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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Xu, Minrui Niyato, Dusit Zhang, Hongliang Kang, Jiawen Xiong, Zehui Mao, Shiwen Han, Zhu Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore Peking University School of Electronics Beijing100871 China Guangdong University of Technology School of Automation Guangzhou510006 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore487372 Singapore Auburn University Department of Electrical and Computer Engineering AuburnAL36849-5201 United States University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

ISBN: (纸本)9798350333336

Metaverse seamlessly blends the physical world and virtual spaces through ubiquitous communication and computing equipment and infrastructure. In intelligent transportation systems, the vehicular Metaverse can provide a fully immersive and hyperreal travel experience (e.g., via augmented reality head-up displays, AR-HUDs) to drivers and passengers in autonomous vehicles (AVs) through roadside units (RSUs). However, providing real-time and immersive services requires effective physical-virtual synchronization between AVs and virtual simulators. This paper proposes a generative AI-empowered physical-virtual synchronization framework for the vehicular Metaverse. In physical-to-virtual synchronization, digital twin (DT) tasks generated by AVs are offloaded for execution in RSUs with future route generation. In virtual-to-physical synchronization, virtual simulators customize diverse and personalized AR content via generative AI models based on user preferences. Furthermore, we propose a multi-task enhanced auction-based mechanism to match and price AVs and virtual simulators for RSUs to provide real-time and effective services. Finally, property analysis and experimental results demonstrate that the proposed mechanism is strategy-proof and adverse-selection free while increasing social surplus. © 2023 IEEE.

关键词： Augmented reality

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Optimizing the performance of the feedback controller for state-based switching bilinear systems

Optimizing the performance of the feedback controller for st...

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作者： Lin, Shu Li, Dewei Schutter, Bart School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China Delft Center for Systems and Control Delft University of Technology Delft Netherlands

This article is concerned with the design and performance optimization of feedback controllers for state-based switching bilinear systems (SBLSs), where subsystems take the form of bilinear systems in different state space polyhedra. First, by further dividing the subregions into smaller regions and designing region-dependent feedback controllers in the resulting regions, the SBLSs can be transformed into corresponding switching linear systems (SLSs). Then, for these SLSs, by imposing contractility conditions on the Lyapunov functions, an upper bound on the infinite horizon quadratic cost can be obtained. Optimizing this upper bound yields the controller design. The optimization problem is formulated as a linear matrix inequalities optimization problem, which can be solved efficiently. Finally, the stability of the close-loop system under the proposed controller is established step by step through a decreasing overall Lyapunov function. © 2020 John Wiley & Sons, Ltd.

关键词： Lyapunov functions

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Stability analysis of network data flow control for dynamic link capacity case

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作者： Yang, Yuequan Li, Yaqin Tan, Min Yi, Jianqiang Wen, John T. Guo, Xuewu College of Information Engineering Yangzhou University Yangzhou 225009 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180 United States Shanxi Jinyao Coking Co. Ltd. Shanxi 030001 China

ISBN: (纸本)3540372555

Much attention has been paid upon network data flow control in recent years. The main problem in this field is how to design good algorithm or control law for flow rate of network data flow sources and for updated price of communication links. Base on Lyapunov stability theory, this paper makes a deep analysis of stability of such network data flow control systems with the consideration of dynamic link capacity case. Simulations show that the stability analysis of dynamic link capacity of network data flow control system provided in the paper is enlightening and meaningful to further understand and design good control strategy of network data flow control problem. © Springer-Verlag Berlin/Heidelberg 2006.

关键词： Flow control

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Position-based Power Allocation for Uplink HSRs Wireless Communication When Two Trains Encounter

Position-based Power Allocation for Uplink HSRs Wireless Com...

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IEEE Global Communications Conference

作者： Tao Li Zhengchuan Chen Pingyi Fan Khaled Ben Letaief Tsinghua National Laboratory for Information Science and Technology (TNList) and Department of Electronic Engineering Tsinghua University Information Systems Technology and Design Pillar SUTD Department of Electrical and Computer Engineering HKUST

ISBN: (纸本)9781509013296

Highly mobile wireless communication attracts much more attention currently due to the rapid development of high speed railways (HSRs) all over the world. Although the single train scenario has been well studied by now, two trains encountering scenario over the general two-way railways is also an important problem deserving to investigate. To this end, this paper concentrates on the uplink information transmission of HSRs in the two trains encountering scenario, which is modeled as a time-varying partial multiple access channel. In order to evaluate the transmission performance, the achievable rate region is utilized as a metric to characterize the tradeoff between the rates that each train can obtain under limited channel source constraint. With the help of superposition modulation and sequential interference cancelling, an optimal adaptive power allocation scheme aided by real-time position information is proposed to achieve the maximal boundary of the achievable rate region, namely alleviating the effect of encountering on information transmission to the largest extent. According to the numerical results, great improvement can be obtained by new proposed adaptive power allocation along time.

关键词： Highly mobile wireless communication Achievable rate region Position-based power allocation achievable rate region power splitting TRAIN CARRIER SYSTEM data transmission adaptive power allocation up link Transmission Characteristics ENCOUNTERS tradeoffs

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Unsupervised Maximum Margin Feature Selection with manifold regularization

Unsupervised Maximum Margin Feature Selection with manifold ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Bin Zhao James Kwok Fei Wang Changshui Zhang State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing China Department of Computer Science and Engineering HKUST Hong Kong China

Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature selection remains as a rarely touched research topic. In this paper, we propose manifold-based maximum margin feature selection (M3FS) to select the most discriminative features for clustering. M3FS targets to find those features that would result in the maximal separation of different clusters and incorporates manifold information by enforcing smoothness constraint on the clustering function. Specifically, we define scale factor for each feature to measure its relevance to clustering, and irrelevant features are identified by assigning zero weights. Feature selection is then achieved by the sparsity constraints on scale factors. Computationally, M3FS is formulated as an integer programming problem and we propose a cutting plane algorithm to efficiently solve it. Experimental results on both toy and real-world data sets demonstrate its effectiveness.

关键词： Filters Pattern recognition Clustering algorithms Face recognition Laplace equations Laboratories Linear programming Feature extraction Unsupervised learning Supervised learning

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A conceptual framework for semantic case-based safety analysis

A conceptual framework for semantic case-based safety analys...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Olawande Daramola Tor Stålhane Thomas Moser Stefan Biffl Department of Computer and Information Science Norwegian University of Science and Technology Norway Christian Doppler Laboratory for Software Engineering Integration for Flexible Automation Systems Vienna University of Technology Austria

Hazard and Operability (HAZOP) Analysis and Failure Mode and Effect Analysis (FMEA) are among the most widely used safety analysis procedures in the development of safety-critical and embedded systems. These analyses are generally perceived as complex and time-consuming, hindering an effective reuse of previous results or experiences. In this paper we present a conceptual semantic case-based framework for safety analysis, which facilitates the reuse of previous HAZOP and FMEA experiences in order to reduce the time and effort associated with these analyses. We present the core technologies of the conceptual framework and evaluated a prototype of the framework, KROSA, in an experiment with domain experts at ABB Norway. Initial results confirm the viability of the conceptual framework for industrial application.

关键词： Ontologies Semantics Natural language processing Libraries Hazards Humans

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Joint User Association and Resource Pricing for Metaverse: Distributed and Centralized Approaches

arXiv

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arXiv 2022年

作者： Huang, Xumin Zhong, Weifeng Nie, Jiangtian Hu, Qin Xiong, Zehui Kang, Jiawen Quek, Tony Q.S. School of Automation Guangdong University of Technology Guangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer and Information Science Indiana University Purdue University Indianapolis United States Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore

Metaverse as the next-generation Internet provides users with physical-virtual world interactions. To improve the quality of immersive experience, users access to Metaverse service providers (MSPs) and purchase bandwidth resource to reduce the communication latency of the Metaverse services. The MSPs decide selling price of the bandwidth resource to maximize the revenue. This leads to a joint user association and resource pricing problem between all users and MSPs. To tackle the problem, we formulate a Stackelberg game where the MSPs are game leaders and users are game followers. We resolve the Stackelberg equilibrium via the distributed and centralized approaches, according to different privacy requirements. In the distributed approach, the MSPs compete against each other to maximize the individual revenue, and a user selects an MSP in a probabilistic manner. The Stackelberg equilibrium is achieved in a privacy-friendly way. In the centralized approach, all MSPs and users accept the unified management and their strategies are instructed. The centralized approach acquires the superior decision-making performance but sacrifices the privacy of the game players. Finally, we provide numerical results to demonstrate the effectiveness and efficiency of our schemes. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision making

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Modified Iterative-Learning-Control-Based Ramp Metering Strategies for Freeway Traffic Control With Iteration-Dependent Factors

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IEEE Transactions on Intelligent Transportation systems 2012年第2期13卷 606-618页

作者： Zhongsheng Hou Jingwen Yan Jian-Xin Xu Zhenjiang Li Advanced Control Systems Laboratory of School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering National University of Singapore Singapore Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing China

For a freeway traffic system with strict repeatable pattern, iterative learning control (ILC) has been successfully applied to local ramp metering for a macroscopic freeway environment by formulating the original ramp metering problem as an output tracking, disturbance rejection, and error compensation problem. In this paper, we address the freeway traffic ramp-metering system under a nonstrict repeatable pattern. ILC-based ramp metering and ILC add-on to ALINEA strategies are modified to deal with the presence of iteration-dependent parameters, iteration-dependent desired trajectory, and input constraints. Theoretical analysis and extensive simulations are used to verify the effectiveness of the proposed approaches.

关键词： Traffic control Trajectory Mathematical model Vehicles Equations Feedback control

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Supervised tensor learning

Supervised tensor learning

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IEEE International Conference on Data Mining (ICDM)

作者： Dacheng Tao Xuelong Li Weiming Hu S. Maybank Xindong Wu School of Computer Science and Information Systems Birkbeck College University of London UK National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China Department of Computer Science University of Vermont USA

This paper aims to take general tensors as inputs for supervised learning. A supervised tensor learning (STL) framework is established for convex optimization based learning techniques such as support vector machines (SVM) and minimax probability machines (MPM). Within the STL framework, many conventional learning machines can be generalized to take n/sup th/-order tensors as inputs. We also study the applications of tensors to learning machine design and feature extraction by linear discriminant analysis (LDA). Our method for tensor based feature extraction is named the tenor rank-one discriminant analysis (TR1DA). These generalized algorithms have several advantages: 1) reduce the curse of dimension problem in machine learning and data mining; 2) avoid the failure to converge; and 3) achieve better separation between the different categories of samples. As an example, we generalize MPM to its STL version, which is named the tensor MPM (TMPM). TMPM learns a series of tensor projections iteratively. It is then evaluated against the original MPM. Our experiments on a binary classification problem show that TMPM significantly outperforms the original MPM.

关键词： Tensile stress Machine learning Support vector machines Supervised learning Data mining Support vector machine classification computer science Minimax techniques Feature extraction Linear discriminant analysis

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GUEST EDITORIAL

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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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