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作者： Cao, Kun Wei, Tongquan Chen, Mingsong Li, Keqin Weng, Jian Tan, Wuzheng College of Information Science and Technology/College of Cyber Security Jinan University Guangzhou China School of Computer Science and Technology East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Department of Computer Science State University of New York New PaltzNY United States

In recent years, the advance in information technology has promoted a wide span of emerging cyber-physical systems (CPS) applications such as autonomous automobile systems, healthcare monitoring, and process control systems. For these CPS applications, service latency management is extraordinarily important for the sake of providing high quality-of-experience to terminal users. Edge-cloud computing, integrating both edge computing and cloud computing, is regarded as a promising computation paradigm to achieve low service latency for terminal users in CPS. However, existing latency-aware edge-cloud computing methods dedicated for CPS fail to jointly consider energy budgets and reliability requirements, which may greatly degrade the sustainability of CPS applications. In this article, we explore the problem of minimizing service latency of edge-cloud computing coupled CPS under the constraints of energy budgets and reliability requirements. We propose a two-stage approach composed of static and dynamic service latency optimization. At static stage, Monte-Carlo simulation with integer-linear-programming technique is adopted to find the optimal computation offloading mapping and task backup number. At dynamic stage, a backup-adaptive dynamic mechanism is developed to avoid redundant data transmissions and executions for achieving additional energy savings and service latency enhancement. Experimental results show that our solution is able to reduce system service latency by up to 18.3% compared with representative baseline solutions. © 2021 John Wiley & Sons, Ltd.

关键词： Cyber Physical System

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NOMANet: A Graph Neural Network Enabled Power Allocation Scheme for NOMA

arXiv

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arXiv 2025年

作者： Hou, Yipu Lu, Yang Chen, Wei Ai, Bo Niyato, Dusit Ding, Zhiguo State Key Laboratory of Advanced Rail Autonomous Operation China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China College of Computing and Data Science Nanyang Technological University 639798 Singapore Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates

This paper proposes a graph neural network (GNN) enabled power allocation scheme for non-orthogonal multiple access (NOMA) networks. In particular, a downlink scenario with one base station serving multiple users over several subchannels is considered, where the number of subchannels is less than the number of users, and thus, some users have to share a subchannel via NOMA. Our goal is to maximize the system energy efficiency subject to the rate requirement of each user and the overall budget. We propose a deep learning based approach termed NOMA net (NOMANet) to address the considered problem. Particularly, NOMANet is GNN-based, which maps channel state information to the desired power allocation scheme for all subchannels. The multi-head attention and the residual/dense connection are adopted to enhance the feature extraction. The output of NOMANet is guaranteed to be feasible via the customized activation function and the penalty method. Numerical results show that NOMANet trained unsupervised achieves performance close to that of the successive convex approximation method but with a faster inference speed by about 700 times. Besides, NOMANet is featured by its scalability to both users and subchannels. © 2025, CC BY.

关键词： Channel state information

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Reciprocating Magnetic Fields in the Pulsar Wind Observed from the Black Widow Pulsar J1720-0534

引用

Research in Astronomy and Astrophysics 2023年第10期23卷 255-266页

作者： Chen-Chen Miao Victoria Blackmon Wei-Wei Zhu Dong-Zi Li Ming-Yu Ge Xiao-Peng You Maura McLaughlin Di Li Na Wang Pei Wang Jia-Rui Niu M.Cruces Jian-Ping Yuan Jun-Tao Bai D.J.Champion Yu-Tong Chen Ming-Min Chi P.C.C.Freire Yi Feng Zhen-Ye Gan M.Kramer Fei-Fei Kou Yu-Xi Li Xue-Li Miao Ling-Qi Meng Chen-Hui Niu Sheng-Nan Sun Zhong-Yi Sun H.M.Tedila Shuang-Qiang Wang Qing-Dong Wu Jing-Bo Wang Zhi-Gang Wen Shen Wang Ya-Biao Wang Cheng-Jie Wang Meng-Yao Xue You-Ling Yue Mao Yuan Ju-Mei Yao Wen-Ming Yan Ru-Shuang Zhao Lei Zhang De Zhao National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China West Virginia University 1500 University AveMorgantownWV 26506USA Institute for Frontiers in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China Cahill Center for Astronomy and Astrophysics California Institute of Technology1216 E California BoulevardPasadenaCA 91125USA Key Laboratory of Particle Astrophysics Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China School of Physical Science and Technology Southwest UniversityChongqing 400715China Research Center for Intelligent Computing Platforms Zhejiang LaboratoryHangzhou 311100China Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China Max-Planck Institut für Radioastronomie Auf dem Hügel 69D-53121 BonnGermany School of Computer Science Fudan UniversityShanghai 200433China Tencent Youtu Lab Shanghai 200233China College of Physical Science and Technology Central China Normal UniversityWuhan 430079China Institute of Optoelectronic Technology Lishui UniversityLishui 323000China Guizhou Normal University Guiyang 550001China

We report the radio observations of the eclipsing black widow pulsar J1720-0534, a 3.26 ms pulsar in orbit with a low mass companion of mass 0.029 to 0.034 M⊙. We obtain the phase-connected timing ephemeris and polarization profile of this millisecond pulsar(MSP) using the Five-hundred-meter Aperture Spherical radio Telescope(FAST), the Green Bank Telescope(GBT), and the Parkes Telescope. For the first time from such a system, an oscillatory polarization angle change was observed from a particular eclipse egress with partial depolarization, indicating 10-milliGauss-level reciprocating magnetic fields oscillating in a length scale of 5 ×10^(3)km(assuming an orbital inclination angle of 90°) outside the companion's magnetosphere. The dispersion measure variation observed during the ingresses and egresses shows the rapid raising of the electron density in the shock boundary between the companion's magnetosphere and the surrounding pulsar wind. We suggest that the observed oscillatory magnetic fields originate from the pulsar wind outside the companion's magnetosphere.

关键词： (stars:)pulsars:general (stars:)pulsars:individual(J1720-0534) (stars:)binaries:eclipsing

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Dual-Branch Attention Network and Swin Spatial Pyramid Pooling for Retinopathy of Prematurity Classification

Dual-Branch Attention Network and Swin Spatial Pyramid Pooli...

引用

IEEE International Symposium on Biomedical Imaging

作者： Jia Zhao Haijun Lei Hai Xie Pingkang Li Yaling Liu Guoming Zhang Baiying Lei Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Shenzhen China National- Regional Key Technology Engineering Laboratory for Medical Ultrasound Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Shenzhen Eye Hospital Shenzhen Key Ophthalmic Laboratory Health Science Center Shenzhen University The Second Affiliated Hospital of Jinan University Shenzhen China

Retinopathy of prematurity (ROP) is an abnormal proliferative vascular disorder that causes blindness and vision impairment in premature children. Early diagnosis of ROP is crucial in reducing the blindness rate. However, traditional convolutional neural networks (CNNs) fail to optimize the global information of pathology images, while the recent popular vision transformer (ViT) model neglects the local details. Also, ROP has a small lesion region and relatively little data. To solve above issues, we propose a dual-branch network, which is a parallel structure composed of ResNet-50 and multi-axis vision transformer (MaxViT) for capturing local and global information about fundus images simultaneously. Multi-scale features are extracted using the Swin Spatial Pyramid Pooling (Swin-SPP) operation in SwinViT blocks. The convolutional block attention module (CBAM) is utilized to highlight the channel and spatial relationships of ROP staging features. The experimental results on internal ROP dataset indicate that our method shows promising for ROP staging.

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Socially Beneficial Metaverse: Framework, Technologies, Applications, and Challenges

arXiv

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arXiv 2023年

作者： Xu, Xiaolong Zhou, Xuanhong Bilal, Muhammad Zeadally, Sherali Crowcroft, Jon Qi, Lianyong Xue, Shengjun Nanjing University of Information Science and Technology Nanjing China School of Software Nanjing University of Information Science and Technology Nanjing China School of Computing and Communications Lancaster University Lancaster United Kingdom College of Communication and Information University of Kentucky Lexington United States Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom State Key Laboratory for Novel Software Technology Nanjing University China School of Computer Science and Technology Silicon Lake College Suzhou China

In recent years, the maturation of emerging technologies such as Virtual Reality, Digital Twin,s and Blockchain has accelerated the realization of the metaverse. As a virtual world independent of the real world, the metaverse will provide users with a variety of virtual activities which bring great convenience to society. In addition, the metaverse can facilitate digital twins, which offers transformative possibilities for the industry. Thus, the metaverse has attracted the attention of the industry, and a huge amount of capital is about to be invested. However, the development of the metaverse is still in its infancy and little research has been undertaken so far. We describe the development of the metaverse. Next, we introduce the architecture of the socially beneficial metaverse (SB-Metaverse) and we focus on the technologies that support the operation of SB-Metaverse. In addition, we also present the applications of SB-Metaverse. Finally, we discuss several challenges faced by SB-Metaverse which must be addressed in the *** Codes 68U01, 68M11, 68U35 © 2023, CC BY.

关键词： Blockchain

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Cluster-guided Contrastive Class-imbalanced Graph Classification

arXiv

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arXiv 2024年

作者： Ju, Wei Mao, Zhengyang Yi, Siyu Qin, Yifang Gu, Yiyang Xiao, Zhiping Shen, Jianhao Qiao, Ziyue Zhang, Ming College of Computer Science Sichuan University Chengdu China School of Computer Science State Key Laboratory for Multimedia Information Processing PKU-Anker LLM Lab Peking University Beijing China College of Mathematics Sichuan University Chengdu China Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA United States Huawei Hisilicon Shanghai China School of Computing and Information Technology Great Bay University Dongguan China

This paper studies the problem of class-imbalanced graph classification, which aims at effectively classifying the categories of graphs in scenarios with imbalanced class distribution. Despite the tremendous success of graph neural networks (GNNs), their modeling ability for imbalanced graph-structured data is inadequate, which typically leads to predictions biased towards the majority classes. Besides, existing class-imbalanced learning methods in visions may overlook the rich graph semantic substructures of the majority classes and excessively emphasize learning from the minority classes. To tackle this issue, this paper proposes a simple yet powerful approach called C3GNN that incorporates the idea of clustering into contrastive learning to enhance class-imbalanced graph classification. Technically, C3GNN clusters graphs from each majority class into multiple subclasses, ensuring they have similar sizes to the minority class, thus alleviating class imbalance. Additionally, it utilizes the Mixup technique to synthesize new samples and enrich the semantic information of each subclass, and leverages supervised contrastive learning to hierarchically learn effective graph representations. In this way, we can not only sufficiently explore the semantic substructures within the majority class but also effectively alleviate excessive focus on the minority class. Extensive experiments on real-world graph benchmark datasets verify the superior performance of our proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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Optimizing Generative AI Networking: A Dual Perspective with Multi-Agent Systems and Mixture of Experts

arXiv

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arXiv 2024年

作者： Zhang, Ruichen Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Zhang, Ping Kim, Dong In The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In the continued development of next-generation networking and artificial intelligence content generation (AIGC) services, the integration of multi-agent systems (MAS) and the mixture of experts (MoE) frameworks is becoming increasingly important. Motivated by this, this article studies the contrasting and converging of MAS and MoE in AIGC-enabled networking. First, we discuss the architectural designs, operational procedures, and inherent advantages of using MAS and MoE in generative AI to explore its functionality and applications fully. Next, we review the applications of MAS and MoE frameworks in content generation and resource allocation, emphasizing their impact on networking operations. Subsequently, we propose a novel multi-agent-enabled MoE-proximal policy optimization (MoE-PPO) framework for 3D object generation and data transfer scenarios. The framework uses MAS for dynamic task coordination of each network service provider agent and MoE for expert-driven execution of respective tasks, thereby improving overall system efficiency and adaptability. The simulation results demonstrate the effectiveness of our proposed framework and significantly improve the performance indicators under different network conditions. Finally, we outline potential future research directions. © 2024, CC BY.

关键词： Multi agent systems

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Electrical Transport Properties of Few-Layer SnS2 Field-effect Transistors

Electrical Transport Properties of Few-Layer SnS2 Field-effe...

引用

2022 International Conference on Electrical, Electronics and Information Engineering, EEIE 2022

作者： Zhang, Lu Li, Tuo Yao, Peng Zou, Xiaofeng Ji, Chao Zhan, Yongzheng He, Jiaqi Zhang, Qing State Key Laboratory of High-end Server & Storage Technology Jinan250013 China Inspur Electronic Information Industry Co. Ltd. Jinan250013 China Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. Ltd. Jinan250013 China Beijing Institute of Computer Technology and Application Beijing100854 China College of Mathematics and Physics Beijing University of Chemical Technology Beijing100029 China

After the discovery of graphene in 2004, two dimensional (2D) materials have fascinated a lot of view due to the excellent properties. Nowadays, the research on 2D materials has spread to other graphene-like layer structured materials, especially transition metal dichalcogenides (TMDCs). Tin disulfide (SnS2) is a kind of TMDCs with a sizable bandgap. Here we introduce few-layer SnS2 field-effect transistors (FETs) fabricated using micromechanical exfoliation method. The FETs show n-type behavior, the on/off ratio exceeding 0.54×104 and the carrier mobility is 0.61 cm2V-1s-1. The electronic and optical characteristics of SnS2 flakes with a finite bandgap illustrate their potential applications in optoelectronics device. © Published under licence by IOP Publishing Ltd.

关键词： Field effect transistors

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Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices

arXiv

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arXiv 2024年

作者： Zeng, Hongye Zou, Ke Chen, Zhihao Gao, Yuchong Chen, Hongbo Zhang, Haibin Zhou, Kang Wang, Meng Goh, Rick Siow Mong Liu, Yong Jiang, Chang Zheng, Rui Fu, Huazhu School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China University of Chinese Academy of Sciences Beijing China National Key Laboratory of Fundamental Science on Synthetic Vision College of Computer Science Sichuan University Chengdu China College of Intelligence and Computing Tianjin University Tianjin China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Beth Israel Deaconess Medical Center Harvard Medical School Boston United States Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore Department of Orthopedics Zhongshan Hospital Fudan University Shanghai China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai China

Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data. In this study, we propose the Training-free Image Style Alignment (TISA) framework to align the style of handheld device data to those of standard devices. The proposed TISA can directly infer handheld device images without extra training and is suited for clinical applications. We show that TISA performs better and more stably in medical detection and segmentation tasks for handheld device data. We further validate TISA as the clinical model for automatic measurements of spinal curvature and carotid intima-media thickness. The automatic measurements agree well with manual measurements made by human experts and the measurement errors remain within clinically acceptable ranges. We demonstrate the potential for TISA to facilitate automatic diagnosis on handheld ultrasound devices and expedite their eventual widespread use. © 2024, CC BY-NC-SA.

关键词： Deep learning

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Perceptual Quality Assessment of Virtual Reality Videos in the Wild

arXiv

引用

arXiv 2022年

作者： Wen, Wen Li, Mu Yao, Yiru Sui, Xiangjie Zhang, Yabin Lan, Long Fang, Yuming Ma, Kede Department of Computer Science City University of Hong Kong Kowloon Hong Kong School of Computer Science and Technology Harbin Institute of Technology Guangdong Shenzhen518055 China School of Information Management Jiangxi University of Finance and Economics Jiangxi Nanchang330032 China Multimedia Lab Bytedance Inc China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

Investigating how people perceive virtual reality (VR) videos in the wild (i.e., those captured by everyday users) is a crucial and challenging task in VR-related applications due to complex *** video databases only consider synthetic distortions, assume fixed viewing conditions, and are limited in size. To overcome these shortcomings, we construct the VR Video Quality in the Wild (VRVQW) database, containing 502 user-generated videos with diverse content and distortion characteristics. Based on VRVQW, we conduct a formal psychophysical experiment to record the scanpaths and perceived quality scores from 139 participants under two different viewing conditions. We provide a thorough statistical analysis of the recordeddata, observing significantimpact of viewing conditions on both human scanpaths and perceived quality. Moreover, we develop an objective quality assessment model for VR videos based on pseudocylindrical representation and convolution. Results on the proposed VRVQW show that our method is superior to existing video quality assessment *** have made the database and code available at https://***/ limuhit/VR-Video-Quality-in-the-Wild. Index Terms-Virtual reality, panoramic videos, video quality assessment, psychophysics. Copyright © 2022, The Authors. All rights reserved.

关键词： Virtual reality

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