Earticle

Topology potential field is a novel model to describe interaction and association of network nodes, which has attracted plenty of attention in community detection, node importance evaluation and network hot topics detection. The local maximum potential point search is a critical step for this research. Hill-climbing is a traditional algorithm for local maximum point search, which may leave out some local maximum potential points, and search performance is greatly influenced by initial node sequence. Based on the detailed analysis of local maximum potential points' characteristics, this paper presents a novel local maximum potential point search algorithm. The results of simulation experiments showed that the new algorithm has better performance than the traditional hill-climbing method. It can find all local maximum potential points with high search efficiency.

The aim of this paper is to analyze the performance of adaptive synthesis filter banks for image compression at low bit rates. In adaptive synthesis filter banks, analysis section comprises of linear phase filters whereas, synthesis section manages a combination of linear phase and non linear filters (in form of delay filters). The adaptive synthesis filter banks have advantages over conventional adaptive filter banks because they have no synchronization issues between analysis and synthesis filters and are compatible with the existing subband coding systems. Their performance is evaluated against various compression ratios by using biorthogonal filters ‘4.4’ and ‘5.5’ which suggest adaptive synthesis filter banks achieve significant gain in PSNR at compression ratio 0.3 ~ 0.6 bit per pixel.

This paper presents the analysis and simulation of the control of double star induction motor, using direct torque control (DTC) based on model reference adaptive control algorithm (MRAC). The DTC is an excellent solution for general- purpose induction drives in very wide range the short sampling time required by the TC schemes makes them suited to a very fast torque and flux controlled drives as well the simplicity of the control algorithm. DTC is inherently a motion sensorless control method. The model reference regulator (MRAC) can improve the double star induction motor performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. Simulation results indicate that the proposed regulator has better performance responses. The implementation of the DTC applied to a double star induction motor based on model reference regulator is validated with simulated results.

This paper presents an improved clustering algorithm with Ant Colony optimization (ACO) based on dynamical pheromones. Pheromone is an important factor for the performance of ACO algorithms. Two strategies based on adaptive pheromones which improved performance are introduced in this paper. One is to adjust the rate of pheromone evaporation dynamically, named as P , and the other is to adjust the strength of pheromone dynamically, named as Q . Two evaluation indices, Precision and Recall, are chosen to validity the improvement strategies. Numerical simulations demonstrate that the two strategies on pheromone can achieve better performance than basic ant colony algorithm and clustering algorithm with ant colony based on best solution kept.

Energy coupling realized by contactless magnetic tank transformer as new approach of rotator excitation in synchronous machine could replace brushes and slip rings of traditional excitation. For new contactless energy transmission (CET) system, its research about energy-efficiency quality still remains a low level because application and research of CET isn’t comprehensive, especially how to improve transfer power and efficiency isn’t enough. According to characteristics of contactless energy transmission system, mutual inductance model was used to describe the loosely coupled connection between primary and secondary winding. Then, optimum energy-efficiency product was proposed. We can use this indicator to consider efficiency, system cost, reliability and so on based on maximum output power. Mutual inductance coupling parameter would be optimized through this indicator and optimum design of system energy-efficiency characteristic would be realized at minimum cost. Although the input voltage had little increase, experiment and simulation research proved that system efficiency had a quit handsome increase based on optimum energy-efficiency product which established mutual inductance coupling parameter. The results of experiment agreed with the results of theory analysis in general and it verified the validity of theory analysis.

In the high-resolution radar imaging system, step-frequency radar signal is very important in getting the high-resolution range-profile, which can be used for target’s detection and recognition. However, target radial velocity will produce many problems, therefore, moving-targets imaging is a bottleneck for step-frequency radar signal. In this paper, an effective motion compensation methods is presented, which is based on the function of Range-profile Contrast. The numeric simulation indicates that this method is effective, which can estimate the target’s velocity in real-time, and it is easy to be used in engineering project. After target’s motion compensation, the high-resolution range-profile will be much better than that is used to be, which can be used for the detection, recognition and ranging of moving targets..

Capture, specification, and communication of requirements is now a critical issue in the product development process. Systems Modeling Language (SysML) was developed to address systems engineering needs. In this approach, use cases are developed along with lists of actions necessary to put them into practice. This paper focuses on the early phases of applying textual and diagrammatic narratives in requirements specification and examines a SysML-based representation of a development process as an example. The paper shows that the series of SysML representations lacks a nucleus around which the various phases of the development process can evolve. The paper produces a sample core by using a Flowthing Model (FM) and contrasts it with the multifarious textual and graphical descriptions of SysML to demonstrate the viability of FM for modeling of requirements and design phases.

The LEACH is a popular protocol used in wireless sensor network analysis and simulation. This paper analyses the advantages and disadvantages of LEACH protocol and then puts forward a clustering routing protocol for energy balance of wireless sensor network based on simulated annealing and genetic algorithm. When the sensor nodes are deployed randomly in the area, Firstly, we cluster the sensor nodes by simulated annealing and genetic algorithm and then calculate the cluster center of each cluster. If the energy of the node in the cluster is higher than the average energy of the cluster, it will become the candidate cluster head; at last the candidate cluster head becomes the cluster head according to the distance from the cluster center of the cluster. Simulations show that the new program could improve Energy Hotspot caused by the uneven distribution of cluster head in LEACH protocol, thus it can balance the wireless sensor network load balance and extend the lifecycle of wireless sensor network.

Moving object tracking technique is to find the exact location of the target in the next frame, and feedback to a tracking system for tracking and to provide an important basis and foundation for the analysis and understanding of the video sequence. Face recognition refers to the method to extract somehow be able to describe the characteristics of each individual's personality. Using 2DPCA image feature extraction, feature dimension reduction is simpler and direct, so the calculation efficiency is relatively high, and it can greatly shorten the training time of the sample collection of images. This method is the first application the 2DPCA optimal representation of characteristics for the original sample matrix, and then apply FLDA optimal discriminate feature for the original sample. The paper proposes the method of moving target tracking based on 2DPCA and FLDA face recognition algorithm.

A testing system has been designed to detect the single event upset failure of SRAM chips in this paper: a visual test bench for failure monitoring is developed based on LabVIEW, it could perform the task of data acquisition, storage and results analysis. At the testing board, the test vectors based on March C- algorithm are written to the reference SRAM and the under-test SRAM through FPGA. NI HSDIO-6548 card is used to collect all the data from the SRAMs, judging whether SEU failure occurred according to comparison results. The system could accomplish the work of real-time monitoring the failure status and test process with a good extensibility.

The Research article includes Model Torque Responses for flexibility of single link manipulators using Linearization Technique named as a LCQ. Manipulators are nothing but one type robotic arms commonly used in the industry .Here the controller design technique used for controlling manipulator was Linear Quadratic Controller Design. Generally the robotic arms are non-linear in nature. In order to control the non-linearity of manipulator and angular displacement, state space technique is used. The topology explains dynamic characteristics occurring in abnormal working condition torque responses are modified by using Linear Quadratic Controller Design Technique. The design method approach in state space control strategy. The dynamic torque responses of single link manipulator in abnormal condition and also using LCQ Technique are shown by M-File Controlling block of Simulink Library in Mat Lab Control tool box.

Considering the management problem for Internet of Things, existing IP-based network management protocols such as Simple Network Management Protocol (SNMP) and the Network Configuration (NETCONF) protocol may possibly be utilized to manage smart objects (the main components in Internet of Things). Based on the thinking of extension indicated by some network management standardizations, this paper tries to introduce Extenics into the study on management of smart objects. This paper proposes a simplified formalization for management of smart objects based on the extension model, and formalizes information, knowledge and policy related to Manager, Agent and Management Information Base (MIB) for management of smart objects by making use of basic-elements, composite-elements, extension transformations, dependent functions and extension sets. The case study of this paper shows that, the proposed formalized framework of Manager, Agent and MIB in the form of information-knowledge-policy for management of smart objects based on the extension model is feasible.

Solar panel is an important structure of the spacecraft, SADA (Solar Array Drive Assembly is often used as the drive organ to realize the step-skipped gesture adjustment. Firstly, the disturbance mechanism impact, which was produced from working SADA, to the electro-mechanism and payload coupling has been taken into account, and the dead, rigid and flexible load SADA disturbance model was established and validated through simulation and experimental measuring. Secondly, implemented the experimental check, calibration and correction to the mathematical model. Finally, the definition of electrical rigidity was proposed to analyze the disturbance mechanism of SADA, and verified its existence through simulation and testing.

Mobile readers are used more and more remarkably, so a persistent connection between a backend server and mobile readers cannot be guaranteed, it brings higher security requirements for RFID systems. RFID search protocol which is used to find specific tags has many applications such as inventory management, supply chain management. In this paper, a hash-based RFID search protocol for mobile readers is proposed, it can meet all known major attacks in RFID systems, and it can protect the privacy of mobile reader holders especially.

New performance leaps has been achieved with multiprogramming and multi-core systems. Present parallel programming techniques and environment needs significant changes in programs to accomplish parallelism and also constitute complex, confusing and error-prone constructs and rules. Intel Cilk Plus is a C based computing system that presents a straight forward and well-structured model for the development, verification and analysis of multi-core and parallel programming. In this article, two programs are developed using Intel Cilk Plus. Two sequential sorting programs in C/C++ language are converted to multi-core programs in Intel Cilk Plus framework to achieve parallelism and better performance. Converted program in Cilk Plus is then checked for various conditions using tools of Cilk and after that, comparison of performance and speedup achieved over the single-core sequential program is discussed and reported.

The main objective of this study is to investigate the impact of corporate research and development (R&D) activities on firm performance. To this end, the stochastic frontier technique is used on a unique balanced longitudinal dataset comparing top global software enterprises over the period 2005-2010. The software companies is divided into system software companies, application software companies and service software companies according to the types of product or service of software companies. In this framework, this study analyzes the effect of R&D, capital and employment on sales, and quantifies technical inefficiency of individual firms. The results of this study suggest that there are two ways in which R&D can influence the system software enterprise, one is to promote the frontier production function boundary forward, namely, to complete technological progress to improve the productivity of enterprise; another one is to improve the technical efficiency of enterprise and reduce waste. With respect to the application software enterprises, R&D can only improve productivity through technological progress; the effect of R&D on software service companies is not significant.

Considering the further opening of China’s economy and the growth of the people’s income, there is a lot of room of growth of demand for imports. This paper is an attempt to identify the demand of different types of imported products in China, which could be the guideline for the international trade for these trading corporations to maximize their profits. GRA and Fuzzy TOPSIS are employed to evaluate the demand of different types of imported products. The managerial implications are also discussed in this paper.

Random constraint satisfaction problem models play a significant role in computer science. They provide instances for benchmarking algorithms, help inform the design of algorithms and heuristics, and provide insight into problem hardness. In this paper, model RA which was revised from classical model A, was studied. When parameter k satisfied k ≥ 3, model RA has the same satisfiability transition with model RB, which was revised from classical model B and has already got considerable theoretical and practical studies. We also compared the performances of fundamental algorithms on model RA with on model RB.

This paper presents a new complexity metric for Object-Oriented (OO) design measurement to find at the design stage whether the classes become more complex, Moderate complex or less complex. The proposed metric is theoretically evaluated against the Weyuker’s properties as well as empirically evaluated against three open source software system. Furthermore, for validating the validity of new complexity metric, the paper has also presented the comparison of proposed metric with some well known complexity metrics like Weighted Method per Class (WMC) metric of Chidamber and Kemerer (CK), Class Complexity (CC) metric of Balasubramanian, and Complexity Metric for OO Design (CMOOD) metric of Rajnish and Bhattacherjee (RB) against the same three open source software system..Automated tool were used to generate the metric values and for analyzing the results, IBM SPSS software used. The results in this paper indicates that the new complexity metric is correlated well with existing complexity metrics and may be used as predictors of complexity of class.

This paper presents a kinds of information fusion algorithm based on multi-channel color image. The color face image is first separated into three pseudo grayscale images: R, G, and B, then the partial characteristics of face is extracted by use of Gabor wavelet transform from each component to be eigenvector in series connection, which will be through dimensionality reduction by sparse kernel principal components to be recognized and classified by the nearest classifier. In order to testify the validity, we make experiment by use of XM2VTS color face dataset and the experimental result supports the proposed method.

A clustering algorithm is proposed in this paper, which is based on discussion of multi-agent meta-heuristic architecture of the ant colony optimization algorithm. The multi-agent architecture of ant colony optimization meta-heuristic includes three levels. Level-0 agents build solutions, level-l agents improve solutions and level-2 agents update pheromone matrix. The updated pheromone then provides feedback information for the next iteration of solution construction. Mutation probability p and pheromone resistance ρ are the adaptive parameters, which can be adjusted automatically during the evolution progress. With the adaptive variable, the algorithm can solve the contradiction between convergence speed and precocity and stagnation. The algorithm has been tested and compared with the clustering algorithm based on Genetic and Simulate annealing. Experimental results show that the proposed algorithm is more effective, and the clustering quality and efficiency are promising.

Container transportation has gradually become the main direction of the development of shipping today. With the ship's large-scale, specialization and modernization the development of handling capacity of modern container terminal plays a key role in low-cost transportation, and efficient circulation. Automated container terminal can not only improve the utilization rate of equipment, reduce operating costs, but also greatly improves the efficiency of terminal. This paper analyzes the efficient and economical automation container terminal based on the frame-bridge handling technology of transport vehicles independently developed by the ZPMC And on this basis put forward the improvement of handling technology, and compare models created to validate the superiority of its improvement plan.

In Robot Colony System(RCS), based on the swarming nature of Ants, the path for the agent robots is designed to perform to search operation to find the shortest path from source to destination for collection of objects and go back to their hive-like home node. The agent always move through the shortest path to reach to the destination. There is a possibility of having a number of path in between the source and destination as defined in the Path Map(PM) in offline mode. If the prefferd shortest path is blocked by means of some obstraction, there must be another way to reach to the destination which have the weight of minimum among the other possible paths. The algorithm shown in this paper for shortest path, based on Kruskal’s Algorithm, shows the way to find the alternative shortest path and the moving direction of the agent. In this paper, the junction-to-junction connectivity is proposed where the path search is replaced by the node search which minimises the computaional time and hence increases the effectiveness and efficiency in agent moving towards the destination from source and also in its reverse direction.

In order to further enhance the performance of syntax parsing, for the shortcomings of hidden Markov model (HMM) in the parameter optimization, an improved syntax parsing method based on adaptive genetic annealing and HMM was presented. First, an adaptive hybrid genetic annealing algorithm was adopted to optimize HMM initial parameters. Second, the improved HMM was trained by Baum Welch algorithm, and then a modified Viterbi algorithm was used to recognize various types of phrases at the same layer, finally a hierarchical analysis algorithm and Viterbi algorithm were combined together to solve hierarchy and recursion in the sentence. In the adaptive genetic annealing HMM algorithm, genetic operators and parameters of simulated annealing (SA) were first respectively improved, subpopulations were classified according to the adaptive crossover and mutation probability of GA in order to realize the multi-group parallel search and information exchange, which could avoid premature and accelerate convergence, then SA was taken as a GA operator to strengthen the local search capability. Compared with several new approaches, Fβ = 1 value is averagely increased by 3%. The experiment results prove that this method is very effective for syntactic parsing.

Error factors of RV reducer are not completely considered, leads to backlash precision is limited, so an improved backlash estimation model is proposed. RV reducer structure and working principle is deeply analyzed, a variety of error factors are considered, and the backlash estimation model is improved according to error propagation. Furthermore, sensitivity of all the error factors are analyzed, RV reducer backlash is obtained through Monte-Carlo simulation, and the simulation results are compared with the traditional computation results. It is conductive to taking fix action in the design stage, reducing backlash, improving the transmission accuracy.

The predominant language model for speech recognition is n-gram language model, which is locally learned and usually lacks global linguistic information such as long-distance syntactic constraints. We first explore two n-best re-scoring approaches for Mandarin speech recognition to overcome this problem. The first approach is linear re-scoring that can combine several language models from various perspectives. The weights of these models are optimized using minimum error rate learning method. Discriminative approach can also be used for re-scoring with rich syntactic features. To overcome the speech text insufficiency problem for discriminative model, we propose a domain adaptation method that trains the model using Chinese pinyin-to-character conversion dataset. Then we present a cascaded approach to combine the two re-scoring models in pipeline that takes the probability output of linear re-scoring model as the initial weight of the discriminative model. Experimental results show that both re-scoring approaches outperform the baseline system, and the cascaded approach achieves the best performance.

In this study, the removal of sunset yellow dye from aqueous solutions using low-cost materials as adsorbents such as modified Rice husk (MRH) and sugarcane bagasse (SB) by a batch system were investigated. Experiments were carried out as a function of contact time, initial concentration, pH and adsorbent dosages. The equilibrium adsorption of sunset yellow dye on adsorbents was analyzed by Langmuir, Freundlich and Temkin models. The results indicate that the Freundlich model provides the best correlation for sunset yellow-MRH system and the Langmuir model provide the best correlation for sunset yellow-SB system and also pseudo-second-order model was best applicable to the sorption data. The results revealed that the sunset yellow is considerably adsorbed on modified rice husk and sugarcane bagasse and it could be an economical method for the removal of sunset yellow from aqueous systems.

Cloud computing is becoming an interesting alternative as a flexible and affordable on-demand environment for deploying custom applications in the form of services. In this work, a self-organizing system model based on dynamic relation network is proposed. In the model, autonomic element can self-adapted to the weight of the relationship under the guidance of the self-organizing policy. Based on this organization model, we present the service-oriented dynamic self-organizing algorithm in Cloud computing, which implement autonomic element self-organization through service finding, service composition, task implementation and service optimization.

The purpose of the paper is to address the problem of estimation and prediction of the Burr type XI distribution under Bayesian framework based on censored samples. Five informative and non-informative priors have been assumed under five different (symmetric and asymmetric) loss functions for posterior analysis. The expressions for Bayes estimators, posterior risks, credible intervals, posterior predictive intervals have been derived and evaluated. The simulation study has been carried out in order to assess and compare the performance of Bayesian point and interval estimators. The study indicated that for Bayesian estimation and prediction of the said distribution, the gamma prior along with quadratic loss function can efficiently be employed.

This paper proposed a new weighted KNN data filling algorithm based on grey correlation analysis (GBWKNN) by researching the nearest neighbor of missing data filling method. It is aimed at that missing data is not sensitive to noise data and combined with grey system theory and the advantage of the K nearest neighbor algorithm. The experimental results on six UCI data sets showed that its filling accuracy is better than the traditional method of K nearest neighbor and filling algorithm presented by Huang and Lee.