Applied Mechanics and Materials Vols. 513-517

Abstract: Semantic feature modeling is a new trend of CAD technology. It is very important for modifying and editing models automatically and semi-automatically. In this paper, a semantic feature modeling method is proposed, in which geometric constraints of models are solved. The new method is history-independent. At the same time, the architecture of semantic feature modeling is given. According to the principles of 3 dimensional rigid bodies, basic geometric constraints can be expressed. Experiment results show an instance modeled by the proposed method.

Abstract: In existed distributed edge extraction method based on MapReduce, the inappropriate dataset split algorithms leaded to the loss problem of image features in result. We presented a distributed computing platform called Split Process Cluster (SPC) to resolve this problem. In SPC, the images are partitioned with the resilient image pyramid model (RIP), a multi-layer and redundant data structure we presented earlier, to ensure the integrity of original image features. And SPC packages the image data to the form of Key-Value pairs, which could be processed through Hadoop, and reduces the results with density-based spatial clustering of applications with noise (DBSCAN) algorithm. Compared to traditional method, the extraction rate of image feature by using SPC has been improved, which indicates that using SPC is an efficient way to improve the extraction rate of distributed edge extraction.

Abstract: Ciphertext-Policy Attribute-based encryption (CP-ABE) mechanism is an extension of attribute-based encryption which associates the ciphertext and user's private key with the attribute by taking the attribute as a public key. It makes the representation of the access control policy more flexible, thus greatly reduces the network bandwidth and processing overhead of sending node brought by fine-grained access control of data sharing. According to the principle of CP-ABE encryption mechanism for this mechanism, an improved cloud computing-based encryption algorithm was proposed in this paper to overcome the deficiencies of permission changing process under the massive data. Experimental results show that compared with traditional methods, the new mechanism significantly reduces time-consuming.

Abstract: With the application of Ethernet communication architecture in electric power telecontrol communication, new requirements of information security have been put forward based on Manufacturing Message Specification (MMS). IEC62351 standard makes two clear security requirements for MMS, which is confidentiality and integrity. Taking into consideration the increasing costs if one algorithm corresponds to one security requirement, this paper designs a MMS-based security message format, applying AES-CCM encryption algorithm to satisfy various safety demands and analyzes algorithms time costs as well as benefits with an example of authenticated encryption mode. Analysis shows that security and interoperability of telecontrol communication can be improved to a large extent using different modes of AES-CCM algorithm for security message transmission under distinct security requirements.

Abstract: The problems of difference of nodes capabilities and the unevenly-distributed bandwidth of the network, widespread exist in the heterogeneous clouding environment. Together with the users randomness of submitting jobs, the problems above lead to server synchronization problems.Under the platform of Hadoop and the situations mentioned above, we come up with a method which is based on the native hadoop speculative algorithm to solve the problems. Through monitoring the load-balance in realtime, dynamically assessing the performance of the node and making the speculative tasks happened in high-performance node which meantime is the nearest node from input split, the algorithm effectively reduces the occupation of the network and accelerates executing speed. The experiment result shows that the method in the execution of which the speculative tasks has a high ratio, significantly improved the efficiency and throughput of the cluster.

Abstract: In order to grasp the security situation of the network accurately and provide effective information for managers of network.GeesePSOSEN-SVM algorithm is proposed in this paper. It can produce and train multiple independent SVM through Bootstrap method and increase the degree of difference among SVM based on learning theories of negative correlation to construct the fitness function.GeesePSO algorithm is used to calculate the optimal weights of SVM.The algorithm chooses the high weights of SVM to integrate. At last, through the experiment on MATLAB for network security situational prediction,the results show that the absolute prediction error is smaller ,and the right trend rate is higher.

Abstract: The network cascade topology structure of large logistics supply chain and its invulnerability were researched. Logistics supply chain is the combination set of entities such as warehouse, highway, railway, aviation, etc. And its stability of network structure determined the survival and development of the user in the network and supply chain. In order to improve the stability and robustness of logistics supply chain network, an improved cascaded topology structure of large logistics supply chain network with Internet of things in complex environment was proposed based on metric uniform random distribution, and cascading invulnerability of mathematical analysis model was proposed. The probability distribution and critical value of logistics and supply chain network cascading failure was solved in complex environment, and the logistics supply chain network paralysis and damage problems were analyzed from the view of probability and critical value analysis. Take the intelligent car supply chain as the example, simulation result shows that the invulnerability analysis effect is perfect, and the cascading invulnerability critical value is solved precisely, research results provide important theoretical support to realize the intelligent logistic management, it has good application value in the research of logistics supply chain network security and stability.

Abstract: This paper mainly discusses task scheduling for multiprocessors. Application requires higher performance of the multiprocessors task scheduling systems. The traditional algorithms majorly consider the accuracy and neglect the real-time performance. In order to improve the real-time performance while maintaining the accuracy, the paper proposes a task scheduling algorithm (GA-ACO) for multiprocessors based on improved neural network. It first builds mathematical models for task scheduling of multiprocessor systems, and then introduces genetic algorithms to quickly find feasible solutions. The simulation results show that the improved neural network algorithm not only has the global optimization ability of genetic algorithm, but also has both local search and the positive feedback capabilities of neural networks; compared with single optimization algorithm, it can quickly find the task scheduling solutions to meet real-time requirements, accelerate the speed of execution of the task, furthermore achieve reasonable, effective task allocation and scheduling for multi-processor.

Abstract: Convergence of unsteady classification model with data fluctuations has strong application value. This paper models the mathematical problem to verify the feasibility and finite convergence of unsteady classification model with data fluctuations, and verifies the feasibility and limited convergence of the model by convex optimization KKT equivalent conditions from different perspectives. Experiments validate the three real data sets collected, and results show that the proposed model is feasible and finite convergence.

Abstract: Given two tubes with non-coplanar axes whose sections are circle, we acquire that axes of the tubes can be smoothly blent by Bezier curve. In this situation, the paper proposes a new method to build the blending surface by generalized Bezier tube. Meantime, we obtain smoothly blending parameter surface.