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20th International Conference on Enterprise information systems, ICEIS 2018

作者： Sebei, Hiba Hadj Taib, Mohamed Ali Ben Aouicha, Mohamed Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (纸本)9783030261689

Social network websites are mainly constructed around the notion of user identities, as set up on the bases of their profiles, and online generated contents such as texts, videos, photos. Still, while some profiles gain an important position in the network, others do not. Similarly, some online generated contents appear to gain a great deal of attention from the part of users, whereas others are completely ignored. In this context, the notion of profile and online content related popularity has come to the forefront. Additionally, several studies turn out to be focused on the area of popularity associated analysis and prediction. Noteworthy, however, is that the popularity evaluative metrics prove to vary from a social network to another. In this respect, the present work is conceived to deal with such challenges through an advanced proposal whereby a unified presentation of popularity metrics related to each social entity, across several social networks, is put forward. Accordingly, a hierarchical structure of popularity metrics, as enhanced with a particular RDF presentation, is suggested, along with a brief summary of wide range of methods used to analyze such entities related popularities. © 2019, Springer Nature Switzerland AG.

关键词： Social networking (online)

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China Communications 2023年第2期 3-6页

作者： Yuan Wu Xu Chen Feng Lyu Xianfu Chen Xumin Huang Jie Gao Yueyue Dai Tony Q.S.Quek Yan Zhang the State Key Laboratory of Internet of Things for Smart City University of Macau the Department of Computer and Information Science University of Macau Sun Yat-sen University Sun Yat-sen University Institute of Advanced Networking and Computing Systems Sun Yat-sen University National and Local Joint Engineering Laboratory the School of Computer Science and Engineering Central South University the VTT Technical Research Centre of Finland the School of Automation Guangdong University of Technology the School of Information Technology Carleton University Huazhong University of Science and Technology Singapore University of Technology and Design(SUTD) the IEEE Communications Society Technical Committee on Green Communications and Computing(TCGCC)

With the growing maturity of the advanced edge-cloud collaboration and integrated sensing-communication-computing systems, edge intelligence has been envisioned as one of the enabling technologies for ubiquitous and l...

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Green Floating Blockchain-Empowered Co-Trust Security Mechanism with Energy Efficiency Against Attack Threat for 6G-IoV

Green Floating Blockchain-Empowered Co-Trust Security Mechan...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yibing Liu Lijun Huo Hansong Xu Qianqian Pan Jun Wu State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China School of Engineering The University of Tokyo Tokyo Japan Graduate School of Information Production and Systems Waseda University Fukuoka Japan

The Internet of Vehicles (IoV) based on the 6-th Generation (6G) communication brings convenience, but also raises anxiety about information security. Researchers have developed static security schemes based on the blockchain, but it results in excessive resource occupation. And it is difficult to resist some attacks such as desynchronization, Denial of Service (DoS), and covert intrusion. In response to the above problems, this paper proposes the Floating Blockchain Consensus Security (FBCS) scheme. It models the attack risk of Road Side Unit (RSU) through the traffic flow prediction to present the credibility evaluation and constructs the floating blockchain based on the results. And the security capability is adjusted through the dynamic joining and exit mode of trusted nodes and untrusted nodes. FBCS also establishes a relationship between blockchain size and energy consumption. Once the system resources are found to be insufficient, it applies the cloud center-based supplementary certification mechanism to provide authentication to untrusted nodes to enhance the stability of the *** analysis and simulation experiments prove that the FBCS can afford data privacy, maintain moderate security capabilities, and adapt defense capabilities according to the attack environment, reduce resource occupation to save cost.

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Hand pose estimation system based on combined features for mobile devices

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International Journal of Intelligent information and Database systems 2020年第2-4期13卷 436-453页

作者： Lahiani, Houssem Neji, Mahmoud National School of Electronics and Telecommunications University of Sfax Tunisia Faculty of Economics and Management University of Sfax Tunisia Multimedia Information Systems and Advanced Computing Laboratory Technopark of Sfax Tunis Road 10 km P.O. Box 242 SFAX 3021 Tunisia

Today's mobile devices or smartphones have a revolutionary impact on how we communicate, especially after the advent of devices like smart watches and Google glasses that require new ways to interact with them. To optimise the use of mobile devices, special input and output peripherals have been designed over the years to facilitate communication with them. The well known peripherals are the multi-touch screens. Smartphones are too small to work freely using their input screens. To solve this problem, recent research has focused on contactless and natural gestural interfaces. In this context, we propose a hand gesture recognition system for mobile devices as a simple way of communication with smartphones. In this work, we describe a hand gesture recognition system for Android devices based on a combination of HOG and LBP features and the SVM classifier. An accuracy rate of about 95% is obtained on the improved 'NUS database I'. In addition, we conduct experiments on different Android devices to know the impact of using such a recognition task on embedded systems like smartphones. © 2020 Inderscience Enterprises Ltd.

关键词： Gesture recognition

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A Novel Remaining Useful Life Prediction Model Based on Adaptive Feature Fusion and its Application to Rolling Bearings

SSRN

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SSRN 2024年

作者： Guo, Kai Ma, Jun Wu, Jiande Xiong, Xin Faculty of Information Engineering & Automation Kunming University of Science and Technology Kunming650500 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming650500 China

As a key component in the transmission system of high-speed trains, once a failure occurs, it will directly affect the safety of train operation. Therefore, it is of great significance to construct a degradation index that can comprehensively characterize the running state of bearings and establish a reliable remaining useful life model to ensure the safety of train operation. Aiming at the problems that the redundant features in the existing multi-feature fusion process affect the diagnosis performance and the spurious fluctuations phenomenon of the fusion features causes the inaccurate determination of the start fault time and leads to the low prediction accuracy of remaining useful life (RUL), A method based on adaptive feature fusion and autoregressive integrated moving average model is proposed for rolling bearings prediction. The research in this study demonstrates that by comparing and verifying with two sets of public data, the proposed method is effective in accurately identifying the features that are most sensitive to degradation trends, accurately determine the initial fault moment of bearings, achieve effective prediction of the RUL of bearings, and the related research results can provide reference basis for predictive maintenance of train bearings. © 2024, The Authors. All rights reserved.

关键词： Forecasting

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Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

arXiv

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arXiv 2023年

作者： Chen, Jinbiao Wang, Jiahai Zhang, Zizhen Cao, Zhiguang Ye, Te Chen, Siyuan School of Computer Science and Engineering Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Sun Yat-sen University China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China School of Computing and Information Systems Singapore Management University Singapore

Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MOCOPs). However, they are still struggling to achieve high learning efficiency and solution quality. To tackle this issue, we propose an efficient meta neural heuristic (EMNH), in which a meta-model is first trained and then fine-tuned with a few steps to solve corresponding single-objective subproblems. Specifically, for the training process, a (partial) architecture-shared multi-task model is leveraged to achieve parallel learning for the meta-model, so as to speed up the training;meanwhile, a scaled symmetric sampling method with respect to the weight vectors is designed to stabilize the training. For the fine-tuning process, an efficient hierarchical method is proposed to systematically tackle all the subproblems. Experimental results on the multi-objective traveling salesman problem (MOTSP), multi-objective capacitated vehicle routing problem (MOCVRP), and multi-objective knapsack problem (MOKP) show that, EMNH is able to outperform the state-of-the-art neural heuristics in terms of solution quality and learning efficiency, and yield competitive solutions to the strong traditional heuristics while consuming much shorter time. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Modeling and Clustering of Parabolic Granular Data

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3728-3742页

作者： Tang, Yiming Gao, Jianwei Pedrycz, Witold Hu, Xianghui Xi, Lei Ren, Fuji Hu, Min Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2V4 Canada Hefei University of Technology School of Computer and Information Hefei230601 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Polish Academy of Sciences Systems Research Institute Warsaw00-901 Poland Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Southeast University School of Computer Science and Engineering Nanjing211189 China University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China

At present, there exist some problems in granular clustering methods, such as lack of nonlinear membership description and global optimization of granular data boundaries. To address these issues, in this study, revolving around the parabolic granular data, we propose an overall architecture for parabolic granular modeling and clustering. To begin with, novel coverage and specificity functions are established, and then a parabolic granular data structure is proposed. The fuzzy c-means (FCM) algorithm is used to obtain the numeric prototypes, and then particle swarm optimization (PSO) is introduced to construct the parabolic granular data from the global perspective under the guidance of principle of justifiable granularity (PJG). Combining the advantages of FCM and PSO, we propose the parabolic granular modeling and optimization (PGMO) method. Moreover, we put forward attribute weights and sample weights as well as a distance measure induced by the Gaussian kernel similarity, and then come up with the algorithm of weighted kernel fuzzy clustering for parabolic granularity (WKFC-PG). In addition, the assessment mechanism of parabolic granular clustering is discussed. In summary, we set up an overall architecture including parabolic granular modeling, clustering, and assessment. Finally, comparative experiments on artificial, UCI, and high-dimensional datasets validate that our overall architecture delivers a good improvement over previous strategies. The parameter analysis and time complexity are also given for WKFC-PG. In contrast with related granular clustering algorithms, it is observed that WKFC-PG performs better than other granular clustering algorithms and has superior stability in handling outliers, especially on high-dimensional datasets. © 2020 IEEE.

关键词： Fuzzy clustering

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Procedia Computer Science 2020年 176卷 763-770页

作者： Randa Ben Ammar Yassine Ben Ayed Multimedia Information System and Advanced Computing Laboratory Sfax University Tunisia

Alzheimer’s disease (AD) is the most leading symptom of neurodegenerative dementia; AD is defined now as one of the most costly chronic diseases. For that automatic diagnosis and control of Alzheimer’s disease may have a significant effect on society along with patient well-being. Language disorder is regarded to be among the most common symptoms of AD, as a direct and natural result of cognitive impairment. Hence, the diagnosis of Alzheimer’s disease using speech-based features is gaining growing attention. The aim of this study is to extract linguistic features following a proposed taxonomy of language impairment of AD patients. Obtained results indicate that the proposed taxonomy of the linguistic features extracted from the speech samples can be used to differentiate between Alzheimer’s disease patients and the healthy control group. Support Vector Machine (SVM) classifier obtained classification accuracy over 90 percent.

关键词： Alzheimer’s disease Speech analysis Machine learning

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AugmentedBook: A collaborative e-learning augmented reality platform 1st

AugmentedBook: A collaborative e-learning augmented reality ...

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1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019

作者： Alzahrani, Nouf M. Lajmi, Sonia Information Technology Department Faculty of Computer Science and Information Technology Albaha University Albaha Saudi Arabia MIRACL: Multimedia InfoRmation Systems and Advanced Computing Laboratory University of Sfax Technological Pole of Sfax Sakiet Ezzit Sfax3021 Tunisia

ISBN: (纸本)9783030256289

This paper introduces an augmented reality-based framework (called AugmentedBook) for e-learning that allows the creation of collaborative notes, illustrative media (i.e. video, 2D or 3D image, audio) for mobile devices or Google glass. The augmented content can be added to real-world educational support to make it more comprehensive, interactive and collaborative. In this platform, students and teachers can add collaborative notes to any part of the educational support system. They can also find illustrative media and indicate the pertinence of the result. Using our AugmentedBook platform, students can also download the enriched support using a mobile device. Our framework solves the problem of standard integration of augmented reality applications in education, offering a distributed framework which is e-learning compliant. © 2020, Springer Nature Switzerland AG.

关键词： Augmented reality

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Co‑packaged optics(CPO):status,challenges,and solutions

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Frontiers of Optoelectronics 2023年第1期16卷 1-40页

作者： Min Tan Jiang Xu Siyang Liu Junbo Feng Hua Zhang Chaonan Yao Shixi Chen Hangyu Guo Gengshi Han Zhanhao Wen Bao Chen Yu He Xuqiang Zheng Da Ming Yaowen Tu Qiang Fu Nan Qi Dan Li Li Geng Song Wen Fenghe Yang Huimin He Fengman Liu Haiyun Xue Yuhang Wang Ciyuan Qiu Guangcan Mi Yanbo Li Tianhai Chang Mingche Lai Luo Zhang Qinfen Hao Mengyuan Qin School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong KongChina HKUST Fok Ying Tung Research Institute Guangzhou 511462China The Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511462China Chongqing United Micro-Electronics Center(CUMEC) Chongqing 401332China Hisense Broadband Multimedia Technologies Co. Ltd.Qingdao 266000China Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China State Key Laboratory of Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China School of Microelectronics Xi’an Jiaotong UniversityXi’an 710049China Zhangjiang Laboratory Shanghai 201210China The State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Huawei Technologies Co. Ltd.Shenzhen 440307China College of Computer National University of Defense TechnologyChangsha 410073China Institute of Computing Technology Chinese Academy of SciencesBeijing 100086China

Due to the rise of 5G,IoT,AI,and high-performance computing applications,datacenter trafc has grown at a compound annual growth rate of nearly 30%.Furthermore,nearly three-fourths of the datacenter trafc resides within *** conventional pluggable optics increases at a much slower rate than that of datacenter *** gap between application requirements and the capability of conventional pluggable optics keeps increasing,a trend that is *** optics(CPO)is a disruptive approach to increasing the interconnecting bandwidth density and energy efciency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and *** is widely regarded as a promising solution for future datacenter interconnections,and silicon platform is the most promising platform for large-scale *** international companies(e.g.,Intel,Broadcom and IBM)have heavily investigated in CPO technology,an inter-disciplinary research feld that involves photonic devices,integrated circuits design,packaging,photonic device modeling,electronic-photonic co-simulation,applications,and *** review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform,identify the key challenges,and point out the potential solutions,hoping to encourage collaboration between diferent research felds to accelerate the development of CPO technology.

关键词： Co-packaged optics Silicon photonics High-performance computing advanced packaging External laser Optical power delivery Co-simulation Standardization Transmitter Receiver

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