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PACE: Reputation-Driven Hierarchical Incentive Mechanism for Trusted Healthcare Transactions in Model Marketplace

IEEE Transactions on Consumer Electronics 2024年第1期71卷 1571-1583页

作者： Lu, Jianfeng Dou, Xiaochi Rathore, Bharati Jhaveri, Rutvij H. Seid, Abegaz Mohammed Erbad, Aiman Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Ministry of Education Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology China United Kingdom Pandit Deendayal Energy University Department of Computer Science and Engineering School of Technology India Hamad Bin Khalifa University College of Science and Engineering Doha Qatar Qatar University College of Engineering Doha Qatar

Federated learning-based model marketplaces have the potential to securely leverage healthcare data for efficient healthcare transactions. However, the willingness to participate in this marketplace is severely hindered by self-interested model sellers, who maximize their personal gains via distorting the quality of their models. To this end, we propose a rePutation-driven hierArchical inCentive mEchanism, called PACE, which combines contract cooperation and game pricing to motivate model sellers to be honest, thereby improving the sustainability of the model marketplace via two-layer cooperation. Specifically, at the training layer, we design a reward payment rule based on multidimensional contracts, while at the trading layer, we use a competitive market pricing game to develop the accuracy pricing rule. In particular, the above rules cleverly combine the fine-grained model sellers' reputations with the willingness of healthcare devices to indirectly affect the model sellers' utilities. Theoretically, we prove that PACE can effectively incentivize model sellers to truthfully report model quality while satisfying both individual rationality and incentive compatibility with a fairness guarantee. Experimental results conducted on four real-world datasets show that our PACE improves the global performance by up to 12.85% and reduces the global loss by at least 19.23% compared with the state-of-the-art baselines. © 1975-2011 IEEE.

关键词： Marketplaces

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An Improved YOLOv5s-Based Smoke Detection system for Outdoor Parking Lots

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Computers, Materials & Continua 2024年第8期80卷 3333-3349页

作者： Ruobing Zuo Xiaohan Huang Xuguo Jiao Zhenyong Zhang State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China School of Information and Control Engineering Qingdao University of TechnologyQingdao266520China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou310027China Key Laboratory of Computing Power Network and Information Security Ministry of EducationQilu University of Technology(Shandong Academy of Sciences)Jinan250353China Text Computing&Cognitive Intelligence Engineering Research Center of National Education Ministry Guizhou UniversityGuiyang550025China

In the rapidly evolving urban landscape,outdoor parking lots have become an indispensable part of the city’s transportation *** growth of parking lots has raised the likelihood of spontaneous vehicle combus-tion,a significant safety hazard,making smoke detection an essential preventative ***,the complex environment of outdoor parking lots presents additional challenges for smoke detection,which necessitates the development of more advanced and reliable smoke detection *** paper addresses this concern and presents a novel smoke detection technique designed for the demanding environment of outdoor parking ***,we develop a novel dataset to fill the gap,as there is a lack of publicly available *** dataset encompasses a wide range of smoke and fire scenarios,enhanced with data augmentation to ensure robustness against diverse outdoor ***,we utilize an optimized YOLOv5s model,integrated with the Squeeze-and-Excitation Network(SENet)attention mechanism,to significantly improve detection accuracy while maintaining real-time processing ***,this paper implements an outdoor smoke detection system that is capable of accurately localizing and alerting in real time,enhancing the effectiveness and reliability of emergency *** show that the system has a high accuracy in terms of detecting smoke incidents in outdoor scenarios.

关键词： YOLOv5s smoke detection deep learning SENet

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Mini-Savi: Realistic Satellite Network Simulation Platform Based on Open-Source Tools 4

Mini-Savi: Realistic Satellite Network Simulation Platform B...

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4th International Conference on Frontiers of Computers and Communication engineering, FCCE 2023

作者： Tang, Zhu Zhao, Jingjing Li, Hu Guo, Tianhang Wang, Quan Chen, Hongyan Zhao, Baokang National University of Defense Technology College of Computer Changsha China National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350333169

Recently, mega satellite constellations are very popular for global instant messaging, and inter-satellite links are planned for delay reduction, leading to satellite network architecture finally. Although there are many satellite orbit simulation tools (e.g. STK, Savi) and network simulation tool (e.g. NS2/3, OPNET, Mininet, SNS3), none of them gives good consideration to both. In this paper, a satellite network and orbit integrated simulation platform (Mini-Savi) is proposed for large scale satellite constellation, which is based on the combination of network simulation tool Mininet and orbit simulation tool Savi. Finally, a typical satellite constellation Iridium system is employed for simulation verification. © 2023 IEEE.

关键词： Simulation platform

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Polarization‑entangled photon‑pair source with van der Waals 3R‑WS_(2) crystal

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eLight 2024年第1期4卷 99-106页

作者： Jiangang Feng Yun‑Kun Wu Ruihuan Duan Jun Wang Weijin Chen Jiazhang Qin Zheng Liu Guang‑Can Guo Xi‑Feng Ren Cheng‑Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Optical Science and Engineering and Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433China

Ultracompact entangled photon sources are pivotal to miniaturized quantum photonic *** der Waals(vdW)nonlinear crystals promise efficient photon-pair generation and on-chip monolithic integration with nanophotonic ***,it remains challenging to generate maximally entangled Bell states of photon pairs with high purity,generation rate,and fidelity required for practical ***,we realize a polarization-entangled photon-pair source based on spontaneous parametric down conversion in an ultrathin rhombohedral tungsten disulfide(3R-WS2)*** vdW entangled photonic source exhibits a high photon-pair purity with a coincidenceto-accidental ratio of above 800,a generation rate of 31 Hz,and two maximally polarization-entangled Bell states with fidelities exceeding 0.93 and entanglement degree over *** results stem from scalable optical nonlinearity,enhanced second-order susceptibility by electronic transitions,and a well-defined symmetry-enabled selection rule inherent in *** polarization entangled photon source can be integrated with photonic structures for generating more complex entangled states,thus paving an avenue for advanced quantum photonic systems toward computation and metrology.

关键词： purity maximal Polarization

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Energy-Efficient Caching and User Selection for Resource-Limited SAGINs in Emergency Communications

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IEEE Transactions on Communications 2024年第6期73卷 4121-4136页

作者： Wei, Qing Chen, Yingyang Jia, Ziye Bai, Wenle Pei, Tingrui Wu, Qihui North China University of Technology School of Information Beijing100144 China Jinan University College of Information Science and Technology Guangzhou510632 China Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China

The ever-increasing requests of users in emergency communication scenarios lead to high data traffic and transmission delay, posing challenges for resource-limited space-air-ground integrated networks (SAGINs). To address this issue, this paper proposes a joint caching optimization and user selection (JCOUS) problem that leverages unmanned aerial vehicle (UAV) caching to maximize the residual energy of the satellite, considering the limited resources of UAVs. To address the complex time-coupling optimization problem with discrete variables, we propose a primal decomposition method to decouple the problem, and design an energy-efficient user selection algorithm with dynamic caching. Furthermore, to reduce computational complexity and cost, we consider a statistical scenario and maximize the statistical residual energy in the JCOUS problem. Simulation results verify that the proposed scheme can achieve a higher residual energy and fast optimization, thus realizing energy saving and quick decision making especially in large-scale computation-intensive SAGINs. © 1972-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Adaptive Channel Assignment for Wireless Mesh Networks Based on Multi-Intelligent Body Reinforcement Learning 7

Adaptive Channel Assignment for Wireless Mesh Networks Based...

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7th IEEE International Conference on Electronic information and Communication technology, ICEICT 2024

作者： Su, Hang Ye, Fang Su, Chunxia Sun, Xue Harbin Engineering University Key Laboratory of Advanced Marine Communication and Information Technology College of Information and Communication Engineering Harbin China Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology College of Information and Communication Engineering Harbin China Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou China

ISBN: (纸本)9798350384437

With the popularity of emerging applications and the diversification of IoT device needs, wireless mesh networks (WMN) have been recognized as an effective way to solve "last mile"coverage. In the scenario where the network environment status is unknown, an adaptive channel allocation algorithm based on multi-agent reinforcement learning is proposed to solve the problem that static channel allocation in wireless mesh network cannot adapt well to traffic changes in the network environment, resulting in the degradation of link communication quality. Map the channel allocation problem as a multi-agent reinforcement learning process. The state space based on multiple factors such as interference and load is established, and the relationship between exploration and utilization in the algorithm is balanced by using the improved greedy action selection mechanism, and the return function based on link satisfaction is designed to guide the channel selection to improve the quality of link communication. The simulation results show that the proposed algorithm can effectively adapt to the dynamic changes of traffic and source nodes in the network to ensure the quality of user service. © 2024 IEEE.

关键词： MESH networking

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Intensified Tropical Cyclones in Global Climate Simulations Employing a High-Wind Drag Relation over Sea Surface

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Journal of Climate 2025年第10期38卷 2205-2223页

作者： Wei, Wei Lu, Yixiong Yang, Shunan Liu, Yiming Wu, Tongwen Song, Zhenya Qiao, Fangli Li, Yubin Wu, Fanghua Rong, Xinyao Li, Jianglong CMA Earth System Modeling and Prediction Centre China Meteorological Administration Beijing China State Key Laboratory of Severe Weather Meteorological Science and Technology CMA Earth System Modeling and Prediction Centre Beijing China National Meteorological Centre China Meteorological Administration Beijing China First Institute of Oceanography Key Laboratory of Marine Science and Numerical Modeling Ministry of Natural Resources Qingdao China School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing China

Accurate parameterization of momentum fluxes at high winds across the air–sea interface is crucial for realistically simulating the surface wind fields of tropical cyclones (TCs). Climate models often struggle to reproduce observed TC intensities, particularly surface wind speeds. This study evaluates the performance of a revised surface drag scheme with a capping drag coefficient at high wind speeds in global climate models (GCMs). Our results indicate that the revised surface drag scheme significantly improves the representation of TCs in a statistical sense: (i) Not only the mature intensity but also the maximum 10-m wind speeds throughout the TC life cycle are largely enhanced;(ii) biases in the pressure–wind relationship are notably alleviated, exhibiting reasonable agreement with observations;and (iii) other TC statistical features, such as TC number, central sea level pressure, individual lifetime, and intensification rate, show relatively minor sensitivity to the surface drag schemes. The main reason for the superiority of the revised high-wind drag relation is that the lower drag coefficient in high-wind conditions significantly increases the maximum potential intensity (MPI), indicating a higher theoretical limit for TC intensities. These findings are consistent across different model versions and resolutions, highlighting the robustness of the high-wind surface drag parameterization in controlling the simulated surface wind speeds of TCs in GCMs. © 2025 American Meteorological Society.

关键词： Tropical cyclone

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Coexistence of Distributed Sensing and Ultra-simple Coherent RoF based Front-haul for Radio Access Network

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Journal of Lightwave technology 2025年第12期43卷 5669-5675页

作者： Liu, Maoqi Wang, Jingchuan Liu, Chen Yu, Changyuan Lu, Chao Huazhong University of Science and Technology National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Wuhan430074 China The Hong Kong Polytechnic University Photonics Research Institute Department of Electrical and Electronic Engineering Hong Kong

The radio access network requires high-speed transmission and multifunctionality to support the increasing demand for advanced communication services. Radio-over-fiber (RoF) technology fulfills these requirements by enabling the delivery of millimeter-wave (MMW) band wireless signals via optical fiber front-haul. This paper presents an ultra-simple RoF system that achieves the coexistence of distributed sensing and telecommunication. A commercially available coherent modulator achieves signal modulation and remote up-conversion by the beat between the residual carrier and the modulated radio signal. The linear-frequency modulated carrier enables distributed sensing while simultaneously serving as the beat tone of RoF communication, showcasing the potential for integrated sensing and communication (ISAC) applications in next-generation radio access networks. We demonstrate the sensing and transmission performance over a 10-km fiber link and a 1-m wireless MMW channel. The system achieves a distributed sensing detection sensitivity of 28 pΕ/√ Hz and supports 1.6 GBaud 16QAM radio transmission in the Ka-band of 28 GHz. © 1983-2012 IEEE.

关键词： Radio access networks

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Test Suite Generation Based on Context-Adapted Structural Coverage for Testing DNN 24

Test Suite Generation Based on Context-Adapted Structural Co...

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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： Kong, Wei Du, Qianjin Cao, Huayang Li, Hu Wang, Tong Tian, Jianwen Kuang, Xiaohui National Key Laboratory of Science and Technology on Information System Security Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9788995004395

Deep learning (DL) introduces a novel data-driven programming paradigm, where the system logic is constructed through data training. However, this approach poses challenges in terms of system analysis and defect detection. To address this issue, recent efforts have focused on testing deep learning systems using intuitive criteria known as Neuron Coverage (NC) and its variants. These criteria measure the activation proportion of neurons in a neural network. Unfortunately, recent DL applications have largely overlooked the importance of context during testing. To address this gap, this paper first incorporates the context of the DL pipeline deployed before test execution, such as medical diagnosis and Android Malware detection. Next, we formulate structural coverage criteria to guide test suite generation based on the properties of DL pipeline in different contexts. Furthermore, we proposed a coverage-guided search algorithm to efficiently generate test suites. Experimental results highlight the effectiveness of our approach in uncovering numerous erroneous behaviors in contexts such as medical image diagnosis and Android malware detection. This approach significantly enhances the robustness of DL models by considering the structural aspects of the DL pipeline. Copyright 2023 KICS.

关键词： Deep learning

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Monolayer MoS_(2)-based transistors with low contact resistance by inserting ultrathin Al_(2)O_(3)interfacial layer

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science China(Technological sciences) 2023年第6期66卷 1831-1840页

作者： CHEN Gang LIN Xin LIU Yuan WANG Fang HU Kai SHAN Xin WU ZeYu ZHANG YuPeng NIE WeiCan ZHONG JiXiang REN TianLing ZHANG KaiLiang Tianjin Key Laboratory of Film Electronic&Communication Devices School of Integrated Circuit Science and EngineeringTianjin University of TechnologyTianjin 300384China School of Materials Science and Engineering Tianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Composite and Functional Materials Key Laboratory of Advanced Ceramics and Machining Technology(Ministry of Education)School of Materials Science and EngineeringTianjin UniversityTianjin 300072China School of Integrated Circuits Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China

Transition metal dichalcogenides(TMDCs)are promising high performance electronic materials due to their interesting semiconductor ***,it is acknowledged that the effective electrical contact between TMDCs-layered materials and metals remains one of the major *** this work,the homogeneous monolayer MoS_(2)films with high crystalline quality were prepared by chemical vapor deposition method on SiO2/Si *** back-gate field-effect transistors(FETs)were fabricated by inserting an ultrathin Al_(2)O_(3)interlayer between the metal electrodes and MoS_(2)*** the addition of an ultrathin 0.8 nm Al_(2)O_(3)interlayer,the contact resistance decreased dramatically from 59.9 to 1.3 kΩμm and the Schottky barrier height(SBH)dropped from 102 to 27 meV compared with devices without the Al_(2)O_(3)*** the same time,the switching ratio increased from~106to~108,and both the on-current and field-effect mobility were greatly *** find that the ultrathin Al_(2)O_(3)interlayer can not only reduce the SBH to alleviate the Fermi level pinning phenomenon at the interface,but also protect the channel materials from the influence of air and moisture as a covering *** addition,the lattice and band structures of Al_(2)O_(3)/MoS_(2)film were calculated and analyzed by first-principles *** is found that the total density of states of the Al_(2)O_(3)/MoS_(2)film exhibits interfacial polarized metals property,which proves the higher carrier transport *** with Al_(2)O_(3)interlayers have excellent stability and repeatability,which can provide effective references for future low power and high performance electronic devices.

关键词： MoS_(2) Schottky barrier height contact resistance Al_(2)O_(3)interlayer first-principles calculation

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