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International Symposium on Networks, computers and Communications (ISNCC)

作者： Yong Zhang Lidong Zhu Chengjie Li Xu Deng Huazhi Feng Institute of Advanced Technology on Communication Chengdu Technological University Chengdu China National Key Laboratory of Science and Technology on Communication University of Electronic Science and Technology of China Chengdu China The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and Technology Southwest Minzu University Chengdu China Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hongkong China

This paper discusses the issue of multi-beam forming for ground station (GS) in LEO satellite communication system. A store-load phased array structure is proposed, which doesn’t require complicated real-time computation. Meanwhile, for generating the pre-stored array pattern, a synthesis approach of array pattern for multi-beam is proposed. Based on a reference pattern designed by using Chebyshev method, the second-order cone programming (SOCP) constraint is applied to obtain optimized array patterns. Numerical simulations have been conducted in our unified platform containing Matlab and SeDuMi tool. The results show that the proposed approach can effectively synthesize array pattern with two beams and keep constant beamwidth at different directions and frequencies.

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PFV2: Packet fragmentation with variable size and vigorous mapping in time-sensitive networking

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Journal of systems Architecture 2025年 166卷

作者： Yan, Wenyan Fu, Bin Wei, Dongsheng Li, Renfa Lei, Yixue Jia, Yuhang Xie, Guoqi Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Hunan Changsha410082 China Center for Convergence of Automobile and Cyberspace Research Institute of Hunan University in Chongqing Chongqing401120 China Future Network Laboratory Tencent Beijing100080 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems School of Computer and Artificial Intelligence Xiangnan University Hunan Chenzhou423000 China

With the rapid advancement of intelligent automobiles, the ever-growing communication data put forward high bandwidth and low latency requirements. To meet these requirements, automotive Original Equipment Manufacturers (OEMs) widely adopt domain-centralized Electrical/Electronic (E/E) architecture. In this architecture, Time-Sensitive Networking (TSN) is expected to serve as the backbone network because of its high bandwidth and deterministic communication. TSN uses the Gate Control List (GCL) to divide its time length into multiple time slots, and the time intervals of these time slots are non-uniform (equal or unequal). Different flows have varying requirements for time slot sizes. To enhance the acceptance ratio of Time-Triggered (TT) flows through GCL time slot allocation, packet fragmentation (i.e., flow fragmentation) is introduced into TSN in the recent study. The state-of-the-art packet fragmentation solution divides one un-schedulable TT flow into multiple equal-sized packets (i.e., equal-sized time slots). In other words, these fixed-size packets are difficult to be mapped into the time slots with different sizes. This study develops a Packet Fragmentation with Variable-size and Vigorous-mapping (PFV2) technique based on the following three innovations: (1) we implement variable-size packet fragmentation, which iteratively divides the un-schedulable TT flow into smaller packets and then dynamically reschedules these packets;(2) we implement the vigorous mapping solution from packets to time slots by deeply searching for available time slots within the flow's deadline;and (3) we verify PFV2 based on the LS1028A with Cortex-A72 (i.e., the NXP automotive-grade development board). PFV2 improves the acceptance ratio by up to 20.18% and bandwidth utilization by up to 7.024% compared with the state-of-the-art solution. The theoretical and practical co-verification experiments demonstrate that the PFV2 can effectively improve the flow acceptance ratio and outperf

关键词： Bandwidth

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Brain multigraph prediction using topology-aware adversarial graph neural network

arXiv

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arXiv 2021年

作者： Bessadok, Alaa Mahjoub, Mohamed Ali Rekik, Islem BASIRA Lab Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Higher Institute of Informatics and Communication Technologies University of Sousse Tunisia National Engineering School of Sousse University of Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia School of Science and Engineering Computing University of Dundee United Kingdom

Brain graphs (i.e, connectomes) constructed from medical scans such as magnetic resonance imaging (MRI) have become increasingly important tools to characterize the abnormal changes in the human brain. Due to the high acquisition cost and processing time of multimodal MRI, existing deep learning frameworks based on Generative Adversarial Network (GAN) focused on predicting the missing multimodal medical images from a few existing modalities. While brain graphs help better understand how a particular disorder can change the connectional facets of the brain, synthesizing a target brain multigraph (i.e, multiple brain graphs) from a single source brain graph is strikingly lacking. Additionally, existing graph generation works mainly learn one model for each target domain which limits their scalability in jointly predicting multiple target domains. Besides, while they consider the global topological scale of a graph (i.e., graph connectivity structure), they overlook the local topology at the node scale (e.g., how central a node is in the graph). To address these limitations, we introduce topology-aware graph GAN architecture (topoGAN), which jointly predicts multiple brain graphs from a single brain graph while preserving the topological structure of each target graph. Its three key innovations are: (i) designing a novel graph adversarial auto-encoder for predicting multiple brain graphs from a single one, (ii) clustering the encoded source graphs in order to handle the mode collapse issue of GAN and proposing a cluster-specific decoder, (iii) introducing a topological loss to force the prediction of topologically sound target brain graphs. The experimental results using five target domains demonstrated the outperformance of our method in brain multigraph prediction from a single graph in comparison with baseline approaches. © 2021, CC BY-NC-SA.

关键词： Graphic methods

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Asymmetric Heat Transfer with Linear Conductive Metamaterials

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Physical Review Applied 2023年第3期20卷 034013-034013页

作者： Yishu Su Ying Li Minghong Qi Sebastien Guenneau Huagen Li Jian Xiong Center for Composite Materials and Structures Harbin Institute of Technology Harbin 150001 China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 310027 China International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining 314400 China UMI 2004 Abraham de Moivre-CNRS Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore

Asymmetric heat-transfer systems, often referred to as thermal diodes or thermal rectifiers, have garnered increasing interest due to their wide range of application possibilities. Most of those previous macroscopic asymmetric thermal devices either resort to nonlinear thermal conductivities with strong temperature dependence that may be quite limited by or fixed in natural materials or rely on active modulation that necessitates auxiliary energy payloads. Here, we establish a straightforward strategy of passively realizing asymmetric heat transfer with linear conductive materials. The strategy also introduces an interrogative perspective into the previous design of passive asymmetric heat transfer utilizing nonlinear thermal conductivity, correcting the misconception that thermal rectification is impossible with separable nonlinear thermal conductivity. The nonlinear-perturbation mode can be versatilely engineered to produce an effective and wide-ranging perturbation in heat conduction, which imitates and bypasses intrinsic thermal nonlinearity constraints set by naturally occurring counterparts. Independent experimental characterizations of surface thermal radiation and thermal convection verify that heat exchange between a graded linear thermal metamaterial and the ambient surroundings can be tailored to achieve macroscopic asymmetric heat transfer. Our work is envisaged to inspire conceptual models for heat-transfer control, serving as a robust and convenient platform for advanced thermal management and thermal computation.

关键词： Heat radiation Heat transfer Metamaterials Thermal conductivity

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A Reinforcement-Learning-Based Evolutionary Algorithm Using Solution Space Clustering For Multimodal Optimization Problems

A Reinforcement-Learning-Based Evolutionary Algorithm Using ...

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Congress on Evolutionary Computation

作者： Hai Xia Changhe Li Sanyou Zeng Qingshan Tan Junchen Wang Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

In evolutionary algorithms, how to effectively select interactive solutions for generating offspring is a challenging problem. Though many operators are proposed, most of them select interactive solutions (parents) randomly, having no specificity for the features of landscapes in various problems. To address this issue, this paper proposes a reinforcement-learning-based evolutionary algorithm to select solutions within the approximated basin of attraction. In the algorithm, the solution space is partitioned by the k-dimensional tree, and features of subspaces are approximated with respect to two aspects: objective values and uncertainties. Accordingly, two reinforcement learning (RL) systems are constructed to determine where to search: the objective-based RL exploits basins of attraction (clustered subspaces) and the uncertainty-based RL explores subspaces that have been searched comparatively less. Experiments are conducted on widely used benchmark functions, demonstrating that the algorithm outperforms three other popular multimodal optimization algorithms.

关键词： Uncertainty Clustering algorithms Evolutionary computation Reinforcement learning Benchmark testing Search problems Feature extraction

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A Novel Scalable Framework For Constructing Dynamic Multi-objective Optimization Problems

A Novel Scalable Framework For Constructing Dynamic Multi-ob...

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Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Hai Xia Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Modeling dynamic multi-objective optimization problems (DMOPs) has been one of the most challenging tasks in the field of dynamic evolutionary optimization. Based on the analysis of the existing DMOPs, several features widely existed in real-world applications are not taken into account: different objectives may have different function models and variables to be optimized; and the number of conflicting variables should be independent from the number of objectives; the time-linkage property is not considered. In order to overcome the above issues, a novel framework for constructing DMOPs is proposed, where all objectives can be designed independently, and the number of the conflicting variables can be tuned by users. Moreover, it is easy to add new dynamic features to this framework. Several classical dynamic multi-objective optimization algorithms are tested on four scenarios, results show that these characteristics are challenging for the existing algorithms.

关键词： Schedules Analytical models Heuristic algorithms Object oriented modeling Evolutionary computation Benchmark testing Dynamic scheduling

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Robust Switched Interval Observer for the Energy Management System in Hybrid Vehicles

Robust Switched Interval Observer for the Energy Management ...

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International Conference on advanced systems and Electric Technologies (IC_ASET)

作者： Fatah Bejaoui Chokri Mechmeche Ali Sghaier Tlili Laboratory of Advanced Systems Polytechnic School of Tunisia (EPT) National High School of Engineering of Tunis (ENSIT) La Marsa Tunis Laboratory of Advanced Systems Polytechnic School of Tunisia (EPT) High Institute of Computer Science (ISI) University of Tunis El Manar La Marsa Tunis

ISBN: (数字)9781728163567

ISBN: (纸本)9781728163574

In this paper, the energy management system model of a hybrid vehicle (EMSHV) is elaborated. Based on this model, a switched interval observer with unknown input is proposed to estimate the output voltage of the DC bus. Sufficient conditions of the stability of such an observer are expressed in terms of LMI. A finite state machine is elaborated to control the EMSHV. To demonstrate the efficacy of the designed observation strategy, a large study, conducted by numerical simulations using Matlab/Simulink, is performed.

关键词： Observers Switches Batteries DC-DC power converters Energy management systems Numerical simulation Linear matrix inequalities

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Cloud-based platform for intelligent healthcare monitoring and risk prevention in hazardous manufacturing contexts

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Procedia CIRP 2021年 99卷 50-56页

作者： Alessandro Simeone Alessandra Caggiano Lev Boun Rebecca Grant Intelligent Manufacturing Key Laboratory of Ministry of Education Shantou University 515063 Shantou Guangdong China Department of Industrial Engineering University of Naples Federico II Piazzale Tecchio 80 80125 Naples Italy Fraunhofer Joint Laboratory of Excellence on Advanced Production Technology (Fh-J_LEAPT UniNaples) Naples Italy Dynamic Computer Systems PoB 1341 30300 Atlit Israel Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University Loughborough LE11 3TU UK

This paper presents an intelligent cloud-based platform for workers healthcare monitoring and risk prevention in potentially hazardous manufacturing contexts. The platform is structured according to sequential modules dedicated to data acquisition, processing and decision-making support. Several sensors and data sources, including smart wearables, machine tool embedded sensors and environmental sensors, are employed for data collection, comprising information on offline clinical background, operational and environmental data. The cloud data processing module is responsible for extracting relevant features from the acquired data in order to feed a machine learning-based decision-making support system. The latter provides a classification of workers’ health status so that a prompt intervention can be performed in particularly challenging scenarios.

关键词： Industry 4.0 cloud manufacturing sustainable manufacturing smart wearables hazardous manufacturing context

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Fiber optic jerk sensor in monitoring earthquake response of high-rise building 27

Fiber optic jerk sensor in monitoring earthquake response of...

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27th International Conference on Optical Fiber Sensors, OFS 2020

作者： Zhang, Wentao Huang, Wenzhu Zhao, Bin Zhang, Jianxiang Li, Zhengbin Li, Li Li, Fang College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing China State Key Laboratory of Transducer Technology Institute of Semiconductors Chinese Academy of Sciences Beijing China College of Civil Engineering Tongji University Shanghai China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Institute of Geophysics China Earthquake Administration Beijing China

This paper proposed an earthquake response monitoring technique of high-rise buliding using fiber optic jerk sensor. The results show that the fiber optic jerk sensor can monitor the jerk response of different seismic... 详细信息

ISBN: (纸本)9781557523075

关键词： Fiber optics

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A controllable coupling structure for silicon microring resonators based on adiabatic elimination

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Chinese Optics Letters 2020年第1期18卷 110-114页

作者： Fenghe Yang Pengfei Sun Ruixuan Chen Zhiping Zhou State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Peking University Shenzhen Research Institute Shenzhen 518057China Nano-optoelectronics Frontier Center of Ministry of Education Peking UniversityBeijing 100871China

Optical microring resonators are extensively employed in a wide range of physical studies and applications due to the resonance enhancement *** coupling control of a microring resonator is necessary in many scenarios,but modifications are essentially added to the resonator and impair the capability of optical ***,we propose a flexible coupling structure based on adiabatic elimination that allows low-loss active coupling control without any modifications to the *** self-coupling coefficient can be monotonically or non-monotonically controllable by the proposed coupler,potentially at a high *** characteristic of the coupler when implemented in silicon microring resonators is investigated in detail using substantiated analytical theory and *** work provides a general method in coupling control while ensuring the resonance enhancement property,making active coupling control in a resonator-waveguide system feasible.

关键词： silicon photonics adiabatic elimination resonance system

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