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arXiv 2022年

作者： Zhang, Wei Deng, Zhaohong Choi, Kup-Sze Wang, Jun Wang, Shitong The School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Key Laboratory of Media Design and Software Technology Wuxi214122 China The School of Artificial Intelligence and Computer Science Jiangnan University Wuxi214122 China ZJLab Shanghai200433 China The Centre for Smart Health The Hong Kong Polytechnic University Hong Kong The Key laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University Shanghai200444 China

Multi-view data are commonly encountered in data mining applications. Effective extraction of information from multi-view data requires specific design of clustering methods to cater for data with multiple views, which is non-trivial and challenging. In this paper, we propose a novel one-step multi-view clustering method by exploiting the dual representation of both the common and specific information of different views. The motivation originates from the rationale that multi-view data contain not only the consistent knowledge between views but also the unique knowledge of each view. Meanwhile, to make the representation learning more specific to the clustering task, a one-step learning framework is proposed to integrate representation learning and clustering partition as a whole. With this framework, the representation learning and clustering partition mutually benefit each other, which effectively improves the clustering performance. Results from extensive experiments conducted on benchmark multi-view datasets clearly demonstrate the superiority of the proposed method. Copyright © 2022, The Authors. All rights reserved.

关键词： Cluster analysis

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A proof-of-majority consensus protocol for blockchain-enabled collaboration infrastructure of 5G network slice brokers 2

A proof-of-majority consensus protocol for blockchain-enable...

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2nd ACM International Symposium on Blockchain and Secure Critical Infrastructure, BSCI 2020, Co-located with AsiaCCS 2020

作者： Lin, Wenmin Xu, Xiaolong Qi, Lianyong Zhang, Xuyun Dou, Wanchun Khosravi, Mohammad R. Institute of VR and Intelligent Systems Alibaba Business School Hangzhou Normal University Hangzhou China Nanjing University of Information and Technology Nanjing China Qufu Normal University Rizhao China Department of Computing Macquarie University Sydney Australia State Key Laboratory of Novel Software Department of Computer Science and Technology Nanjing University Nanjing China Department of Electrical and Electronic Engineering Shiraz University of Technology Shiraz Department of Computer Engineering Persian Gulf University Bushehr Iran

ISBN: (纸本)9781450376105

With network slicing technology, 5G changes the classical mobile network business model from a network-operator-oriented business to a more open system with multiple stakeholders. In this context, a network slice broker plays the role of agency between network resource providers and vertical service providers, to lease and provide on-demand network slice services. In practice, a single network slice broker normally owns limited types of network slices. And a collaboration infrastructure could be built up to enable network slice sharing among multiple network slice brokers, so as to improve user experience, and enhance the resource utilization rate. However, a major challenge with such an infrastructure is how to support fair and secure slice trading process among multiple un-trusted network slice providers. Blockchain technology, on the other side, brings in high opportunities to implement a fair and secure trading system without a trusted third-party. In view of this observation, this paper proposes a design of blockchain-enabled collaboration infrastructure for network slice brokers, where a group of registered brokers can trade their network slices in a fair and secure manner. To enhance the accountability of slice trading records, transactions are verified and sorted by each broker node, which are further packed into blocks and appended to a shared ledger maintained by each member in the collaboration network. More specifically, we design a Proof-of-Majority (PoM) consensus protocol to sort slice trading transactions before packing transaction blocks of the shared ledger. Furthermore, an optimization for the basic PoM protocol is discussed, with dependency resolving strategy to improve system performance. Experiments are conducted to verify the feasibility of our proposal. © 2020 ACM.

关键词： 5G mobile communication systems

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Budgeted Persuasion on User Opinions via Varying Susceptibility

Budgeted Persuasion on User Opinions via Varying Susceptibil...

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IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Wenyi Tang Xinrui Xu Guangchun Luo Zaobo He Kaiming Zhan School of Computer Science and Engineering University of Electronic Science and Technology of China School of Information and Software Engineering University of Electronic Science and Technology of China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Miami University Sichuan Jiuyuan Yinhai Software Co. Ltd

ISBN: (数字)9781728198293

ISBN: (纸本)9781728198309

Nowadays, the social network becomes an indispensable part of people's daily life, meanwhile offers an unprecedentedly convenient access for purposive individuals to influence the opinions of network users. Current studies present a subtle persuasion approach that finds a number of key users meanwhile varies their susceptibility extent to impact the public opinion. Such persuasion is significantly critical for public security, as it could facilitate both the spreading and dispelling of malicious rumors. However, the major body of these studies enclose impractical assumptions, such that persuaders have an unlimited budget, or the costs of varying different users' susceptibilities are the same, thus rendering these works unsuitable for realistic scenarios. Therefore, this work originally proposes a more practical and generalized problem of persuasion, where varying the susceptibilities of different users holds different costs. The analysis of its non-convexity, non-submodularity and complexity shows that solving the proposed problem is nontrivial, thus inspiring us to provide an intuitive greedy algorithm. Furthermore, we design an accelerated algorithm based on the community property, which reduces the time consumption more than one order of magnitude. The acceleration is based on the intuition that the impact of a user within a proper community could be a good estimation of the impact in the whole network, while the computation of the former one is much more efficient. The relationship between two algorithms is fully analyzed, which shows the community-based algorithm can degenerate to the intuitive greedy algorithm under a specific setting. Finally, comprehensive evaluations on real-world datasets show the superiority of proposed algorithms on both effectiveness and efficiency.

关键词： Greedy algorithms Social networking (online) Heuristic algorithms Search problems Rendering (computer graphics) Acceleration Security

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A comparative study on HIPAA technical safeguards assessment of android mHealth applications

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Smart Health 2022年 26卷 100349页

作者： Mia, Md Raihan Shahriar, Hossain Valero, Maria Sakib, Nazmus Saha, Bilash Barek, Md Abdul Faruk, Md Jobair Hossain Goodman, Ben Khan, Rumi Ahmed Ahamed, Sheikh Iqbal Department of Computer Science at Marquette University WI United States Department of Information Technology at Kennesaw State University GA United States Department of Software Engineering and Game Development at Kennesaw State University GA United States 4A Security & Compliance PA United States Dell Medical School at University of Texas Austin TX United States

Protecting personal health records is becoming increasingly important as more people use Mobile Health applications (mHealth apps) to improve their health outcomes. These mHealth apps enable consumers to monitor their health-related problems, store, manage, and share health records, medical conditions, treatment, and medication. With the increase of mHealth apps accessibility and usability, it is crucial to create, receive, maintain or transmit protected health information (PHI) on behalf of a covered entity or another business associate. The Health Insurance Portability and Accountability Act (HIPAA) provides guidelines to the app developers so that the apps must be compliant with required and addressable Technical Safeguards. However, most mobile app developers, including mHealth apps are not aware of HIPAA security and privacy regulations. Therefore, a research opportunity has emerged to develop an analytical framework to assist the developer to maintain a secure and HIPAA-compliant source code and raise awareness among consumers about the privacy and security of sensitive and personal health information. We proposed an Android source code analysis framework that evaluates twelve HIPAA Technical Safeguards to check whether a mHealth application is HIPAA compliant or not. The implemented meta-analysis and data-flow analysis algorithms efficiently identify the risk and safety features of mHealth apps that violate HIPAA regulations. Furthermore, we addressed API level checking for secure data communication mandated by recent CMS guidelines between third-party mobile health apps and EHR systems. Experimentally, a web-based tool has been developed for evaluating the efficacy of analysis techniques and algorithms. We have investigated 200 top popular Medical and Health & Fitness category Android apps collected from Google Play Store. We identified from the comparative analysis of the HIPAA rules assessment results that authorization to access sensitive resources, data

关键词： Android Data flow analysis HIPAA technical safeguards Metadata analysis mHealth Privacy Security Static analysis

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Distance-aware Edge User Allocation with QoE Optimization

Distance-aware Edge User Allocation with QoE Optimization

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IEEE International Conference on Web Services (ICWS)

作者： Zhiwei Xu Guobing Zou Xiaoyu Xia Ya Liu Yanglan Gan Bofeng Zhang Qiang He School of Computer Engineering and Science Shanghai University Shanghai China School of Information Technology Deakin University Burwood Australia School of Computer Science and Technology Donghua University Shanghai China School of Software and Electrical Engineering Swinburne University of Technology Hawthorn Australia

ISBN: (数字)9781728187860

ISBN: (纸本)9781728187877

Nowadays, the world is witnessing a rapid development of edge computing. As an important issue in the edge computing paradigm, the edge user allocation (EUA) problem has attracted considerable attention. EUA aims at allocating the end-users in a specific area to the edge servers in that area, and ensure end-users' low-latency access to app vendor's services deployed on those edge servers. However, existing approaches simply assume that each edge server has a specific coverage and neglect the complexity of wireless signal transmission. To ensure end-users' low latency, an EUA approach must take into account the distance between end-users and their nearby edge servers, as it significantly impacts their Quality of Experience (QoE). Accordingly, EUA must maximize the overall QoE of the app vendor's users. To tackle this new distance-aware EUA problem, we propose two novel approaches, namely DEUA-O and DEUA-H. DEUA-O aims to find the optimal solution while DEUA-H aims to find the sub-optimal solution in large-scale scenarios efficiently. Four series of experiments are conducted on a real-world dataset to evaluate DEUA-O and DEUA-H. The results demonstrate the substantial gains of our approaches over the state-of-the-art.

关键词： Wireless communication Web services Servers Quality of experience Resource management Task analysis Edge computing

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Augmented random search to reinforcement learning parameters

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AIP Conference Proceedings 2024年第1期2919卷

作者： Bonthu Kotaiah B. Padmaja Amitabha Yadav Department of Computer Science & Information Technology Maulana Azad National Urdu University Hyderabad. India Department of CSE (AI & ML Institute of Aeronautical Engineering Hyderabad India Department of Software DDUKK National P.G. College Lucknow Uttar Pradesh India

In a simple view, we introduce and evaluate a model-free of Hierarchical Reinforcement-Learning with parameters by using Augmented Random Search. The purpose is to improve the model based on Augmented Random Search Algorithm and Reinforcement Learning Algorithm we are using for those who are unableto stand on their feet or Physically Challenges and, who lose physical part due to accidents. Linear-Quadratic or classic complicationcontrolling method. Our simulations variability in performance in these approach tasks, the algorithm is Fifteen times high active than the quickest competing model-free approaches. Our approaches function generally use evaluation theReinforcement Learning.

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A Comparison of Classification Algorithms Based on The Number of Features

A Comparison of Classification Algorithms Based on The Numbe...

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Chinese Control Conference (CCC)

作者： Peichen Xiong Wei Ping Computer Science and Software Engineering Xi’an Jiaotong-Liverpool University Suzhou P. R. China School of Information Engineering College of Science and Technology Ningbo University Ningbo P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

As the most widely known data mining algorithm, classification algorithms have attracted wide attention. K-Nearest Neighbor (KNN) algorithm and decision tree algorithm are the two widely known algorithms in classification algorithms. Sometimes, people not sure how to choose the suitable to solve the classification problems. In this paper, we establish KNN algorithm model and decision tree ID3 algorithm model to analyze the accuracy of the two algorithms in the same data set with different number of features. Through the learning curve and cross validation, we find ID3 algorithm is better than KNN algorithm, and when the number of feature increased the accuracy of KNN is increasing while ID3 is decreased.

关键词： Decision trees Training Prediction algorithms Predictive models Analytical models Machine learning algorithms Data mining

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Conceptual Design of a Generic Nodal Abstraction (GNA) for a Human-Agent Collaboration Systems

Conceptual Design of a Generic Nodal Abstraction (GNA) for a...

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International Conference on Green engineering Technology and Applied Computing 2019, IConGETech2 019 and International Conference on Applied Computing 2019, ICAC 2019

作者： Abbas Mohammed, Khudhair Abdul Majid, Mazlina Sharifuddin Ahmad, Mohd Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Kuantan Malaysia College of Computer Science and Information Technology Universiti Tenaga Nasional Selangor Kajang43000 Malaysia

The issues of modelling software agents in collaborative systems present some problems and difficulties caused by the diversity of tasks and the procedures attached to them. Consequently, such diversity poses a critical challenge to implement scheduled tasks. In this paper, we propose collaborative human-agent system in which a software agent collaborates and cooperates with its human counterpart in several job positions of an organization. The goal of the GNA approach is to improve collaboration between humans when performing tasks within a workflow process. The GNA is built based on the concept of a node which comprises of a human, agents, and their shared functions. This concept espouses the notion that agents could be deployed to assist humans in many common workflow processes and to handle mundane tasks. Furthermore, a multi-agent system is advocated as an application or platform for managing distributed data. Specifically, this paper describes a conceptual design of a generic approach based on the notion of nodes to construct a Generic Nodal Abstraction (GNA) approach that is deployable as a modeling and simulation platform for organizational processes. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Multi agent systems

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Narrowband-internet of things (NB-IoT) system for elderly healthcare services 5

Narrowband-internet of things (NB-IoT) system for elderly he...

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5th International Conference on engineering, Applied sciences and Technology, ICEAST 2019

作者： Manatarinat, Wiraphon Poomrittigul, Suvit Tantatsanawong, Panjai Electrical Engineering Department Faculty of Engineering Pathumwan Institute of Technology Bangkok Thailand Software Engineering and Information System Department Faculty of Science and Technology Pathumwan Institute of Technology Bangkok Thailand Computer Technology Department Faculty of Science Silpakorn University Bangkok Thailand

ISBN: (纸本)9781728100678

3G and 4G wireless communication technology, which requires broad network resources and large amounts of available electricity, was designed for high-speed Internet usage. Most narrowband-Internet of Things (NB-IoT) devices do not require high-speed Internet because most IoTs work by sending commands to and receiving commands from a server only. NB-IoT is a low-power wide area (LPWA) technology that was developed to accommodate a broad variety of new IoT devices. A low-power wide area network (LPWAN) uses narrow frequencies that support the use of devices in the 900 MHz frequency range that are inexpensive and that can be used in both buildings and wide areas. NB-IoT devices can also be used to assist medical patients, the elderly, and disabled people that are susceptible to falling. Our newly developed monitoring system has the ability to immediately recognize a fall, and then automatically alert up to 4 contacts via the LINE application. If dispatch of a medical unit is required, the patient's location is automatically available without the need for voice contact by the patient. © 2019 IEEE.

关键词： Internet of things

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A systematic collection of medical image datasets for deep learning

arXiv

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arXiv 2021年

作者： Li, Johann Zhu, Guangming Hua, Cong Feng, Mingtao Bennamoun, Basheer Li, Ping Lu, Xiaoyuan Song, Juan Shen, Peiyi Xu, Xu Mei, Lin Zhang, Liang Shah, Syed Afaq Ali Bennamoun, Mohammed School of Computer Science and Technology Xidian University China School of Medicine University of Notre Dame Australia Data and Virtual Research Room Shanghai Broadband Network Center China Third Research Institute of The Ministry of Public Security China Discipline of Information Technology Media and Communications Murdoch University Australia Department of Computer Science and Software Engineering University of Western Australia Australia

The astounding success made by artificial intelligence (AI) in healthcare and other fields proves that AI can achieve human-like performance. However, success always comes with challenges. Deep learning algorithms are data-dependent and require large datasets for training. The lack of data in the medical imaging field creates a bottleneck for the application of deep learning to medical image analysis. Medical image acquisition, annotation, and analysis are costly, and their usage is constrained by ethical restrictions. They also require many resources, such as human expertise and funding. That makes it difficult for non-medical researchers to have access to useful and large medical data. Thus, as comprehensive as possible, this paper provides a collection of medical image datasets with their associated challenges for deep learning research. We have collected information of around three hundred datasets and challenges mainly reported between 2013 and 2020 and categorized them into four categories: head & neck, chest & abdomen, pathology & blood, and "others". Our paper has three purposes: 1) to provide a most up to date and complete list that can be used as a universal reference to easily find the datasets for clinical image analysis, 2) to guide researchers on the methodology to test and evaluate their methods’ performance and robustness on relevant datasets, 3) to provide a "route" to relevant algorithms for the relevant medical topics, and challenge leaderboards. © 2021, CC BY-NC-SA.

关键词： Deep learning

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