Applied Mechanics and Materials Vols. 556-562

Abstract: The analysis of two-dimensional rotation and impact properties of volleyball serving benefits detailed force analysis during the process of hitting and serving. In this paper, a method combining modeling and actual impact properties analysis is proposed and utilized to analyze two-dimensional rotation curve of volleyball. And the actual serving, sideways position, backhand hit are taken as example to carry out a detailed analysis of the process, and build up the model to reflect the effect of speed, arc, rotation and other factors on the two-dimensional rotation in volleyball serving. The test results show that this method has a good guiding significance for the analysis of the actual volleyball.

Abstract: Aerobics is one of the sports welcomed by the majority of the people. In competitive aerobics sport, a certain evaluation method is adopted to ensure multiple evaluation criteria of aerobics can achieve the best performance, and enhance the competitive level of aerobics players. The traditional aesthetic evaluation method of aerobics is coaches guided out-field approach, the aesthetic effect is optimized by guided and dominated by coaches, but athletes cannot participate in the evaluation system, which leads to poor guidance effect. In this paper, an aerobics movement reconstruction method based on three-dimensional motion vision is proposed. Computer visual recognition technology is utilized to extract characteristic image point of aerobics body, obtain the main features of the edge contour of aerobics body, and then three-dimensional evaluation is processed, the experiment group contains 4 different bodies. Simulation results show that the proposed method which is used to extract the body characteristics image point to process three-dimensional aerobics body shape evaluation, can improve the overall effect greatly, with a good guiding significance.

Abstract: Most constraint-handling methods in constrained evolutionary optimization usually take advantage of only the valuable information of feasible solutions, while they don’t exploit adequately the information from infeasible ones. In this paper, a concept of “feasible component” is introduced to recognize the characteristics of diverse information extracted from infeasible solutions. Then a component-based ranking strategy is proposed for evolutionary optimization with sparse constraints by integrating feasible components and the idea of stochastic ranking. Experimental results on several problems with sparse constraints show that the component-based ranking strategy performs better than the stochastic ranking.

Abstract: In this paper, the evidence combination principle of Dempster-Shafer (D-S) evidence theory is analyzed in detail. And the method of evidence combination is improved because of the deficiency of D-S evidence theory. Considering the principle“the minority should be subordinate to the majority”, based on Yager’s rule, we put forward a new effective combination rule which works more reasonably.

Abstract: In this paper a complete and improved mathematical framework of the geometric approach based on the Scaled convex hull (SCH), which includes two parts, SCH-based geometric algorithms for SVM and a fast and novel geometric method for model selection in SCH-based SVM, is developed to solve SCH-based SVM classification of large data sets. On the basis of this framework, these geometric algorithms are more suitable for classification task of large data sets. Results of numerical experiments show that the proposed geometric algorithms can reduce kernel calculations and display nice performances on large medical data sets, such as computer assisted screening for lung cancer.

Abstract: Trusted computing is a hot topic of information security technology research nowadays. It was developed based on computing and Information Systems. At the same time, business processes for e-commerce and Web service applications, suppliers and customers define a binding agreement or contract between the two parties, specifying quality of service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. In this paper, we discuss the present situation about QoS in the environment of trusted computing. It describes the factors related to each attribute, as well as possible tradeoffs and existing efforts to achieve that quality. The paper also discusses key issues in services level agreements that are used to contract the level of services quality between service providers and users.

Abstract: This paper applies the dynamic self-organizing maps algorithm to determining the number of clustering. The text eigenvector is acquired based on the vector space model (VSM) and TF.IDF method. The number of clustering acquired by the dynamic self-organizing maps. The threshold GT control the network’s growth.Compared to the traditional fuzzy clustering algorithm, the present algorithm possesses higher precision. The example demonstrates the effectiveness of the present algorithm.

Abstract: Data mining is a technique that aims to analyze and understand large source data reveal knowledge hidden in the data. It has been viewed as an important evolution in information processing. Why there have been more attentions to it from researchers or businessmen is due to the wide availability of huge amounts of data and imminent needs for turning such data into valuable information. During the past decade or over, the concepts and techniques on data mining have been presented, and some of them have been discussed in higher levels for the last few years. Data mining involves an integration of techniques from database, artificial intelligence, machine learning, statistics, knowledge engineering, object-oriented method, information retrieval, high-performance computing and visualization. Essentially, data mining is high-level analysis technology and it has a strong purpose for business profiting. Unlike OLTP applications, data mining should provide in-depth data analysis and the supports for business decisions.

Abstract: This paper introduces an improved localization algorithm that bases on distance and local coordinate system which is built up by beacon nodes. This algorithm evaluates the differences of several independent localization information to determine whether upgrade this node as beacon nodes according to the size of the difference whether beyond the prescribed or not. It can effectively prevent and reduce the accumulated and spread error in localization process by the audit of beacon nodes, and improve the positioning accuracy of nodes in the network.

Abstract: Stochastic job - shop scheduling problem (SJSSP) is a kind of stochastic programming problem which transformed from job - shop scheduling problem (JSSP). The current methods to solve SJSSP ignored characteristics of SJSSP, which lead to large solution times and inefficient solution. Aiming at the problem,An adaptive Hyper-Heuristics genetic algorithms (AHHGA) is proposed combing with characteristics of SJSSP to solve SJSSP with the objective to minimize make span (minimize the expected value of make span). Four heuristics rules for SJSSP were designed. Portfolios of processing times of job can be seen as a scenario. The outer loop of the proposed algorithms is to determine heuristics rules on each scenario in scenario set.