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arXiv 2019年

作者： Xing, Yuying Yu, Guoxian Domeniconi, Carlotta Wang, Jun Zhang, Zili Guo, Maozu College of Computer and Information Science Southwest University Chongqing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China Department of Computer Science George Mason University FairfaxVA United States School of Information Technology Deakin University GeelongVIC Australia School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Multi-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the inter or intra relations between objects (or bags), instances, and labels, which can convey important contextual information for M3L. As such, they may have a compromised performance. In this paper, we propose a collaborative matrix factorization based solution called M3Lcmf. M3Lcmf first uses a heterogeneous network composed of nodes of bags, instances, and labels, to encode different types of relations via multiple relational data matrices. To preserve the intrinsic structure of the data matrices, M3Lcmf collaboratively factorizes them into low-rank matrices, explores the latent relationships between bags, instances, and labels, and selectively merges the data matrices. An aggregation scheme is further introduced to aggregate the instance-level labels into bag-level and to guide the factorization. An empirical study on benchmark datasets show that M3Lcmf outperforms other related competitive solutions both in the instance-level and bag-level prediction. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix factorization

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Towards Privacy-preserving Incentive for Mobile Crowdsensing Under An Untrusted Platform

Towards Privacy-preserving Incentive for Mobile Crowdsensing...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Zhibo Wang Jingxin Li Jiahui Hu Ju Ren Zhetao Li Yanjun Li State Key Laboratory for Novel Software Technology Nanjing University P. R. China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University P. R. China School of Information Science and Engineering Central South University P. R. China Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education College of Information Engineering Xiangtan University P. R. China School of Computer Science and Technology Zhejiang University of Technology P. R. China

Reverse auction-based incentive mechanisms have been commonly proposed to stimulate mobile users to participate in crowdsensing, where users submit bids to the platform to compete for tasks. Recent works pointed out that bid is a private information which can reveal sensitive information of users (e.g., location privacy), and proposed bid-preserving mechanisms with differential privacy against inference attack. However, all these mechanisms rely on a trusted platform, and would fail in bid protection completely when the platform is untrusted (e.g., honest-but-curious). In this paper, we focus on the bid protection problem in mobile crowdsensing with an untrusted platform, and propose a novel privacy-preserving incentive mechanism to protect users' true bids against the honest-but-curious platform while minimizing the social cost of winner selection. To this end, instead of uploading the true bid to the platform, a differentially private bid obfuscation function is designed with the exponential mechanism, which helps each user to obfuscate bids locally and submit obfuscated task-bid pairs to the platform. The winner selection problem with the obfuscated task-bid pairs is formulated as an integer linear programming problem and proved to be NP-hard. We consider the optimization problem at two different scenarios, and propose a solution based on Hungarian method for single measurement and a greedy solution for multiple measurements, respectively. The proposed incentive mechanism is proved to satisfy ε-differential privacy, individual rationality and γ-truthfulness. The extensive experiments on a real-world data set demonstrate the effectiveness of the proposed mechanism against the untrusted platform.

关键词： Task analysis Privacy Differential privacy Sensors Mobile handsets Cryptography Integer linear programming

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Optimization of Missile Path Planning Based on APMO-HV Algorithm

Optimization of Missile Path Planning Based on APMO-HV Algor...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Hu Zhang Shuai Wang Tonglin Liu Aimin Zhou Yi Zhang Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China School of Mechanical Engineering Changzhou University Changzhou China Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University Shanghai China

In this paper, with considerations of low efficiency of missile path planning (MPP) by traditional aggregation technology, it uses affinity propagation based multi-objective evolutionary algorithm with hypervolume environment selection (APMO-HV) to solve the problem of MPP after establishing the MPP model. The experimental part compares and analyzes APMO-HV with six state-of-the-art algorithms, and applies it to address the MPP problem. The experimental results show that compared with the other six algorithms, APMO-HV has achieved the best solution performance in both the GLT test suite and MPP problem. This not only validates the effect of the proposed algorithm, but also enriches and improves the research results of MPP.

关键词： Missiles Optimization Path planning Turning Planning Target tracking Sociology

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An experimental-based review of image enhancement and image restoration methods for underwater imaging

arXiv

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arXiv 2019年

作者： Wang, Yan Song, Wei Fortino, Giancarlo Qi, Lizhe Zhang, Wenqiang Liotta, Antonio Academy for Engineering & Technology Fudan University China College of Information Technology Shanghai Ocean University Shanghai201306 China University of Calabria Italy Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China Napier Edinburgh University School of Computing Edinburgh United Kingdom

Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major breakthroughs have been made recently in the general area of image enhancement and restoration, the applicability of new methods for improving the quality of underwater images has not specifically been captured. In this paper, we review the image enhancement and restoration methods that tackle typical underwater image impairments, including some extreme degradations and distortions. Firstly, we introduce the key causes of quality reduction in underwater images, in terms of the underwater image formation model (IFM). Then, we review underwater restoration methods, considering both the IFM-free and the IFM-based approaches. Next, we present an experimental-based comparative evaluation of state-of-the-art IFM-free and IFM-based methods, considering also the prior-based parameter estimation algorithms of the IFM-based methods, using both subjective and objective analysis (the used code is freely available at https://***/wangyanckxx/Single-UnderwaterImage-Enhancement-and-Color-Restoration). Starting from this study, we pinpoint the key shortcomings of existing methods, drawing recommendations for future research in this area. Our review of underwater image enhancement and restoration provides researchers with the necessary background to appreciate challenges and opportunities in this important field. Copyright © 2019, The Authors. All rights reserved.

关键词： Image reconstruction

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A nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity 6

A nonlinear impulsive control system with impulse time windo...

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6th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2019

作者： Feng, Yuming Wang, Zitao Liu, Xiaoyu Zhang, Wei Chongqing Engineering Research Center of Internet of Things Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing404100 China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing404100 China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing404100 China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing404100 China

ISBN: (纸本)9781728158570

Based on the fact that there always exists error in the impulsive intensity, which leads to the fact that the coefficient is un-fixed, and in the occurrence of the impulses, we propose a new model, which is called nonlinear impulsive control system with impulse time windows and un-fixed coefficient of impulsive intensity. We find sufficient conditions for ensuring its stability by using Lypunov's method. We choose chaotic Lorenz system and Chua's system as numerical examples to show the effectiveness of the results, by employing such method, the systems are controlled. © 2019 IEEE.

关键词： Numerical methods

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Implementing Security-Enhanced PHR System in the Cloud using FAME

Implementing Security-Enhanced PHR System in the Cloud using...

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IEEE Global Communications Conference

作者： Zuobin Ying Wenjie Jiang Ximeng Liu Shengmin Xu School of Computer Science & Technology Anhui University Hefei China School of Electrical & Electronic Engineering Nanyang Technological University Singapore College of Mathematics & Computer Science Fuzhou University Fuzhou China Fujian Provincial Key Laboratory of Information Security of Network Systems Fuzhou University Fuzhou China School of Information Systems Singapore Management University Singapore

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Personal Health Record (PHR) plays an important role in realizing the exchange and interaction of medical information as well as in managing chronic diseases. In the recent decade, plenty of researches have been carried out to resolve the secure sharing issue of PHR in the cloud via access control schemes. Attribute-based Encryption (ABE) is a promising technique, which implements access control by introducing the access policy. When ABE is used to construct access control scheme in the cloud, hiding and updating access policy have always been two research hotspots. However, all of the existing solutions only consider one of these two issues separately. How to combine policy hiding and policy updating to achieve secure and efficient access control has always been avoided. Furthermore, the practical deployments of traditional ABE in the medical environment are limited by its small attribute universe. In this paper, we propose a policy hiding and updating ABE (PHU-ABE) based on the Fast Attribute-based Encryption (FAME) to tackle these challenges. We argue the security of PHU-ABE. The experimental results demonstrate that our scheme not only protects users' privacy but also realizes efficient policy updating.

关键词： Encryption Public key Access control Hospitals Diseases

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A Hybrid Replacement Strategy for MOEA/D 13th

A Hybrid Replacement Strategy for MOEA/D

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13th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2018

作者： Chen, Xiaoji Shi, Chuan Zhou, Aimin Xu, Siyong Wu, Bin Beijing Key Lab of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing100876 China Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University Shanghai200062 China

ISBN: (纸本)9789811328251

In MOEA/D, the replacement strategy plays a key role in balancing diversity and convergence. However, existing adaptive replacement strategies either focus on neighborhood or global replacement strategy, which may have no obvious effects on balance of diversity and convergence in tackling complicated MOPs. In order to overcome this shortcoming, we propose a hybrid mechanism balancing neighborhood and global replacement strategy. In this mechanism, a probability threshold is applied to determine whether to execute a neighborhood or global replacement strategy, which could balance diversity and convergence. Furthermore, we design an offspring generation method to generate the high-quality solution for each subproblem, which can ease mismatch between subproblems and solutions. Based on the classic MOEA/D, we design a new algorithm framework, called MOEA/D-HRS. Compared with other state-of-the-art MOEAs, experimental results show that the proposed algorithm obtains the best performance. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Multiobjective optimization

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BIRA-NET: BILINEAR ATTENTION NET FOR DIABETIC RETINOPATHY GRADING

arXiv

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arXiv 2019年

作者： Zhao, Ziyuan Zhang, Kerui Hao, Xuejie Tian, Jing Chua, Matthew Chin Heng Chen, Li Xu, Xin Institute of Systems Science National University of Singapore Singapore University of Electronic Science and Technology of China China School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan China

Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis purposes, DR image grading aims to provide automatic DR grade classification, which is not addressed in conventional research methods of binary DR image classification. Small objects in the eye images, like lesions and microaneurysms, are essential to DR grading in medical imaging, but they could easily be influenced by other objects. To address these challenges, we propose a new deep learning architecture, called BiRA-Net, which combines the attention model for feature extraction and bilinear model for fine-grained classification. Furthermore, in considering the distance between different grades of different DR categories, we propose a new loss function, called grading loss, which leads to improved training convergence of the proposed approach. Experimental results are provided to demonstrate the superior performance of the proposed approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Eye protection

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First encounters on Bethe Lattices and Cayley trees

arXiv

引用

arXiv 2020年

作者： Peng, Junhao Sandev, Trifce Kocarev, Ljupco School of Math and Information Science Guangzhou University Guangzhou510006 China Guangdong Provincial Key Laboratory co-sponsored by province and city of Information Security Technology Guangzhou University Guangzhou510006 China Research Center for Computer Science and Information Technologies Macedonian Academy of Sciences and Arts Bul. Krste Misirkov 2 Skopje1000 Macedonia Institute of Physics & Astronomy University of Potsdam Potsdam-GolmD-14776 Germany Institute of Physics Faculty of Natural Sciences and Mathematics Ss. Cyril and Methodius University Arhimedova 3 Skopje1000 Macedonia Faculty of Computer Science and Engineering Ss. Cyril and Methodius University P.O. Box 393 Skopje1000 Macedonia

In this work we consider the first encounter problems between a fixed and/or mobile target A and a moving trap B on Bethe Lattices and Cayley trees. The survival probability (SP) of the target A on the both kinds of structures are analyzed analytically and compared. On Bethe Lattices, the results show that the fixed target will still prolong its survival time, whereas, on Cayley trees, there are some initial positions where the target should move to prolong its survival time. The mean first encounter time (MFET) for mobile target A is evaluated numerically and compared with the mean first passage time (MFPT) for the fixed target A. Different initial settings are addressed and clear boundaries are obtained. These findings are helpful for optimizing the strategy to prolong the survival time of the target or to speed up the search process on Cayley trees, in relation to the target’s movement and the initial position configuration of the two walkers. We also present a new method, which uses a small amount of memory, for simulating random walks on Cayley trees. Copyright © 2020, The Authors. All rights reserved.

关键词： Random processes

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引用

25th International Conference on Neural information processing, ICONIP 2018

作者： Liu, Wenfeng Liu, Peiyu Yi, Jing Yang, Yuzhen Liu, Weitong Li, Nana School of Information Science and Engineering Shandong Normal University Jinan250014 China School of Computer Heze University Heze274015 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China

ISBN: (纸本)9783030041816

How to effectively measure the similarity between two sentences is a challenging task in natural language processing. In this paper, we propose a sentence similarity comparison method that combines word embeddings and syntactic structure. First of all, by generating the corresponding syntactic tree, we synthetically analyze the two sentences and block them according to the syntactic components. Secondly, we prune the syntactic tree, remove the stop words and perform morphological restoration. Then, some important operations will be performed, such as passive flipping, negative flipping, and so on. Finally, the similarity of two sentence pairs is calculated by weighting the block embeddings of the syntactic tree. Experiments show the effectiveness of this method. © Springer Nature Switzerland AG 2018.

关键词： Embeddings

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