Applied Mechanics and Materials Vols. 385-386

Abstract: DO-Swoosh algorithm maps the input data to domain ontology and count the amount of data for each leaf node. Then define the distance between nodes according to the hierarchical relationships reflected by domain ontology and propose a node merging algorithm based on the principles of data balance and nearest merge. At last, perform entity resolution for each group according to the node merging result. DO-Swoosh still keeps the good generality and gets better performance and scalability with the aid of MapReduce.

Abstract: To systematically harmonize the conflict between selective pressure and population diversity in estimation of distribution algorithms, an improved estimation of distribution algorithms based on the entropy increment theorem (IEDAEI) is proposed in this paper. IEDAEI conforms to the entropy increment theorem in simulating the competitive mechanism between energy and entropy in annealing process, in which population diversity is measured by the entropy increment theorem. By solving some typical high-dimension problems with multiple local optimizations, satisfactory results are achieved. The results show that this algorithm has preferable capability to avoid the premature convergence effectively and reduce the cost in search to some extent.

Abstract: In this article,take into account QoS characteristics comprehensively and build a reliable QoS ontology model. Based on the model,Web service QoS matching will be divided into three stages.Firstly,make a estimation of semantic comparability between QoS parameters of candidate services meeting the functional requirements and the QoS parameters of requirements in QoSIndependent ontology,find candidate services meeting users needs; Then,according to the critical QoS parameters between adjacent services constraints to further refine the matching between the candidate services;Finally choose the maximum service QoS value meeting the user requests in specific areas. So as to improve the efficiency and accuracy of service matching.

Abstract: This paper presents an ETL system for a data warehouse designed for a PVC profile manufacturing enterprise. The system implements the data extraction, data transformation and load from the data sources of ERP system, CRM system and production line operation data collection system. The ETL requirements are discussed. The system design and implementation methods, including system structure, functions, data processing methods as well as tray program implementation are addressed.

Abstract: In this paper we present a method of reachability analysis for Internet of Things (IoT) perception layer scheduling. First, the model of perception layer information flow and behavior is formed. Because perception network is a system with coexistence of discrete events and successive events, so we use hybrid dynamic logic modeling approach to form the information perception model; Then inequality proving theory, semi-algebraic system and related tools Discoverer soft package are used to give reachability analysis of the model of perceptual system, and the feasibility of this method is verified by the vehicle condition monitoring system application.

Abstract: Taking the construction of information system as application background, a cutomizable modeling workflow system based on the theory of the Process Virtual Machine is put forward in this paper. The flow parsing model supports multiple business flow description language and the corresponding parsing mechanism. One kind of description language and the corresponding parsing mechanism are mainly elaborated. The information system which integrates this kind of workflow system is enhanced in its robustness and scalability characteristics.

Abstract: There are many learning evaluation methods, but most of them are subjective, which contains a lot of man-made factors. This paper presents a new learning evaluation method based on radial basis function (RBF) neutral network. By analysis the orthogonal least squares for RBF and determines the center of the basis functions, the model of RBF neural network was constructed. Experimental studies show that the Method Based on RBF Neural Network is effective for learning Evaluation.

Abstract: Requirement engineering is the basis of software development, and it is a key factor determines whether a software development can be successful or not. This article first presents the requirement engineering at capability maturity model (CMM). Then the problem in demand development and demand management are discussed in the second section. Finally, a CMM based requirement engineering model is presented. This model provides a more efficient and effective method in requirement engineering. As the most important parts of this model, requirements analysis, form requirement document, review requirement and change control are described in detail.

Abstract: It is important to notice that the access control mechanism has been widely applied in various areas, such as on-line video systems, wireless network, and electronic documents. We propose an access control mechanism which is constructed based on two mathematical fundamentals: Lagrange interpolation and ElGamal algorithm. We conduct performance analysis to compare the efficiency of our proposed scheme with that of several related published schemes in both key generation phase and key derivation phase. Our new scheme is proven to be more efficient. It is shown, as expected, a more efficient scheme provides relatively less security and a more secure scheme is relatively less efficient for private keys of the same size.

Abstract: By combining LVS cluster architecture and could computing technology, system architecture of the cloud computing service platform is proposed. Cloud computing technology is suitable to support large-scale applications with flash crowds by support elastic amounts of bandwidth and storage resource etc. But traditional algorithms of load balancing provided by LVS are unsuitable for the proposed service platform, because these algorithms are designed for static server resource provided by traditional cluster technology. Taking both the overall utilization rate of server resources and the active connections of the server into counter, an adaptive adjustable load balancing algorithms (Least Comprehensive Utilization and Connection Scheduling algorithm, called LUCU) is proposed in this paper. According the utilization of cloud resource and the users demand, automatic switching between Round Robin (RR) algorithm and LUCU algorithm is achieved. When the cloud capacities are not able to meet the instantaneous demands, LUCU is chosen instead of RR. The proposed platform and algorithm are verified and evaluated using large-scare simulation experiments. The test results show that the equilibrium load is nearly achieved by adopting the proposed algorithms.