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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Feng Dai Youqiang Zhang Yike Ma Hongliang Li Qiang Zhao Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

Saliency prediction is an important way to understand human's behavior and has a wide range of applications. Although lots of algorithms have been designed to predict saliency for planar images, there are few works for 360° images. In this paper, we propose an encoder-decoder network for panoramic image saliency prediction. Dilated convolutional layers are deployed in the network, which can extract more representative features and improve the accuracy of saliency prediction. To deal with the image distortions in 360° images, our network takes cube map format as input and processes six faces of cube map simultaneously. Respecting the saliency distribution of ground truth, we also propose a new data augmentation method to train the network, which is validated to be helpful for performance improvement. Extensive experiments show that our method gives new state-of-the-art results on 360° image saliency prediction.

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Dynamic analysis of high-dimensional fractional-order gene regulation networks with time delay

Dynamic analysis of high-dimensional fractional-order gene r...

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第三十九届中国控制会议

作者： Zhe Zhang Can Ding Jing Zhang Feng Liu Yingjie Zhang FanyongCheng College of Electrical and Information Engineering Hunan University School of Automation China University of Geosciences College of Computer Science and Electronic Engineering Hunan University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University

This paper mainly analyzes the stability of high-dimensional fractional-order gene regulatory network systems with time *** on the judgment of eigenvalues,this paper proposes sufficient information about the stability of high-dimensional fractional-order gene regulatory network systems with time ***,and by analyzing the characteristic equations,the bifurcation conditions of the high-dimensional fractional-order gene regulatory network system with time delay are ***,the theoretical part of this paper is verified by numerical simulation.

关键词： Gene regulatory network system Stability analysis Dynamic analysis Time delay

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Multi-level feature fusion model-based real-time person re-identification for forensics

Multi-level feature fusion model-based real-time person re-i...

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作者： Wang, Shiqin Xu, Xin Liu, Lei Tian, Jing School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan430065 China Artificial Intelligence Institute Wuhan University of Science and Technology Wuhan430065 China Institute of Systems Science National University of Singapore Singapore119615 Singapore

Person forensics aims to retrieve the specified person across non-overlapping cameras. It is difficult owing to the appearance variations caused by occlusion, human pose change, background clutter, illumination variation, etc. In this scenario, current models face great challenges in extracting effective features. Recent deep learning models mainly focus on extracting representative deep features to cope with appearance variations, while handcrafted features are not fully explored. In this paper, a multi-level feature fusion model (MFFM) is designed to combine both deep features and handcrafted features in real time. MFFM is first utilized to describe person appearance. Then, local binary pattern (LBP) and histogram of oriented gradient (HOG) are extracted to cope with geometric change and illumination variance. Using LBP and HOG, 11.89% on the CUHK03, 15.30% on the Market-1501 and 8.25% on the VIPeR top-1 recognition accuracy improvement for the proposed method are achieved with only 9.66%, 4.90%, and 7.59% extra processing time. Experimental results indicate MFFM can achieve the best performance compared to the state-of-the-art models on the Market1501, CUHK03, and VIPeR datasets. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Local binary pattern

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Corrigendum to "Hybridization chain reaction circuit controller: CRISPR/Cas12a conversion amplifier for miRNA-21 sensitive detection" [Talanta 266 (2024) 125130]

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Talanta 2024年 269卷 125395页

作者： keyi Long Gaihua Cao Yue Qiu Nannan Yang Jian Che Mei Yang Changjun Hou Danqun Huo Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Chongqing University Three Gorges Hospital Chongqing 404000 PR China. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Electronic address: yangmei@***. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing School of Microelectronics and Communication Engineering Chongqing University Chongqing 400044 PR China. Electronic address: houcj@***. Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing 400044 PR China. Electronic address: huodq@***.

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Edge corona product as an approach to modeling complex simplical networks

arXiv

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arXiv 2020年

作者： Wang, Yucheng Yi, Yuhao Xu, Wanyue Zhang, Zhongzhi Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China Shanghai Blockchain Engineering Research Center Shanghai200433 China

Many graph products have been applied to generate complex networks with striking properties observed in real-world systems. In this paper, we propose a simple generative model for simplicial networks by iteratively using edge corona product. We present a comprehensive analysis of the structural properties of the network model, including degree distribution, diameter, clustering coefficient, as well as distribution of clique sizes, obtaining explicit expressions for these relevant quantities, which agree with the behaviors found in diverse real networks. Moreover, we obtain exact expressions for all the eigenvalues and their associated multiplicities of the normalized Laplacian matrix, based on which we derive explicit formulas for mixing time, mean hitting time and the number of spanning trees. Thus, as previous models generated by other graph products, our model is also an exactly solvable one, whose structural properties can be analytically treated. More interestingly, the expressions for the spectra of our model are also exactly determined, which is sharp contrast to previous models whose spectra can only be given recursively at most. This advantage makes our model a good test-bed and an ideal substrate network for studying dynamical processes, especially those closely related to the spectra of normalized Laplacian matrix, in order to uncover the influences of simplicial structure on these processes. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

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Wavelet packet coefficient of transient first half wave line selection method for single-phase grounding fault

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IOP Conference Series: Earth and Environmental Science 2022年第1期983卷

作者： Jing Gong School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044 China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044 China

Overvoltage will occur after single-phase grounding fault in distribution network, endangering system insulation. It is of great significance to find out the fault line as soon as possible to ensure the safe operation of the system. Wavelet modulus maxima can be used to detect the sudden change singularity of transient current. However, the judgement of single mode maximum value is easily influenced by the form of fault and interference, leading to misjudgement. In this paper, the transient characteristics of single-phase grounding fault are analyzed, and the magnitude and phase characteristics of the first half wave are given; Based on wavelet packet algorithm, several key problems such as boundary effect, wavelet selection and decomposition scale are explored; Taking the zero sequence voltage as the reference to determine the fault interval, the zero sequence current of each line is decomposed by three-scale wavelet packet using db6 wavelet, and the wavelet coefficients of the characteristic frequency band are extracted for comparison. The fault line is the one with the largest amplitude and different phase from others. The distribution system model of neutral grounding through arc suppression coil is built. Simulation is carried out for several cases with great difficulty in line selection, such as short circuit when phase voltage crosses zero, high resistance grounding and long line fault. The experimental results prove the reliability of this method.

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Contrastive Learning for Robust Android Malware Familial Classification

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IEEE Transactions on Dependable and Secure Computing 2022年 1-14页

作者： Wu, Yueming Dou, Shihan Zou, Deqing Yang, Wei Qiang, Weizhong Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China University of Texas at Dallas Dallas USA National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfuscated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware family analysis can be achieved through contrastive learning. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and other types of malware. Based on the proposed analysis, we design a system that can achieve robust and interpretable classification of Android malware. To achieve robust classification, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classification, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps can be obtained by visualization techniques. These heatmaps can help users understand why the malware is classified as this family. We implement IFDroid and perform extensive evaluations on two datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classification systems. Moreover, IFDroid is capable of maintaining a 98.4% F1 on classifying 69,421 obfuscated malware samples. IEEE

关键词： Semantics

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Particle swarm optimization based on weighted aggregation degree and adaptive decision

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第1期82卷 231-240页

作者： Wan, Renxia Zhu, Lijun Liu, Kai Chen, Ruidian Ningxia Key Laboratory of Intelligent Information and Big Data Processing North Minzu University China College of Mathematics and Information Science North Minzu University China Mathematics’ Group Pinghu College China Fujian Hongyang Software co. LTD China

In response to the problem that particle swarm optimization algorithm (PSO) is prone to falling into local optimum and premature convergence in later operations, this paper reconstructs the concept of weighted aggregation based on a redefined similarity to describe the degree of diversity of the population, and adjusts the particle searching space with an adaptive decision to improve the global searching ability of PSO. Optimization ability, convergence speed and stability of the particle swarm algorithm are finally effectively improved. The experimental analysis further shows the effectiveness of the algorithm. © 2020, Politechnica university of Bucharest. All rights reserved.

关键词： Agglomeration

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The Research of G-Chain Transitive and G-Chain Mixing on the Hyperspace of Topological Group Action

The Research of G-Chain Transitive and G-Chain Mixing on the...

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International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Ji Zhan-Jiang Shi Wei School of Information and Electronic Engineering Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University China Party Committee Office Wuzhou Vocational College China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

G-chain transitive and G-chain mixing have an important significance in terms of theory and application. According to the definition of chain transitive and chain mixing, we give the concept of G-chain transitiveand G-chain mixing in this paper. By inference, some conclusions of the hyperspace were extended to the hyperspace of topological group action. We have the following result: (1)Letbe the hyperspace of. Ifis a G-chain transitive map, thenis a G-chain transitive map; (2)Letbe the hyperspace of. Ifis a G-chain mixing map, thenis a G-chain mixing map; (3)Letbe the hyperspace ofandbe a equivariant map. All non-empty open set are invariable for. Thenis a G-exact map if and only ifis a G-exact map. These results enriched the theory of the G-chain transitive and G-chain mixing on the hyperspace of topological group action.

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Influence of wavelet characteristics on single-phase grounding fault line selection

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IOP Conference Series: Earth and Environmental Science 2022年第1期983卷

It is difficult to select the fault line in distribution network because of the small single-phase grounding fault current. Wavelet transform is especially suitable for fault transient analysis because of its unique time-frequency localization performance. However, the characteristics of different wavelets have a direct impact on the line selection results. Improper selection of wavelets will directly lead to misjudgment. Firstly, the transient characteristics of single-phase grounding fault and the relationship between wavelet transform modulus maxima and singularity are analysed, and the line selection criterion of wavelet modulus maxima is given. Then, the influence of wavelet vanishing moment order, support length, symmetry, and orthogonality on the detection effect of signal singularity is analysed, and four principles for selecting wavelet in fault line selection are proposed. The larger the order of vanishing moment and support length, the more conducive to detection. The influence of vanishing moment order is much greater than that of support length. The 10kV system simulation model is built, five representative wavelets are selected to decompose the zero- sequence current of the fault line in four scales respectively, and the different modulus maxima corresponding to the sudden change point are compared. The experimental results prove the reliability of the wavelet selection principles proposed in this paper.

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