Earticle

DE is a topic of current interest in the optimization field. It is the most capable evolutionary algorithm based on biological theory of evolution because of its ease and competence in solving variety of problems, like multi-objective, multi-modal, dynamic optimization problems. But premature convergence or stagnation is a main problem with it. So In order to improve the performance of DE, significant number of DE variants has been proposed by many researchers over the last few decades. Mutation is one of the key tasks of DE. It appreciably influences the performance of DE. In this paper, DE variants with four different mutation techniques- DE/rand/1, DE/local-to-best, DE/either-or and MODE are studied and implemented. Comparison of DE having these mutation strategies is made for variety of dimension and population size and results shows that DE/local-to-best performs best on all the benchmark functions where as MODE also show significant performance.

The delta deposition pattern is the most important and universal sedimentation type in reservoirs, yet it is still unclear to engineers and researchers concerned about its evolution, adjustment and preliminary equilibrium of the sedimentation. Taken the reservoir named Xi Luodu as a typical case study the whole deposition processes of the delta evolution can be divided into two stages according to the time the delta arrives at the dam site, corresponding to the formation of the wedged shape deposition. Sedimentation in the first stage composes the majority deposits of the reservoir total accumulation volume. Although in the second stage the deposition rate is much slower than the first one it is the period for the reservoir to rebuild its new equilibrium mainly by changing the configuration of its cross-section to regain sufficient sediment carry capacity. The delta profile and the cross-section deformation were both discussed in detail during the two stages. Characteristics of the deposition/erosion along with the sediment delivery ratio were also analyzed throughout the whole processes.

Silverlight technology is a new generation of rich internet application technology. The paper proposes a new solution based on the Silverlight technology to achieve a 3D virtual reality system which takes the pictures around the objects with 360 degree displaying in the local computer or a web page. The 3D visual sense and image matching of this system are the key technical problems. The automatic matching technology in image synthesis field plays a very important role in the system. Based on the SURF algorithm, this paper takes strategies of density threshold suppression to reduce the number of matched feature points; using the quasi Euclidean distance to complete the feature points matching process, the improved algorithm also greatly reduces the matching time of feature points and improves the matching accuracy. Through theoretical analysis and experimental contrast, demonstrates the reliability and validity of the algorithm.

This paper presents an Adaptive Cuckoo Search Algorithm (ACSA) for solving economic load dispatch problem where thermal units with multiple fuel options and valve point loading effect are taken into account. ACSA is first developed by improving the optimal solution search ability of conventional Cuckoo search algorithm. In ACSA, the initial eggs are evaluated and classified into two groups including good group and bad group. The updated step size in ACSA at the first new solution generation via Lévy is adaptive at each iteration and therefore the selection of the parameter is not an issue in the paper. The proposed ACSA method is tested on a ten-unit system considering multiple fuel options and valve point loading effect with different load cases. The comparisons of obtained results among the proposed method with others reported in the paper have indicated that ACSA is efficient for applying to the problem.

In order to accelerate the construction of transshipment container terminal in Chinese mainland, and to strength our global competitiveness about container terminals, a design plan of container yard for transshipment hubs is explored, which is suitable to China’s conditions and aims at Shanghai Port mainly. Considering the actual operation of transshipment in Chinese container terminals and overseas, a new yard template planning with mixed handling technology is proposed, which is appropriate for the container terminals located in Chinese mainland. An inbound unloading process model of proposed plan is built by eM-Plant, and the simulation result is analyzed to verify the feasibility and superiority of the new design plan. The exploration and design for transshipment hubs provide new thoughts and ideas for the container terminals development in China.

Active disturbance rejection control (ADRC) is a unique control strategy that combines the effectiveness of error driven PID controller, usefulness of state observer and strength of nonlinear feedback. This control algorithm, not only actively (online) estimates but also compensates the effects of unknown internal and external disturbances, present inherently in the plant with the help of a well-tuned extended state observer (ESO). Although, the classical solution to the parameter tuning performed by using parameterization technique provides good solution, it is not optimal for having desired performance specifications. Consequently, it became imperative to have intelligent tuning technique to achieve optimized solution to parameter tuning problem. In this regards, the Evolutionary Algorithms (EA), inspired by natural system and based on swarm intelligence, are proven to be the best tool to find the optimized solution of multi-dimensional problems. This paper presents an application of an EA optimized ADRC controller on an uncertain 2-DoF revolute-prismatic (RP) robotic manipulator for efficient trajectory tracking and parametric robustness. Eventually, the conventional ADRC design problem is converted into a special optimization problem for finding the optimal controller tuning parameters. To accomplish this task, two well-known EA’s viz. Particle Swarm Optimization (PSO) and Bacteria Foraging Optimization (BFO) are implemented and performance of EA based controller-plant configuration is individually analyzed for each algorithm. The results of this note illustrate the benefits and weakness of the EA for implementing ADRC on MIMO systems. The performance of both the optimization techniques is compared in terms of computational time and convergence efficiency. Further, the optimized controllers are tested for the robustness in presence of disturbance and sensor noise to imitate real engineering. MATLAB based simulation results are presented and compared to demonstrate the effectiveness of both the EA's in designing an ADRC controller for improving manipulator tracking ability.

To improve driving ability of electric vehicle, a braking regenerative energy recovery of electric vehicle was designed and the structure of it was introduced, the energy recovery efficiency of whole system was defined and a highly efficient control strategy was put forward, then it was embedded into the simulation of ADVISOR2002. The recovery efficiency of the system was up to 60%, the electric vehicle energy recovery efficiency was effectively improved.

In this paper, present a graph cuts based geodesic active contours (GAC) approach to object segmentation problems. Our method is a combination of geodesic active contours and the optimization tool of graph cuts and differs fundamentally from traditional active contours in that it uses graph cuts to iteratively deform the contour. Consequently, it has the following advantages. 1. It has the ability to jump over local minima and provide a more global result. 2. Graph cuts guarantee continuity and lead to smooth contours free of self-crossing and uneven spacing problems. Therefore, the internal force which is commonly used in traditional energy functions to control the smoothness is no longer needed, and hence the number of parameters is greatly reduced. 3 Our approach easily extends to the segmentation of three and higher dimensional objects. In addition, the algorithm is suitable for interactive correction and is shown to always converge. Experimental results and analyses are provided.

Most of controllers need real time mobility operation so one of the most important devices which can be used to solve this challenge is Field Programmable Gate Array (FPGA). FPGA can be used to design a controller in a single chip Integrated Circuit (IC). To have higher implementation speed with good performance cMinimum Control Unit (MCU) is implemented on Spartan 3E FPGA using Xilinx software. Design a 4 bits Field Programmable Gate Array (FPGA)- based carry lookahead MCU is the main challenging works. MCU is control unit to control of data transfer between input and output and process the input data. In this research, MCU is used to control the 4 bits, Arithmetic Logic Unit (ALU). Combinational logic characterized by its propagation delay and contamination delay. To reduce the delay hardware description language (HDL) type of programming is very important. To reduce the route delay and logic delay, type of HDL design is very important. In this research, we used lookahead design, which reduce about 10% delay in comparison with ripple carry.

Feature selection is an important data preprocessing technique and has been widely studied in data mining, machine learning and granular computing. In this paper, we introduced an effective feature selection method using the hybrid approaches, that is, use the mutual information to select the candidate feature set, then, obtain the super-reduct space from the candidate feature set by a wrapper search approach, finally, the wrapper method determined to select the proper features. The experimental results show that our approach owned the obvious merits in the aspect of classification accuracy ratio and number features selected by extensive comparing with other methods.

Parameter uncertainty of chaotic systems brings the complexity to the design of control law in many past research papers. In order to simplify the design of adaptive PID composite synchronous rule further and use the robust control method to deal with uncertainty conveniently, two kind of robust adaptive and nonlinear sliding mode synchronization algorithms are proposed for uncertain chaotic systems in this paper. The design strategy of the algorithm lies in using the boundedness of chaotic systems. The unknown information of driven system and response system is limited to be a given uncertainty range described by a bounded function. The robust adaptive controller is designed to complete synchronization. At last, it can be seen from the simulation that chaotic systems can achieve synchronization and eliminate the vibration phenomenon at the same time. The only disadvantage is that the precision of synchronization is limited by the control gain.

This paper presents an Analog behavioral model (ABM) of the Insulated Gate Bipolar Transistor (IGBT) with Orcad Pspice 16.5. The Spice model was built using device parameters extracted through experiment. A full study of switching behavior of IGBT during turn-off and turn-on for inductive load with freewheeling diode is presented and simulated. All simulation results presented in this paper are validated, compared and showed good agreement with the measured data. The temperature dependent behavior is simulated and analyzed.

Teaching new material and reviewing what has already been taught are two important activities in the educational process. Different students with different learning abilities need to review at different rates, that is to say, a personalized teaching process is necessary. Review has a spacing effect, namely it is most useful only if it is executed neither too soon nor too late. How should designers of educational software schedule the learning process to satisfy the need that different students learn different material? We present a mathematical model to capture the issue in idealized form. The learning abilities of students and the spacing effect of review are modeled as some input parameters’ constraints on the schedule. Our results include the optimal scheduling in accordance with which tutoring systems teach one student specific material, characteristics of the rate at which new material can be introduced under different conditions, and the reproduction of ladder-like educational process.

Nowadays security matter is a great challenge in web-based systems and we are using various types of HIP to defend malwares in web. But today’s conventional HIP models are able to defend bots but make a user ireful. This paper will focus on a new and simple model of CAPTCHA to defend bot-attack. This model makes a user easily to pass and also amuse them with its simplicity. Considering computational complexity, we are using a thin algorithm with some other technical tricks to make it both robust & simple.

Numerical simulation has been widely applied in ocean engineering owing to its low cost, short cycle and wide application range. However, post-processing software of numerical simulation doesn’t support production specification of marine engineering and other industries, and integration production is not flexible. According to particularity of numerical simulation and user requirements, this paper took GIS as the solution to achieve dynamic visualization of numerical simulation and one-click generation of business products. Firstly, based on its characteristics, convert marine numerical simulation data into vector field represented by arrows or scalar field represented by grid. Secondly, GIS based spatial display and analysis technology is used to realize the visualization expression of marine numerical simulation data. In order to improve the effect of display and expression, we achieve rendering through symbol and color stretching mapping. Finally, we output numerical thematic map through custom map range and great map decoration function.

Because of the nonlinear characteristics of monitoring system in military barracks, the traditional KPCA method either have low sensitivity or unable to detect the fault quickly and accurately. In order to make use of higher-order statistics to get more useful information and meet the requirements of real-time fault diagnosis and sensitivity, a new method of fault detection and diagnosis is proposed based on multivariate statistical kernel principal component analysis (MSKPCA), which combines statistic pattern analysis framework (SPA) and kernel principal component analysis (KPCA). First, the transformation of multivariate statistics and kernel function are conducted in which technology of moving time window is used. Then, PCA is executed to analysis the kernel function obtained from the first step. Moreover, the statistics of T^2 and SPE and the control limits of them are calculated. Finally, simulations on a typical nonlinear numerical example show that the proposed MSKPCA method is more effective than PCA and KPCA in terms of fault detection and diagnosis.

DE\BBO is the combination of differential evolution and biogeography based optimization algorithm to get a better optimization algorithm in terms of convergence speed. In DE\BBO, constant crossover rate has been used which sometimes affect the performance of the hybrid algorithm leading to increase in convergence speed. To cope up with this problem, variable crossover rate has been introduced in the hybrid algorithm helping in removing the problem of constant crossover rate. Modified algorithm has been named as DE\BBO\L in which local search mutation and variable crossover rate are used. Testing of BBO, DE\BBO\rand\1 and DE\BBO\L has been performed on different test functions. The results reveal that DE\BBO\L with variable crossover rate is better than DE\BBO with constant crossover rate.

Fast and exact searching for sequences similar to a query sequence in genomic databases remains a challenging task in molecular biology. In this paper, the problem of finding all e-matches in a large genomic database is considered, i.e. all local alignments over a given length w and an error rate of at most e. A new database searching algorithm called QFLA is designed to solve this problem. The proposed algorithm is a full-sensitivity algorithm which is a refined q-gram filter and implemented on a q-gram index. First, new features are extracted from match-regions by logically partitioning both query sequence and genomic database. Second, a large part of irrelevant subsequences are eliminated quickly by these new features during the searching process. Last, the unfiltered regions are verified by the well-known smith-waterman algorithm. The experimental results demonstrate that our algorithm saves time by improving filtration efficiency in a short filtration time.

This paper offers a framework for understanding the dynamics formation of complementary industry convergence and substitution industry convergence from the respective of industry evolution, according to convergence may involve changes in competitive and/or complementary relations between two or more industries. Based on the characteristics of ICT-intensive industry, this paper describes the relationship between industry convergence, industry symbiosis and industry evolution. Through the evolution modeling of industry system and analyzing of symbiosis stability, we find that complementary industry convergence and substitution industry convergence occur when subsystems cooperate mutually or the degree of substitution isn’t strong, and complementary integration mechanisms dominate substitution mechanisms. In the complementary industry convergence, converging industry and original industry are symbiotic, and the industry system has more room for development.

Certification refers to the verification of definite feature of an object, person, or an organization. This verification is often, but not always, provided by some form of external review, education, assessment, or audit. In general, the main certification idea is to bring quality process to a certain software product. One of the core goals to achieve quality in component based product is to acquire reliability, quality and compatibility with other components. We have proposed an evaluation process for certification of component-based software. Certification is performed at component as well as system level. The six factors given by ISO are used to certify the system or component. Some other factors are also taken into consideration for certification process. Unstructured weighting technique is used to assign weights to these seven factors.

The research of defect detection technology of magnetic sheet surface has important significance for improvement of production efficiency and product quality in enterprise. A single threshold method is used for binary segmentation of magnetic sheet image in this paper, then the template localization algorithm is used for template position of magnetic sheet image after binary segmentation, the magnetic sheet image with different position should be transformed into a unified coordinate system for detecting, then least square method is used for fitting straight line and fillet edge, then the calculated values are compared with standard value to determine whether are knock edges. Further, the appropriate grayscale threshold is set by the pitting and scratches characteristics of magnetic sheet image, the magnetic sheet image should be segmented according to the determined threshold value, if the defect exists, the defect area or length will be calculated, then the result is compared with standard values to determine whether is pitting or scratches. The final tests of technology in this paper show that the detection rate of knock edge and the detection rate of pitting or scratches are both acceptable.

An efficient government office automation system, which contributes significantly to social supervision, administrative efficiency, administrative quality, and service capacity, has been an important criterion for assessing the development of a country. With the rapid development of the global economy, more and more such systems are designed and implemented. However, few of them could take into unified account ever changing requirements of government affairs. In this paper, we develop an integrated and automated management system for government affairs. In the beginning, we analyze why we need the new system by introducing the overall background of the electronic governments and the office automation system. Then, according to system requirements, we divide the system into four functional modules, i.e., the login module, the approval flow module, the document management module, and the system management module. After that, we present many details about the architecture, the modules, and the database for the system design. Finally, illustrating both processes and interfaces of required modules, we implement the system based on the well known three-tier B/S architecture.

DE is a topic of current interest in the optimization field. It is the most capable evolutionary algorithm based on biological theory of evolution because of its ease and competence in solving variety of problems, like multi-objective, multi-modal, dynamic optimization problems. But premature convergence or stagnation is a main problem with it. So In order to improve the performance of DE, significant number of DE variants has been proposed by many researchers over the last few decades. Mutation is one of the key tasks of DE. It appreciably influences the performance of DE. In this paper, DE variants with four different mutation techniques- DE/rand/1, DE/local-to-best, DE/either-or and MODE are studied and implemented. Comparison of DE having these mutation strategies is made for variety of dimension and population size and results shows that DE/local-to-best performs best on all the benchmark functions where as MODE also show significant performance.

Cultivation of innovative talents has already been the focus of education research, in this paper; we research the innovation and entrepreneurship education system, constructing the index system of innovation and entrepreneurship education for college students. Using the analytic hierarchy process and gray theory, we studied the quantitative evaluation of innovation and entrepreneurship education of college students. Taking North China University of science and engineering as an example, we put forward a set of countermeasures and suggestions on the cultivation of innovation and entrepreneurship education for college students.

Fluid simulation is an important application of High Performance Computing. The hybrid atomistic-continuum coupling fluid simulation can effectively handle the contradictory of the reduction of the simulation scale and the increase of the computation load when trying to improve the accuracy. The pre-processing procedure of the coupling simulation is quite important in the whole simulation process and requires the support of an efficient, user-friendly interface. Under the demand of efficient coupling fluid simulation, in this paper we design and implement a visualized pre-processing framework HACP2 based on SALOME, for the unified molecular dynamic-computational fluid dynamics modeling and apply it into the coupling simulation process. The experimental verification indicates that our HACP2 framework can offer efficient, easy-to-use pre-processing for the hybrid atomistic-continuum coupling simulation, and effectively improve the efficiency of the coupling simulation.

Optimizing the utilization factor of the system resources such as efficiency, bandwidth, and the storage capacity for cost reduction is one important aim of enormous amount of studies. For the image compression one can use the embedded processors as the most suitable ones. This image compression schemes for images will be based on the Discrete Cosine Transform (DCT). This paper implements an efficient and effective algorithm for still image compression of relatively high signal to noise ratio. The implemented technique considers that only zeros of the zigzag scanning is the repeated runs. This results in possibility of zero byte of the Run Length Encoding (RLE) output elimination. Word-length reduction and higher compression ratio can be customized.

Aiming at the path planning problem of mobile robot, a chaotic ant colony system was presented. The idea of the algorithm was that first generated chaotic sequences as the initial pheromone matrix and then ant colony traversed grids environment once, pheromone on the path was updated, as the completeness of the pheromone initialization. Pheromone update strategy adopt self-adaptive chaotic disturbance to avoid the search being trapped in local optimum. Grids environment simulated the robot workspace. Through the process of self-organization and chaos, the ant colony found the optimal path in the robot’s static environment. Simulation results show that chaotic ant colony system not only enhances the global search capability, but also more effective than the traditional ACS, moreover, it’s a novel approach to the robot path planning.

Hub and spoke network has been widely used in air transport, road freight, shipping network and urban distribution areas as part of the strategic decisions, which may have a profound effect on the future of enterprises. In view of the existing network structure, as time goes on, the number of spokes and the flow change because of different sources of uncertainty. Hence, the incremental optimization of the capacitated single-allocation hub and spoke network problem is considered in this paper, and the decisions to be made to cope with change comprise (i) whether new hubs need to be setup and their selection, (ii) whether the capacity levels of original hubs need to be adjusted, and their new capacity levels, (iii) whether the original hubs need to be closed, (iv) the new allocation of the spoke nodes to the hubs, (v) the flow distribution through the sub network defined by all the hubs. The objective is to minimize the total cost, which includes the setup costs for the new hubs, the closure costs and the adjustment costs for the original hubs as well as the flow routing costs. Two mixed-integer linear programming formulations are proposed and analyzed for this problem. A set of computational tests are performed, and we analyze the changes in the solutions driven by the number of spokes and the flow. The tests also allow an analysis to consider the effect of variation in parameters on the network.

Currently, from the statistical analysis of accidents at home and abroad, the number of automobile defects and the resulting automobile accidents are very large. Obviously, the automobile defects have become one of the main factors affecting traffic safety, and risk assessment as an automobile key technical defect of risk management, the elimination of defects and reduce automobile accidents are of great significance. Through statistical study of automobile defect recall, this paper analyzes the automobile defects and its risk characteristics and the event tree analysis (ETA) method was introduced to determine the risk flow route of automobile defects. Based on thousands of automobile breakdown cases for risk probability forecast, this paper proposes a three-dimensional matrix risk assessment model of automobile defect. According to the dispersibility of automobile, a risk forecast method based on the Weibull distribution is established. The results indicate that on gathering actual failure data from after-sales service, the Weibull distribution model has a favorable applicability for forecasting risk possibility, and then apply it to auto defect in three-dimensional matrix model so as to get the overall risk level of defect automobile.