Applied Mechanics and Materials Vols. 58-60

Abstract: Re-design is a new concept based on visual-thinking, which not only emphasis more on apperceive of objects with vision system, but also for the judgment made by it. The thesis discussing for the relationship between the processes of visual-thinking, visual design based on computer and macromedia by tracing of the theories as well as instance of visual communication. The purpose of the paper is to lead the designer go beyond the audient and to recreate new visual forms to express intentions.

Abstract: Training a SVM corresponds to solving a linearly constrained quadratic problem (QP) in a number of variables equal to the number of data points, this optimization problem becoming challenging when the number of data points exceeds few thousands. Because the computational complexity of the existing algorithms is extremely large in case of few thousands support vectors and therefore the SVM QP-problem becomes intractable, several decomposition algorithms that do not make assumptions on the expected number of support vectors have been proposed instead. In this paper we propose a heuristic learning algorithm of gradient type for learning a SVM using linear separable data, and analyze its performance in terms of accuracy and efficiency. In order to evaluate the efficiency of our learning method, several tests were performed against the Platt’s SMO method, and the conclusions are formulated in the final section of the paper.

Abstract: Many power distribution systems have been operated with neutral ineffectively earthed, and earth fault current is no more than a few tens of amperes. Traditional earth fault detection methods based on zero sequence current has poor precision and sensitivity in this case. For improvement, a novel principle for feeder grounding fault protection based on fuzzy clustering algorithms is presented in this paper. First, the historical data are divided into two groups by fuzzy clustering algorithms. The space relative distance among detected pattern and two cluster centers is then calculated to discriminate the faulted feeder. It can detect high impedance grounding faults (HIGF). The scheme has been verified by EMTP simulation, and results show that the proposed scheme always trips all kinds of grounding faults with high sensitivity and robustness in neutral ineffectively earthed power systems (NIEPS).

Abstract: Category-based statistic language model is an important method to solve the problem of sparse data. But there are two bottlenecks about this model: (1) the problem of word clustering, it is hard to find a suitable clustering method that has good performance and not large amount of computation. (2) class based method always lose some prediction ability to adapt the text of different domain. The authors try to solve above problems in this paper. This paper presents a novel definition of word similarity. Based on word similarity, this paper gives the definition of word set similarity. Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance. At the same time, this paper presents a new method to create the vari-gram model.

Abstract: In Insurance industry, data redundancy is an extremely common problem in the population statistics. As a result a satisfactory clustering quality can rarely be obtained with the traditional clustering method. To handle this kind of problems a clustering model based on attributes reduction and SOM neural network was proposed. Using attributes reduction rules redundant information can be easily distinguished and essential attributes effectively located. And therefore the clustering quality can also be improved evidently. Experiments conducted in the H life insurance company show the method can cope with the problems mentioned above effectively.

Abstract: The modular inversion is an essential and the most time consuming arithmetic operation in Elliptic Curve Cryptography (ECC). This paper presents an improved scalable dual-field Montgomery modular inversion algorithm which is based on Kaliski algorithm. It can support the prime number modular inversion algorithm and binary modular inversion algorithm. According to the algorithm, the hardware architecture is designed. The result of experimentation shows that the hardware design is superior to other hardware designs in operation time, circuit area and flexibility.

Abstract: Research on nodes localization in Wireless Sensor Networks (WSN) has been a hot spot in recent years. How to improve the reliability and accuracy of nodes localization is a hard and challenging problem in the area, and is far to be solved satisfactorily. This paper proposes an effective self-adapting localization algorithm in WSN based on optimized RSSI and DV-Distance algorithm. In order to enhance the precision of localization, the presented algorithm introduces an effective method to reduce the error of RSSI-measured distance. The algorithm also uses Small-World-Network theory to help select beacon nodes from localized normal nodes, so as to raise the performance and efficiency. Experimental results show that the algorithm has effectively improved the accuracy, self adaptivity, performance and efficiency of nodes localization in WSN.

Abstract: This paper reviews several current methods of calculating buffer on the basis of pointing out each merits and pitfalls and then introduces Bayesian statistical approach to CCS / BM domain to calculate the size of the project buffer, to overcome that the current method of the buffer calculation is too subjective and the defect on lacking of practical application. In Crystal Ball, we compare the simulation results of implementation process on the benchmark of C&PM, RESM and SM. The results show that the buffer using this method can ensure the stability of the project’s completion probability, and this method has great flexibility.

Abstract: The rapid development of information technology has offered a very good chance for the development of travel industry, there is a great space for travel agencies of our country to apply the internet. Because the conceptions of development and design are backward, tourist products of China’s travel agencies are crude and lack personalities, thus have restricted the development of China’s travel agencies seriously. Aiming at these problems, this paper adopts the methods of induction and systems analysis, has explained the necessities for China’s travel agencies to innovate on tourist products by using the internet, analyzed the problems existing in the tourist products of China’s travel agencies and proposed some corresponding innovative strategies. Finally, such a conclusion has been reached: as long as China’s travel agencies understand fully the existing problems in their tourist products, adopt some corresponding measures, using internet to innovate on their products continuously, then China’s travel agencies will surely get a sustainable and healthy development.

Abstract: This paper analyzed the principle and insufficient of traditional simulated annealing algorithm, and on the basis of the traditional simulated annealing algorithm, this paper used improved simulated annealing algorithm to solve vehicle routing problems. The new algorithm increases memory function, and keeps the current best state to avoid losing current optimal solution while reducing the computation times and accelerating the algorithm speed. The experimental results show that, the algorithm can significantly improve the optimization efficiency, and has faster convergence speed than traditional simulated annealing algorithm.