查看更多>>摘要：Due to existence of different environments and noises, the existing method is difficult to ensure the recognition accuracy of animal sound in low Signal-to-noise (SNR) conditions. To address these problems, we propose a double feature, which consists of projection feature and Local binary pattern variance (LBPV) feature, combined with Random forest (RF) for animal sound recognition. In feature extraction, an operation of projecting is made on spectrogram to generate the projection feature. Meanwhile, LBPV feature is generated by means of accumulating the corresponding variances of all pixels for every Uniform local binary pattern (ULBP) in the spectrogram. Short-time spectral estimation algorithm is used to enhance sound signals in severe mismatched noise conditions. In the experiments, we classify 40 kinds of common animal sounds under different SNRs with rain noise, traffic noise, and wind noise. As the experimental results show, the proposed framework consisting of short-time spectrum estimation, double feature, and RF, can recognize a wide range of animal sounds and still remains a recognition rate over 80％ even under 0dB SNR.
查看更多>>摘要：Cyclic codes as a subclass of linear codes have wide applications in communication systems, consumer electronics and data storage systems, due to their efficient encoding and decoding algorithms. We construct three classes of optimal ternary cyclic codes, which meet some certain bound. The weight distributions of their duals are also completely determined. The results show that their duals have few nonzero weights.
查看更多>>摘要：Leakage of private information including private key has become a threat to the security of computing systems. It has become a common security requirement that a cryptographic scheme should withstand various leakage attacks, including continuous leakage attacks. In order to obtain an Identity-based encryption (IBE) scheme which can keep its original security in the continuous leakage setting, we propose a new construction method of IBE scheme with Chosen-ciphertext attacks (CCA) security, which can tolerate continuous leakage attacks on many private keys of each identity, and whose security is proved based on the hardness of the classical Decisional bilinear Diffie-Hellman (DBDH) assumption in the standard model. The leakage parameter is independent of the plaintext space and has the constant size.
查看更多>>摘要：In a revocable broadcast encryption scheme, the group manager can flexibly set revoked users who cannot decrypt the ciphertext. Many applications of the revocable broadcast encryption have been found in the secure cloud data sharing. An adaptively secure revocable broadcast encryption system with constant ciphertext and private key size under standard assumptions is more suitable for use in the cloud environment. Few existing revocable broadcast encryption schemes meet such a requirement. We propose a revocable broadcast encryption scheme with constant size ciphertext and private key by combining the RSA cryptographic accumulator with an efficient identity based encryption system. We prove it to be adaptively secure under standard assumptions using dual system encryption techniques.
查看更多>>摘要：Keccak is the final winner of SHA-3 competition and it can be used as message authentic codes as well. The basic and balanced divide-and-conquer attacks on Keccak-MAC were proposed by Dinur et al. at Eurocrypt 2015. The idea of cube attacks is used in the two attacks to divide key bits into small portions. By carefully analysing the mappings used in Keccak-MAC, it is found that some cube variables could divide key bits into smaller portions and so better divide-and-conquer attacks are obtained. In order to evaluate the resistance of Keccak-MAC against divide-and-conquer attacks based on cubes, we theoretically analyse the lower bounds of the complexities of divide-and-conquer attacks. It is shown that the lower bounds of the complexities are still not better than those of the conditional cube tester proposed by Senyang Huang et al.. This indicates that Keccak-MAC can resist the divide-and-conquer attack better than the conditional cube tester. We hope that these techniques still could provide some new insights on the future cryptanalysis of Keccak.
查看更多>>摘要：Linear codes with few weighs have many applications in secret sharing. Determining the access structure of the secret sharing scheme based on a linear code is a very difficult problem. We provides a method to construct a class of two-weight torsion codes over finite non-chain ring. We determine the minimal codewords of these torsion codes over the finite non-chain ring. Based on the two-weight codes, we find the access structures of secret sharing schemes.
查看更多>>摘要：Public crisis has the characteristics of suddenness and uncertainty, and it is necessary to combine the knowledge with the experience of other similar situations to make decisions effectively and quickly. This work combines artificial intelligent theory with information technology and brings case-based reasoning to build models consisting of the features of public crisis. We explore the case-representation approach and build a case-based retrieval algorithm. Combining the specificness of Case-based reasoning (CBR) technology in the monitoring of public crisis events, a new case retrieval algorithm for public crisis cases, named as Combined multi-similarity with set of simi-larity matching algorithm based on sememe (CMSBS), is proposed to analyze the cases with high similarity to current case. The CMSBS algorithm considers the structural and semantic similarities between two public crisis cases comprehensively. Simulation experiments are performed to validate the representation method of the knowledge, and the simulation results demonstrate that the CMSBS algorithm has superior performance in the average number of matching cases and matching accuracy rate and can work well in providing reference cases for subsequent events.
查看更多>>摘要：The deficiencies of existing polyp detection methods remain: i) They primarily depend on the manually extracted features and require considerable amounts of preprocessing. ii) Most traditional methods cannot specify the location of the polyps in colonoscopy images, especially for the polyps with variable size. In order to derive the improvement and lift the accuracy, we propose a novel and scalable detection algorithm based on deep neural networks—an improved Faster Region-based Convolutional neural networks (Faster R-CNN)—by increasing the fusion of feature maps at different levels. It can be employed to detect and locate polyps, and even achieve a multi-object task for polyps in the future. The experimental consequences demonstrate that the best version among improved algorithms achieves 97.13％accuracy on the CVC-ClinicDB database, overtaking the previous methods.
查看更多>>摘要：Attribute reduction, also known as feature selection, is a vital application of rough set theory in areas such as machine learning and data mining. With several information systems constantly and dynamically changing in reality, the method of continuing the incremental attribute reduction for these dynamic information systems is the focus of this research. In an incomplete information system, the increasing form of attribute sets is an important form of dynamic change. In this paper, the definition of conditional entropy is first introduced in the incomplete information system, and for the circumstances of the dynamic change of the attribute sets, two types of incremental mechanisms of the matrix and non-matrix forms based on conditional entropy are subsequently proposed. In addition, on the basis of the two incremental mechanisms, the incremental attribute reduction algorithm is given when the attribute set increases dynamically. Finally, the experimental results of the UCI (University of California Irvine) datasets verify that the two proposed incremental algorithms exhibit a superior performance with regard to attribute reduction when compared with the non-incremental attribute reduction algorithm, which in turn is superior to other relative incremental algorithms.
查看更多>>摘要：For the shortcomings of the basic flower pollination algorithm, this paper proposes a differential evolution flower pollination algorithm with dynamic switch probability based on the Weibull distribution. This new algorithm improved the convergence rate and precision. The switch probability is improved by Weibull distribution function combined with the number of iterations. It can balance the relationship between the global pollination and the local pollination to improve the overall optimization performance of the algorithm. Random mutation operator is merged into the global pollination process to increase diversity of the population, enhance the ability of the algorithm's global search and avoid premature convergence. In the process of local pollination, directed mutation and crossover operation of the differential evolution are incorporated, it makes the individual flower position update with the memory function, which can choose the direction of variation reasonably. The use of cross-operation can avoid new solutions crossing the boundary. Convergence rate is improved and the algorithm can approach the global optimal solution continuously. Theoretical analysis proved the convergence and time complexity of the improved algorithm. The simulation results based on the function optimization problem show that the improved algorithm has better performance of optimization, faster convergence speed and higher convergence accuracy.
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