Secure Multi-party Computation (SMC) plays an important role in information security under the circumstance of cooperation calculation, so SMC on privacy-preservation is of great interest. In this paper we discuss an ...
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Secure Multi-party Computation (SMC) plays an important role in information security under the circumstance of cooperation calculation, so SMC on privacy-preservation is of great interest. In this paper we discuss an issue which is a special SMC problem. Based on Scalar Product Protocol, Monte Carlo Method and Oblivious Transfer, we give two solutions to the problem about how to decide the areas. That is, a polygon is divided into two parts by a line: S 1 and S 2 . Furthermore, we analyze the security and computational complexity, as well as the comparison of these two protocols. The results of analysis show that the proposed protocols are secure and efficient. We believe the two protocols will be useful in other geometric and combinatorial problems.
In the real world, images always have several visual objects instead of only one, which makes it difficult for conventional object recognition methods to deal with them. In this paper, we present a topologically sorte...
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Space time adaptive processing (STAP) can be used to remove hostile jammers interfering for Global Positioning System (GPS) receivers, especially in the presence of jammer multipath. However, the STAP filter can bring...
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Data indexing is common in data mining when working with high-dimensional, large-scale data sets. Hadoop, a cloud computing project using the MapReduce framework in Java, has become of significant interest in distribu...
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Technique of space-time adaptive processing (STAP), which is usually employed by airborne radar to reject the ground clutter and jamming and at the same time, detect the ground moving targets, can not estimate the spa...
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In our real world, there usually exist several different objects in one image, which brings intractable challenges to the traditional pattern recognition methods to classify the images. In this paper, we introduce a C...
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This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet d...
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This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet decomposition technique with the grayscale integral projection technique. And then, the attribute reduction algorithm based on FRST is applied in face recognition. The reduction algorithm based on FRST can eliminate the redundant features of sample dataset and reduce the space dimension of the sample data. The proposed method avoids losing of information caused by dispersing before original rough set attribute reduction. Experimental results show that it can improve the classification accuracy in face recognition as compared with the method using the original rough set.
Along with the expansion and in-depth of the application domain of cluster analysis, one kind of new cluster algorithm called Spectral Clustering algorithm has been aroused great concern by scholars, Spectral Clusteri...
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Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locat...
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Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.
Attribute reduction is a basic issue in rough set theory. But related researches on reduction in inconsistent incomplete decision system (IIDS) are currently rarely reported. In this paper, the concept of assignment r...
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