We introduce a new logic programming paradigm-answer set programming with uncertain facts (LPuF for short). A LPuF program is an extension of answer set programs (ASP for short). We first define the syntax of LPuF pro...
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The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditiona...
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The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditional algorithms. The purpose of this paper is to develop a novel algorithm of packet matching based on improving differential evolutionary algorithm, which also combines with classic packets matching algorithms to improve the performance of algorithm. For the sake of objectivity, the statistics method was used to compute the fitting value. Experiments showed that this new algorithm effectively improved the performance in the speed and storage space, as compared with the traditional one. For the first time, evolutionary algorithm is used to solve the network data packet forwarding, and packets can be forwarded at the linear speed. In addition, this new algorithm is universal, so it can be adapted for many equipment.
Cloud computing will be a main informa- tion infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for c...
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Cloud computing will be a main informa- tion infrastructure in the future; it consists of many large datacenters which are usually geographically distributed and heterogeneous. How to design a secure data access for cloud computing platform is a big challenge. In this paper, we propose a secure data access scheme based on identity-based encryption and biometric authentication for cloud computing. Firstly, we describe the security concern of cloud computing and then propose an integrated data access scheme for cloud computing, the procedure of the proposed scheme include parameter setup, key distribu- tion, feature template creation, cloud data processing and secure data access control. Finally, we compare the pro- posed scheme with other schemes through comprehensive analysis and simulation. The results show that the pro- posed data access scheme is feasible and secure for cloud computing.
The problem that the localization accuracy of unknown nodes is not high in DV-Hop localization algorithm is about to be solved. According to this algorithm deficiency, an improved DV-Hop localization algorithm is prop...
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The problem that the localization accuracy of unknown nodes is not high in DV-Hop localization algorithm is about to be solved. According to this algorithm deficiency, an improved DV-Hop localization algorithm is proposed which was based on corrected the average hop distance error correction value δ to modify the average hop distance, to reduce the deviation between the average hop distance and the true average hop distance. Finally, the average hop distance of the traditional DV-Hop algorithm is modified effectively. Simulation results show that, the improved algorithm has reduced the average localization error of unknown nodes, improved the localization accuracy, and not require additional hardware.
To explore the association relations among disease, pathogenesis, physician, symptoms and drug, we adapt a variational Apriori algorithm for discovering association rules on a dataset of the Qing Court Medical Records...
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Independent component analysis (ICA), instead of the traditional discrete cosine transform (DCT), is often used to project log Mel spectrum in robust speech feature extraction. The paper proposed using symmetric ortho...
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Recommending suitable routes to taxi drivers for picking up passengers is helpful to raise their incomes and reduce the gasoline consumption. In this paper, a pick-up tree based route recommender system is proposed to...
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Image segmentation evaluation is still a hotspot problem. Various methods of image segmentation evaluation have been proposed. Amongst all the evaluation approaches, Segmentation Entropy Quantitative Assessment (SEQA)...
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Image segmentation evaluation is still a hotspot problem. Various methods of image segmentation evaluation have been proposed. Amongst all the evaluation approaches, Segmentation Entropy Quantitative Assessment (SEQA) is one of the most popular methods. In this paper, segmentation entropy is proposed. In experiments, some standard images which are segmented by multi-level thresholds are tested and used to conclude the characteristics of SEQA, including its application conditions, advantages and disadvantages in image segmentation evaluation.
Link Detection (abbr. LDT) is to determine whether two stories discuss the same topic in Topic Detection and Tracking (abbr. TDT) track. The key issue is to correctly measure the relevance between two stories. Most re...
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Link Detection (abbr. LDT) is to determine whether two stories discuss the same topic in Topic Detection and Tracking (abbr. TDT) track. The key issue is to correctly measure the relevance between two stories. Most researches on LDT use a series of independent words to describe stories (each story is a text specially discussing news), and the relevance between two stories is determined based on the percentage and weight of overlapping words between them. Although substantial improvement has been achieved, inadequate descriptions of word sense and semantics still have negative influences on the accuracy of LDT. In this paper we propose an online semantic tree, which is hierarchically constructed by the most relevant words extracted from previous story streams. In online semantic tree, word sense is described by a series of words in a sense closed-loop, and semantic relation among words is measured by depth and width of level that words locate in. In LDT, online semantic tree is built for each story, and the relevance between two stories is determined by measuring the KL divergence between their online semantic trees. The method performs quite well on TDT4 corpus. The Min Norm CDet of the method in testing is 0.2274 lower than that of the baseline.
Image segmentation is still a crucial problem in image processing. It hasn yet been solved very well. In this study, we propose a novel multi-level thresholding image segmentation method based on PSNR using artificial...
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