Earticle

With the widely application of the distributed generation technology, micro grid islanding detection technology has been greatly developed. A new type of islanding detection technique is proposed in this paper. The new detection technology has realized the rapid, efficient, stable and reliable islanding detection, and achieved the zero non detection zone. At the same time, which put money into limit in minimum range. This paper presents the principle of islanding comprehensive detection technology. This paper designs and describes the method to realize the new islanding detection technology. The new technology makes up for a series of shortcomings,such as the non-detection zone (NDZ) is larger of the local testing technology. And it also overcomes a great many shortcomings of the remote detection technology, such as a big investment and too single.

The concern of this study is to identify software risks and controls in the software development lifecycle. The aim of this study is to rank the software risks factors according to their importance and occurrence frequency based on the data source. The survey questionnaire is used to collect data and method of sample selection referred to as ‘snowball’ and distribution personal regular sampling was used. The seventy six software project managers have participated in this study who works in the Palestinian software development. Fifty software risk factors in all phases SDLC and thirty risk management techniques were presented to respondents. The results show that all risks in software projects were significant and important in software project manager's perspective. However, the ranking of the importance of the risks is assigned according to it: Analysis, planning, maintenance, design, and implementation. In addition, the top ten software risk factors in software development are selected and used for further analysis such as: Risk13, Risk 14, Risk15, Risk16, Risk11, Risk18, Risk12, Risk50, Risk19, and Risk 9. The concern of this paper the top ten controls are used to model its relationship with the risk, such as: C29, C30, C20, C27, C21, C19, C28, C25, C26, and C23. Software risks can be modelled empirically with risk management control techniques. We recommended applying more studies in software risk management practices with real world companies and building tools to identification and analysis software risks based on quantitative and intelligent techniques.

Dominance relation is an important method in incomplete interval-valued information systems. In order to solve the problem that too many attributes maybe result in the ranking failure in the incomplete interval-valued information systems, the concepts of extended possibility degree, extended possibility degree dominance relation and average comprehensive dominance degree are defined. Based on them, a ranking method based on extended possibility degree dominance relation is proposed. Finally, comparing with other ranking methods, this new ranking method based on extended possibility degree dominance relation not only has stronger differentiation degree, but also can make ranking results more objective and reasonable.

Pre and Post silicon validation automation is used for testing graphics in the computers, tablets and smart phones. A graphics driver is software that allows operating system and programs to use computer graphics hardware. To test the performance of this display system pre and post silicon automation is used such that end users get the best high definition experience. Pre silicon automation is based on emulation of graphics hardware and testing on it before it is actually build. Post silicon automation is testing of actual graphics hardware after it has been manufacture. Post silicon automation works to detect and fix bugs in graphics hardware of the system after it has been manufacture. Due to complex design of the hardware it is impossible to fix all bugs before it is manufacture. Pre silicon automation is an attempt to rectify any bug that can occur before the manufacture of graphics hardware such that it is way to reduces number of cases of bugs in graphics hardware that can occur after it is produce. Graphic Behavior in which each section is to assigned team of architects and micro-architects whose expertise targets a particular functional area for both hardware and software. It is record of all information that is kept for registers used in any sequences such that all information generated after running from driver is used to cross verify.

Textile products due to the industrial design will be left wide variety of chemical substances, when human contact with these chemicals can cause acute injury or chronic cumulative, so the research of exposure assessment of textile products is necessary. Due to cadmium is harmful to human health,we select the cadmium ion as the research object. In this paper, samples from some cities in Shandong were cadmium ion detection, analysis of data and derived their form of distribution. By drawing on the EU recommended harmful chemicals exposure assessment methods, we established a textile heavy metal exposure assessment model, and completed the application and verification. From the result of using this model to assess the amount of cadmium expose to human, we found that could have a bad effect on human body.

Internet banking is regarded as a delivery channel, which over a period of time has gained recognition. It in fact has experienced growth in many countries and has changed the traditional way of banking. This channel has provided competitive advantage to the banks. With the help of internet banking the consumer has an access to number of services just at the click of a mouse. The present study is based on the responses of 450 consumers surveyed in Delhi and National Capital Region to understand the consumer awareness towards internet banking and the respondents were selected from public, private and foreign sector banks. To achieve the objectives of the study a questionnaire with five-point Likert scale consisting of various aspects related to internet banking was designed and random sampling method was adopted to collect the responses. The results of the study indicate that the level of consumer awareness is higher in case of private and foreign sector banks in comparison to public sector banks. Public sector banks need to focus on their working in order to battle with the private and foreign sector banks.

A fuzzy sliding mode control method is proposed to eliminate the interference that suspended floating objects suffered in the on-ground low-gravity simulation system. Due to the change of sling swing-angle that caused by the external interference is weak, the time integral of the sling swing-angle is taken as tracking errors. Meanwhile the values of angle and the angle differential should be converged to 0. A fuzzy sliding mode controller is designed according to the dynamic model. The traditional sliding mode control method and fuzzy control method are combined in this paper. The simulation results indicate that the servo platform is capable of tracking a floating object rapidly. And the servo platform is able to move in constant velocity synchronously with the floating object while the sling is kept upright. The feasibility of applying fuzzy sliding mode control method to the field of tracking suspension floating object is verified.

Low power SRAM memory designs has become challenging for portable device applications. Semiconductor/ VLSI industry growth has exponentially demanding low leakage power SRAM designs for high performance chips and microprocessors. To get optimized standard cell memory design for battery operated devices at deep sub micron CMOS technology, a low leakage Asynchronous 8T SRAM is proposed. In this paper gated–ground P-P based low leakage 8T SRAM bit cell design is proposed for reducing the standby leakage power dissipation. The Proposed 8T SRAM bit - cell has used single bit line (single voltage source) for reading and writing operations to reduce active power consumption. The reduction of voltage swing and low standby leakage results appreciable reduction in total power consumption of the proposed design. The SPECTRE simulation and analysis at a 45nm CMOS feature size shows significant results in the proposed design at 0.7v supply voltage. Proposed Asynchronous single ended 8T SRAM bit - cell greatly reduced 99.92% stand by leakage power consumption and 11.76% of write ‘1’ active power consumption from the existing 8T SRAM bi – cell design. Whereas comparing with the standard 6T SRAM bit – cell design, proposed design also achieved 99.88% standby leakage power reduction and 95.8% of total active write ‘1’ power consumption from the conventional 6T SRAM bit – cell. This results overall total average power reduces in the proposed 8T SRAM bit-cell design i.e. reduction of 99.93% from the existing 8T SRAM bit – cell and 80.63% from the conventional 6T SRAM bit – cell design while keep maintaining the read static noise margin and write noise margin.

To solve the problem of abnormal battery discharge in the operation of electric vehicles, a method of fault tolerance based on data driven is proposed. First, based on the relation between transient voltage and the aging degree, battery SOC estimation model is built through LS-SVM method. Then, the fault-tolerant control scheme is put forward, which aims at abnormal discharge of power battery. When known battery exception occurs, the corresponding model control law is implemented to achieve fault tolerance control. When the unknown abnormal battery fault occurs, using dynamic data circulation way, the unknown exception model is rapidly established implementing system fault tolerant control for unknown exception. Finally, the accuracy of the method is verified by the simulation, which shows that this method is good for the fault tolerance of known and unknown faults.

Due to the normal forecasting methods for subgrade settlement using observation data have different applicabilities, and the predicting results has bigger volatility and lower accuracy. The Combined forecasting model of subgrade settlement based on Least Square twin support vector regession is put forward in this paper. At the first, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve with the S-type characteristics are choosed as single forcasting model; Then taking prediction results of each individual model as the least square support vector regression model input and to construct the combined forecasting model of subgrade settlement. The result of engineering practice shows that the proposed method has better prediction accuracy and stability.

Information systems and technology have become essential tools for organizations to achieve their goals. Therefore, many technology acceptance theories and models have been developed in the field. Research showed a number of models that introduce the factors which make information systems successful. Based on the theoretical lens rooted in the literature, the researchers critically reviewed ten models and theories on individual acceptance of technology. The review identifies the major models to make explicit assumptions. The present study tries to provide a summary of strengths and weaknesses that have been discussed about these models and theories.

With the rapid development of education in colleges and universities, college students employment situation is increasingly grim, encourage students through independent innovation entrepreneurship to better adapt to the development of the society become inevitable trend.Through the integrated use of Web services architecture, database applications, e-commerce knowledge, put forward a platform for innovation in colleges and universities of the MVC design pattern, by analyzing the feasibility of the system has better.

Affinity propagation algorithm is a new powerful and effective clustering method. One of the major problems in clustering is the determination of the optimal number of clusters. In this paper, the particle swarm optimization algorithm is utilized to cope with this problem by using the parameter p as each particle and Silhouette index as the fitness, which can search for the optimal value of p and determine the optimal number of clusters automatically. Moreover, the problem of information overlap is the main drawback of affinity propagation algorithm in dealing with complex structure or high dimensional data for clustering. Hence the enhanced Locality preserving projections method is proposed to integrate with affinity propagation algorithm to reduce the dimension of the data as a processing step. As the result of experiment shows, the proposed method can simultaneously obtain the optimal number of clusters accurately and improve the clustering accuracy by eliminating the redundant information of the data without losing the internal nonlinear structure.

Utilizing a computer-aided simulation approach, this work studies the impacts of different inter-stop transport distances on the transport efficiency evaluated by the transport time cost intensity of a typically composed Chinese freight train hauled by representative types of locomotives in view of different target speeds. It is found that the decelerated decrease of the transport time cost intensity with improving the target speed is much traded off by decreasing the stop-spacing especially below approximately 20.00 km. Moreover, the decrease of the inter-stop transport distance especially shorter than about 20.00 km obviously increases the transport time cost intensity in an accelerated way for the same target speed. Such a trend is more apparent when the target speed becomes relatively high. Therefore, it is suggested that the inter-stop transport distance of a freight train ought to be over 20.00 km for relatively high transport efficiency.

Due to the slow convergent speed of particle and easily get trapped in the local optima, a novel simple PSO algorithm with opposition-based learning average elite strategy is proposed. In this algorithm, a particle updating formula of the simplified swarm optimization (sPSO) algorithm is adopted. Moreover, the opposition-based learning elite strategy and Gaussian disturbance are exerted on the personal best particles and then replace personal best particle of sPSO with the average of elite opposite solutions with Gaussian disturbance of personal best particles. The adjustment of inertia weight is based on setting a threshold and then the inertia weight selects each mode adaptively according to its current state. A set of experimental results on benchmark functions demonstrate that the proposed PSO algorithm is an effective and efficient approach for optimization problems. Furthermore, the T-test analysis shows that the proposed algorithm is able to achieve better results.

To solve the automorphism group of a graph is a fundamental problem in graph theory. Moreover, it usually is an essential process for graph isomorphism testing. At present, because existing algorithms ordinarily cannot efficiently compute the automorphism group of a graph, ones cannot entirely resolve the graph isomorphism problem. To calculate the automorphism group of a weighted graph, first, briefly review the history of automorphism. Second, introduce the concept of eigenvalue partition. Third, using algebraic methods, examine not only the relationships between the diagonal form of an adjacency matrix and its eigenvalues and eigenvectors, but also the relationships between its eigenvalues and eigenvectors and the automorphism group. Furthermore, prove Theorem 2 to 8. In addition, propose Conjecture 1 and three open problems. By these theorems, present a novel method to resolve the automorphism group of a weighted graph. If a graph has no duplicate eigenvalues and Conjecture 1 is true, it can determine the automorphism group of a weighted graph in polynomial time by the method. Although this method has certain limitations and needs improvements, it is theoretically a necessary complement to solve the automorphism group. Finally, it shows the close relationships that exist between an orthogonal matrix and a permutation matrix, also an orthogonal matrix and an automorphism.

This paper introduces a novel intelligent computation adopted from a natural phenomenon entitled Thunderstorm Algorithm (TA) which is applied to optimize an economic dispatch under various technical constraints and environmental requirements. These studies used an IEEE-62 bus system as the sample model for demonstrating ability of TA while searching the optimal solution. Obtained results show that TA gives good performances for determining the optimal solution. This demonstration also describes that the optimal solution is searched in faster convergence and shorter time. This computation also performs its characteristic in smooth and stable processes for completing all steps. In detail, the optimal solution is obatined in 22 steps for 15,586 $/h after pointing at 28,858 $/h at the first streaming. Based on executions, the computation needed 2.5 s for the streaming and it also needed 0.09 for covering the dead tracks included 0.5 s for the replacement.

Aiming at 4-axial orthogonal turn-milling by end mill, its theoretical 3d model for stable range of dither was put forward on the basis of its cutting principle by using analytical method. Based on modal trial, the stable range leaf figure of end mill’s dither in 4-axial turn-milling with eccentricity was simulated and analyzed. The results show that besides geometrical shape of mill, material of workpiece and frequency response function of machine-tool’s structure etc that can produce dither in 4-axial turn-milling, the rotating speed of mill and cutting depth are also related to dither. In trial of 4-axial turn-milling by end mill, the results of cutting force spectrum analysis show that: cutting is stable and un-dither when frequency of cutter tooth cutting-in plays leading role in force spectrum. Dither is produced when modal frequency of system plays leading role in force spectrum, the measured value of cutting force and surface roughness are also higher than those in the condition of un-dither. Thus the theoretical model and results of emulation can predict stability of end mill’s dither in 4-axial orthogonal turn-milling with eccentricity correctly and can provide theoretical guidance for surface quality and processing efficiency of workpiece.

In order to obtain the minimum supply and demand scheduling under Cloud manufacturing platform, the fisher fishing algorithm is applied in it. Firstly, the optimization algorithm of fisher fishing is studied. Secondly, the supply and demand scheduling mode under Cloud manufacturing platform is constructed, and the corresponding optimization mathematical model is established. Finally, the simulation results of supply and demand scheduling time is carried out, results show that the fisher fishing algorithm is an effective tool.

Orthogonal array-based Latin hypercube designs (OALHDs) were constructed for four input variables computer experiments. The proposed designs have some advantages over the random Latin hypercube designs in terms of better space-filling properties and maximin distance criterion employed in the construction. There is a link between Graeco-Latin squares and orthogonal arrays (OAs). Graeco-Latin squares are two mutually orthogonal Latin squares of the same order such that when one is superimposed on the other, each symbol in the body of one square appears together with each symbol in the body of the other exactly once. This method is fast and straightforward to implement. In this paper, orthogonal arrays, OA (25, 4, 5, 2) and OA (49, 4, 7, 2) were generated from Graeco-Latin square of orders 5 and 7 and the orthogonal arrays generated were used to construct OA(25, 4)LHD and OA(49, 4)LHD for use in a computer experiment that involves only four input variables. The OALHDs constructed have better space-filling properties. MATLAB 2012a package was used for the development of the program that constructs the OALHDs in this paper.

Considering the probability matrix decomposition model, direct trust and indirect trust, trust propagation, as well as similarity between users and other factors, this paper proposes a new recommendation algorithm which fully taps the trust mechanism, and takes into account the similarity between users. Firstly, a new trust matrix is obtained based on the trust value of social network. Then all the trust relationships are integrated into the recommendation algorithm through the RSTE model. Finally, the prediction score is produced and the recommended list is given. Experimental results on public data sets show that this recommendation algorithm has obvious feasibility and superiority.

In order to improve the motion reliability of space manipulator during its long time service on-orbit, multiple indexes which can reflect the motion performance and multiple factors (control variables of manipulator) which have influence on motion reliability are involved in establishing an optimization control model. Thus the problem of motion reliability improvement is expressed as an multiple-objective problem (MOP). In order to solve the MOP, dimension reduction strategy is proposed based on covariance matrix of motion reliability indexes. As a result, the MOP is turned into single objective problem. Then control variables are optimized based on null space of space manipulator, and the best weight matrix can be obtained when the objective is minimal. Simulations are carried out to verify the feasibility and effectiveness of the optimization control strategy. By decreasing the error introduction into the control variables, the motion reliability can be effectively improved.

Precise control of hospital pharmacy inventory is an important guarantee for hospital. The optimal inventory policy for a multi-level medicine inventory control in hospital pharmacy was considered in this paper, and modeling simulation technology and intelligent optimization has been used. Analyzed with large-scale hospitals data, this paper has discussed the following problems: random fluctuations of demand in hospital departments, total volume limits and uncertainty response time of suppliers’ delivery. Establish multilevel pharmaceutical inventory simulation model, then use PSO method for intelligent optimization. Examples of simulation models and PSO algorithms verified by numerical results show that: when each department was tested randomly varying demand of the patients, multi-level inventory management must be overall coordination in order to achieve optimum system.

This paper emphasises on the control of a magnetic ball levitation system using an enhanced proportional integral derivative (PID) controller. Though PID controllers produce a controlled output for stable and unstable systems, the performance of the system in terms of overshoot, settling time, Integral Square Error (ISE) and Integral Absolute Error (IAE) are poor. To solve this problem, an enhanced PID controller is designed based on the system open loop transfer function. A compensator in cascade with the PID controller is designed based on bode plot response of the system. The efficacy of the proposed controller is demonstrated via simulation study of a magnetic ball levitation system. The results are compared with the classical PID controller. The proposed controller eliminates the overshoot and reduces ISE and IAE, thus provides smoother system responses.

Nowadays, the big success of deep learning makes artificial neural network becoming a hot topic once again, and the size of neural networks’ structure is a key visual cue for structured learning. The greater network may get the study task done well, while it may increase network computation overhead easier and cost more. Hence, network construction is an important issue, as well as a difficult problem. In this paper, we proposed a novel sensitivity-based adaptive architecture pruning algorithm for Madalines. The algorithm establishes a pruning measure based on the network sensitivity to its structure variation and a minimal disturbance principle. The measure can be used to evaluate the performance loss due to its structure changes more or less. And the loss can be compensated by relearning. Thus, the new adaptive pruning mechanism is developed with measuring, pruning, and compensating. The simulation experimental results based on some benchmark data demonstrate that the pruning measure is rationality and the new algorithm is effective.

As the rapid development of IOT (the Internet of Things), RFID technology has been widely applied, and it generates a large of RFID trajectory stream data with the spatial-temporal characteristic. Because RFID has many characteristics, it leads to become very difficult that extracting moving objects groups that together moving (ie. traveling partners) in a period of time from RFID trajectory stream data. Existing methods are difficult to efficiently find this model. This paper presents a closed clustering and intersecting algorithm (CCI) for RFID data to detect movement along traveling partners, which is mainly constituted by two steps: first step is clustering sub-trajectory, it generates sub-trajectory clusters; second step is intersecting sub-trajectories with the traveling partners’ candidate set to improve the candidate set, and find out traveling partners. In this process, we use the principle of Closure to accelerate our processing. Through experiments on the RFID synthetic dataset, we demonstrate the effectiveness and efficiency of our algorithm, thus show that our algorithm is suitable for discovering traveling partners in RFID applications.

Information diffusion in online social network especially in microblog system, can largely affect the public opinion and even the development of events, so the prediction of the future dynamics of diffusion could be very valuable at many aspects. In this research, a novel graph-based cascades construct algorithm is proposed, with which we build a prediction model for future information diffusion dynamics. By learning user influence features that related with the network topology and users’ interactions from a large scale real Weibo dataset, we successfully predicted the short term topic related tweets population dynamics.

Using the Cloud-based Offloading heartbeat aggregation method can solve the smart mobile terminal bearing the burden of persistent connections. It effectively reduces the heartbeat storm. But with the popularity of MTC (Many-Task Computing), especially in the environment of MMTC (Mobile MTC), using XMPP to communicate cause high energy consumption problem at the same time. The traditional XMPP protocol format already cannot adapt to the high performance transmission under the new environment. This paper is based on the MMTC environment, proposed the new communication method of mobile terminal and cloud with XMPP protocol to achieve more energy efficiency.