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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer Graphics, EG 2019

作者： Langenfeld, Florent Axenopoulos, Apostolos Benhabiles, Halim Daras, Petros Giachetti, Andrea Han, Xusi Hammoudi, Karim Kihara, Daisuke Lai, Tuan M. Liu, Haiguang Melkemi, Mahmoud Mylonas, Stelios K. Terashi, Genki Wang, Yufan Windal, Feryal Montes, Matthieu Laboratoire GBCM EA7528 Conservatoire National des Arts-et-Métiers 2 rue Conté Paris75003 France Team Information Technologies Institute Centre for Research and Technology Hellas Greece ISEN-Lille Yncréa Hauts de France Department of Computer Science Università di Verona Strada le Grazie 15 Verona37134 Italy Department of Biological Sciences Purdue University West LafayetteIN United States Université Haute-Alsace IRIMAS EA 7499 MulhouseF-68100 France Department of Computer Science Purdue University West LafayetteIN United States Complex Systems Division Beijing Computational Science Research Center Beijing100193 China School of Software Engineering University of Science and Technology China Suzhou Jiangsu215123 China

ISBN: (纸本)9783038680772

This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from different organisms and showing the same activity). All methods were able to retrieve a member of the same class as the query in at least 94% of the cases when considering the first match, but show more divergent when more matches were considered. Last, similarity metrics trained on databases dedicated to proteins improved the results. © 2019 The Author(s)

关键词： Proteins

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Design and Development of a Mobile Robotic Complex

Design and Development of a Mobile Robotic Complex

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International Conference on Recent Innovations in Electrical, Electronics & Communication engineering (ICRIEECE)

作者： Aigul Adamova Tamara Zhukabayeva Laula Zhumabayeva Zhanna Mukanova Khu Ven-Tsen Department of Computer engineering and software Saken Seifullin Kazakh Agrotechnical University Astana Kazakhstan Department of Computing Engineering L.N. Gumilyov Eurasian National University Astana Kazakhstan Department of Information Systems and Power Engineering S. Yessenov Caspian State University of Technology and Engineering Aktau Kazakhstan Department of Information and Computing Systems Karaganda Economic University of Kazpotrebsoyuz Karaganda Kazakhstan Department of Computer engineering and software programming M. Auezov South Kazakhstan State University Shymkent Kazakhstan

ISBN: (数字)9781538659953

ISBN: (纸本)9781538659960

Development of the mobile robot can be executed in two different ways. Firstly, this creation of the built-in system, secondly, the use of "ready to use" industrial components. With distribution of the industrial mobile robots in the market there are more and more components which can be used for creation of all control system and sensors of the robot mobile platform. Use of the ready components doesn't demand the hardware development that accelerates time of development and reduces cost. The chassis of the Belarus-132 mini-tractor is used as a platform of robotic system in the research, "creation" of the program for traffic control is required. Results of the practical research on design and model development of a mobile robotic complex are given.

关键词： Control systems Robot kinematics Mobile robots Navigation Robot sensing systems

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A Time Effect based Collaborative Filtering Approach for User Preference Statistics and Recommendation

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Yuxi Chen Xiaotong Zhang Qing Zhao Faheem Akhtar School of Statistics and Mathematics Country Central University of Finance and Economics Beijing 100081 China Harpur College of Arts and Sciences Binghamton University-SUNY New York 13902 America Faculty of Information Technology Beijing University of Technology Beijing 100124 China. Department of Computer Science Vrije Universiteit Amsterdam 1081 HV The Netherlands School of Software Engineering Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing 100124 China Department of Computer Science Sukkur IBA University Sukkur 65200 Pakistan

With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The recommendation system is an intelligent system that applies historical knowledge of users to infer their preferences and make a personalized recommendation. However, it suffers from the problem of time effect of user's behaviour, which means a user's interests may change over time. To overcome this problem, we propose a time effect based collaborative filtering approach to adaptively statistics the change of user preferences. Firstly, Item-based collaborative filtering is used to calculate rating similarity between items. Since an Item-based collaborative filtering algorithm doesn't consider the time effect; next, the time decay function is proposed to statistics the change of user interests. Experimental results show that the proposed scheme retained higher accuracy compare to traditional collaborative filtering method.

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Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing 7

Fuzzy adaptive teaching learning-based optimization strategy...

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7th IEEE International Conference on System engineering and Technology, ICSET 2017

作者： Din, Fakhrud Zamli, Kamal Z. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Pahang Malaysia Department of Computer Science and IT University of Malakand KPK Pakistan

ISBN: (纸本)9781538603833

Pairwise strategies have tested effectively a range of software and hardware systems. These testing strategies offer solutions that can substitute exhaustive testing. In simple terms, a pairwise testing strategy significantly minimizes large input parameter values (or configuration options) of a system into a smaller set based on pairwise interaction (or combination). Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. ATLBO employs Mamdani fuzzy inference system to select adaptively either teacher phase or learner phase based on performance instead of blind sequential application as in original TLBO. In this paper, two pairwise testing strategies based on ATLBO and TLBO are proposed. Experimental results suggest that the proposed strategies are capable to be part of testers' toolkit as they outperformed competing meta-heuristic based pairwise testing strategies and tools on many pairwise benchmarks. Moreover, ATLBO based strategy generated optimal pairwise test suites than the one based on TLBO. © 2017 IEEE.

关键词： software testing

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Reinforcement learning meets minority game: Toward optimal resource allocation

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Physical Review E 2019年第3期99卷 032302-032302页

作者： Si-Ping Zhang Jia-Qi Dong Li Liu Zi-Gang Huang Liang Huang Ying-Cheng Lai The Key Laboratory of Biomedical Information Engineering of Ministry of Education The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs and Institute of Health and Rehabilitation Science School of Life Science and Technology Xi'an Jiaotong University Xi'an 710049 China Institute of Computational Physics and Complex Systems Lanzhou University Lanzhou 730000 China Institute of Theoretical Physics Key Laboratory of Theoretical Physics Chinese Academy of Sciences P.O. Box 2735 Beijing 100190 China School of Software Engineering Chongqing University Chongqing 400044 People's Republic of China School of Electrical Computer and Energy Engineering Department of Physics Arizona State University Tempe Arizona 85287 USA

The main point of this paper is to provide an affirmative answer through exploiting reinforcement learning (RL) in artificial intelligence (AI) for eliminating herding without any external control in complex resource allocation systems. In particular, we demonstrate that when agents are empowered with RL (e.g., the popular Q-learning algorithm in AI) in that they get familiar with the unknown game environment gradually and attempt to deliver the optimal actions to maximize the payoff, herding can effectively be eliminated. Furthermore, computations reveal the striking phenomenon that, regardless of the initial state, the system evolves persistently and relentlessly toward the optimal state in which all resources are used efficiently. However, the evolution process is not without interruptions: there are large fluctuations that occur but only intermittently in time. The statistical distribution of the time between two successive fluctuating events is found to depend on the parity of the evolution, i.e., whether the number of time steps in between is odd or even. We develop a physical analysis and derive mean-field equations to gain an understanding of these phenomena. Since AI is becoming increasingly widespread, we expect our RL empowered minority game system to have broad applications.

关键词： Collective dynamics Competition Self-organized systems Mean field theory

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IoTChain: A three-tier blockchain-based IoT security architecture

arXiv

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arXiv 2018年

作者： Bao, Zijian Shi, Wenbo He, Debiao Choo, Kim-Kwang Raymond Department of Computer Science and Engineering Northeastern University Shenyang China School of Computer and Communication Engineering Northeastern University Qinhuangdao China State Key Lab of Software Engineering Computer School Wuhan University Wuhan China Department of Information Systems and Cyber Security Department of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX78249 United States

There has been increasing interest in the potential of blockchain in enhancing the security of devices and systems, such as Internet of Things (IoT). In this paper, we present a blockchain-based IoT security architecture, IoTchain. The three-tier architecture comprises an authentication layer, a blockchain layer and an application layer, and is designed to achieve identity authentication, access control, privacy protection, lightweight feature, regional node fault tolerance, denial-of-service resilience, and storage integrity. We also evaluate the performance of IoTchain to demonstrate its utility in an IoT deployment. Copyright © 2018, The Authors. All rights reserved.

关键词： Internet of things

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One-Time-Username: A Threshold-based Authentication System

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Procedia computer Science 2018年 129卷 426-432页

作者： Abdulrahman Alhothaily Arwa Alrawais Chunqiang Hu Wei Li Department of Computer Science The George Washington University Washington DC 20052 USA General Department of Payment Systems Saudi Arabian Monetary Authority Riyadh KSA College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University KSA School of Software Engineering Chongqing University Chongqing 400044 China Department of Computer Science Georgia State University Atlanta GA 30303 USA

Due to the complexity and volume, memorizing static usernames and passwords is deemed to be one of the most cumbersome tasks for ordinary users. Nevertheless, verifying the access legitimacy of a user without using a verification table and securely granting permissions based on an access control policy assigned to the user are two critical challenges to build an authentication scheme which is practical and effective. Traditional approaches either completely ignore the importance of user-centric access control or rely on a single point of verification or a third party authority; but in practice, access control and distributed verifiers are important for enhancing security and dealing with the dynamics caused by the user online browsing activities. In this paper, we propose a threshold-based authentication system leveraging user computing devices and allowing users to designate various permissions. Various (t,n) physical or virtual devices can participate to run an authentication protocol and provide the user with a one-time credential to access an online banking system. Our evaluation and results show that the solution is not only practical, but it also minimizes the risks associated with traditional approaches.

关键词： Security Authentication Threshold Cryptosystem One-Time Username RSA Access Control

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Role Playing Game Quest Design in Multiplayer Educational Game

Role Playing Game Quest Design in Multiplayer Educational Ga...

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第22届全球华人计算机教育应用大会

作者： Zhong-Xiu, Lu Xue, Luo Maiga, Chang Rita, Kuo Kuo-Chen, Li School of Software Engineering Tongji University School of Computing and Information Systems Athabasca University Department of Information Management Chung Yuan Christian University Department of Computer Science and Engineering New Mexico Institute of Mining and Technology

In this research,we discuss how to design learning activities in the educational role-playing games with balance between fun and *** major stages in integrating learning contents into the educational role-playing games are proposed in this ***,four principles are recommended for designing learning activities in the *** with the two stages and four principles,the earning activities for Fundamental Java Programming are designed in a multiplayer on-line role playing *** evaluate whether the learning activities designed by the research team can engage students' learning motivation or not,a semester-long experiment in designed in 2018 Spring in north Taiwan.

关键词： Game-based Learning Role-Playing Game Quests Design Java Programming Language

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Parallel medical imaging for intelligent medical image analysis: Concepts, methods, and applications

arXiv

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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

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Context-Driven Mobile Learning Using Fog Computing

Context-Driven Mobile Learning Using Fog Computing

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International Conference on Platform Technology and Service (PlatCon)

作者： Hameed Pinjari Anand Paul Gwanggil Jeon Seungmin Rho School of Computer Science and Engineering Kyungpook National University Daegu South Korea Department of Embedded Systems and Engineering Incheon National University Incheon South Korea Department of Media Software Sungkyul University Anyang South Korea

There has been a rapid development in mobile, cloud computing and sensor technologies which enables learners to learn more effectively, flexibly and efficiently from anywhere. Using mobile devices for learning exploits the features of mobile computing such that they can be used to develop customizable systems that help in context-aware learning. Mobile learning refers to the use of mobile devices for the purpose of learning while on the move. In this paper we propose to apply fog computing in mobile learning in order to achieve efficient context-aware learning. Using fog computing reduces the latency and the time complexity of using a mobile learning application.

关键词： Cloud computing Task analysis Edge computing computer architecture Mobile handsets Servers Mobile computing

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