Intelligent Computing and Information Science

This paper presents a solution of unified e-currency based on the fourth party platform integrated payment service. The purpose of the paper is to solve the problem of distribution and resource-wasting caused by the lack of unified electronic currency, and to solve regulatory difficulties due to regulation size caused by a wide variety of e-currency. Methods: This article first analyzes the problems in the development of electronic money, and then proposes the concept of a unified electronic currency based on the fourth party platform integrated payment service. Besides, it proposes a unified mechanism and transaction procedures for unified e-currency, and analyzes the liquidation process, security and regulatory requirements, which are involved in using unified electronic currency.

Based on power dual-branching transmission system of herringbone gears, the mechanical structural model was established. This study represented the simplified algorithm to obtain its power flow situations through formulating the deformation compatibility condition for the linear relationship between the torque and transverse deformation of tooth surface and the torque equilibrium condition. Besides, the effects on the power flow of system were calculated under all kinds of the installation error and processing error of gear pairs. Finally, the power flow situations of dual branches were solved via Programming. A numerical example that illustrated the developed theory was provided. The research results can be applied to analyze the actual application of herringbone gears power split-path transmission system.

To solve the order tracking of across enterprises in Dynamic Virtual Enterprise (DVE), a SaaS and web service based order tracking solution was designed by analyzing the order management process in DVE. To achieve the system, the SaaS based architecture of data management on order tasks manufacturing states was constructed, and the encapsulation method of transforming application system into web service was researched. Then the process of order tracking in the system was given out. Finally, the feasibility of this study was verified by the development of a prototype system.

There are lots of differences between multi-temperature refrigerated vehicles and ordinary ones in many aspects such as structure and running circumstances, hence the hugely different heat-transfer characters and response coefficients. This paper researched the unsteady heat transfer process of the multi-temperature refrigerated vehicle by response coefficients method, numerically calculated the unsteady heat transfer of inner thermal insulation materials in the multi-temperature refrigerated vehicle by computers, and studied the influences of different term numbers of equation root, term numbers of response coefficients on load calculation accuracy. It showed that the accuracy requirement could be met when the root of equation was -25 and the term number of response coefficient was 30.

At first, this article gives an introduction to the principle and evaluation procedures of TOPSIS. Secondly, Using TOPSIS method to assess 8 prefecture-level cities of a province of China based on the basis of statistical data. The evaluation results demonstrate that the application of TOPSIS method to Industrial economic benefits is Reasonable. TOPSIS has some practical value in the economic field, can provide scientific basis for the scientific management.

The optimization of modeling method and distributing research of choosing the measuring points for thermal error of CNC machine were presented based on the theory of weighted grey relative analysis in the article. The model of weighted grey relation was set up firstly, then, by calculating the matrix of grey relation between the temperature data serial of thermal points and thermal error data serial, after classify the thermal points which placed on the CNC machine, 5 critical points which should be in different classes were picked out from whole16 temperature points according to the degree of grey relation. At last, the thermal forecasting model was founded using the 5 critical points. The model was validated to be more accurate and robust.

This paper proposes a direct-sequence UWB Gaussian pulse of cognitive radio systems based on bridge function smart sequence matrix and the Gaussian pulse. As the system uses the spreading sequence code, that is the bridge function smart code sequence, the zero correlation zones (ZCZs) which the bridge function sequences’ auto-correlation functions had, could reduce multipath fading of the pulse interference. The Modulated channel signal was sent into the IEEE 802.15.3a UWB channel. We analysis the ZCZs’s inhibition to the interference multipath interference (MPI), as one of the main system sources interferences. The simulation in SIMULINK/MATLAB is described in detail. The result shows the system has better performance by comparison with that employing Walsh sequence square matrix, and it was verified by the formula in principle.

Industry-university-institute cooperation is an important means to accelerate technical development and achievements for high-tech enterprises. Considering that Zhejiang high-tech enterprises existed some problems which included low cooperative level, single distribution, weak secondary R&D ability, obvious risk and so on, government should play an guiding role on improving information service system, enhancing cooperative level, promoting scientific intermediary service organization system construction, and building better environment for Industry-university-institute cooperation.

Aiming at puncture image characteristic of robot auxiliary radio frequency ablation, a modified tradition camera calibration method is proposed in this paper. Based on the comprehensive analysis for puncture image distortion characteristic, there are three geometric distortions in the puncture image system: radial distortion, centrifugal distortion and thin lens distortion, we research the distortions and establish the correction matrixes one by one, and then establish the camera mathematical model under the puncture condition, complete the coordinate systems’ conversion calculation to obtain the camera internal and external parameters, finally to get the puncture system calibration polynomial. Through the comparative experiment that takes the area as parameter, we get that the puncture system calibration method after image correction can meet the accuracy requirement in actually.

Utilizing the sleep switch transistor technique and dual threshold voltage technique, a source following evaluation gate (SEFG) based domino circuit is presented in this paper for simultaneously suppressing the leakage current and enhancing noise immunity. Simulation results show that the leakage current of the proposed design can be reduced by 43%, 62%, and 67% while improving 19.7%, 3.4 %, and 12.5% noise margin as compared to standard low threshold voltage circuit, standard dual threshold voltage circuit, and SEFG structure, respectively. Also, the inputs and clock signals combination static state dependent leakage current characteristic is analyzed and the minimum leakage states of different domino AND gates are obtained. At last, the leakage power characteristic under process variations is discussed.

In this paper, an empirical mode decomposition (EMD) scheme is applied to analyze the steady-state visually evoked potentials (SSVEP) in electroencephalogram (EEG). Based on EMD method, the oscillatory activities of the decomposed SSVEP signal are analyzed. It is observed that the 6

th

IMF showed the features of the attention-to-rest transition response. In other words, high powers are observed instantly after the volunteer turns from an attentively focusing stage into an unfocused attention stage. Having made the point that the 6

th

IMF of the SSVEP signals corresponds to very low frequency (0.5 – 2 Hz), this drives us to look into that frequency range of the SSVEP signal. All of this reflects that a very low frequency seems to occur during the attention-to-rest transitions. Experiments are performed with different people. The result shows that the attention-to-rest transition can be detected with an accuracy of 82.6%.

In recent years considerable concerns have arisen over building

Intelligent Transportation System

(ITS) which focuses on efficiently managing the road network. One of the important purposes of ITS is to improve the usability of transportation resources so as extend the durability of vehicle, reduce the fuel consumption and transportation times. Before this goal can be achieved, it is vital to obtain correct and real-time traffic information, so that traffic information services can be provided in a timely and effective manner. Using

Mobile Stations

(MS) as probe to tracking the vehicle movement is a low cost and immediately solution to obtain the real-time traffic information. In this paper, we propose a model to analyze the relation between the amount of

Periodic Location Update

(PLU) events and traffic density. Finally, the numerical analysis shows that this model is feasible to estimate the traffic density.

The features and classifications of Virtual Reality Techniques have been summarized and recommendation of applying Virtual Reality on distance education has been made. Future research is needed on the design and implementation of virtual classroom and courseware.

The essay advances a unified authentication based on the fourth integrated payment platform. The research aims at improving the compatibility of the authentication in electronic business and providing a reference for the establishment of credit system by seeking a way to carry out a standard unified authentication on a integrated payment platform. The essay introduces the concept of the forth integrated payment platform and finally put forward the whole structure and different components. The main issue of the essay is about the design of the credit system of the fourth integrated payment platform and the PKI/CA structure design.

With the popularity of virtual machines, forensic investigators are challenged with more complicated situations, among which discovering the evidences in virtualized environment is of significant importance. This paper mainly analyzes the file suffixed with .vmem in VMware Workstation, which stores all pseudo-physical memory into an image. The internal file structure of .vmem file is studied and disclosed. Key information about processes and threads of a suspended virtual machine is revealed. Further investigation into the Windows XP SP3 heap contents is conducted and a proof-of-concept tool is provided. Different methods to obtain forensic memory images are introduced, with both advantages and limits analyzed. We conclude with an outlook.

This paper deals with an approach to the optimization and reconfiguration of advanced manufacturing mode based on the object-based knowledge mesh (OKM) and improved immune genetic algorithm (IGA). To explore the optimization and reconfiguration of the new OKM by the user’s function requirements, an optimization procedure of an OKM aiming at the user’s maximum function-satisfaction is proposed. Firstly, based on the definitions of the fuzzy function-satisfaction degree relationships of the users’ requirements for the OKM functions and the multiple fuzzy function-satisfaction degrees of the relationships, the optimization model of the OKM multiple set operation expression is constructed. And the OKM multiple set operation expression is optimized by the immune genetic algorithm, with the steps of the OKM optimization presented in detail as well. Based upon the above, the optimization and reconfiguration of an advanced manufacturing mode are illustrated by an actual OKM example. The proposed approach proves to be very effective.

Presently water resource in most watersheds in China is distributed in terms of administrative instructions. This kind of allocation method has many disadvantages and hampers the instructional effect of market mechanism on water allocation. The paper studies South-to-North Water Transfer Project and discusses water allocation of the node lakes along the Project. Firstly, it advanced four assumptions. Secondly, it analyzed constraint conditions of water allocation in terms of present state of water allocation in China. Thirdly, it established a goal model of water allocation and set up a systematic model from the angle of comprehensive profits of water utilization and profits of the node lakes. Fourthly, it discussed calculation method of the model by means of Simulated Annealing Hybrid Genetic Algorithm (SHGA). Finally, it validated the rationality and validity of the model by a simulation testing.

Contraposing to the shortage of narrow efficient area and over current when vector control method is applied to vehicle drive motors, this paper proposes a feed-forward MAP-based vector control method of vehicle drive motor. According to required motor torque and speed, directly control the magnitude and direction of voltage space vector to realize the aim of motor torque control. So, the calculation of torque current component and field current component is no need, which not only avoids over current that the PID closed-loop control leads to, improving the reliability of controller, but also avoids the dependence on current measurement, improving control precision and motor efficiency. Finally, simulation results and motor bench test prove this method can significantly enlarge efficient area, and it is suitable for vehicle running conditions.

Based on the construction feature and operating principle of the wet-shift clutch transmission, the condition monitoring and fault diagnosis for the transmission of the tracklayer with wet-shift clutch were implemented with using the oil analysis technology, function parameter test method and vibration analysis technology. The new fault diagnosis methods were proposed, which are to build the gray modeling with the oil analysis data, and to test the function parameter of the clutch press, the rotate speed of each gear, the oil press of the steer system and lubrication system and the hydraulic torque converter. It’s validated that the representative function signals were chosen to execute the condition monitoring analysis, when the fault symptoms were found, and the oil analysis data were used to apply the gray modeling to forecast the fault occurs time can satisfy the demand of the condition monitoring and fault diagnosis for the transmission regular work.

In recent years, many research works have revealed some technological networks including internet to be small-world networks, which is attracting attention from computer scientists. One can decide if or not a real network is Small-world by whether it has high local clustering and small average path distance which are the two distinguishing characteristics of small-world networks. So far, researchers have presented many small-world models by dynamically evolving a deterministic network into a small world one by stochastic adding vertices and edges to original networks. Rather few works focused on deterministic models. In this paper, as a important kind of Cayley graph, the circulant graph is proposed as models of deterministic small-world networks, thinking if its simple structures and significant adaptability. It shows circulant graph constructed in this document takes on the two expected characteristics of small word. This work should be useful because circulant graph has serviced as some models of communication and computer networks. The small world characteristic will be helpful to design and analysis of structure and performance.

With China’s changing economic structure and increasingly fierce competition in the market, the uncertainty and risk factors in the projects of electric power construction are increasingly complex, the projects will face huge risks or even fail if we don’t consider or ignore these risk factors. Therefore, risk management in the projects of electric power construction plays an important role. The paper emphatically elaborated the influence of cost risk in electric power projects through study overall risk management and the behavior of individual in risk management, and introduced the Bayesian network to the project risk management. The paper obtained the order of key factors according to both scene analysis and causal analysis for effective risk management.

The development status of logistics in the financial crisis requires the shippers and carriers’ overall goal focus on cost reduction. This paper firstly analyzes the problem of information mismatch between shipper and carrier in nowadays, and describes the shippers and carriers’ demand for information platform. Then based on requirement investigation and questionnaire statistics, the specific demands for logistics information matching platform are analyzed. Finally, logistics information matching platform system for highway transportation is designed.

Neural network is an intelligent method in conditon trend prediction, while the condition trend prediction is important to guarantee the safe operation of large equipments. In order to overcome the deficiency of basically the same probability contribution of neural network input to output predicted, this paper proposes an intelligent prediction method based on information entropy weighted neural network, taking Elman neural network as the basis, combining with information entropy theory to construct the prediction model based on information entropy weighted Elman neural network. Condition trend prediction results of the flue gas turbine showed that the proposed new method has better prediction precision and real time performance.

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Tourist is a conventional kind of commuters in the urban transport system. During some mega-events, such as Olympic Games or Expos, tourists would become the most important and sizable part of commuters in the host city. Expo 2010 Shanghai will attract 70 millions tourists during the whole 184 days duration. The large number of tourists expected to be carried, combined with the congested urban road network and limited parking spaces, will make it difficult for individual transport to be used during the Expo; as such, high rates of utilization of public transport will be necessary. Hence, exploring the trip mode choice behavior of Expo tourists is the keystone for traffic planning of Expo 2010 Shanghai, especially for the difference of heterogeneous tourists from various departure areas. A joint model system, in the form of associating clustering analysis and HL model, is developed in this paper to investigate the differences of trip mode choice behaviour among heterogeneous tourist groups. The clustering analysis method is used in this paper to distinguish the various types of Expo tourists for the choice sets are variable with the attributes of groups. Sorted by the attribute of departure area, tourists of Expo Shanghai could be divided into three kinds: local visitors, out-of-town one-day-trip visitor and out-of-town lodging visitors. The statistic parameters of three kind models constructed by this joint system show that this modeling method improves analytic precision effectively.

Schema matching is the process of identifying semantic mappings, or correspondences, between two or more schemas. Schema matching is a first step and critical part of data integration. For schema matching of deep web, most researches only interested in query interface, while rarely pay attention to abundant schema information contained in query result pages. This paper proposed a mixed schema matching technique, which combines attributes that appeared in query structures and query results of different data sources, and mines the matched schemas inside. Experimental results prove the effectiveness of this method for improving the accuracy of schema matching.

This paper talked about the character of DS/FH communication system, and studied on how the DS/FH technology uses in TT&C system. A scheme using DS/FH in the TT&C is presented in this paper, including the work model and the design of hardware. The result of validation board shows the scheme is available and suitable for TT&C system.

This paper presents a critical path expert system for the agility manufacture process management based on radio frequency identification (RFID) technology. The paper explores that the agility manufacture processes can be visible and controllable with RFID. The critical paths or activities can be easily found out and tracked by the RFID tracing technology. And the expert system can optimize the bottle neck of the task process of the agility management with the critical path adjusting and reforming method. Finally, the paper gives a simple application example of the system to discuss how to adjust the critical paths and how to make the process more agility and flexibility with the critical path expert system. With an RFID-based critical path expert system, the agility manufacture process management will be more effective and efficient.

Based on the features of artificial immune system, a new evolutionary strategy is proposed in order to calculate the numerical integration of functions. This evolutionary strategy includes the mechanisms of swarm searching and constructing the fitness function. Finally, numerical examples are given for verifying the effectiveness of evolutionary strategy. The results show that the performance of evolutionary strategy is satisfactory and more accurate than traditional methods of numerical integration, such as trapezoid formula and Simpson formula.

With the development of thermal power industry, statistics on the NOx emissions become important. In this paper, based on the traditional support vector machine model, we establish support vector machine model optimized by chaos optimization algorithm, improve the prediction accuracy of SVM model. Use the NOx emissions data from 1995 to 2009, predict the NOx emissions from thermal power plant in the year of 2010, and verify the reasonableness of the COSVM model.

Cell culture at large scale normally uses stirred structure. And the situation of temperature field distribution is very important to the cell culture at large scale. Some cells are very sensitive to the circumstances. The local temperature is too high or too low all influences the cell survival and low the cell quantity at unit volume. This paper simulates the temperature field under three different heating conditions. Then analysis and contrast the simulation results. The mixed situation in bioreactor is extremely significant for nutrition transmit. Usually, use ways to measure the average mixture time in bioreactor, and improve the mixture circumstance in the bioreactor through stirred impeller and bioreactor structure change. This paper adopts numerical calculation method to investigate the flow field in bioreactor. It gets the mixture time of bioreactor through virtual tracer in simulate flow field and detects the tracer density time variation curve in the bioreactor.

The task of topic detection becomes the hotspot research direction in the field of natural language processing in recent years. The cyberspace public opinion has given the significant impact on the large numbers of internet users. This makes the effective public opinion detection and tracking become very important. We select the effective features in the story document and the vector center model is taken to represent the text document. The algorithm of distance based clustering is carried out for public opinion detection. It identifies the emergence of new events and also merges the story to the corresponding cluster. Finally, we give the performance evaluation by the F-Value and entropy value. The system achieves the performance of 76% F value on the test set. The technique of topics detection can monitor the information sources in various languages, and it will provide the efficient guidance for judging the hot spots on the web.

A low-jitter clock duty cycle corrector circuit applied in high performance ADC is presented in the paper, such circuits can change low accuracy input signals with different frequencies into 50% pulse width clock. The result have show that the circuit could lock duty cycle rapidly with an accuracy of 50% ± 1% in 200ns. This circuit have 10%-90% of duty cycle input, and clock jitter could be suppressed to less than 5ps. The method used in the circuit, which provides little relationship with the noise and process mismatch, is widely used Implemented in 0.18

μ

m CMOS process.

The risk in the process of enterprise’ technology innovation is concluted five subsystems: environmental risk, market risk, enterprise capacity risk, project risk and project management risk, 16 risk factors under each subsystem are identified. A Interpretative Structural Modeling(ISM) of of risk factors is established, the relationship and influence levels of them is confirmed, the purpose is to help enterprise assessing risks and taking countermeasure to minimize the potential loss and increase the innovation income.

The reservoirs dispatch of ERSNWT underway the environment of water resources market allocation, and water rights constraints must be considered, as well as the relationship between cost and flow when dispatch, which determines the pure technology optimization no longer fit the requirements of reservoirs dispatching of ERSNWT, while the minimum cost maximum flow in network flow in line with characteristic of this reservoirs dispatch of ERSNWT. A network flow dispatching model is established, which constrained by water rights. Finally take the first phase of Eastern Route of South-to-North Water Transfer Project as an example to verify the validity of the model, the result shows that the model meets the characteristics of water dispatching of Eastern Route.

In recent years, the problems with multi-objective optimization have become a hot topic among the interest of scholars. In this paper, a new artificial immune algorithm is proposed based on the concept of Pareto optimization. The mechanism of clone is imported into this new immune algorithm, at the same time, the new immune algorithm consists the two concepts, which are trichotomy overlap method and preference difference respectively in order to build an efficient immune clone model of solving multi-object problems. Finally, an example shows that the new immune clone algorithm can obtain better results when it is used to solve the multi-object problems.

Cultivation of students’ learning autonomy has raised new challenges to teachers’ professional development, dynamic, continuous, lifelong full-scale development, with emphasis on the creativity and constancy of the teachers’ quality development. The teachers’ professional development can take the following approaches: studying theories about foreign language teaching with the aid of modern information technology; organizing online teaching research activities supported by information technology and carrying peer observation and dialogue –teaching reflection in internet environment and fostering scholarly teachers.

In a real stream environment, labeled data may be very scarce and labeling all data is very difficult and expensive. Our goal is to derive a model to predict future instances’ label as accurately as possible. Active learning selectively labels instances and can tackle the challenges raised by highly dynamic nature of data stream, but it ignores the effect of unlabeled instances utilization that can help to strength supervised learning. In this paper, we propose a framework that combines active and semi-supervised learning to get advantage of both methods, to boost the performance of learning algorithm. This framework solves the active learning problem in addition to the challenges of evolving data streams. Experimental results on real data sets prove the effectiveness of our proposed framework.

The new type of flywheel battery requires control system with compact structure and low manufacturing cost. To meet this requirement, a new method for the sensorless vector control of flywheel battery is proposed in this paper. The advantage of the proposed control system is that it does not need an extra sensor to obtain the flywheel speed and position information. The determination of flywheel position and thereby speed are made by estimating back electromotive force (EMF) using the artificial neural network (ANN) observers. By doing so, the dimensions and cost of the driver system can be reduced. The ANN observers use the instantaneous values of stator voltages and currents and the estimated error of the stator current as their input to output the back EMF components in the

α

-

β

reference frame. A simulation model was established by the use of MATLAB/Simulink software to carry out the numerical experiments. The test results demonstrate that the proposed charging control system for flywheel battery has a good control performance and a good robustness. The speed /position estimation precision is high and the error is acceptable for a wide speed range.

Automated document classification approaches are divided into two major groups. The first is the group of keyword-based classification methods; these are frequently associated with unclear meanings of keywords and other issues. The second group is based on semantic analysis. Various academicians have constructed ontologies to solve semantic problems. However, ontology depends on expert knowledge of the problem domain, and the process of constructing knowledge depends on the participation of knowledge engineers. Folk classification (Folksonomy) is associated with Web2.0. Since Folksonomy is keyword-based, it still is associated with a semantic problem. This study presents an improved weighting mechanism to solve the semantic problems and the problematic effects of poor classification. The results of this study indicate that the Folksonomy-related weight classification mechanism can effectively reduce the number of classification results by more than 30% significantly improved the quality of tagging, and increased user satisfaction.

Due to the gyro random walk and other reasons, Schuler oscillation amplitude of undamped inertial navigation system will increase with time. The marine inertial navigation systems were often required to work continuously for hours to days or even longer, over divergent INS position error will cause loss of navigation function. Thus, the appropriate algorithm in the system must be added to damp the Schuler oscillations. The damping networks for INS level channels are designed. For the applications of marine INS, a new internal damping method which uses its own measurements as reference velocity rather than external inputs is presented. Marine test results show that the proposed internal damping method can suppress the Inertial Navigation System Schuler oscillation error and make it no longer divergent, thereby improving the navigation accuracy of INS in long-endurance applications, and has practical values in engineering.

Process migrating technology usually is used to solve the problems like user process death, system crash or lower executing efficiency because of the load unbalancing among the multi-processors. Virtual machine can supply system level backup and migration. But it is too much overhead sometimes. In this paper, a process migration technology on program level is put forward and a demo program has been developed for validation. It possesses high performance, low cost and pertinence. Aiming at the information involved in process migration, obtain process data from JVM by calling Java JDI API, and transmit them to the node having idle computing resources. This technology is platform-independent, and the efficiency of distributed system would be enhanced with it. It also has the advantages such as strong commonality, protecting local environment from intrusion, and preventing from malicious code filching local information.

In this paper, a set of evaluation system is proposed by GQM (Goal-Question-Metrics) for enterprise information systems. Then based on Similarity to Ideal Solution (TOPSIS), the evaluation model is proposed to evaluate enterprise information systems’ adaptability. Finally, the application of the evaluation system and model is proved via a case study, which provides references for optimizing enterprise information systems’ adaptability.

Damage alarm is an important step among structure damage identification. Its objective is to evaluate the structure health. The existing damage alarm methods are mostly based on Back-Propagation Neural Networks without thinking over testing noise. Therefore, in order to avoid the disadvantages of conventional Back-Propagation Neural Networks, a modified Back-Propagation Neural Networks was proposed for structure damage alarm system in this paper. The experiment results of steel truss girder bridge show that the improved method is better than BPNN for structural damage alarm.

An efficient method for computing invariant sets of mode transitions systems is proposed. The method is based on the convex optimization technique, the linear matrix inequality techniques and an iterative method. Computation of ellipsoidal invariant sets and polyhedral invariant sets is given. An invariant set for mode transitions systems which includes a finite-duration transition is computed by an iterative procedure. Finally, an example is given to validate this method.

Aiming at the characteristics of the surface vibration signals measured from the diesel engine, a novel method combining local wave decomposition (LWD) and lifting wavelet denoising is proposed, and is used for feature extraction and condition evaluation of diesel engine vibration signals. Firstly, the original data is preprocessed using the lifting wavelet transformation to suppress abnormal interference of noise, and avoid the pseudo mode functions from LWD. Obtaining intrinsic mode functions(IMFs) by using LWD, the instantaneous frequency and amplitude can be calculated by Hilbert transform. Hilbert marginal spectrum can exactly provide the energy distribution of the signal with the change of instantaneous frequency. The vibration signals of diesel engine piston-liner wear are analyzed and the results show that the method is feasible and effective in feature extraction and condition evaluation of diesel engine faults.

In free field, the directivity of sound pressure is omni directional, and the directivity of vibration velocity is dipole directional, it can bring many advantages for acoustic measurements by combining utilization of both sound pressure and vibration velocity information. However, under the condition of boundary, the directivity of pressure and vibration velocity will be distorted by diffraction wave. In this paper, the soft boundary element model of finite cylinder baffle is established; the sound diffraction field of a plane wave from it at different frequencies and incident angles is calculated, the characteristics of directivity of pressure and vibration velocity at different frequencies and different distances are analyzed.

This paper discusses the method of intervenient optimum analysis based on non-optimum theory of system, and points out main problems of exploring uncertainty decision. Then analyses the key is short of the intervenient optimum to the problems of uncertainty decision. The article establishes drowsy set and intervenient optimum principle based on uncertainty problems analysis; and puts forward that decision system is degree measured along with non-optimum traced up to systematic optimum and so on.

In this paper, we consider question A in higher education community cup 2100 mathematical contest in modeling competition. We lucubrate the deflection identify of the oil storage tank and the demarcation matter of the oil storage tank’s volume, and builds models to solve the relationship between volume and depth storing up oil. We build the corresponding model with the method of linear regress, data close, interpolation, finally we obtain the required value with MATLAB software. We build an integral model with integral formula, and get the relationship between volume and depth storing up oil, basing on the integral formula with the method of closing polynomial functions to build a new function formula which makes it easier to be solved. By analysis the error and comparing the curve generated with the real data, the error is less.

The yaw dynamics of a miniature unmanned helicopter exhibits a complex, nonlinear, time-varying and coupling dynamic behavior. In this paper, simplified yaw dynamics model of MUH in hovering or low-velocity flight mode is established. The SISO model of yaw dynamics is obtained by mechanism modeling and system identification modeling method. PID control based on RBF neural network method combines the advantages of traditional PID controller and neural network controller. It has fast response, good robustness and self-adapting ability. It is suitable to control the yaw system of MUH. Simulation results show that the control system works well with quick response, good robustness and self adaptation.

An Identity-based signature scheme is proposed based on additive elliptic curve group. The verification result of the signature is a constant with respect to the signer’s identifier. Then an inter-domain authentication scheme is constructed by combining the proposed signature scheme. During the authentication, a user constructs the signature of timestamp as authentication proof, which realizes secure inter-domain authentication and user anonymity. It is showed that the proposed scheme has superiority in both security and efficiency, and is more suitable for pervasive computing.

An in-house explosion program is presented to evaluate blast wall protection under Methane-Air Explosion on an offshore platform, based on two-dimensional, time-dependent, reactive Navier–Stokes equations including the effects of viscosity, thermal conduction and molecular diffusion. The results show that this program can successfully produce explosion process of methane-air gas cloud. Because the overpressure behind the blast wall and on the lifeboat plate is more than 1.0atm when explosion wave passes, the current blast wall is not enough to keep the person and lifeboat safe. So the blast wall needs to be re-designed. The explosion wave of methane-air gas cloud undergoes a successive process of detonation formation, detonation transmission, shock attenuation, regular reflection and Mach reflection etc. Additionally, due to high overpressure generated in gas cloud explosion, it is extremely devastating and must be avoided at all times on offshore platform.

With the development of Internet of Things industry, more and more scholars start to study in the field of the Internet of things. The monitoring of the transmission state of information is one of the important fields of research in Internet of Things. This paper uses the discrete-time non-persistent CSMA with monitoring function random access mode to realize the monitoring features of the transmission state of information in the Internet of Things. And we get to the throughput of the system using the average cycle analysis method, through computer simulations to verify the correctness of the analysis.

Compared to the traditional way of doing advertising, such as ad Banners, internet product placement is now emerging as a promising strategy for advertisers to do their job effectively in this Web 2.0 era. Therefore, this study focuses on the effectiveness of product placement advertising on the Internet. The results show that product prominence (Subtle or Prominent) and presentation of the advertising (Video or Images) significantly impacts the effectiveness of product placement advertising on the Internet, including brand impression, advertising attitude, and intention to click. Product prominence and presentation of the advertisement have an interactive impact. Our findings indicated that presenting the product through videos will enhance higher levels of advertising attitude, brand impression, and intention to click than presenting it through still images. Subtle placements will increase the level of advertising attitude and intention to click more so than prominent placements. But prominent placements increase the brand impression more than the subtle placements.

The Arithmetic and Logic Unit (ALU) design is one of the important topics in Computer Architecture and Organization course in Computer and Electrical Engineering departments. There are ALU designs that have non-modular nature to be used as an educational tool. As the programmable logic technology has developed rapidly, it is feasible that ALU design based on Field Programmable Gate Array (FPGA) is implemented in this course. In this paper, we have adopted the modular approach to ALU design based on FPGA. All the modules in the ALU design are realized using schematic structure on Altera’s Cyclone II Development board. Under this model, the ALU content is divided into four distinct modules. These are arithmetic unit except for multiplication and division operations, logic unit, multiplication unit and division unit. User can easily design any size of ALU unit since this approach has the modular nature. Then, this approach was applied to microcomputer architecture design named BZK.SAU.FPGA10.0 instead of the current ALU unit.

The cost of manually annotating corpora is one of the significant issues in many text based tasks such as text mining, semantic annotation and generally information extraction. Active Learning is an approach that deals with reduction of labeling costs. In this paper we proposed an effective active learning approach based on minimal variance that reduces manual annotation cost by using a small number of manually labeled examples. In our approach we use a confidence measure based on the model’s variance that reaches a considerable accuracy for annotating entities. Conditional Random Field (CRF) is chosen as the underlying learning model due to its promising performance in many sequence labeling tasks. The experiments show that the proposed method needs considerably fewer manual labeled samples to produce a desirable result.

The hereditary algorithm is a kind of random searching and method of optimizing based on living beings natural selection and hereditary mechanism. In recent years, because of the potentiality in solving complicate problems and the successful application in the fields of industrial project, hereditary algorithm has been widely concerned by the domestic and international scholar. Routing Selection communication has been defined a standard communication model of IP version 6.This paper proposes a service model of Routing Selection communication, and designs and implements a new Routing Selection algorithm based on genetic algorithm.The experimental simulation results show that this algorithm can get more resolution at less time and more balanced network load, which enhances search ratio and the availability of network resource, and improves the quality of service.

In this paper, using the results of classifier composition is one of the methods of increasing efficiency of face recognition systems that many researchers paid attention to it in recent years. However AdaBoost algorithm is as one of the efficient boosting algorithm that has been used as to decrease the dimensions of characteristic space extracted from face recognition systems, it hasn’t been used as classifier in face recognition systems. In this paper paid attention to how to use this algorithm in classifying face recognition systems. At first the methods evaluated of classifier composition. Then, the result is presented of several composition methods in comparison with singular classifying methods; therefore, database has correct recognition of 96.4% and improved the results of KNN method with PCA specification. AdaBoost method is used according to weak learning, as proposed classifier system with the aim of identification validate.

In this paper a 4 codebook, Vector Quantization (VQ) core is implemented on FPGA (Field Programmable Gate Array). The proposed design has certain advantages over the earlier architecture in the form of design reuse of VQ core to build a large VQ system. The proposed core aims at increased compressing speed, modular design for design flexibility, easy reconfigurability. Modularity helps in flexile design changes for VQ with different codebook sizes and hence controls the recovered image quality. In general, the new VQ core, meets the specific and challenging needs of a single functioned, tightly constrained real time VQ encoder. The synthesis results show that a speed up of 5 is achieved. Experiments and analyses indicate that our design can satisfy the performance requirements of 30 image frames per sec for a real time image processing. The proposed VQ requires more memory and implements VQ encoder with codebook size which are in multiples of 4.

Current researches of query-focused update summarization often overlook influence of the query upon historical information. In this paper, we proposed a new information detection method which treats query-relevant and query-irrelevant old information in different way. Old information in the document set is removed in the process of sentence scoring stage instead of in additional stage after the sentences scored. Experiment results on TAC 2009 shows effectiveness of our method.

The Green Function method is one of the basic methods of studying the theory of electromagnetic field. This paper, starting from the Green formula, through the establishment of the integral expression about harmonic function on the plane, draws forth Green Function on the plane, finds the Green Function formula of the circular area (mathematical model) through the “image method”, and finds potential function of any given point of the circle area, then programs the Green Function using Matlab, and finally achieves visualization of f Green unction of the electric charge of the electric field inside and outside the circular area.

The aim of this paper is to minimise the makespan. The flexible job-shop scheduling is very common in practice and parallel machine is used in job-shop environment as flexibility. These flexibilities could be used for increasing the throughput rate, avoiding the production stop, removing bottleneck problems and finally achieving competitive advantages in economical environments. In opposition to classic job-shop where there is one machine in each stage, in this problem production system consists of multistage which in each stage there are one or several parallel machines with different speeds. The flexible job-shop scheduling with parallel machines problem consists of two sub-problems for solving: assigning and sequencing sub-problem.

This paper proposed a new core image coding algorithm based on Wavelet Packet Embedded Block Coding with Optimized Truncation (WP-EBCOT), for the characteristics of rich textures and complex edges in the core images. The entropy-based algorithm for best basis selection is used to decompose the core image, and then the wavelet packet subband structure is tested by EBCOT with various different code blocks size, as a result we find that the optimal size of the code blocks is 64*64. Results show that the proposed algorithm outperforms the base-line JPEG2000 for PSNR, and provides better visual quality for core images.

A novel method of facial expression recognition (FER) is presented, which uses stochastic proximity embedding (SPE) for data dimension reduction, and support vector machine (SVM) for expression classification. The proposed algorithm is applied to Japanese Female Facial Expression (JAFFE) database for FER, better performance is obtained compared with some traditional algorithms, such as PCA and LDA etc.. The result have further proved the effectiveness of the proposed algorithm.

In order to develop and evaluate future Unmanned Air Vehicles for the hazardous environmental monitoring, the comprehensive simulation test and analysis of new advanced concepts is imperative. This paper details an on-going proof of concept focused on development of a neurobiologically-inspired system for the high level control of a Air Vehicle team. This study, entitled Neurobiologically Enabled Autonomous Vehicle Operations, will evaluate initial System-Under-Test concept data by selecting well defined tasks, and evaluating performance based on assignment effectiveness, cooperation, and adaptability of the system. The system will be tested thoroughly in simulation, and if mature, will be implemented in hardware.

According to surveys, 80 % of security related events threatening information in medical organizations is due to improper management. Most research on information security has focused on information and security technology, such as network security and access control; rarely addressing issues at the management issues. The main purpose of this study is to construct a BS7799 based mechanism for the management of information with regard to security as it applies to medical organizations. This study analyzes and identifies the most common events related to information security in medical organizations and categorizes these events as high-risk, transferable-risk, and controlled-risk to facilitate the management of such risk.

Rate control is an important part of video coding. This paper presents an improved frame layer rate control algorithm by using the combined frame complexity and the adjusted quantization parameter (QP). The combined frame complexity can be used to more reasonable implement bit allocation for each frame, and the quantization parameter adjusted by the encoded frame information also can get more accurate rate control. Experimental results show that our proposed algorithm, in comparison to the original algorithm, reduces the act bit rate error of video sequences and gets a better average PSNR with smaller deviation.

Vertexes in the hexagonal mesh and torus network are placed at the vertices of a regular triangular tessellation, so that each node has up to six neighbors. The network is proposed as an alternative interconnection network to mesh connected computer and is used also to model cellular networks where vertexes are based stations. Hexagonal tori are known to belong to the class of Cayley graphs. In this paper, we use Cayley-formulations for the hexagonal torus to develop an elegant routing and broadcasting algorithm.

In component-based software engineering, components have become increasingly important. Software component is a unit of computing in software system. First, the definition of OR-transition Colored Petri Net is given. Second, in accordance with the related properties of software component, the formal definition of component is presented. In OR-transition Colored Petri Net, the transitions can effectively represent the operations of the software component. So, based on OR-transition Colored Petri Net, an approach is put forward to modeling the software component formally.

In the oriented-object software, coupling is the degree of inter dependence between objects. In order to measure the coupling of a software system formally, a novel approach is presented. Firstly, the coupling of Object-oriented software system is analyzed. Second, the definition of the structure entropy is given; Entropy is the most influential concept to arise from statistical mechanics. Entropy measures the disorder in a system. Finally, based on the structure entropy, an approach to measure the coupling of the oriented-object software system is presented.

A corridor of highway or railway generally may be considered as a continuous trajectory in 3D space, and may refer to procedures for locating corridors in three dimensions space. However, most of methods about it used 2D grid for the problem in literature. After summarizing a few of 2D grids for the corridor problem and analyzing existing 3D spatial models, this paper proposes a 3D grid structure with axes and layers so that the corridor finding can be realized in 3D environment. The 3D grid is a natural extension of 2D square grid.

By constructing the linear delay cost and exponential delay cost function, we formulate the consumer decision models with different delay cost based on the threshold strategies in dual-mechanism, and prove that there exists a unique symmetric Nash equilibrium in which the high-valuation consumers use a threshold policy to choose between the two selling channels. Then we extend our model under general delay cost function and find that consumers with higher valuation will choose threshold strategies to make decision once arriving at websites only if the delay cost function of them continuous strict increases with the auction remaining time.

The nonlinear inverted-pendulum system is an unstable and non-minimum phase system. It is often used to be the controlled target to test the qualities of the controllers like PID, optimal LQR, Neural network, adaptive, and fuzzy logic controller, etc. This paper will describe a new fuzzy controller for an inverted pendulum system. In this case, a fuzzy controller followed with a state space controller was implemented for control. It is achieved to design a control condition for the pendulum to swing up in one direction only because that the movement of throwing a bowling ball can only from one side to the unstable equilibrium point. Simulation and experimental results show that the fuzzy control can swing up the single inverted pendulum in short time with well stability and strong robustness.

With the development and application of Automatic Vehicle Identification (AVI) technologies, a novel high resolution OD estimation method was proposed based on AVI detector information. 4 detected categories (O

x

 + D

y

, O

x

/D

y

 + Path(s), O

x

/D

y

, Path(s)) were divided at the first step. Then the initial OD matrix was updated using the O

x

 + D

y

sample information considering the AVI detector errors. Referenced by particle filter, the link-path relationship data were revised using the last 3 categories information based on Bayesian inference and the possible trajectory and OD were determined using Monte Carlo random process at last. Finally, according to the current application of video detector in Shanghai, the North-South expressway was selected as the testbed which including 17 OD pairs and 9 AVI detectors. The results show that the calculated average relative error is 12.09% under the constraints that the simulation error is under 15% and the detector error is about 10%. It also shows that this method is highly efficient and can fully using the partial vehicle trajectory which can be satisfied with the dynamic traffic management application in reality.

It is obvious that the railway develops towards the trend of high speed and overload. So the rail quality required becomes more and more strict. The quenching is highlighted as the final method to improve rail behaviors. Stress field of U71Mn rail-ends during quenching was simulated by the FEM software. And various kinds of factors that may influence the stress field’s distribution were researched. The result shows that the rail-end stress can be significantly diminished, if the heating, holding time and air-blast pressure during the wind cooling can be accurately chosen. It is significantly valuable for the choice of relevant parameters for the heat treatment of U71Mn heavy rails.

This Paper proposes an Information-based Adaptive Target algorithm, considering the mobility of a mobile target. This algorithm is based on dynamic cluster and the target prediction mechanism. It consciously adjusts the information collection distance and time interval, depending on the target’s velocity, acceleration and angle variations. And it adaptively adjusts the time interval of real cluster prediction formation, depending on the velocity and angle variations of a mobile target. When the predicted time interval which is used to generate the next real cluster leads to the formation of the dynamic real cluster is not continuous, it introduces another level monitoring mechanism, namely virtual cluster monitoring, which ensures that the mobile target has been monitored in WSN all the time. It achieves different levels of monitoring and data collection using real clusters and virtual clusters, and effectively saves system resources. Simulation results show that this algorithm has better tracking precision, low energy consumption under different scenes.

The golden section effect physical pendulum is an experiment equipment which uses the optimization combined with physical pendulum and analysis data by computer management system. It adopt the golden section method to determine the period extreme value of pendulum, precisely record the experimental data, and truly portray the diagram curve, so as to allow students experience the application of optimization and computer in physical experiment.

In this paper, we introduce a W-band gyro-traveling wave (gyro-TWT) tube to suppress spurious oscillations, which is used in facilities for Aquaculture. The spurious oscillations block achieving high gain and high power in high-power broadband millimeter amplifier. In order to suppress spurious oscillations, we study the interaction circuit including input coupler and output section, design the gyro-traveling wave tube with distributed-loss based on MIG. The results of simulation show that high power and broad-band capabilities.

Internet worms are becoming more and more harmful with the rapid development of the Internet. Due to the extremely fast spread and great destructive power of network worms, strong dynamic quarantine strategies are necessary. Inspired by the real-world approach to the prevention and treatment of infectious diseases, this paper proposes a quarantine strategy based on dynamic worm propagation model: the SIQRV dual quarantine model. This strategy uses dynamic quarantine method to make the vulnerable host and infected host quarantined, and then release them after a certain period of time, regardless of whether quarantined host security is checked. Through mathematic modeling, it has been found that when the basic reproduction number R

0

is less than a critical value, the system will stabilize in the disease-free equilibrium, that is, in theory, the infected hosts will be completely immune. Finally, by comparing the simulation results and numerical analysis, the basic agreement between the two curves supports the validity of the mathematical model. Our future work will be focusing on taking both the delay and double-quarantine strategy into account and further expanding the scale of our simulation work.

Keyword extraction is widely applied in auto digest, information retrieval, text classification and text clustering. But the majority algorithms set keywords’ attribute weights manually and there are no objective calculation of the keyword attributes, so its subjectivity is too strong. This paper proposed an statistical method (PCA) on the basis of summarizing and improving the sentence keyword attributes to weigh the keyword attributes and sort of keyword scores so as to obtain the keyword weight sort sequence. Experiments show that, the algorithm in this paper can extract the keywords precisely.

An approach for the retrieval of price information from internet sites is applied to real-world application problems in this paper. The Web Information Retrieval System (WIRS) utilizes Hidden Markov Model (HMM) for its powerful capability to process temporal information. HMM is an extremely flexible tool and has been successfully applied to a wide variety of stochastic modeling tasks. In order to compare the prices and features of products from various web sites, the WIRS extracts prices and descriptions of various products within web pages. The WIRS is evaluated with real-world problems and compared with a conventional method and the result is reported in this paper.

An algorithm for intrusion detection based on improved evolutionary semi- supervised fuzzy clustering is proposed which is suited for situation that gaining labeled data is more difficulty than unlabeled data in intrusion detection systems. The algorithm requires a small number of labeled data only and a large number of unlabeled data and class labels information provided by labeled data is used to guide the evolution process of each fuzzy partition on unlabeled data, which plays the role of chromosome. This algorithm can deal with fuzzy label, uneasily plunges locally optima and is suited to implement on parallel architecture. Experiments show that the algorithm can improve classification accuracy and has high detection efficiency.

This paper depicts a longitudinal investigation of knowledge management system development from industrial perspectives. Snapshots on three surveys (2002, 2006, and 2010) of Taiwanese companies were conducted and compared, which is to explore the perceived understandings and requirements for the applications of a knowledge management system.From the surveys, it was found that the most useful applications were document management, knowledge search and retrieval, and knowledge repository and map. The emerging applications were expert management, document security, and knowledge automation such as auto-classification, auto-abstract and auto-keyword generation. The most wanted services along with KMS were consulting service, success story-sharing, and modularization while deploying knowledge management system in the enterprises. The trends and transformation of a KM system were also collected and analyzed. We suggest that a company should use different knowledge management approach according to its corporate main business function. Combing intellectual capital theories proposed by other researchers, we categorize knowledge management focus as staff-centric, system-centric, and customer-centric knowledge from industrial perspectives.

Sheet positioning time is one of the main influence factors to improve the printing velocity of offset printing press. In the process positioning system, stepping motor, transducer and roller wheels replace the traditional mechanical front and side guide system. Front and side guiding is finished while the paper is moving in the feeding table. The paper position signal detected by transducer is transferred to the stepping motors which control the wheels above the paper. Then the paper moves in the longitudinal and side direction. So the front and side position of the printing paper is definite.

The monocular vision is the key technology for the locomotive anti-collision warning system. The range precision influence the system’s performance. In this paper according to the question of video jitter result in the accuracy reducing, proposes a new EIS algorithm based on the orbital characteristic, through extracting and matching partial feature template obtained the global movement vector. Treat the partial feature template instead of treating the global image, speed of the system is improved obviously. The result of simulation indicates that this algorithm can effectively eliminate image migration which produces because of the video jitter, has solved the deviation of ranging precision, and satisfies the real-time request of system.

Control area network (CAN) is an international protocol of field bus and universal serial bus (USB) is developing more and more widely. On the other hand, the USB technology combined with the CAN application is still in the development stage, so this research has broad prospects. The USB-based CAN bus system hardware consists of a CAN module, a USB communication module and a micro controller. It has been designed for real-time display and can save the CAN bus message. In addition it has been debugged in actual measurement accompanied by the Kvaser USB CAN II. The test results show that the system can correctly receive all messages frame from Kvaser CanKing. Finally the system has been applied to the project of citrus orchard for transmission of data of the citrus and tree parameters.

Both controller area network (CAN) and wireless local area network (WLAN) bus technologies are developing rapidly nowadays. But the study on WLAN technology with CAN bus data is relative to be less researched. So a WLAN CAN bus data test system was present in this paper. The system hardware consists of two control modules, each of which consistently allows link test to the CAN bus network. Each hardware of the module is composed by a microcontroller STC12C5410AD, a CAN bus control unit MCP2515, a CAN bus transceiver MCP2551 and a RF wireless module RF903. During the test process, the CAN bus analyzer, Kvaser USBCAN II, receives and dispatches the CAN messages. Test results showed that the system’s error score was approximately zero when messages are transmitted and the system can message transmission from one side of CAN panel point to the other side. The communication of the system is suitable for the CAN treaty standard and it can allow wireless message transmission to other suitable networks meeting the CAN treaty standard as well. Finally the system has been applied to the project for hill citrus leaf area index (LAI) acquisition.

Video surveillance is playing more and more important role in people’s social life. Real-time alerting of threaten events and searching interesting content in stored large scale video footage needs human operator to pay full attention on monitor for long time. The labor intensive mode has limit the effectiveness and efficiency of the system. A framework of simple event detection is presented advance the automation of video surveillance. An improved inner key point matching approach is used to compensate motion of background in real-time; frame difference are used to detect foreground; HOG based classifiers are used to classify foreground object into people and car; mean-shift is used to tracking the recognized objects. Events are detected based on predefined rules. The maturity of the algorithms guarantee the robustness of the framework, and the improved approach and the easily checked rules enable the framework to work in real-time. Future works to be done are also discussed.

According to “Software processes are software too” proposed by L.Osterweil, we assume a software process model with independent functions as a component. To fully describe the evolution behavior of process-based components, the concept of evolution behavior interface is introduced and a Petri net based ESDDM model is discussed. By applying on a realistic case, we conclude that ESDDM, a software evolution process model based on evolution behavior interface, is able to effectively support the concurrent engineering.

In recent years, the new technologies related with tissue engineering improving continuously bring the hope for the complete regeneration of the morphology and physiological function of the degenerated intervertebral disc. According to the biomechanics of intervertebral disc, from the mechanical characteristic of human activities, we have developed a dual-frequency compression-torsion loading device for intervertebral disc tissue engineering. The device consists of three systems. The dual-frequency compression part contains two systems which produces low-frequency high-amplitude compression (frequency 0-3Hz, amplitude 0-3mm) and high-frequency low-amplitude (frequency 10-90Hz, amplitude 0-40

μ

m). Rotary system provides torsion loading to the culture by back and forth rotation controlled by step moter. The maximum rotation angle is set smaller than 30°. The design goal of the loading device is to achieve the mechanical condition of dual-frequency compression- torsion loading as close as possible to that of in vivo condition of the native disc tissue. And also is used to study the mechanobiology of intervertebral disc.

With the application and development of radio technology in all fields, the problem of spectrum scarcity is getting more and more attention. The cognitive radio is introduced to perform opportunistic usage of spectrum of primary user by a secondary user. Therefore a secondary user should be capable of spectrum sensing. In this paper, we analyze the problem of designing the optimal spectrum sensing frame time, under considering dynamics of the state of the operating chnnel and restriction on collision probability, in order to maximize the expected reward in throughput of a multiple-channel cognitive radio network in which there is at least a idle channel at one time, meanwhile, the energy cost of spectrum sensing and data transmission and channel switching is taken into account. We study the problem using the framework of partially observable Markov decision processes (POMDP).

The mass transfer is one of important aspects to maintain the physiological activity proper of tissue, specially, cartilage cannot run without mechanical environment. The mechanical condition drives nutrition in and waste out in the cartilage tissue, the change of this process plays a key role for biological activity. Researchers used to adopt compression to study the mass transfer in cartilage, here we firstly establish a new rolling depression load (RDL) device, and also put this device into practice. The device divided into rolling control system and the compression adjusting mechanism. The rolling control system makes sure the pure rolling and uniform speed of roller applying towards cultured tissue. The compression adjusting mechanism can realize different compressive magnitudes and uniform compression. Preliminary test showed that rolling depression load indeed enhances the process of mass transfer articular cartilage.

Target tracking in wireless sensor networks with limited recourses is a challenging problem. Thus, sensor scheduling algorithms designed for sensor network must focus on power conservation in this paper; we proposed a cluster honeycomb structure-based sensor scheduling algorithms for target tracking in Wireless Sensor Networks, which sensing area is divided into clusters based on transmitting range of nodes .The nodes’ state will change during with the target moving in order to keep energy. The cluster head is selected by remaining energy of the node and the position function is also given.

The use of multiple antennas at both transmitter and receiver can increase wireless communication system capacity enormously. The optimal detection algorithm for MIMO system is Maximum likelihood detection (MLD) algorithm, which provides the best bit error rate (BER) performance for MIMO system. However, the computational complexity of MLD algorithm grows exponentially with the number of transmit antennas and the order of modulation. An improved MIMO detection algorithm which combined M-algorithm with stack algorithm was presented in this paper. The proposed algorithm was a multistage detection which was consisted with three parts: MLD, M-algorithm and stack algorithm. In MIMO communication system with

m

transmit antennas, after performing QR decomposition of the channel matrix, the MLD with length

L

was done firstly. The partial accumulated metrics were calculated and sorted, which produced an ordered set. Then selecting the first

M

partial symbol vectors to form a new ordered set. Based on the new ordered set, stack algorithm was performed to search for the symbols with the minimum accumulated metrics. The proposed algorithm combining M algorithm and stack algorithm reduced numbers of ordering with the original stack algorithm, the probability of look back and improving the detection performance.

The cooperative hunting research of mobile wireless sensor network based on improved dynamic alliance is proposed in this paper. Considering the communication cost, link covering, energy and so on, the improved dynamic alliance mechanism is introduced into the cooperation of multi-mobile sensor nodes to solve the cooperative hunting of single target. Simulation result shows that the cooperative hunting based on dynamic alliance for mobile wireless sensor networks is feasibility.

One of the important reasons for poor recognition rate in optical character recognition (OCR) system is the error in character segmentation. In case of Bangla scripts, the errors occur due to several reasons, which include incorrect detection of matra (headline), over-segmentation and under-segmentation. We have proposed a robust method for detecting the headline region. Existence of overlapping characters (in under-segmented parts) in scanned printed documents is a major problem in designing an effective character segmentation procedure for OCR systems. In this paper, a predictive algorithm is developed for effectively identifying overlapping characters and then selecting the cut-borders for segmentation. Our method can be successfully used in achieving high recognition result.

This paper introduces a minimum input and largest output ideal decision-making unit on the basis of using the traditional method of data envelopment analysis from the point of efficiency view. The DEA evaluation model is modified, and the decision-making units are full evaluation and ranking. The modified DEA model analyses the Competitiveness evaluation of representative listed companies in China new energy industry representative. Through the analysis and solution for the data on 11 new energy listed company, the results indicate the effectiveness of this method, reflect the competitiveness of new energy listed companies, and provide relevant decision-making information for new energy industry operation.

Inspired by locomotion principle of earworms, a shape memory alloy (SMA) actuated earthworm-like robot is designed and developed in this paper. Four groups of SMA wires as actuator and one spring as accumulator were introduced. The SMA wires and spring play a role in contraction and extension of an earthworm muscle respectively. For temporal position stopping control, two groups of electromagnets were used as setae of earthworm. By SMA wires were driven independently or simultaneity according to defined movement patterns, the all-round movement of the artificial earthworm freely to different directions was realized. A series of experiments on the self-developed robot moving and turning with different actuation frequencies were carried out. The results showed the validity of the locomotion mobility of the SMA actuated earworm-like robot.

Now, as a popular language for the development of sever and desktop applications, Java is also playing a more and more important role in embedded development owning to its features like platform independence, high development efficiency, etc. Accordingly, JPOR-32, a 32-bit Java processor optimized for real-time specification for Java, is designed. In this paper, taking JPOR-32 as an example, the instruction execution stage design for embedded real-time Java processor is presented. The run time operand stack and method stack is implemented, which lays the foundations of execution of instruction set based on stack. For instruction execution stage, this paper presents on emphasis the control signal operation mechanism and the instruction execution stage data path.

System design becomes really important for software production due to continuous increase in size and complexity of software systems. It is a complex design activity to build architecture for the systems like large enterprises. Thus it is a critical issue to select the correct architecture in software engineering domain. Moreover, in enterprise architecture selection different goals and objectives must be taken into consideration as it is a multi-criteria decision making problem. Generally this field of enterprise architecture analysis has progressed from the application of linear weighting, through integer programming and linear programming to multi-criteria decision making (MCDM) models. In this paper we survey two multi-criteria decision making models (AHP, ANP) to determine that to what extent they have been used in making powerful decisions in complex enterprise architecture analysis. We have found that by using ANP model, decision makers of an enterprise can make more precise and suitable decisions in selection of enterprise architecture styles.

This system is targeted by enterprises manufacturing machine shop, analyzes their business needs and builds the plant management information system of Manufacture time and Manufacture time information management. for manufacturing process Combined with WEB technology, based on EXCEL VBA development of methods, constructs a hybrid model based on PLM workshop Manufacture time management information system framework, discusses the functionality of the system architecture, database structure.

During several minutes acquisition of dynamic contrast enhancement breast magnetic resonance images(DCE breast MRI), patient movement and respiration activity can lead to misunderstanding enhancing regions, causing longer reading times and less clear diagnoses. It is necessary for MRI to be spatially registered before diagnoses. The paper presents a non-rigid registration method for DCE breast MRI which employs improved demon algorithm. Polynomial and least square method is used to correct intensity change between pre and post contrast images before registration of demon method. The experiment results show that the presented approach works better than original demon algorithm and free form deformation (FFD) algorithm.

The purpose of this paper is to prove the iterative processes generated by a nonexpansive semigroup and a generalized contraction mapping converge strongly to common fixed point

p

of the nonexpansive semigroup, and

p

is the unique solution to some variational inequality. The result extends some theorems in the literature.

Water supply system optimization makes use of the latest advances in hybrid genetic algorithm to automatically determine the least-cost pump operation for each pump station in large-scale water distribution system while satisfying simplified hydraulic performance requirements. Calibration results of the original model were pretty good. The comparison results show that the difference between the simplified and the original mode simulation of nodal pressure and pipe flow was less than 5%. The precision of the simplified model could satisfy the requirement for pump operation optimization. When the simplified model was used instead of the microscopic model, the calculation time of optimal control model was greatly saved, but the precision was basically the same. The results of optimal control model for the water distribution system in City S showed that the simplified model for optimal control had remarkable advantage cause the calculation time of optimal control model was greatly saved, but the precision was basically same.

Recently, WS-BPEL has gradually become the basis of a standard for web service description and composition. However, WS-BPEL cannot efficiently describe distributed workflow services for lacking of special expressive power and formal semantics. This paper presents a novel method for modeling distributed workflow service composition with Concurrent TRansaction logic (CTR). The syntactic structure of WS-BPEL and CTR are analyzed, and new rules of mapping WS-BPEL into CTR are given. A case study is put forward to show that the proposed method is appropriate for modeling workflow business services under distributed environments.

By using dynamic programming (DP) which is a kind of global optimization algorithm, an energy management control strategy for a parallel PHEV on different charging depleting range (CDR) had been studied. The results show that motor-dominant control strategy should be applied to the PHEV when CDR is less than 55km, and engine-dominant control strategy should be used when CDR is more than 55km. With optimal control strategies from DP, the best economic performance can be obtained as CDR is 55km; PHEV average equivalence fuel consumption can be reduced to 2.9L/100km which is 63% lower than that of prototype vehicle.

With the rapid development and wide application of electronics, communication and embedded system technologies, the global agriculture is changing from traditional agriculture that is to improve the production relying on the increase of labor, agricultural inputs to the new stage of modern agriculture with low yields, high efficiency, real-time and accuracy. On the other hand the research and development of the Internet of Things, which is an information network to connect objects, with the full capacity to perceive objects, and having the capabilities of reliable transmission and intelligence processing for information, allows us to obtain real-time information of anything. The application of the Internet of Things in field information online monitoring is an effective solution for present wired sensor monitoring system, which has much more disadvantages, such as high cost, the problems of laying lines and so on. In this paper, a novel field information monitoring system based on the Internet of Things is proposed. It can satisfy the requirements of multi-point measurement, mobility, convenience in the field information monitoring process. The whole structure of system is given and the key designs of system design are described in the hardware and software aspect. The studies have expanded current field information measurement methods and strengthen the application of the Internet of Things.

In this system, with technology of motion detection, the data frames include vehicle digital image can be detected automatically from a Video for Windows (AVI) File, at the same time, vehicle type will be recognized and displayed automatically. The system’s process consists of five steps: Read the AVI file and decompose it into digital image frames; Motion detection; Vehicle digital image processing; Counting number of black pixels included in vehicle body contour and project on car image; Module of vehicle type classification. In particular, algorithm of vehicle recognition through counting number of black pixels included in vehicle body contour is one innovation algorithm. Experiment on actual AVI files shows: the system design is simple and effective.

This paper investigated the validity of three-dimensional scans as a tool for visual fit analysis. We used traditional live models and three dimensional scans to compare the fit assess on women pant. Results from different areas of pant showed different levels of accuracy. In the waistband, upper hip and hip area, the results were more accurate while the crotch and side seam were not.

In Intelligent Vehicular Networks, featured as car-to-car and car-to-infrastructure wireless communication, most applications need important location information or credential information. We address a location-based encryption method that not only ensures messages confidentiality but also authenticates identity and location of communication peers. The authentication of location means that a message can only decrypted by the receiver which is “physically” present inside a decryption region specified by locations, and is moving at a specific speed, acceleration and at a specific time period. A secret key is generated by converting location, time and mobility information (such as speed and acceleration) into a unique number. The determination of the decryption region is addressed in two steps: predicting and updating. The proposed method evaluated by simulations is efficient and secure.

Intelligent Vehicular Networks, known as Vehicle-to-Vehicle and Vehicle-to-Roadside wireless communications (also called Vehicular Ad hoc Networks), are revolutionizing our daily driving with better safety and more infortainment. Most, if not all, applications will depend on accurate location information. Thus, it is of importance to provide intrusion-tolerant location information services. In this paper, we describe an adaptive algorithm that detects and filters the false location information injected by intruders. Given a noisy environment of mobile vehicles, the algorithm estimates the high resolution location of a vehicle by refining low resolution location input. We also investigate results of simulations and evaluate the quality of the intrusion-tolerant location service.

Simulators are important tools in evaluating research in vehicular networks. Typically, vehicle movements are determined by a vehicle mobility simulator, and the movement trace is then input into a network simulator to simulate communication between the vehicles. So, it is important to consider both mobility and network simulators. We present an overview of popular simulators used in vehicular networking research along with an experimental comparison of two popular vehicular mobility simulators. We show that the mobility model and topology used can greatly affect the network performance.