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arXiv 2019年

作者： Wei, Zhipeng Chen, Jingjing Wei, Xingxing Jiang, Linxi Chua, Tat-Seng Zhou, Fengfeng Jiang, Yu-Gang Jilin University Fudan University Beihang University National University of Singapore Health Informatics Lab College of Computer Science and Technology Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin130012 China

We study the problem of attacking video recognition models in the black-box setting, where the model information is unknown and the adversary can only make queries to detect the predicted top-1 class and its probability. Compared with the black-box attack on images, attacking videos is more challenging as the computation cost for searching the adversarial perturbations on a video is much higher due to its high dimensionality. To overcome this challenge, we propose a heuristic black-box attack model that generates adversarial perturbations only on the selected frames and regions. More specifically, a heuristic-based algorithm is proposed to measure the importance of each frame in the video towards generating the adversarial examples. Based on the frames’ importance, the proposed algorithm heuristically searches a subset of frames where the generated adversarial example has strong adversarial attack ability while keeps the perturbations lower than the given bound. Besides, to further boost the attack efficiency, we propose to generate the perturbations only on the salient regions of the selected frames. In this way, the generated perturbations are sparse in both temporal and spatial domains. Experimental results of attacking two mainstream video recognition methods on the UCF-101 dataset and the HMDB-51 dataset demonstrate that the proposed heuristic black-box adversarial attack method can significantly reduce the computation cost and lead to more than 28% reduction in query numbers for the untargeted attack on both datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Heuristic methods

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Ordered proposition fusion based on consistency and uncertainty measurements

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Science China(Information Sciences) 2017年第8期60卷 117-135页

作者： Dayou LIU Yungang ZHU Ni NI Jie LIU College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Beijing Entry-Exit Inspection and Quarantine Bureau

The fusion of ordered propositions is an important and widespread problem in artificial intelligence,but existing fusion methods have difficulty handling the fusion of ordered propositions. In this paper, we propose a solution based on consistency and uncertainty measurements. The main contributions of this paper are as follows. First, we propose the concept of convexity degree, mean, and center of basic support function to comprehensively describe the basic support function of ordered propositions. Second, we introduce entropy as a measure of uncertainty in the basic support function of ordered propositions. Third, we generalize the indeterminacy of the basic support function and propose a novel method to measure the consistency between two basic support functions. Finally, based on the above researches, we propose a novel algorithm for fusing ordered propositions. Theoretical analysis and experimental results demonstrate that the proposed method outperforms state-of-the-art methods.

关键词： uncertainty processing ordered proposition evidence theory dempster rule of combination information fusion

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Efficient zonal diagnosis with maximum satisfiability

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Science China(Information Sciences) 2018年第11期61卷 17-30页

作者： Meng LIU Dantong OUYANG Shaowei CAI Liming ZHANG College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of EducationJilin University State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences

Model-based diagnosis(MBD) has been widely acknowledged as an effective diagnosis ***, for large scale circuits, it is difficult to find all cardinality-minimal diagnoses within a reasonable time. This paper proposes a novel method that takes a significant step in this direction. The idea is to divide a circuit into zones and compute the cardinality-minimal diagnoses by finding subset-minimal diagnoses with cardinality-minimal via a maximum satisfiability(MaxSAT) solver on an abstracted circuit that is composed of these zones instead of all components. We also propose a new propagate-extend method for extending the seed-TLDs to obtain all cardinality-minimal diagnoses efficiently. We implement our method with a state-of-the-art core-guided MaxSAT solver, and present evidence that it significantly improves the diagnosis efficiency on ISCAS-85 circuits. Our method outperforms SATbD, which was recently shown to outperform most complete MBD approaches using satisfiability(SAT).

关键词： model-based diagnosis MaxS AT subset-minimal diagnoses cardinality-minimal diagnoses zone propagate-extend

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Detection of Glue Spray on Bottom of Vehicle Based on Machine Vision

Detection of Glue Spray on Bottom of Vehicle Based on Machin...

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2018 International Conference on Network, Communication, Computer engineering (NCCE 2018)

作者： Dongyang Liu Jindong Zhang Xiaofeng Zhang Xiaoyu Ma Yuxin Kou College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University College of Software Jilin University

ISBN: (纸本)9781510871076

With the continuous development of machine vision,intelligent detection of bottom spray glue has gradually become a *** this paper,we proposed an algorithm of detection the glue spray on bottom of vehicle based on machine *** sampling and detecting the spray interest area,the algorithm can obtain its features which were used for intelligent identification of the spray interest area,and then carry out the pseudo target and detect whether the detection area is complete or *** can test the vehicles on pipeline in real *** the average,each frame's processing time is less than 150 *** there is an unqualified area,it will alarm and inform the operators of the wrong *** algorithm can improve the quality of the vehicle and save human resources and identify the spray interest area with high *** research directions in the future is to accelerate the speed to meet the practical application requirements,and to solve the intelligent identification of the spray interest area which has the same color with the vehicle body.

关键词： Glue spray Machine vision intelligent detection

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The vehicle audio encryption system based on scrambling thought

The vehicle audio encryption system based on scrambling thou...

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2018 International Conference on Network, Communication, Computer engineering (NCCE 2018)

作者： Peibin Wu Jindong Zhang Yang Liu Dongqi Han Yiding Sun College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University State Key Laboratory of Automobile Simulation and Control Jilin University

ISBN: (纸本)9781510871076

In this paper,the vehicle audio encryption system based on scrambling thought and applied to vehicle-mounted media is *** pseudo random number is generated each time it is encrypted,and it is substituted into the Fibonacci transform to generate a key with variable *** audio data is divided by the number of pseudo random numbers into the Fibonacci sequence,and is encrypted in permutation *** Fibonacci transform has symmetry and creates an audio file that cannot be parsed and played after the permutation *** the security analysis of encryption algorithm,the audio files of different length are *** key space,anti-attack ability,key sensitivity and other indicators are tested to achieve good *** addition,this algorithm is simple in calculation and can realize the ideal real-time performance in practical application.

关键词： vehicle media audio encryption scrambling thought security analysis

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Live Video Streaming Authentication for Vehicle Multimedia based on Merkle Tree

Live Video Streaming Authentication for Vehicle Multimedia b...

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2018 International Conference on Network, Communication, Computer engineering (NCCE 2018)

作者： Dongqi Han Jindong Zhang Yang Liu Peibin Wu Yiding Sun College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University State Key Laboratory of Automobile Simulation and Control Jilin University

ISBN: (纸本)9781510871076

Merkle tree has been widely applied in the field of P2 P *** this paper,an efficient authentication scheme is proposed in the integrity check module for vehicle live video streaming system by optimizing the construction and verification of the Merkle *** can create and check nodes at the same time in a shorter time without trusted *** the same time,in order to prevent the oversensitivity of hash algorithm,this paper uses the perceptual hash algorithm to generate the hash value of nodes in the Merkle *** performance evaluation and analysis,our algorithm can build a Merkle tree with 2 N-1 nodes only after the N+log2 N times hash *** has better time performance than the traditional tree,whether receiving attacks or *** it is proved that the scheme is secure under the condition that the vehicle live video streaming system is safe.

关键词： vehicle streaming media system Merkle tree P2P-streaming integrity authentication perceptual hash algorithm

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Multi-Classification of Cancer Samples Based on Co-Expression Analyses

Multi-Classification of Cancer Samples Based on Co-Expressio...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Hongyang Jiang Qiang Huang Liang Chen Zhi Li Ying Xu Huiyan Sun Yi Chang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China College of Engineering Key Laboratory of Intelligent ManufacturingTechnology of Ministry of Education Shantou University Shantou China Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province The First Hospital of China Medical University Shenyang China The China-Japan Union Hospital Cancer Systems Biology Center Jilin University Changchun China The China-Japan Union Hospital School of Artificial Intelligence Cancer Systems Biology Center Jilin University Changchun China School of Artificial Intelligence Jilin University Changchun China

Cancer staging, grading and subtyping all represent important problems for precision diagnosis, treatment and mechanistic studies of cancer. The majority of the existing computational methods solve this problem via multi-classification of differential gene-expressions of cancer samples of specific classes (Stages, Grades and subtypes) vs. controls. However, the performance of such classification techniques is generally not satisfactory since the discerning power of differential expression patterns in such classifications is limited. We present here a multi-classification technique, based on co-expression patterns specific to individual subclasses in provided training data as co-expression patterns tend to be more conserved than differential expressions within each subclass. A challenge in implementing this strategy lies in how to effectively derive co-expression patterns in individual samples, which is solved through comparing co-expression patterns within a subclass and those in the subclass plus a new sample. Compared with the state-of-the-art gene expression-based classification methods, our method outperforms them in cancer staging, grading and subtyping of cancer samples from TCGA in almost all the measures used. In addition, the co-expressed genes computationally selected for classifications are biologically meaningful, which will prove important for diagnostic biomarker design, treatment plan selection and possibly mechanistic studies of cancer.

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An improved fruit fly optimization algorithm for solving traveling salesman problem

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Frontiers of Information Technology & Electronic engineering 2017年第10期18卷 1525-1533页

作者： Lan HUANG Gui-chao WANG Tian BAI Zhe WANG College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering (Jilin University) Ministry of Education Changchun 130012 China

The traveling salesman problem(TSP), a typical non-deterministic polynomial(NP) hard problem, has been used in many engineering applications. As a new swarm-intelligence optimization algorithm, the fruit fly optimization algorithm(FOA) is used to solve TSP, since it has the advantages of being easy to understand and having a simple implementation. However, it has problems, including a slow convergence rate for the algorithm, easily falling into the local optimum, and an insufficient optimization precision. To address TSP effectively, three improvements are proposed in this paper to improve FOA. First, the vision search process is reinforced in the foraging behavior of fruit flies to improve the convergence rate of FOA. Second, an elimination mechanism is added to FOA to increase the diversity. Third, a reverse operator and a multiplication operator are proposed. They are performed on the solution sequence in the fruit fly's smell search and vision search processes, respectively. In the experiment, 10 benchmarks selected from TSPLIB are tested. The results show that the improved FOA outperforms other alternatives in terms of the convergence rate and precision.

关键词： Traveling salesman problem Fruit fly optimization algorithm Elimination mechanism Vision search Operator

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Topology-Aware Task Allocation for Distributed Stream Processing with Latency Guarantee

Topology-Aware Task Allocation for Distributed Stream Proces...

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作者： Xiaohui Wei Xun Wei Hongliang Li Yuan Zhuang Hengshan Yue College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education

Nowadays it becomes more and more critical to process the increasingly large amounts of data in timely *** order to meet this requirement and ensure the reliable processing of streaming data,a variety of distributed stream processing architectures and platforms have been developed,which handles the fundamental task of allocating processing tasks to the currently available physical resources and routing streaming data between these ***,many stream processing systems lack an intelligent scheduling mechanism,in which their default schedulers allocate tasks without taking resource demands and availability,or the transfer latency between resources into *** stream processing has a strict request for *** it's important to give latency guarantee for distributed stream *** this paper,we propose a new algorithm for stream processing with latency guarantee,the algorithm both consider transfer latency and resource demand in the process of task *** experiments verify the correctness and effectiveness of our *** the condition of satisfying the latency constraints,the heuristic algorithm AHA on average,reduce more than 21.3% and 58.9% resources compared with the greedy and the round-robin algorithms.

关键词： Distributed stream processing Task allocation Transfer latency

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A Layered Co-evolution Based Rough Feature Selection Using Adaptive Neighborhood Radius Hierarchy and Its Application in 3D-MRI

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Chinese Journal of Electronics 2017年第6期26卷 1168-1176页

作者： DING Weiping GUAN Zhijin WANG Jiehua TIAN Di School of Computer Science and Technology Nantong University State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology

As the conventional feature selection algorithms are prone to the poor running efficiency in largescale datasets with interacting features, this paper aims at proposing a novel rough feature selection algorithm whose innovation centers on the layered co-evolutionary strategy with neighborhood radius hierarchy. This hierarchy can adapt the rough feature scales among different layers as well as produce the reasonable decompositions through exploiting any correlation and interdependency among feature subsets. Both neighborhood interaction within layer and neighborhood cascade between layers are adopted to implement the interactive optimization of neighborhood radius matrix, so that both the optimal rough feature selection subsets and their global optimal set are obtained efficiently. Our experimental results substantiate the proposed algorithm can achieve better effectiveness, accuracy and applicability than some traditional feature selection algorithms.

关键词： Layered co-evolution Rough feature se lection Adaptive neighborhood radius hierarchy Longitudinal cortical surface labeling

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