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Coordination of networking and computing: toward new information infrastructure and new services mode

Frontiers of Information Technology & Electronic engineering 2024年第5期25卷 629-632页

作者： Xiaoyun WANG Tao SUN Yong CUI Rajkumar BUYYA Deke GUO Qun HUANG Hassnaa MOUSTAFA Chen TIAN Shangguang WANG China Mobile Communications Corporation Beijing 100032China China Mobile Research Institute Beijing 100053China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China CLOUDS Lab School of Computing and Information SystemsUniversity of MelbourneMelbourneVIC 3010Australia National Key Laboratory of Information Systems Engineering National University of Defense TechnologyChangsha 410073China School of Computer Science Peking UniversityBeijing 100871China Intel Corporation Santa ClaraCA 95054USA State Key Laboratory for Novel Sofiware Technology Nanjing UniversityNanjing 210023China State Key Laboratory of Networking and Switching Technology Bejing University of Posts and TelecommunicationsBeijing 100876China

Computing,serving as the cornerstone of information processing,plays a pivotal role in the digital service ***"network"and"computing,"responsible for information transmission and processing respectively,traditionally belong to different stakeholders and have evolved ***,the recent trend toward the coordination and integration of computing and networks has garnered significant attention from both industry and *** such as"computility network"and"computing force network"have emerged,and the International Telecommunication Union-Telecommunication Standardization(ITU-T)has initiated efforts to develop standards for the coordination of networking and computing(CNC),focusing on the architecture and framework.

关键词： computing services network

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Towards hybrid approach based SVM and Radiomics features for COVID-19 classification and segmentation

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International Journal of Hybrid Intelligent systems 2024年第PRE-PRESS期Pre-press卷 1-20页

作者： Azizi, Ridha Sakly, Houneida Wajdi, Abdallah Ahmed Hmida, Alaa Eddinne Ben Bouhlel, Med Salim Research Lab: Smart systems for Engineering and E-health based on Technologies of Image and Telecomunications (SETIT) ISBS Sfax University Tunisia Center for Research on Microelectronics and Nanotechnology (CRMN) Sousse Technopole Sahloul Sousse Tunisia RIADI Laboratory ENSI Manouba University Campus Universitaire de la Manouba La Manouba Tunisia Department IT Higher Institute of Computer Science and Mathematics of Monastir Tunisia Department IT Higher Institute of Computer Science and Mathematics of Monastir Tunisia

In the battle against the COVID-19 pneumonia outbreak, which is brought on by the coronavirus strain SARS-Cov-2, radiological chest exams, such as chest X-rays, are crucial. In order to understand the unique radiographic characteristics of COVID-19, this research looks into classification models to distinguish chest X-ray images based on Radiomics features. This study is performed with datasets composed of 136 segmented chest X-rays, which were used to train and test the categorization algorithms. First and second-order statistical texture characteristics were extracted from the right (R), left (L), superior, middle, and bottom lung zones for each lung side using the Pyradiomics collection. Data was divided into training (80%) and test (20%) groups for feature selection. After assessing the respective feature significance and confirmation accuracy, the most pertinent Radiomics features were chosen. A model of lung segmentation based grey level pixels was used to evaluate support vector machines (SVM) as possible classifiers (AUC = 83.7%). Our research reveals a preference for the upper lung zone and a preponderance of Radiomics feature selection in the right lung. Our future research will concentrate on COVID-19 categorization and segmentation for more precise forecast using a hybrid method based on SVM and Radiogenomics features.

关键词： COVID-19 radiomics pyradiomics classifiers segmentation SVM radiogenomics

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Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles

Generative AI-Enhanced Cooperative MEC of UAVs and Ground St...

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Annual Conference on Information sciences and systems (CISS)

作者： Jiahao You Ziye Jia Chao Dong Qihui Wu Zhu Han The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Department of Electrical and Computer Engineering University of Houston Houston TX USA Department of Computer Science and Engineering Kyung Hee University Seoul South Korea

ISBN: (数字)9798331513269

ISBN: (纸本)9798331513276

The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible aerial services, and ground stations (GSs) can provide powerful supports, which can cooperate to help the USVs in complex scenarios. However, the collaboration between UAVs and GSs for USVs faces challenges of task uncertainties, USVs trajectory uncertainties, heterogeneities, and limited computational resources. To address these issues, we propose a cooperative UAV and GS based robust multi-access edge computing framework to assist USVs in completing computational tasks. Specifically, we formulate the optimization problem of joint task offloading and UAV trajectory to minimize the total execution time, which is in the form of mixed integer nonlinear programming and NP-hard to tackle. Therefore, we propose the algorithm of generative artificial intelligence-enhanced heterogeneous agent proximal policy optimization (GAI-HAPPO). The proposed algorithm integrates GAI models to enhance the actor network ability to model complex environments and extract high-level features, thereby allowing the algorithm to predict uncertainties and adapt to dynamic conditions. Additionally, GAI stabilizes the critic network, addressing the instability of multi-agent reinforcement learning approaches. Finally, extensive simulations demonstrate that the proposed algorithm outperforms the existing benchmark methods, thus highlighting the potentials in tackling intricate, cross-domain issues in the considered scenarios.

关键词： Adaptation models Uncertainty Heuristic algorithms Computational modeling Autonomous aerial vehicles Prediction algorithms Feature extraction Trajectory Vehicle dynamics Optimization

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Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways

Learning Perceptual Hallucination for Multi-Robot Navigation...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jin-Soo Park Xuesu Xiao Garrett Warnell Harel Yedidsion Peter Stone Department of Electrical and Computer Engineering The University of Texas at Austin United States Department of Computer Science George Mason University United States Everyday Robots United States Department of Computer Science The University of Texas at Austin United States Army Research Laboratory United States Sony AI Japan

While current systems for autonomous robot navigation can produce safe and efficient motion plans in static environments, they usually generate suboptimal behaviors when multiple robots must navigate together in confined spaces. For example, when two robots meet each other in a narrow hallway, they may either turn around to find an alternative route or collide with each other. This paper presents a new approach to navigation that allows two robots to pass each other in a narrow hallway without colliding, stopping, or waiting. Our approach, Perceptual Hallucination for Hallway Passing (PHHP), learns to synthetically generate virtual obstacles (i.e., perceptual hallucination) to facilitate passing in narrow hallways by multiple robots that utilize otherwise standard autonomous navigation systems. Our experiments on physical robots in a variety of hallways show improved performance compared to multiple baselines.

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Sum Rate Maximization for Movable Antenna Enhanced Multiuser Covert Communications

arXiv

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arXiv 2024年

作者： Mao, Haobin Pi, Xiangyu Zhu, Lipeng Xiao, Zhenyu Xia, Xiang-Gen Zhang, Rui The School of Electronic and Information Engineering The State Key Laboratory of CNS/ATM Beihang University Beijing100191 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore The Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China

In this letter, we propose to employ movable antenna (MA) to enhance covert communications with noise uncertainty, where the confidential data is transmitted from an MA-aided access point (AP) to multiple users with a warden attempting to detect the existence of the legal transmission. To maximize the sum rate of users under covertness constraint, we formulate an optimization problem to jointly design the transmit beamforming and the positions of MAs at the AP. To solve the formulated non-convex optimization problem, we develop a block successive upper-bound minimization (BSUM) based algorithm, where the proximal distance algorithm (PDA) and the successive convex approximation (SCA) are employed to optimize the transmit beamforming and the MAs' positions, respectively. Simulation results show that the proposed MAs-aided system can significantly increase the covert sum rate via antenna position optimization as compared to conventional systems with fixed-position antennas (FPAs). Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

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Optimal Evasion from a Sensing-Limited Pursuer

Optimal Evasion from a Sensing-Limited Pursuer

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American Control Conference (ACC)

作者： Dipankar Maity Alexander Von Moll Daigo Shishika Michael Dorothy Department of Electrical and Computer Engineering North Carolina Battery Complexity Autonomous Vehicle and Electrification Research Center (BATT CAVE) University of North Carolina Charlotte NC USA Air Force Research Laboratory WPAFB Control Science Center OH USA Army Research Directorate DEVCOM Army Research Laboratory APG MD USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper investigates a partial-information pursuit evasion game in which the Pursuer has a limited-range sensor to detect the Evader. Given a fixed final time, we derive the optimal evasion strategy for the Evader to maximize its distance from the pursuer at the end. Our analysis reveals that in certain parametric regimes, the optimal Evasion strategy involves a ‘risky’ maneuver, where the Evader's trajectory comes extremely close to the pursuer's sensing boundary before moving behind the Pursuer. Additionally, we explore a special case in which the Pursuer can choose the final time. In this scenario, we determine a (Nash) equilibrium pair for both the final time and the evasion strategy.

关键词： Games Nash equilibrium Sensors Trajectory

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Reconfigurable topological modes in acoustic non-Hermitian crystals

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Physical Review B 2023年第20期107卷 L201108-L201108页

作者： Haiyan Fan He Gao Tuo Liu Shuowei An Xianghong Kong Guoqiang Xu Jie Zhu Cheng-Wei Qiu Zhongqing Su Department of Mechanical Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong SAR China Department of Electrical and Computer Engineering National University of Singapore Singapore 116083 Singapore Key Laboratory of Noise and Vibration Research Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China Institute of Acoustics School of Physics Science and Engineering Tongji University Shanghai 200092 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai 201210 China

Non-Hermiticity, usually represented in the context of gain and loss, gives rise to many exotic topological phenomena and offers more opportunities to steering topological functions. In modern acoustics, it has been widely perceived that the topological mode will be altered if topological phase changes. Our work shows otherwise in non-Hermitian acoustic crystals. We experimentally demonstrate an acoustic quadrupole topological insulator, whose topological corner, edge, and bulk modes could be arbitrarily engineered at any desired positions with its topological phase maintained. These non-Hermiticity-controlled topological modes bestow a bulk structure with unique features beyond the classical bulky state, offering a reconfigurable and versatile approach to manipulating topological phenomena. This non-Hermitian scheme can be readily generalized to other topological systems in various dimensions, such as the three-dimensional photonic/phononic lattices, which offer advanced and externally controllable recipes for manipulating topological phenomena.

关键词： Acoustic metamaterials Metamaterials Topological defects Non-Hermitean systems

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On the Impact of Spatial Mode Dispersion for Strongly-Coupled Multicore Fiber Submarine Transmission

On the Impact of Spatial Mode Dispersion for Strongly-Couple...

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Sun, Lin Chen, Bin Liu, Gordon Ning Cai, Yi Li, Zhaohui Lu, Chao Shen, Gangxiang Soochow University Suzhou Key Laboratory of Advanced Optical Communication Network Technology School of Electronic and Information Engineering Suzhou215006 China Hefei University of Technology School of Computer Science and Information Engineering Hefei China Sun Yat-Sen University Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips School of Electronics and Information Technology Guangzhou511400 China The Hong Kong Polytechnic University Photonics Research Center Department of Electrical and Information Engineering Kowloon Hung Hom Hong Kong

Strongly-coupled multicore fibers exhibit the improved tolerance to fiber non-linearity. Their potentials in optical submarine communications are investigated with considering the coupling length and spatial mode disp... 详细信息

ISBN: (纸本)9781957171180

关键词： Submarines

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Impact of Foreign Objects on Wireless Power Transfer Efficiency in Magnetic Coupling systems

Impact of Foreign Objects on Wireless Power Transfer Efficie...

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electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Hassan Khalid Saad Mekhilef Marizan Mubin Mehdi Seyedmahmoudian Mehmet Zahid Erel Hussain Bassi Obaid Alshammari Department of Electrical Engineering Power Electronics and Renewable Energy Research Laboratory (PEARL) University of Malaya Kuala Lumpur Malaysia Department of Electrical Engineering School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Victoria Australia Department of Electrical Engineering University of Malaya Kuala Lumpur Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Victoria Australia Department of Energy Systems Engineering Ankara Yildirim Beyazit University Ankara Turkey Water Technologies Innovation Institute & Research Advancement (WTIIRA) Saudi Water Authority (SWA) Al Jubail Saudi Arabia Department of Electrical Engineering College of Engineering University of Hail Hail Saudi Arabia

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

Inductive wireless charging has emerged as a viable solution for charging electric vehicles (EVs) both in stationary mode and on the go, i.e., dynamic charging. EVs are produced at a commercial level, and their wired charging stations are widely available. However, challenges still restrict the development of wireless charging infrastructure on a commercial scale. One significant challenge is the presence of foreign objects on the magnetic coupler surface. Although several foreign object detection (FOD) methods exist, the implementation of each method is cost-dependent. Among these methods, the parametric detection method is considered the most cost-effective. However, the effective precision of this method is still debatable. In this article, the performance of the magnetic coupler is analyzed under the influence of different materials as foreign objects. The analysis presented in this article is threefold. Firstly, a mathematical model of the magnetic coupler in the presence of a foreign object is developed. Secondly, the effect of different materials is analyzed as a function of coil parameters, including inductance, resistance, and coil losses. Lastly, the magnetic field distribution and magnitude are studied using finite element analysis (FEA). The influence of these materials is ultimately evaluated in terms of output power losses and efficiency. The study concludes that the presence of aluminium as a foreign object is responsible for significant power losses in the wireless power transfer system.

关键词： Coils Magnetic flux Inductive charging Couplers Wireless power transfer Voltage Electric vehicles Mathematical models Magnetic analysis Magnetic fields

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DMINet: A lightweight dual-mixed channel-independent network for cataract recognition

DMINet: A lightweight dual-mixed channel-independent network...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiao Wu Yu Chen Qiuyang Yan Yuhang Zhao Jilu Zhao Xiaoqing Zhang Risa Higashita Jiang Liu Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Tomey Corporation Nagoya Japan Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China

Cataracts are the leading cause of visual impairment and blindness globally attracting abroad attention from society. Over the years researchers have developed many state-of-the-art convolutional neural networks (CNNs) to recognize cataract severity levels based on different ophthalmic images. However most current works focus on improving cataract recognition performance by designing complex CNNs often ignoring resource-constrained medical device limitations. To this problem this paper proposes a novel dual-mixed channel-independent convolution (DMIConv) method which takes advantage of the multiscale convolution kernels by combining a depthwise convolution with a depthwise dilated convolution sequentially. Moreover we build a lightweight dual-mixed channel-independent network (DMINet) to recognize cataracts. To verify the effectiveness and efficiency of DMINet we conduct extensive experiments on a clinical anterior segment optical coherence tomography (AS-OCT) dataset of nuclear cataract (NC) and a publicly available OCT dataset. The results show that our proposed DMINet keeps a better tradeoff between the model complexity and the classification performance than efficient CNNs e.g DMINet outperforms MixNet by 3.34% of accuracy by using 4.58 % fewer parameters

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