup game, the tasks of attack and defense are results of some series state or action transition, including division of roles, finding the ball, keeping the ball, etc. Therefore, the key is how to control and describe the state or action of mobile robots in the competition effectively. Finite Automata model is adopted when designing the decision-making system for mobile robots. In the first place, the robot and environmental information all around are all abstracted into some special symbols and states. Meanwhile, the transition functions of the robots state are set using the perception system of vision and transformed to the inputting symbols of Finite Automata. Finite Automata enters into the next state or remains its original state, according to the preset state transition functions. In the end, it will transmit the order to kinematic mechanism. The experiment proved that the method was able to link and smooth all kinds of action or state of mobile robots efficiently; kinematic mechanism of mobile robots was provided with higher real-time and accuracy.

The development of multi-core processor makes the parallelization of traditional sequential algorithms increasingly important. Meanwhile, transactional memory serves a good parallel programming model. This paper takes the advantage of software transactional memory to parallelize the Multi-Exit Asymmetric Adaboost algorithm for face detection. The parallel version is evaluated on three different implementations of software transactional memory. The experiment results show that the transactional memory based parallelization outperforms the traditional lock based approach. A speedup of nearly seven is achieved on a eight-core machine on an eight-core system.

In this paper, digital image enhancement method is studied and the theory of choosing hard-threshold and soft-threshold in wavelet transform is analyzed, and according to the trait of seismic data, the wavelet threshold is improved. Through the verification of the seismic images in Daqing oil field the new threshold function can effectively remove Gaussian white noise and impulse noise, and the image enhancement effect is remarkable.

Aimed at the dynamical design of the column for a high speed machining center, an optimization design is carried on under the restrain of mass and frequency. Dynamical stiffness is the optimization target. Using the Ansys Workbench, the optimal thickness of ribs in column is solved, and the increment of dynamical stiffness is also given. Optimal model is analysised to verify the optimization design. It is a method to dynamical design typical parts in machining tools.

In this paper, the analysis of reliability software was developed using the MATLAB language. This software has the functions as following: creating sample data with the specify Probability distribution types and parameters, test sample data analysis, solving the reliability problem with 2 to 4 stochastic variable. Reliability function is input by user which enhances the applicability. The method of Monte Carlo is presented to verify the result. The development of this software is an application of computer to the engineering.

This paper aims to make a detail analysis of B-spline interpolation and inverse algorithm that are widely used in CAD/CAM. It points out the nature of two definitions of B-spline curve as well as five correction methods of one B-spline interpolation. In this paper, it explores B-spline inverse algorithm and gives the scope of the algorithm. In addition, it verifies this algorithm by writing a program using VB 6.0.

Quality assessment plays an important role in video business. The bit-stream-layer quality assessment model becomes popular in recent years because of its low-complexity advantage. This paper defines and analyzes some content-related bit-stream features derived from encoded MPEG-2 HD videos. We divide the features into three categories: spatial features, temporal features and compression settings. 9 HD videos with different types of content were used in our experiment. They were encoded at 6 kinds of bit rates. Subjective test and feature extraction were performed on all the bit-rate samples. Then we analyzed all the data by correlation matrix. The results show some compression setting features have very high linear correlation (up to 89.89%) with subjective perceived scores. At the same time, some spatial and temporal features are graphed as functions of bit rate to show their ability of depicting spatial-temporal characteristics of videos. In future, these features will be used for building a bit-stream-layer quality assessment model.

The problem of traffic control is studied according to the system self-organization theory, and from the non-equilibrium traffic system point of view. The rule of the traffic system from existence to evolution is analyzed using the theories. Based on this study, the concept of non-equilibrium traffic control system is introduced, and resulted in the establishment of a fundamental frame work for the non-equilibrium traffic system. Moreover, a practicable methodology is presented.

By using the method of game theory, this paper has analyzed the information asymmetry game of both the offensive and defensive parts in the network honeypot through the complete but imperfect information dynamic game model. From the perspective of game theory, it has conducted the analysis of feasibility and necessity on the intrusion detection system of introducing the honeypot technology and has described the general intrusion and the intrusion detection behavior. Through the analysis on such characteristics as information security asymmetry, incomplete information, rationality and repeated game, and the analysis on game model elements and general model, we have constructed the offense and defense game model in the network honeypot and game process model in the intrusion detection. Meanwhile we have conducted a thorough study and analysis on the game process and then put forward the effective measures of improving the network system security and the attackers’ attacking difficulty.

Considering the expectation of enjoying a tour and many movement function limitations of senior citizens, the author analyzed the advantages and restrictions of the virtual tourism net work for them. The design methods, principles, theories and impression drawings, which meet the physical and mental demands of senior citizens, has been fully detailed.

Crucial biochemical parameters are hard to be measured on-line in real-time in batch fermentation process, which brings difficulties to control and optimization of this process. To solve this problem, soft-sensor technique is applied to implement the on-line estimation of crucial biochemical parameters, and a staged modeling method is presented. Firstly, the modeling data are classified according to their stages by using fuzzy c-means clustering algorithm. Then, a model for the on-line identification of fermentation stages and some local soft-sensor models corresponding to each stage are developed by using neural network. Lastly, simulation is performed based on the production data from Nosiheptide batch fermentation process. The results show the effectiveness of the presented soft-sensor modeling method.

This paper presented a high accuracy voltage source with current limiting function. A high-speed (250 MHz), high-resolution (16 bit) dual DAC is used for generating stimulate voltage by DDS technique. The amplitude of source could be adjusted by wide bandwidth, low noise variable gain amplifiers from -11 to +51 dB. The 4-Opamp architecture is applied to realize a high gain, high-accuracy variable gain instrument amplifier circuit for tiny current sensing. By using analog comparator to convert over-current time into length of digital pulse, the FPGA could monitor the amplitude of current in real-time. Evaluation results show that system has good SFDR performance and fast response speed. With the advantages of accuracy and bandwidth, it is suitable for cell impedance tomography application.

Face detection in the image is an important research branch of face recognition. For the purpose of detecting the faces in images efficiently, a new method of face detection, which is based on AdaBoost merging with the eye contour feature by combining statistics-based with feature-based approach, is proposed. Experimental results show that the algorithm can gain higher face detection efficiency.

In this research we have developed a complete automated experimental setup for the measurement of on-chip delay variations through dynamic partial reconfiguration. The experiment is performed on two different Virtex-5 devices on the basis of which intra-die and inter-die speed comparisons have been made. We developed an on-chip sensor map consisting of 60 sensors out of which only alternating sensors remains active at a time. This is done to avoid affects of inter-sensor heat dissipation. Once finished collecting the data, on-chip processor communicates with the sensor hardware to extract and encode the data, and send it to the online Graphical User Interface implemented on the LabVIEW platform. Afterwards, the processor dynamically loads another bitstream from the Compact Flash Memory Card to activate another alternate group of sensors to perform remaining analysis. While using the same sensor topology we found the intra-die speed variations of up to 6-10%. However, inter-die speed comparison result depicts that one chip is 2-10% faster than another one.

The advanced descriptor, i.e., Local Self-Similarities (LSS), is successfully adopted for object classification and scene recognition. However, it is only invariance against small geometric and photometric transformations. In this paper, two low-dimensional descriptors for extracting distinctive invariant features from interest regions are presented, i.e., PCA and Local Self-Similarities feature based descriptors, namely PCA-LSS and PLSS. They are achieved by applying PCA on LSS feature field and the improved LSS descriptors of normalized patches, respectively. The performance of these proposed PCA-LSS and PLSS descriptors to image matching is studied through extensive experiments on the INRIA Oxford Affine dataset. Empirical results indicate that the proposed PLSS achieves more transformation invariance, significantly outperforms the original LSS, and also outperforms the SIFT.

In order to solve the lack of high resolution imagery and DEM in the accurate simulation of lunar terrain, a fast algorithm for simulating the lunar terrain is presented in this paper. The algorithm fits simple shapes of lunar craters based on rotational equation, and simulates the true distributing of craters using random function. The experimental results demonstrate that the proposed algorithm is not only effective in the simulating of craters which accord with the true lunar terrain well in shape and distributing but also actualizes the secondary impact of craters.

By qualitative analysis and stepwise regression, authors explored the relationship between share prices of Chinese gold companies and the gold prices both internationally and domestically. The results show that the share prices of gold enterprises are generally positively related to the domestic and international gold prices, with the former price impacting more obviously than the latter one, and the gold price in Euro is more powerful than that in US dollar in term of influencing the share price. The rule above is slightly different for different gold companies.

In this paper, we propose mixed generalized Hermite-Legendre spectral method for partial differential equations set in a infinite strip. We investigate mixed generalized Hermite-Legendre approximation. We propose the new algorithm for various boundary condition problems.The global convergence of proposed algorithms are proved.

Artificial Neural Networks(ANN) has been increasingly used by researchers. An ANN model based on fractal growth is introduced in this paper. The design was inspired by the physiology of biological nervous system. Driven by data, fractal structure generates and evolves. Classification interface forms from the fractal structure, which makes the classifier have the capacity on following changes. And a tailor method was designed to change the fractal structure which strengthened the following capacity. The voting framework brings the networks a strong antijamming capability by means of considering several targets at the same time. The design was realized on platform VC/MFC and applied on classification of SEMG. The classification accuracy rate was 91.59%. This model is expected to work well in fields like pattern recognition of weak signal, financial forecast, etc..

In order to alleviate traffic congestions and the influence on environmental impact, developing a model to evaluate under various geometric and traffic conditions is desirable, which is the objective of this study. This study develops a novel traffic simulation model consisting of car following model and lane change model based on desired speed on freeways. Phase transitions of traffic flows are reproduced by using this simulation model.

Recently there has been considerable interest in Multi-agent systems(MAS). However, it is very difficult to accurately design and implement simulation of MAS, in respect that the systems are often extremely complex and based on autonomous software and hardware components, termed as agents, which cooperate within an environment to perform some task. Obviously interoperability is one of the key roles to play in the investigation and development of Multi-agent systems. This paper begins with introduction to High Level Architecture; following, provides an emphatic introduction to agent architecture. Then we outline an approach how to make the MAS simulation accord with the HLA framework. Especially show how the agents simulated on different machines can become a legal Agent Federate joining the flexibly MAS simulation federation. Also emphatically describe the simulation cycle of the MAS system.

Lip-reading and lip identification are the hot spots in the technology of human-machine interaction. Researchers have been committed to work out the key issue that how to extract the most effective features for lip reading. This paper selects feature points and feature parameters for lip-reading based on FDP and FAP defined by MPEG-4. This paper uses an improved snake model on the location and extraction of the feature points. The algorithm has better robustness and has improved the accuracy of contour extraction. Then the SFFS method and correlation analysis are exploited to obtain the quicker optimal sub-aggregate and eliminate the redundancy features. Experimental results of the real data show that the features extracted from the sequence image have a high recognition rate in lip-readings recognition system.

Response time is one of the most important metrics quality of service and response time prediction has always been the a hot topic. Based on random process, there are many common methods for predicting response. However, we find that there are also some features of response time data of service running. According to these features, we summarize the the patterns of response time and propose a novel algorithm for predicting response time. To evaluate our algorithm, we compare PIPA with other algorithms. Experimental results show that PIPA can efficiently improve the accuracy of the prediction.

To satisfy the requirement of user customized business processes, a special kind of computation independent model named well-structured sequential business process model was researched. The method to check the structure of sequential business process models was also proposed. The well-structured sequential business process model was designed in business process modeling notation 1.1 version. It was converted to flowchart model in Windows Workflow Foundation 4.0 version directly, and the tool for model checking was implemented on Windows platform. Experimental results showed that this method supported model converting, and improved the quality of business process models.

Wind power industry developed rapidly in recent years. wind power is a type of power with randomness and fluctuation. Accurate wind speed forecasting can reduce the impact of wind power. Paper analyzed the wind speed signal with wavelet packet decomposition method from low-frequency and high-frequency, selected the optimal wavelet tree through the principle of minimum entropy. Short-term wind speed prediction model is built with support vector machine regression. This algorithm has advanced and better accuracy by comparing the results.

In a large virtual environment, people always tend to lost themselves because of they are unfamiliar to the VE. Autonomous roaming combined with the eagle eye navigator could assist the positioning in the larger scene. This article sets up a bridge between three-dimensional virtual scene and the two-dimensional plane using the web scripting language - JAVA Script. Thus they are synchronized to the HTML page. It allows the visitor to understand the current position of the large virtual scene and anyone can roam unimpeded in the scene.

Biometrics has become one of the most promising authentification techniques in last few years. This paper summarizes the multimodal biometrics techniques which identify an individual from others and also describes a lot of multimodal biometrics systems. Many literatures show that multimodal biometrics techniques have performed more reliability and security than monomodal biometrics ones as they take more than one physiological or behavioral characteristics of the person into account to identify and verify that person. Multimodal biometrics have become one of inevitable trends in the future.

In this paper, we study a novel problem, population burst detection, one of the important issues related population monitoring and management within a city. Based on the detected population bursts, we can trace and analyze these bursts, which can help security departments to infer the cause of bursts and be prepared for the future possible bursts. Though it is useful, it is not trivial to detect population bursts, especially under the condition that we can hardly get the population samples within a city from time to time. To address the difficulties of lacking real population data, we take the advantage of communication networks, specifically, mobile phone networks, which offer enormous communication data between peoples. Most importantly, we find the fact that we can use these communication data to infer the population samples. Therefore, we propose an effective and efficient algorithm to detect bursts over call volumes. We verify the performance of our proposed mechanism with an onsite case study and real calling data.

In this paper, we study a novel problem, population burst trajectory retrieval, one of the important issues related population monitoring and management within a city. Based on the detected population bursts, we can trace and analyze these bursts until retrieve the burst trajectories, which can help the city departments to infer the cause of bursts and be prepared for the future possible bursts. Though it is useful, it is not trivial to retrieve population burst trajectories, especially under the condition that we can hardly get the population samples within a city from time to time. To address the difficulties of lacking real population data, we take the advantage of communication networks, specifically, mobile phone networks, which offer enormous communication data between peoples. Most importantly, we find the fact that we can use these communication data to infer the population samples. Therefore, we propose an effective and efficient algorithm to mine burst trajectories with the help of geographical information systems. We verify the performance of our proposed mechanism with an onsite case study and real calling data.

The transforming criterions and definitions from the interval valued data to the vague valued data are presented and the two transforming formulas from the interval valued data to the vague valued data are presented. The examples make known that the distinct formulas have distinct characters.

Designing and manufacturing of an automatic ultrasonic testing system (scanner) for flaw detection of compressed natural gas (CNG) cylinders, particularly in heat treatment quality assessment, is explained in this paper. Ultrasonic scanners have been installed on 5 different CNG production lines in the territory providing a fast and reliable test of cylinders with the capability of logging results according to customer demands. The paper explains both the machine specifications and the challenges faced during the manufacturing and starting up stages. A questioner was designed to collect the opinions of operators in different sites about handling easiness and performance of the scanners. It was proved that the ultrasonic scanners efficiently identify defects caused in different stages of CNG production line especially in heat treatment furnace. Besides the innovations applied to overcome the practical matters in machine manufacturing, the knowledge of ultrasonic interpreting has been transferred to operators and they earned enough proficiency to distinguish between flaws and noise signals.

The Theta model created a lot of interest in academic circles due to its surprising performance in the M3-competition, the biggest ever time series forecasting competition. As a result in the subsequent years it became a benchmark in any empirical forecasting exercise and an essential tool for efficient Supply Chain Management ad planning as it provides very accurate point forecasts. The present study focuses on if the Theta model is a special case of Simple Exponential Smoothing with drift (SES-d). The Theta model outperforms SES-d in the Quarterly-M3 and Other-M3 subsets by 0.30% and 0.36%.

Because P type immune feedback controller can’t well overcome dynamic interference and eliminate static error, based on P type controller, this paper designs a fuzzy-immune-pid controller, which uses fuzzy control rules and immune feedback control law to adjust the proportion, integral and differential parameters of controller on line, and it is applied to the wired networked control systems with software of truetime1.5 for simulation platform. Because the fuzzy control rules are more refined than immune, from theory analysis, the modified fuzzy immune controller has better control effect and robustness. The simulation results show that the improved control system has a quicker response speed and smaller overshoots and higher robustness.

Considering it is cockamamie to adjust the experiment data of the fuzzy control systems, and it’s easy to get into the problem of local optimum, the researchers propose a fuzzy-immune-pid controller, which combines the fuzzy control and immune PID control, It does not only has the reliability of PID and the strong robustness of the fuzzy algorithm, but also has the ability of global optimizing of immune algorithm. Based on the conventional fuzzy immune controller, this paper improves the fuzzy-immune-pid controller, this improved controller which combined fuzzy immune rules and feedback control theory, which respectively controls the proportion, integral and differential parameters, it make more accurate parameters adjustment. At last, this paper uses the software of truetime1.5 as the simulation platform to apply in wired networked control systems. Simulation results show that the improved fuzzy-immune-pid controller has the characteristics of strong robustness and rapid response.

A common method for moving target detection in image sequences involves a self-adaptive threshold for segmentation. This paper discusses each pixel modeling in the image as a mixture of Gaussian distributions and gives an improved method to update the model. First, the characteristics of the different frames method and a mixture of Gaussian distributions will be discussed. And then, the two methods, different frames method and a mixture of Gaussian distributions are combined to decide which learning rate is suitable for the updating method at this moment. If there is no moving target in the image sequences, the background model should be updated quickly to get the real background with low noise. The better foreground images will be gotten by this method with low computational complexity. The improved algorithm performs more robustly and powerfully than the classical Gaussian Mixture Model in moving target detecting.

The article deals with the problem of reliability assessment of robotic systems and it is specifically focused on the analysis of the current situation in the field of component reliability prediction. The techniques of the component reliability prediction using the most credible methods (MIL-HDBK-217F, PRISM) and reliability databases (EPRD-97, NPRD-95) are presented in the article. Also the latest reliability prediction methods FIDES, 217Plus and reliability database SPIDR are presented.

Ontologies are essential for smart home, as they act as the semantics for describing the services provided by appliances. However there is no domain upper ontology to differentiate the concepts and explicate the relations among them. By analyzing the context of home service, we abstract six key concepts in the field and analyze the relations among them. As a result, we propose an upper ontology to illustrate the inter-relations and inter-dependency of concepts. Finally two scenarios are given to show the usage of our ontology.

A novel automatic gas-tungsten arc-welding (GTAW) system has been developed at NSRRC for welding the aluminium (A6061-T651) vacuum chambers to be installed in an Ultra-high vacuum (UHV) system. This welding system has a XY stage that is built and configured to provide high-performance positioning along multiple welding axes. The automatic system comprises six welding torches to implement simultaneously two longitudinal side welds of an aluminium chamber, and is innovative in using computer-based software to control the welding movements and the welding energy of the six-torch output. In traditional single-torch welding, the key success factors focus on eliminating as much as possible the distortions of structural assemblies. The six-torch welding and the clamp-free approach together address the issue of reducing distortion and minimizing residual stresses with a novel one-step welding process. This paper introduces the mechanical configuration and the motion-control program. Real-time measurements for thermal and deformation monitoring to analyze the temperature distribution along the chamber surface are discussed. The welded chambers are tested with a leakage-free hermeticity test <5(10-10 mbar·L/s; the maximum deformation is controlled under 0.3 mm.

The neural transmission delay of DIVA model was studied.Based on the detailed analysis of the speech transmission delay characteristics,the feedforward and feedback control strategy was proposed.It is proved that the delay can be controlled reasonably.Aiming at the network state disturbance caused by parameters changes during the neural network learning process, this paper does related emulation experiments. Experimental results show that this method is effective and gives good robustness.

DIVA (Directions Into Velocities of Artculators) is a mathematical model of the processes behind speech acquisition and production, it is also an adaptive neural network that learns to control movements of a simulated vocal tract in order to produce words, syllables or phonemes. But the research of recognition system in DIVA model is fuzzy. This article analyze the description of speech target based on the DIVA model, and the way of speech production is improved, so as to supplement the speech recognition system of DIVA model.

The paper use two different methods of image moment invariants and wavelet packet-energy entropy (WP-EE) to extract the pump dynamograph’s eigenvector, then making the collected date is training samples and test samples for the support vector machine (SVM) classifier separately, finally comparing the accuracy of two methods. The experimental results show that when choosing classifier based on support vector machine, the method of extracting image moment invariants has more higher accuracy than the other method.

The models of two kinds of height control system which include the attitude autopilot inner loop and acceleration autopilot inner loop respectively are built. The response rate, stabilization and engineer realization of gravity compensation of the height control systems are analyzed and compared. The result shows that they have same performances and can be used both in missile altitude control. The gravity compensation can improve the transition quality of height control and decrease the overshoot. The gravity compensation command matching attitude autopilot depends on the flying parameter heavily, so the engineer reliability is lower than acceleration autopilot.

Along with the development of virtualization technology, the computing tasks’ type worked in virtual machine is more diverse and GPU intensive task has become a trend. But most current VMM scheduling algorithms pay little attention to the task types of diversification, but abide by "fair" principle and distribute CPU resources equally, which would be unable to meet the requirement for latency-sensitive tasks. Through theoretical analysis and a series of experiments, this paper confirme that the CPU resources sensitivity of different task type is different and put forward an optimized scheduling strategy based on task type. The VMM calculates the real-time scheduling priority according to CPU and GPU resource utilization of all active guest domains, and then redistributes the physical CPU resources. The experiments show that the optimized scheduling strategy can promote the performance of the GPU intensive tasks and improve user experience.

With the improvement of living standard, people are paying more and more attention on the freshness of meat products. T he Machine olfactory system was established to detect meat freshness simply and quickly. In this paper the principle of electronic nose system was introduced, six types of gas sensors were selected according to the composition of smell of corrupted meat, and hardware system of a machine olfactory was built by sensor array and data acquisition card. In addition, LabVIEW and MATLAB were used to finish data acquisition, data analysis and waveform display. In order to find the relationship between corrupted meat odor and the freshness, a machine olfactory system experiment device was made to do identification experiments of meat sample that stored 1-5 days. The results of experiment showed that gas concentration of detected pork samples was related to the storage time. So, it is feasible to identify meat freshness with machine olfactory system experiment device.

In an ambient assisted living project, a novel way to be proposed in order to protect privacy, increase comfort and safety: a system that with different kinds of sensors installed in the living environment and observe the daily activities of the elderly. Based on the daily activities of the user an activity model will be build. In case of unusual activities the system will send alarm signal to caregiver according the build activity model.

The huge amount data from sensors is a computational burden for the system and an obstacle for the system to get character parameters to build activity model. In the paper data correlation is used to deal with the data and detect the relationship between sensors. In predefined time interval the data from sensors is correlated. The huge amount data is translated to a few correlation parameters between sensors. Furthermore the values of correlation parameters between sensors are changing in different time interval. That means different activities of the user are detected by the system.

The São Paulo sanitation sector generates annually great revenues, becoming a great attraction to investors. Improve results and expand the customer base is responsibility of the company’s commercial area. Increase the sales has become a great challenge for the managers. One of the ways to increase the business is through the effective use of large amounts of information stored on corporate systems. In this context the Business Intelligence emerged as a key differentiator, since this architecture allow to access and explore the information contained in corporate databases. The Enterprise Architecture provides a set of best practices focused on improving the performance by structuring the information and integrated views of strategy, business processes, systems and technologies. The aim of this paper is to analyze the BI application in conjunction with Enterprise Architecture in the commercial area of a sanitation company to identify the contribution of the association of these two architectures.

Nowadays, more and more people are shopping online. With the increase of user session, how to provide better e-commerce services and how to describe the network load as well as the advantages and the disadvantages of current services have become the urgent problems. Through the description of e-commerce workload, an intuitive and reliable result can be provided to the managers of website for the current runnability and the development trends, which can also provide the reference for the further improvement and the upgrade of website. And in this paper, the e-commerce workload has been analyzed from the aspects of theory and implementation.

It is a significant challenges to deal with the noise data in data mining and knowledge discovery applications. Most of previous works on data cleansing and correction have been focused on addressing class noise or attribute noise for the benefit of the subsequent mining process. In this paper, we propose an error-sensitive(ES) data mining framework, which makes use of noise knowledge to restore original data distributions and accommodates noise knowledge to enhance data classification accuracy. We materialize our main idea by constructing Attribute-Decision tree and measureing correlation among attributes. Experimental results show that ES data mining procedure has ability to significantly improve the quality of data mining results.

Based on our previous researches, this paper introduces a new differential equation model to describe the dynamics of traditional Chinese medicines (TCM) + nucleoside analogues (NA) anti-HBV infection treatment for the chronic hepatitis B (CHB) patients. This model has five state variables. A treatment-activated specific term in this model is in charge of directly clearing patients’ HBV rather than damaging patients’ hepatocytes. As an application, we use this model to simulate the dynamics of TCM + NA anti-HBV infection personalized combination treatments. The numerical simulations and analysis show that the TCM + NA combination treatments are able to activate patients’ abilities of cytokine-midiated noncytolytic HBV clearance.

The paper describes special active power filter solution. There are given control algorithms and methods for the filter current regulation. Firstly, there is described power part structure of the filter with the resonant converter and general conception structure of the filter. Then there is description and calculations of the control algorithms and methods for the filter currents regulation. In the paper are given results of practical realization, which was, in this case, mainly orientated to control algorithm research. For this purpose was selected DSP TMS320F2812 and implemented to the control unit of the filter. Control unit was practically realized by use of development DSP kit. Sample of practically realized control unit was designed as universal control unit for power electronics applications. Reached results that are presented in the paper are simulation and practical realization results.

Steel billet recognition is an urgent requirement in the steel industry of heavy rail line. Due to high temperature and complex scene in the rolling line, the recognition at the end of billet is quite different from optical character recognition with simple background and vehicle license plate recognition. In order to solve the problem, this paper presents some new schemes in character location, segmentation and recognition in the complex scene. These proposed algorithms include the location algorithm of multilevel filter based on separability criterion, the segmentation algorithm based on intelligent multi-agent and the recognition algorithm of character features matching combining the template matching. The results show that the proposed algorithms are effective for steel billet character recognition in the complex scene.

When an autonomous vehicle (AV) performing automated tracking maneuver under complex road conditions such as driving with curves or with lane changing, the strong dynamic coupling effects exist in vehicle motion, thus it is very important to get ideal control effect by integrated lateral and longitudinal control system. In order to achieve automatic tracking control, assuming that a vehicle model based rigid body is make according to the simplified kinematic vehicle model. From this vehicle coupling model, the tracking control system of AV is derived. Based on Backstepping control method, the vehicle coupling variable structure control law has been designed. The stability of the tracking control system is analysed by using Lyapunov function method. Simulation results demonstrate that the control law designed could track the reference trajectory quickly, ang that it is effective and stable during AV’s path tracking maneuver.

Dominant plane detection is an essential task for an autonomous navigation of mobile robots equipped with a vision system, as we assume that the robot moves on the dominant plane. In this paper, a brief review about state-of-art method for planar region detection is presented. All these methods are classified into three types, that is stereo-based, monocular-based and multi-sensor fusion based method according to the sensor they used. And the monocular-based method is further divided into three kinds, projection invariance, homography based and optical flow based method. For each kind of the method, the correspondent references and its main process are summarized. Finally, the challenges for plane detection with vision are presented in authors view. We hope that this paper can be a start point to probe deep insight in this field.

This article based on the structure of Lucene indexing system , analyzes the common advantages of index-related technology and scalability. Finally, summed up some quality attributes , which need to focus on the index system, indicating that the distributed environment of the indexing system works. Then designed a full-text retrieval system based on Lucene model, and applied this model to the search engine system of the forestry information system to experiment. Experimental results show that, the indexing system based on Lucene is not only efficient but also faster retrieval speed.

Design a new type of broadband electromagnetic method system with GPS simultaneous localization, so as to meet the ever-increasing demand of geophysical prospecting. The system consists of three main parts, namely transmitter and receiver and GPS positioning. Magnetic field is stimulated by transmitter with broadband in a continuously controllable way, and three receiving coils with different spacing receive signals simultaneously, so that measurement data are more extensive and analysis results are more complete. Through simultaneously recording location information by GPS, a wide range of surveying tasks can be finished once. Compared to traditional electromagnetic method equipments, the system is more convenient and greatly reduces work intensity of technical personnel.

In this article a system is developed to improve the performance of Computerized Numerically Controlled (CNC) machines by utilizing on-line vision based monitoring and control systems. Two different types of CNC machines are used in the investigation. Two cameras are mounted on the machine spindle of each of the two employed CNC machines to provide valid image data according to the cutting direction. Proper selection and activation of relative camera is achieved automatically by the developed system which analyze the most recent conducted tool path movement to decide on which camera is to be activated. In order to assess the machining surface quality and cutting tool status, image data are processed to evaluate resulting tool imprints on the machined surface. An indicating parameter to assess resulting tool imprints is proposed and used. Results show the validity of the approach and encourage further development to realize industrial scale intelligent vision-controlled-CNC machines.

TA mobile robotic arm that can be controlled using computer is proposed in this paper. For PC based controller, a graphical user interface (GUI) software was used to provide control capability on the mobile robot developed using Visual Basic. The PC is connected to the mobile robot via serial port (RS232). The mobile robot also can be controlled using our portable control box. For hardware interfacing, Programmable Interface Controller (PIC) was used. The PIC receives the signal from the PC to provide motion control on the mobile robot. This PIC acts like analyzer that will analyze a serial signal from PC and produce a PWM (Pulse Width Modulation) combined with Electronic Speed Controller (ESC) that has high current spec to control high power motor. All of thees combinations were used to control motor speed. It has been shown that the designed robot can grip up to 500 grams load. The robotic arm can be used in multi-purpose applications such as in industrial manufacturing and servicing robot.

In the field of surveillance, Effective and rapid video object segmentation is a key technology for video analysis and processing. For the complex scene and noise that affect segmentation issue in the fixed occasion, on the base of classic Gaussian Mixture Background Model (GMM), a new algorithm named the fusion of Spatio-Temporal based on GMM is proposed for video object segmentation, which classifies for each pixel in Time and Space scales. Firstly, the algorithm constructs dynamically Gaussian Mixture Background Model for each pixel and segment foreground objects through background subtraction. Secondly, the algorithm detects synchronously the neighborhood statistic feature of each pixel through two lemmas. Finally, a result is produced using the spatial segmentation coupling with the temporal segmentation by “and” operator. Experiments show that our proposed algorithm can segment the moving object effectively and quickly from video sequences and has stronger robustness application prospect contrasted with other algorithms.