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arXiv 2023年

作者： Wang, Hao Zhang, Libo Fan, Heng Luo, Tiejian School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Institute of Software Chinese Academy of Sciences Beijing100190 China Department of Computer Science and Engineering University of North Texas DentonTX76203 United States

As the most critical components in a sentence, subject, predicate and object require special attention in the video captioning task. To implement this idea, we design a novel framework, named COllaborative three-Stream Transformers (COST), to model the three parts separately and complement each other for better representation. Specifically, COST is formed by three branches of transformers to exploit the visual-linguistic interactions of different granularities in spatial-temporal domain between videos and text, detected objects and text, and actions and text. Meanwhile, we propose a cross-granularity attention module to align the interactions modeled by the three branches of transformers, then the three branches of transformers can support each other to exploit the most discriminative semantic information of different granularities for accurate predictions of captions. The whole model is trained in an end-to-end fashion. Extensive experiments conducted on three large-scale challenging datasets, i.e., YouCookII, ActivityNet Captions and MSVD, demonstrate that the proposed method performs favorably against the state-of-the-art methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Data Poisoning Attack to X-armed Bandits

Data Poisoning Attack to X-armed Bandits

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Zhi Luo Youqi Li Lixing Chen Zichuan Xu Pan Zhou School of Cyber Science and Engineering Huazhong University of Science and Technology School of Cyberspace Science and Technology and School of Computer Science Beijing Institute of Technology Institute of Cyber Science and Technology Shanghai Jiao Tong University School of Software Dalian University of Technology Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology

X-armed bandits have achieved the state-of-the-art performance in optimizing unknown stochastic continuous functions, which can model many machine learning tasks, specially in big data-driven personalized recommendation. However, bandit algorithms are vulnerable to adversarial attacks. Existing works mainly focus on attacking multi-armed bandits in discrete setting; nevertheless, the attacks against X-armed bandits in continuous setting have not been well explored. In this paper, we aim to bridge this gap and investigate the robustness problem for the X-armed bandits. Specifically, we consider data poisoning attack and propose an attack algorithm named Confidence Poisoning Attack algorithm, which could hijack the clean tree-based X-armed bandits algorithm, i.e., high confidence tree (HCT) and make it choose the nodes including the arm targeted by the attacker very frequently with a sub-linear attack cost, i.e., O(T α )(0

关键词： Threat modeling Privacy Costs Machine learning algorithms Stochastic processes Machine learning Robustness

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Blockchain-based Medical Image Data Trading Platform with Copyright and Privacy Protection

Blockchain-based Medical Image Data Trading Platform with Co...

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International Conference on computer Supported Cooperative Work in Design

作者： Baowei Wang Wenjue Huang Bin Li Yi Yuan Fan Yang Zhengyu Hu Engineering Research Center of Digital Forensics Ministry of Education Nanjing China Waterford Institute Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) Nanjing China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

In recent years, blockchain-based data trading platforms have gained great popularity in many fields because blockchain is decentralized, transparent, antitamper, and traceable. However, data trading for medical images still has problems such as privacy protection and copyright protection, so we propose a blockchain-based data trading scheme for medical images with copyright and privacy protection. Our scheme utilizes smart contracts in the blockchain to achieve automation and intelligence of data trading. We also combine digital watermarking and image encryption to further solve copyright, secure transmission, and privacy issues during medical image transactions. We conduct relevant experiments and verify the feasibility of our proposed scheme.

关键词： Data privacy Privacy Federated learning Smart contracts Watermarking Pricing Encryption

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Fuzzy-Based Automatic Epileptic Seizure Detection Framework

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computers, Materials & Continua 2022年第3期70卷 5601-5630页

作者： Aayesha Muhammad Bilal Qureshi Muhammad Afzaal Muhammad Shuaib Qureshi Jeonghwan Gwak Shaheed Zulfikar Ali Bhutto Institute of Science and Technology IslamabadPakistan Department of Computer Science&IT University of Lakki MarwatKPKPakistan Stockholm University StockholmSweden Department of Computer Science School of Arts and SciencesUniversity of Central AsiaKyrgyz Republic Department of Software Korea National University of TransportationChungju27469Korea Department of Biomedical Engineering Korea National University of TransportationChungju27469Korea Department of AI Robotics Engineering Korea National University of TransportationChungju27469Korea Department of IT&Energy Convergence(BK21 FOUR) Korea National University of TransportationChungju27469Korea

Detection of epileptic seizures on the basis of Electroencephalogram(EEG)recordings is a challenging task due to the complex,non-stationary and non-linear nature of these biomedical *** the existing literature,a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning *** characterizing features of epileptic and non-epileptic EEG signals overlap;therefore,it requires that analysis of signals must be performed from diverse *** studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG *** pose the challenge mentioned above,in this paper,a fuzzy-based epileptic seizure detection model is proposed that incorporates a novel feature extraction and selection method along with fuzzy *** proposed work extracts pattern features along with time-domain,frequencydomain,and non-linear analysis of *** applies a feature selection strategy on extracted features to get more discriminating features that build fuzzy machine learning classifiers for the detection of epileptic *** empirical evaluation of the proposed model was conducted on the benchmark Bonn EEG *** shows significant accuracy of 98%to 100%for normal *** classification cases while for three class classification of normal ***-ictal *** accuracy reaches to above 97.5%.The obtained results for ten classification cases(including normal,seizure or ictal,and seizure-free or inter-ictal classes)prove the superior performance of proposed work as compared to other state-of-the-art counterparts.

关键词： Medical image processing electroencephalography machine learning fuzzy system models seizure detection epileptic seizure virtualization

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Research and Application of Multi-source Data Fusion Identity Authentication System

Research and Application of Multi-source Data Fusion Identit...

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第十九届分布式计算及其应用国际学术研讨会

作者： Ma Tianlong Xu Yingying Zhu Yanni Xu Xinxin Zhu Quanyin Gao Shangbing Wang Shengbiao Faculty of Computer & Software Engineering Huaiyin Institute of Technology

Aiming at the problem of low efficiency and timeconsuming of the traditional college attendance sign-in method, an attendance system based on face recognition, wireless network verification, fingerprint and voice verification was proposed and designed. This design splits the attendance system into four functions: wireless network list acquisition verification, face recognition, voice verification, fingerprint acquisition, and signin record *** on this, a database for storing data and a graphical interface are designed to achieve The function of the time and attendance system.

关键词： multi-source integration time and attendance system identity authentication

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Research and Application of Nuclear Reactor Computational Data Framework Based on HDF5 7th

Research and Application of Nuclear Reactor Computational Da...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Lu, Wei Feng, Jintao Yang, Hao Zeng, Hui Pan, Junjie Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China School of Computer Science Chengdu University of Information Technology Chengdu610225 China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

ISBN: (纸本)9783030786175

Nuclear reactor computing software need to process and maintain complex and massive data sets. In order to meet the requirement of mass data storage and processing in software, the data storage model and I/O method and programming interface of HDF5 (Hierarchical Data Format v5) are deeply studied. According to the data storage and processing requirement of typical nuclear reactor computing data such as assembly or core neutronics computing data and core thermal-hydraulic computing data, RCDF-H5 (Reactor Compute Data Framework based on HDF5) is proposed. KYMRES (KYlin-2 Main RESults databank) and COMRES (COre Main RESults databank) are designed and implemented based on RCDF-H5. The performance tests show that RCDF-H5 has a higher I/O efficiency than conventional storage solutions. A new data storage and management solution for nuclear reactor computing software is provided. © 2021, Springer Nature Switzerland AG.

关键词： Digital storage

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Analysis of Public Opinion on Weibo and Construction of Knowledge Gragh

Analysis of Public Opinion on Weibo and Construction of Know...

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第十九届分布式计算及其应用国际学术研讨会

作者： Dandan Wei Chunxiao Zhao Boxuan Zhang Jialin Ma Quanyin Zhu Xinxin Xu Shengbiao Wang Faculty of Computer & Software Engineering Huaiyin Institute of Technology

Weibo is gradually replacing traditional media, becoming the main way for netizens and youth groups to obtain and exchange information. Weibo public opinion will have a great impact on society. This system is mainly based on the topic of public opinion mining and sentiment analysis, constructing a topic and sentiment knowledge graph on Weibo public opinion to provide a basis for guiding the direction of Weibo public opinion.

关键词： Knowledge Graph Weibo Public Opinion Sentiment Analysis

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Conceptual Clustering Based on Linguistic-Valued Layered Concept Lattice 1

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3rd International Conference on Artificial Intelligence Logic and Applications, AILA 2023

作者： Pang, Kuo Kang, Ning Zou, Li Lu, Mingyu Information Science and Technology College Dalian Maritime University Dalian116026 China Software Engineering Institute East China Normal University Shanghai200062 China School of Computer Science and Technology Shandong Jianzhu University Jinan250102 China

ISBN: (数字)9789819978694

ISBN: (纸本)9789819978687

Formal concept analysis (FCA) is well suited to explain the meaning of clusters. However, most of the existing FCA-based concept clustering algorithms cannot handle fuzzy linguistic information. In this work, we propose a conceptual clustering based on linguistic-valued layered concept lattice is generated by the fuzzy linguistic coupling relationship between attributes. To obtain bi-clustering results for linguistic concepts, attribute-induced and object-induced matrices are first proposed. Second, the problem of overlapping clustering results is handled by calculating the stability of linguistic-valued layered concepts. In addition, the conceptual clustering results can be obtained at different granularities by varying the fuzzy linguistic-valued trust degrees. Finally, illustration example is used to demonstrate the effectiveness of our proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Linguistics

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Spatio-Temporal Aware Knowledge Graph Embedding for Recommender Systems

Spatio-Temporal Aware Knowledge Graph Embedding for Recommen...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Liu Yang Xin Yin Jun Long Tingxuan Chen Jie Zhao Wenti Huang School of Computer Science and Engineering Central South University Changsha China School of Software Technology Zhejiang University Zhejiang China Big Data Institute Central South University Changsha China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

Knowledge Graphs (KGs) have been incorporated into recommender systems as side information to solve the clas-sical data-sparsity and cold-start problems, with explanations for recommended items. Traditional embedding-based recommender systems generally utilize abundant information from KGs directly to enrich the representation of items or users, but the influences of spatial and temporal dependencies are usually ignored among them. In this paper, we propose a Spatio-Temporal Aware Knowledge Graph Embedding (STAKGE) for recommender systems, which incorporates spatio-temporal information with bias when propagating potential preferences of users in knowl-edge graph embedding. Moreover, we construct a multi-source KG-based recommender dataset - YelpST, containing spatio-temporal information. The experiments on YelpST dataset show that our proposed approach can capture comprehensive spatio-temporal correlations and improve the prediction performance as compared to various state-of-the-art baselines.

关键词： Correlation Knowledge graphs Recommender systems

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Quantum Algorithms and Experiment Implementations Based on IBM Q

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computers, Materials & Continua 2020年第11期65卷 1671-1689页

作者： Wenjie Liu Junxiu Chen Yinsong Xu Jiahao Tang Lian Tong Xiaoyu Song Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information Engineering Jiangsu Maritime InstituteNanjing211100China Department of Electrical and Computer Engineering Portland State UniversityOregon97207USA

With the rapid development of quantum theory and technology in recent years,especially the emergence of some quantum cloud computing platforms,more and more researchers are not satisfied with the theoretical derivation and simulation verification of quantum computation(especially quantum algorithms),experimental verification on real quantum devices has become a new *** this paper,three representative quantum algorithms,namely Deutsch-Jozsa,Grover,and Shor algorithms,are briefly depicted,and then their implementation circuits are presented,*** program these circuits on python with QISKit to connect the remote real quantum devices(i.e.,ibmqx4,ibmqx5)on IBM Q to verify these *** experimental results not only show the feasibility of these algorithms,but also serve to evaluate the functionality of these devices.

关键词： Quantum algorithms implementation circuit IBM Q QISKit program

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