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37th Annual Conference on Learning Theory, COLT 2024

作者： Wan, Yuanyu Wei, Tong Song, Mingli Zhang, Lijun The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China School of Software Technology Zhejiang University Ningbo China Institute of Blockchain and Data Security Hangzhou China School of Computer Science and Engineering Southeast University Nanjing China National Key Laboratory for Novel Software Technology Nanjing University Nanjing China

We investigate decentralized online convex optimization (D-OCO), in which a set of local learners are required to minimize a sequence of global loss functions using_only local computations and communications. Previous studies have established O(n5/4ρ-1/2 √T) and O(n3/2ρ-1 log T) regret bounds for convex and strongly convex functions respectively, where n is the number of local learners, ρ -1/4 √T) and Õ(nρ-1/2 log T). The primary technique is to design an online accelerated gossip strategy that enjoys a faster average consensus among local learners. Furthermore, by carefully exploiting the spectral properties of a specific network topology, we enhance the lower bounds for convex and strongly convex functions to Ω(nρ-14 √T) and Ω(nρ-1/2), respectively. These lower bounds suggest that our algorithms are nearly optimal in terms of T, n, and ρ. © 2024 Y. Wan, T. Wei, M. Song & L. Zhang.

关键词： Optimization algorithms

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A concentration reflector device of a bifacial photovoltaic module 7

A concentration reflector device of a bifacial photovoltaic ...

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2024 7th International Conference on Mechanical, Electrical and Material Application, MEMA 2024

作者： Yuan, Quanhong Department of Electromechanical Engineering Guangdong University of Science and Technology Guangdong Dongguan523083 China Dongguan Key Laboratory of Industrial Software for Intelligent Manufacturing Guangdong University of Science & Technology Dongguan523083 China

At present, the development of bifacial photovoltaic modules is rapid, but there is a lack of concentrating light devices in bifacial photovoltaic modules for power generation. This paper analyzes the changing patterns of solar altitude and azimuth angles and the influence of plane mirror reflection concentrating light on the performance of bifacial photovoltaic power generation. Using MATLAB programming, it calculates the pattern of change of the intensity of reflected light with the installation height h of the plane mirror. Then, a double plane mirror concentrating device is designed, which can do real-time dynamic tracking of the sun's azimuth and altitude angle and realize the power generation capacity of the PV module is multiplied. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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A Short Review of Truck and Drone Collaborative Delivery Problem 10

A Short Review of Truck and Drone Collaborative Delivery Pro...

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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Zhu, Yena Liu, Min Jin, Dongyao Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China Hunan Key Laboratory for Service computing and Novel Software Technology Xiangtan China

ISBN: (纸本)9798350312461

With the emergence of efficient logistics models and the development of drone technology, the last-mile delivery problem has become a focus of attention for scholars in various fields. The advantages of drones, such as low cost, energy saving, and independence from road conditions, have made them increasingly popular in the delivery industry. However, drones have shortcomings such as short endurance, small payload capacity, and susceptibility to interference. Therefore, the cooperative delivery model of vehicles and drones has important theoretical research significance and practical application value. Existing literature reviews focus on static truck-drone delivery problems (TDDPs) and methods such as exact algorithms, heuristics, and metaheuristics. However, real-life truck-drone delivery problems are easily affected by dynamic environmental changes. Accordingly, this article introduces some new dynamic variants of TDDPs proposed in recent years, which consider variable drone flight endurance, urban crowded road conditions, stochastic customer demands, and the influence of weather changes. In recent years, some new methods for solving TDDPs have been introduced, such as the increasingly popular machine learning and reinforcement learning methods. Finally, the possible future research directions and development trends of TDDPs are presented. © 2023 IEEE.

关键词： Reinforcement learning

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Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

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China Communications 2024年第5期21卷 1-16页

作者： Qin Zhen He Shoushuai Wang Hai Qu Yuben Dai Haipeng Xiong Fei Wei Zhenhua Li Hailong College of Communications Engineering Army Engineering University of PLANanjing 210000China Department of Information and Communication Noncommissioned Officer Academy of PAPHangzhou 310000China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing 211106China College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China CMC Political and Law Commission Beijing100120China Xi’an Research Institute of High Technology Xi’an 710025China

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this *** proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for ***,we introduce the AGC-MEC architecture and elaborate three typical use ***,we discuss four main challenges in the AGC-MEC as well as their potential ***,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement ***,we highlight several potential research directions of the AGC-MEC.

关键词： air-ground architecture collaborative mobile edge computing

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STTG-net:a Spatio-temporal network for human motion prediction based on transformer and graph convolution network

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 224-238页

作者： Lujing Chen Rui Liu Xin Yang Dongsheng Zhou Qiang Zhang Xiaopeng Wei tional and Local Joint Engineering Laboratory of Computer Aided Design School of Software EngineeringDalian UniversityDalian 116622China School of Computer Science and Technology Dalian University of TechnologyDalian 116024China

In recent years,human motion prediction has become an active research topic in computer ***,owing to the complexity and stochastic nature of human motion,it remains a challenging *** previous works,human motion prediction has always been treated as a typical inter-sequence problem,and most works have aimed to capture the temporal dependence between successive ***,although these approaches focused on the effects of the temporal dimension,they rarely considered the correlation between different joints in ***,the spatio-temporal coupling of human joints is considered,to propose a novel spatio-temporal network based on a transformer and a gragh convolutional network(GCN)(STTG-Net).The temporal transformer is used to capture the global temporal dependencies,and the spatial GCN module is used to establish local spatial correlations between the joints for each *** overcome the problems of error accumulation and discontinuity in the motion prediction,a revision method based on fusion strategy is also proposed,in which the current prediction frame is fused with the previous *** experimental results show that the proposed prediction method has less prediction error and the prediction motion is smoother than previous prediction *** effectiveness of the proposed method is also demonstrated comparing it with the state-of-the-art method on the Human3.6 M dataset.

关键词： Human motion prediction Transformer Gragh convolutional network

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Color Image Steganalysis Algorithm Based on Quaternion Convolutional Neural Network 30th

Color Image Steganalysis Algorithm Based on Quaternion Convo...

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30th International Conference on Computational and Experimental engineering and Sciences, ICCES 2024

作者： Xu, Meng Wang, Jinwei State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China Department of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9783031687747

Most of the images on the Internet are color images, and steganalysis of color images is a very critical issue in the field of steganalysis. The current proposed color image steganalysis features mainly rely on manual design, and the steganalysis features do not fully consider the internal connections between the three channels of color images. Most steganalyzers based on deep learning are also designed for grayscale images. In recent years, the continuous introduction of advanced steganography techniques for color images has also brought more severe challenges to the steganography analysis of color images. Quaternions are a tool that can effectively represent color images, and utilizing quaternion transformations can fully exploit the correlation between color image channels. Combining quaternion theory with convolutional neural networks, this paper proposed a color image steganalysis algorithm based on quaternion convolutional neural networks. Firstly, the image is represented by quaternion, and then input into the quaternion convolutional neural network. The convolution kernel in the network is composed of quaternions, and then perform convolution and pooling. The experimental results have demonstrated the significant effectiveness of the proposed network. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks

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Tailored energy absorption for a novel auxetic honeycomb structure under large deformation

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 63-80页

作者： Xiuhui Hou Bin Wang Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710129China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

In comparison to conventional hexagonal honeycomb structures,auxetic metamaterials with re-entrant configurations have exhibited superior mechanical properties in terms of energy *** further enhance the energy absorption capacity of these materials,a novel re-entrant honeycomb configuration,named novel auxetic re-entrant honeycomb(NARH),is developed by incorporating“<>”-shaped cell walls into the conventional auxetic re-entrant honeycomb(ARH).Two analytical models for the plateau stress are formulated to consider the plastic deformation of NARH during quasi-static compression and the dynamic impact using the linear momentum ***-static compression tests on 3D printed NARH honeycomb specimens and finite element simulations are performed to verify the effectiveness of the theoretical *** exhibits higher plateau stresses compared with ARH during compression,which can be attributed to the presence of more plastic hinges formed in *** hinges,the embedded parts with inclined cell walls,not only improve stability by forming stable triangles during compression but also enhance the energy absorption capacity.A parametric study is conducted to analyze the effect of impact velocity,thickness,and incline angle of cell walls on *** simulations demonstrate higher sensitivity of the mechanical properties to impact velocity and cell wall *** ribs to the“<>”-shaped cell walls in NARH further reduces the initial peak force during dynamic crushing while maintaining high energy *** research provides valuable guidelines for the design of energy absorption metamaterials.

关键词： absorption walls shaped

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A blockchain-based framework for data quality in edge-computing-enabled crowdsensing

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Frontiers of Computer Science 2023年第4期17卷 127-139页

作者： Jian AN Siyuan WU Xiaolin GUI Xin HE Xuejun ZHANG School of Computer Science and Technology Shaanxi Province Key Laboratory of Computer NetworkXi’an Jiaotong UniversityXi’an 710049China School of Software Henan UniversityKaifeng 475001China School of Electronic and Information Engineering Lanzhou Jiaotong UniversityLanzhou 730070China

With the rapid development of mobile technology and smart devices,crowdsensing has shown its large potential to collect massive *** the limitation of calculation power,edge computing is introduced to release unnecessary data *** edge-computing-enabled crowdsensing,massive data is required to be preliminary processed by edge computing devices(ECDs).Compared with the traditional central platform,these ECDs are limited by their own capability so they may only obtain part of relative factors and they can’t process data *** involved in one task are required to cooperate to process the task *** privacy of participants is important in crowdsensing,so blockchain is used due to its decentralization and *** crowdsensing tasks,it is usually difficult to obtain the assessment criteria in advance so reinforcement learning is *** mentioned before,ECDs can’t process task data comprehensively and they are required to cooperate quality ***,a blockchain-based framework for data quality in edge-computing-enabled crowdsensing(BFEC)is proposed in this ***(Delegated Proof of Reputation),which is proposed in our previous work,is improved to be suitable in ***,the final result is calculated without revealing the privacy of *** on the open datasets Adult,Blog,and Wine Quality show that our new framework outperforms existing methods in executing sensing tasks.

关键词： crowdsensing edge computing devices blockchain quality assessment reinforcement learning

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Deep Learning-Based Joint Channel Estimation and Implicit CSI Feedback 11th

Deep Learning-Based Joint Channel Estimation and Implicit C...

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11th China Conference on Command and Control, C2 2023

作者： Wan, Liangtian He, Jifeng Liu, Kaihui Sun, Lu Wang, Xianpeng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan523820 China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China State Key Laboratory of Marine Resource Utilization in South China Sea and School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9789819990207

Previous studies often address channel estimation and channel state information (CSI) implicit feedback issues in 5G new radio (NR) system independently, posing a challenge to achieve effective coordination between the two processes in a shared environment. Consequently, we propose a deep learning-based scheme that jointly addresses channel estimation and implicit CSI feedback. In this scheme, the received pilot information from user equipment (UE) is regarded as a two-dimensional image. Channel estimation is performed employing the ResMLP architecture, whereas the Transformer architecture is utilized for implicit CSI feedback. Furthermore, a novel training approach is introduced to further enhance the performance of the proposed scheme. Simulation results illustrate a substantial improvement compared to the reference scheme employed in the 3rd Wireless Communication Artificial Intelligence (AI) Competition (WAIC). © Chinese Institute of Command and Control 2024.

关键词： Channel estimation

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Autonomous Aspect-Image Instruction A2II: Q-Former Guided Multimodal Sentiment Classification 30

Autonomous Aspect-Image Instruction A2II: Q-Former Guided Mu...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Feng, Junjia Lin, Mingqian Shang, Lin Gao, Xiaoying State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Technology Nanjing University China School of Engineering and Computer Science Victoria University of Wellington New Zealand

ISBN: (纸本)9782493814104

Multimodal aspect-oriented sentiment classification (MABSC) task has garnered significant attention, which aims to identify the sentiment polarities of aspects by combining both language and vision information. However, the limited multimodal data in this task has become a big gap for the vision-language multimodal fusion. While large-scale vision-language pretrained models have been adapted to multiple tasks, their use for MABSC task is still in a nascent stage. In this work, we present an attempt to use the instruction tuning paradigm to MABSC task and leverage the ability of large vision-language models to alleviate the limitation in the fusion of textual and image modalities. To tackle the problem of potential irrelevance between aspects and images, we propose a plug-and-play selector to autonomously choose the most appropriate instruction from the instruction pool, thereby reducing the impact of irrelevant image noise on the final sentiment classification results. We conduct extensive experiments in various scenarios and our model achieves state-of-the-art performance on benchmark datasets, as well as in few-shot settings. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Sentiment analysis

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