The simulation of crowd evacuation has a great significance. It contributes to the formulation of corresponding contingency plans, guides the design of the scene, as well as can prevent or reduce the casualties in eme...
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Crowd simulation system can provide fundamental guide on crowd behaviors in real life. For instance, it can be applied to emergency evacuation of large public places to reduce casualties and property losses. However, ...
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With the rapid development of economy and society, public activities are increased significantly. Since these situations involved growing security threats, it is of great importance to create emergency plan. In order ...
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Reliable broadcasting for a network can be obtained by using completely independent spanning trees(CISTs). Locally twisted cubes are popular networks which have been studied widely in the literature. In this paper, we...
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ISBN:
(纸本)9781467393010
Reliable broadcasting for a network can be obtained by using completely independent spanning trees(CISTs). Locally twisted cubes are popular networks which have been studied widely in the literature. In this paper, we study the problem of using CISTs to establish reliable broadcasting in locally twisted cubes. We first propose an algorithm, named LTQCIST, to construct two CISTs in locally twisted cubes, then exemplify the construction procedures to construct CISTs. Finally, we prove the correctness of Algorithm LTQCIST and simulate CISTs with JUNG.
Data integrity is the prime concern for users to consider whether to use cloud storage services or not. And data integrity verification is not only an effective measure for users to detect their stored data whether se...
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This paper researched an improved digital video watermarking algorithm based on relationship. The algorithm combines the video processing and video coding compression principle which adopts improved Arnold algorithm a...
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The nonlocal estimation has been widely used in image processing for its effectiveness. Based on the nonlocal self-similarity of natural images, this paper presents an iterative interpolation method for image zooming....
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Recent studies have shown that utilizing a mobile sink to harvest and carry data from wireless sensor network (WSN) can enhance network operations and balance the network energy consumption. Because of the sink mobili...
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ISBN:
(纸本)9781467370066
Recent studies have shown that utilizing a mobile sink to harvest and carry data from wireless sensor network (WSN) can enhance network operations and balance the network energy consumption. Because of the sink mobility, the paths between the sensor nodes and the sink change frequently, and have profound influence on the lifetime of WSN. To find an efficient protocol that can maintain the routes between the mobile sink and nodes with few network resources are important. We propose a swarm intelligent algorithm based route maintaining protocol in this paper to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction, and the optimal routing selection to maintain the data delivery route. Using the immune based artificial bee colony (IABC) algorithm to optimize the forwarding path, the protocol could find an alternative path efficiently when sink moves. The results of our experiments demonstrate that the protocol could balance the network traffic load.
Aiming at the disadvantages of basic Cultural Algorithms (CA) like being trapped easily into a local optimum, this paper improves the basic Cultural Algorithms and proposes the improved cultural algorithm with adaptiv...
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This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as...
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ISBN:
(纸本)9781479919611
This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
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