Advanced Materials Research Vols. 143-144

Abstract: Aiming at the problem of tight coupling and interface complexity of WebService based on XML-RPC interactive model, this paper proposed the REST-based WebService, and gave out the design method of each part, including the design of restful Resource-Oriented Architecture, design of request and response interactive model and design of service discovery architecture based on semantic search. This research result was applied into an actual project, which indicated this WebService is loose coupling, interface uniform, portability, reliability and has good web-scale scalability features. Finally, an example is presented to illustrate this WebService architecture.

Abstract: Supply chain network is a complex giant system and its complexity determined by the structure of network. A new security analysis method of supply chain network is proposed in this paper , which concentrate on the topology structure security of networks based on complex network theory. According to the complexity of network topology and its kinetic characteristics, we found that the growth of supply networks with scale-free properties, which is robustness on the random attack, but fragile on the selected attack. This paper propose two options to improve supply chain network survivability, the one is to protect these core enterprises; the other is the formation of local alliance between enterprises.

Abstract: In this paper, we propose a temporal-based aythorization model for Group-centric Secure Information Sharing(g-SIS) . The traditional approach to information sharing focuses on attaching attributes and policies to an object as it is disseminated from producer to consumers in a system. In contrast, group-centric sharing brings subjects and objects together in a group to facilitate sharing. In such contexts, authorizations are influenced by the temporal ordering of subject and object group membership. That is, the authorizations are decided by the time that subject joins group and the time that object is added to group. But, the model doesn’t consider the time constraint of group enabling and access enabling. For example, a secure meeting room is open only at 8:00—10:00 am and 15:00—17:00 pm every Monday. We develop a temporal-based authorization model for group-centric information sharing which takes the temporal intervals of group and access enabling into consideration. We also discuss a usage scenario to illustrate practical application in secure meeting system.

Abstract: Support Vector Machine has been widely studied in recent years. The algorithm of least squares support vector machine is studied, the shortcomings of the algorithm are given. The result of algorithm is lack of sparseness. In this paper greedy algorithm is introduced into the least squares support vector machine. Sparseness is obtained again. A new algorithm of sparse least squares support vector machine is given. The new algorithm was used to sewage treatment plant daily monitoring. Experimental results demonstrate the improved algorithm of support vector machine was successful.

Abstract: The multiple-instance classification problem is formulated using a linear or nonlinear kernel as the minimization of a linear function in a finite dimensional real space subject to linear and bilinear constraints by SVM-based methods. This paper presents a new multiple-instance classifier that determines two nonparallel planes by solving generalized eigenvalue proximal SVM. Our method converges in a few iterations to a local solution. Computational results on a number of datasets indicate that the proposed algorithm is competitive with the other SVM-based methods in multiple-instance classification.

Abstract: The execution time of shortest path computing determines the efficiency and quality of dynamic traffic assignment. This paper focuses on the design of a parallel calculation system for the shortest path in traffic network aims to reduce the execution time of shortest path computing in dynamic traffic assignment. Here we mainly focus on the process of algorithm parallelization and network decomposition. As the core of the system, a two-queue parallel algorithm is designed for the shortest path in the traffic network which the recursive spectral bisection decomposition approach is employed to separate the network into several parts and the algorithm acts on every sub-network on each processor. The proposed system are experimented on real traffic network and a set of policies are employed that the number of processors is designed in each policy in the study case, and the performances of the parallel calculation system are discussed, the proposed algorithm is proved to be the efficient and effective.

Abstract: According to the characteristics of an environmental risk emergency management decision support information system, this paper builds a complete system outline and structure, using a C/S and B/S hybrid structure and loose integrated model. It proposes the system implementation techniques route, designs the system function modules and database, completes the database construction and the main system functions.

Abstract: To solve more complex manufacturing problems and perform larger scale collaborative manufacturing, a new service-oriented networked manufacturing model—Cloud Manufacturing is presented. The paper presents a resource virtualization model to support resource sharing in cloud manufacturing environment. It can be decomposed into four layers: manufacturing resources layer, concrete web service layer, logical service layer and application layer. The relationships of every layer are discussed in detail. At last, we make a conclusion and put forward the future work.

Abstract: Determining which peptides bind to a specific major histocompatibility complex (MHC) class I molecule is not only helpful to understand the mechanism of immunity, but also to develop effective anti-tumor epitope vaccines. In order to further study the specificity of MHC class I molecule binding antigen peptide, the support vector regression (SVR) and four amino acid descriptors were used to build four models of predicting binding affinities between peptides and MHC class I molecules. Comparison among performances of the four models indicated that the model based on physicochemical properties of amino acids is more satisfying (AC=75.0%, CC=0.499). Furthermore, the specificities of MHC class I molecule binding antigen peptide were obtained through analysis based on the contribution of the amino acids to peptide-MHC class I molecule binding affinities in the predictive model.

Abstract: In this paper, we propose a class of estimators for the population mean of a sensitive variable, taking account into a generic randomization scheme, under the simple random sampling with replacement (SRSWR), when the mean of a supplementary non-sensitive variable is known. The minimum attainable variance bound of the class is obtained and the best estimator is also defined. We prove that the best estimator acts as a regression estimator which is at least as efficient as the corresponding estimator without the auxiliary variable. A new measure of privacy protection is built, and some models can be compared from the perspective of efficiency and privacy protection.