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Towards Prevention of Sportsmen Burnout:Formal Analysis of Sub-Optimal Tournament Scheduling

computers, Materials & Continua 2022年第1期70卷 1509-1526页

作者： Syed Rameez Naqvi Adnan Ahmad S.M.Riazul Islam Tallha Akram M.Abdullah-Al-Wadud Atif Alamri Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Research Chair of Pervasive and Mobile Computing King Saud UniversityRiyadh11543Saudi Arabia

Scheduling a sports tournament is a complex optimization problem,which requires a large number of hard constraints to *** the availability of several such constraints in the literature,there remains a gap sincemost of the new sports events pose their own unique set of requirements,and demand novel *** talking of the strictly time bound events,ensuring fairness between the different teams in terms of their rest days,traveling,and the number of successive games they play,becomes a difficult task to resolve,and demands *** this work,we present a similar situation with a recently played sports event,where a suboptimal schedule favored some of the sides more than the *** introduce various competitive parameters to draw a fairness comparison between the sides and propose a weighting criterion to point out the sides that enjoyed this schedule more than the ***,we use root mean squared error between an ideal schedule and the actual ones for each side to determine unfairness in the distribution of rest days across their entire *** latter is crucial,since successively playing a large number of games may lead to sportsmen burnout,which must be prevented.

关键词： Sports scheduling optimization constraint programming fatigue analysis

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Power Optimization for Low Transmission Delay in Software Defined Data Center Networks

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IEEE Transactions on mobile computing 2025年第7期24卷 5716-5730页

作者： Zhao, Yong Cao, Jiannong Wang, Xingwei Li, Fuliang He, Qiang Liu, Xiaojie University of Electronic Science and Technology of China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Laboratory of Intelligent Collaborative Computing Chengdu611731 China Hong Kong Polytechnic University Department of Computing Hung Hom Hong Kong Northeastern University College of Computer Science and Engineering Shenyang110819 China Northeastern University College of Medicine and Biological Information Engineering Shenyang110819 China Pengcheng Laboratory Shenzhen518066 China

Software-Defined Data Center Networks (SDDCNs) utilizes Software Defined Networking (SDN) as a network architecture to achieve highly flexible, programmable, and automated management of Data Center Networks (DCNs). The high energy consumption of DCNs remains a persistent and significant challenge. Thus, the energy saving is crucial and imperative for DCNs. Current energy-efficient solutions primarily rely on flow consolidation and dynamic device sleeping techniques to reduce energy consumption. However, these approaches often yield long Flow Completion Time (FCT), potentially resulting in violations of service-level agreements, particularly for delay-sensitive applications. In this paper, we formulate the problem of minimizing the power consumption in SDDCNs as key objective while ensuring timely FCT for delay-sensitive applications. To solve this problem, we first introduce the Active Network Generation (ANG) approach, which generates a minimal active subnet with the least number of active devices while meeting the current traffic demand. Subsequently, we propose two algorithms based on the type of applications: the Delay-Tolerant Flow Route (DTFR) algorithm for delay-tolerant applications and the Delay-Sensitive Flow Route (DSFR) algorithm for delay-sensitive applications. Simulation results demonstrate that our propose solution achieves an energy-saving rate of up to 67.77% and significantly reduces FCT compared to benchmark solutions. © 2002-2012 IEEE.

关键词： Energy efficiency

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Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

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Digital Communications and Networks 2023年第2期9卷 400-410页

作者： Lingwei Xu Hao Yin Hong Jia Wenzhong Lin Xinpeng Zhou Yong Fu Xu Yu Department of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen UniversityXiamen361005China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University) Fuzhou350121China Faculty of Information Science and Engineering Ocean University of ChinaQingdao266100China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)JinanChina

mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent *** mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all *** variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication *** data secure transmission is critical for mobile IIoT *** paper investigates the data secure transmission performance prediction of mobile IIoT *** cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first ***,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction *** mobile signals,the important features may be removed by the pooling *** will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is *** of the input and output layers,it removes the pooling layer and contains six convolution ***,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed *** simulation analysis,good prediction accuracy is achieved by the CNN *** prediction accuracy obtains a 59%increase.

关键词： mobile IIoT networks Data secure transmission Performance analysis Intelligent prediction Improved CNN

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A Demonstration of QoE Assessment for Cloud-based Social XR Applications over mobile Networks

A Demonstration of QoE Assessment for Cloud-based Social XR ...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Henrique Souza Rossi Karan Mitra Justin Gavrell Christer Åhlund Pervasive and Mobile Computing Department of Computer Science Electrical and Space Engineering Luleå University of Technology Skellefteå Sweden

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

Cloud-based social eXtended Reality (XR) services are the cornerstone for realizing the promises of the Metaverse. These services hosted either on datacenters or edge, will demand stringent mobile network quality of service (QoS) to operate effectively and provide an acceptable user quality. It becomes fundamental to study how mobile networks QoS factors round-trip time (RTT), packet loss (PL), and jitter affect these services by measuring their effect on users' perceived quality of experience (QoE). Subjective QoE assessment involves carefully controlled laboratory environments to generate the desired conditions between a large set of users. The requirements for a cloud-based social XR service lab-setup are complex: Identify a reliable streaming service, a customizable VR application, emulate network conditions, define activities or tasks for users to perform, collect their data, label it; all while mitigating possible human mistakes. To address these requirements, we present an effective technical setup that can consistently repeat the same conditions between users and that can be easily replicated to other labs conducting cloud-based social XR research.

关键词： Cloud computing Metaverse Extended reality Laboratories Packet loss Quality of service Jitter Time measurement Quality of experience Reliability

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Diversified and compatible web APIs recommendation based on game theory in IoT

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Digital Communications and Networks 2024年第4期10卷 1198-1209页

作者： Wenwen Gong Huiping Wu Xiaokang Wang Xuyun Zhang Yawei Wang Yifei Chen Mohammad R.Khosravi College of Information and Electrical Engineering China Agricultural UniversityBeijing100000China Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyShouguang262700China Department of Computer Science St.Francis Xavier UniversityAntigonishNSCanada Department of Computing Macquarie UniversitySydneyNSW2122Australia Department of Computer Engineering Persian Gulf UniversityBushehr***Iran Department of Electrical and Electronic Engineering Shiraz University of TechnologyShiraz71557-13876Iran

With the ever-increasing popularity of Internet of Things(IoT),massive enterprises are attempting to encapsulate their developed outcomes into various lightweight Web Application Programming Interfaces(APIs)that can be accessible *** this context,finding and writing a list of existing Web APIs that can collectively meet the functional needs of software developers has become a promising approach to economically and easily develop successful mobile ***,the number and diversity of candidate IoT Web APIs places an additional burden on application developers’Web API selection decisions,as it is often a challenging task to simultaneously ensure the diversity and compatibility of the final set of Web APIs *** this challenge and latest successful applications of game theory in IoT,a Diversified and Compatible Web APIs Recommendation approach,namely DivCAR,is put forward in this *** of all,to achieve API diversity,DivCAR employs random walk sampling technique on a pre-built“API-API”correlation graph to generate diverse“API-API”correlation ***,with the diverse“API-API”correlation subgraphs,the compatible Web APIs recommendation problem is modeled as a minimum group Steiner tree search problem.A sorted set of multiple compatible and diverse Web APIs are returned to the application developer by solving the minimum group Steiner tree search *** last,a set of experiments are designed and implemented on a real dataset crawled from *** results validate the effectiveness and efficiency of our proposed DivCAR approach in balancing the Web APIs recommendation diversity and compatibility.

关键词： Internet of things Web APIs recommendation Game theory Diversity and compatibility

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Transfer Learning-Assisted DementiaNet: A Four Layer Deep CNN for Accurate Alzheimer’s Disease Detection from MRI Images 16th

Transfer Learning-Assisted DementiaNet: A Four Layer Deep CN...

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16th International Conference on Brain Informatics, BI 2023

作者： Umme Habiba, Sultana Debnath, Tanoy Islam, Md. Khairul Nahar, Lutfun Shahadat Hossain, Mohammad Basnin, Nanziba Andersson, Karl Khulna University of Engineering & Technology Khulna Bangladesh Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science and Engineering University of Chittagong Chittagong Bangladesh Leeds Beckett University Leeds United Kingdom Pervasive and Mobile Computing Laboratory Luleå University of Technology Luleå Sweden

ISBN: (纸本)9783031430749

Alzheimer’s disease is the most common type of dementia and the sixth highest cause of mortality among people over 65. Also, according to statistics, the number of deaths from Alzheimer’s disease has increased dramatically. As a result, early detection of Alzheimer’s disease can improve patient survival chances. Machine learning methods using magnetic resonance imaging have been utilized in the diagnosis of Alzheimer’s disease to help clinicians and speed up the procedure. This research mainly focuses on Alzheimer’s disease detection to overcome previous limitations. We use a publicly available dataset which contains 6400 MRI images. In order to train our dataset, we employ our suggested model, "DementiaNet", using "EfficientNet" as a feature extractor and a Deep CNN as a classifier. In order to capture all the features, this framework uses a small number of convolutional layers, which improves the effectiveness of feature learning and results in a more accurate and reliable output. In addition, to address the issue of data imbalance, we apply data augmentation to enhance the size of the minority class by considering four stages of dementia. Also, in this study, we take advantage of the transfer learning approach with the attachment of "EfficientNet", which allows our model to easily solve the overfitting problem and also extract all the features in a effective way. Finally, we compare our proposed models with those reported in the literature. Our experimental results indicate that our "DementiaNet" model achieve an overall classification accuracy of 97% to detect Alzheimer from brain MRI images, exceeding all other state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Magnetic resonance imaging

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Adaptive Multi-modal Data Fusion Method for Dermatosis Diagnosis

Adaptive Multi-modal Data Fusion Method for Dermatosis Diagn...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Li, Yaning Yang, Xiaodong Chen, Yiqiang Chen, Shubai Zeng, Bixiao Cai, Hong Chinese Academy of Sciences The Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Beijing China University of Jinan College of Information Science and Engineering Shandong China Shandong Academy of Intelligent Computing Technology Shandong China Air Force Medical Center of the PLA Department of Dermatology Beijing China

ISBN: (纸本)9798350337488

Meta-data, e.g., gender, medical history, etc., is of vital importance for dermatosis diagnosis clinically, while most existing AI-based methods ignore this information and only employ dermoscopy images. Due to the modality disequilibrium of image and meta-data, there would be unequal optimization during the modal fusion, resulting in the weak meta-data modality being suppressed and losing their contributions to the classification. To address this issue, we propose an Adaptive Multi-modal Fusion (AMF) method for dermatosis diagnosis, which reweights the fusion factor of image and meta-data by evaluating their optimization discrepancy through the Euclidean norm. What's more, the Co-Attention mechanism is employed to align the two modalities implicitly. To evaluate the effectiveness of the proposed method, extensive experiments are conducted on multi-modal dermatosis public datasets including ISIC 2019, PDA-UFES-20, and HAM10000. The results demonstrate that the proposed method can achieve better performance in comparison to the state-of-the-art methods. © 2023 IEEE.

关键词： Deep Learning Dermatosis Diagnosis Multi-modal Fusion Transformer

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Distributed reinforcement learning based framework for energy-efficient UAV relay against jamming

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Intelligent and Converged Networks 2021年第2期2卷 150-162页

作者： Weihang Wang Zefang Lv Xiaozhen Lu Yi Zhang Liang Xiao Department of Information and Communication Engineering Xiamen UniversityXiamen 361005China Beijing Key Laboratory of Mobile Computing and Pervasive Device Beijing 100190China

Unmanned aerial vehicle(UAV)network is vulnerable to jamming attacks,which may cause severe damage like communication *** to the energy constraint,the source UAV cannot blindly enlarge the transmit power,along with the complex network topology with high mobility,which makes the destination UAV unable to evade the jammer by flying at *** maintain communication with a limited battery capacity in the UAV networks in the presence of a greedy jammer,in this paper,we propose a distributed reinforcement learning(RL)based energy-efficient framework for the UAV networks with constrained energy under jamming attacks to improve the communication quality while minimizing the total energy consumption of the *** framework enables each relay UAV to independently select its transmit power based on historical state-related information without knowing the moving trajectory of other UAVs as well as the *** location and battery level of each UAV need not be shared with other *** also propose a deep RL based anti-jamming relay approach for UAVs with portable computation equipment like Raspberry Pi to achieve higher and faster *** study the Nash equilibrium(NE)and the performance bounds based on the formulated power control *** results show that the proposed schemes can reduce the bit error rate(BER)and reduce energy consumption of the UAV network compared with the benchmark method.

关键词： unmanned aerial vehicles relay jamming reinforcement learning

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A metasurface-based light-to-microwave transmitter for hybrid wireless communications

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Light(science & Applications) 2022年第6期11卷 1139-1148页

作者： Xin Ge Zhang Ya Lun Sun Bingcheng Zhu Wei Xiang Jiang Qian Yu Han Wei Tian Cheng-Wei Qiu Zaichen Zhang Tie Jun Cui State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University210096 NanjingChina National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University210096 NanjingChina Frontiers Science Center for Mobile Information Communication and Security Southeast University210096 NanjingChina Purple Mountain Laboratories 211111 NanjingChina Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

Signal conversion plays an important role in many applications such as communication,sensing,and *** signal conversion between optical and microwave frequencies is a crucial step to construct hybrid communication systems that combine both optical and microwave wireless technologies to achieve better features,which are highly desirable in the future wireless ***,such a signal conversion process typically requires a complicated relay to perform multiple operations,which will consume additional hardware/time/energy ***,we report a light-to-microwave transmitter based on the time-varying and programmable metasurface integrated with a high-speed photoelectric detection circuit into a *** a transmitter can convert a light intensity signal to two microwave binary frequency shift keying signals by using the dispersion characteristics of the metasurface to implement the frequency division *** illustrate the metasurface-based transmitter,a hybrid wireless communication system that allows dual-channel data transmissions in a light-to-microwave link is demonstrated,and the experimental results show that two different videos can be transmitted and received simultaneously and *** metasurface-enabled signal conversion solution may enrich the functionalities of metasurfaces,and could also stimulate new information-oriented applications.

关键词： microwave surface light

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Energy Efficient Probabilistic Semantic Communication over SAGIN

Energy Efficient Probabilistic Semantic Communication over S...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhao, Zhouxiang Yang, Zhaohui Chen, Mingzhe Gan, Xu Huang, Chongwen Xu, Wei Zhang, Zhaoyang Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Hangzhou China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States Southeast University National Mobile Communications Research Laboratory Nanjing China

ISBN: (纸本)9798350351255

In this paper, the energy efficiency maximization problem in space-air-ground integrated network (SAGIN)-enabled probabilistic semantic communication (PSC) is investigated. In the considered model, a satellite needs to transmit data to multiple ground terminals (GTs) via an unmanned aerial vehicle (UAV) acting as a relay. During transmission, the satellite and the UAV can use PSC technique to compress the transmitted data, while the GTs can automatically recover the original data. In the considered PSC system, shared probability graphs serve as a common knowledge base among the transceivers, allowing for resource-saving communication at the expense of increased computation resource. Therefore, it is important to study the trade-off between communication and computation to achieve optimal energy efficiency. The joint communication and computation problem is formulated as an optimization problem aiming to minimize the total communication and computation energy consumption of the network under latency, semantic compression ratio, and UAV location constraints. To solve this non-convex problem, we propose an alternating algorithm. Numerical results show the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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