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Improvement in hydrogen storage performance of MgH_(2) by vanadium doped with ZIF-8 derived a single-atom catalyst V-N-C

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Rare Metals 2024年第6期43卷 2623-2635页

作者： Fei-Fan Hong Wei-Tao Shi Ruo-Lin Zhao Yi Fan Zi-Qi Liu Si-Zhi Ding Hai-Zhen Liu Wen-Zheng Zhou Jin Guo Zhi-Qiang Lan Guangxi Novel Battery Materials Research Center of Engineering Technology and Center on Nanoenergy Research Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationCarbon Peak and Neutrality Science and Technology Development InstituteSchool of Physical Science and TechnologyGuangxi UniversityNanning 530004China Nanning Engineering Technology Research Center for Power Transmission System of New Energy Vehicle Transportation CollegeNanning UniversityNanning 530200China

Herein,the successful preparation of a singleatom catalyst V-N-C using vanadium-doped zeolitic imidazolate framework(ZIF)-8 as a precursor is *** experimental results showed that the V-N-C had a good promoting effect on the hydrogen storage performance of MgH_(2),and the optimal addition amount of V-N-C was 10wt%.The hydrogenation and dehydrogenation apparent activation energies of 10 wt%V-N-C-catalyzed MgH_(2)were reduced by 44.9 and 53.5 kJ·mol^(-1),respectively,compared to those of additive-free MgH_(2).The 10 wt%V-N-C-catalyzed MgH_(2)could reabsorb 5.92 wt%of hydrogen in 50 min at 150℃,with a capacity retention rate of 99.1%after 30 cycles of hydrogen absorption and *** analysis showed that V-N-C was partially transformed into VN and metallic V when it was milled with MgH_(2);the in-situ-formed VN and metallic V played an important role in improving the hydrogen storage performance of MgH_(2).This approach provides a potential solution for obtaining high-performance Mg-based hydrogen storage materials through synergistic interactions between V,N and C.

关键词： MgH_(2) Hydrogen storage materials Catalyst Hydrogen storage perormance

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Federated Learning for Lidar Super Resolution on Automotive Scenes 24

Federated Learning for Lidar Super Resolution on Automotive ...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Gkillas, Alexandros Arvanitis, Gerasimos Lalos, Aris S. Moustakas, Konstantinos Industrial Systems Institute Athena Research Center Patras Greece Electrical and Computer Engineering University of Patras Greece

ISBN: (纸本)9798350339598

In this paper, the problem of lidar super-resolution is explored under a federated learning perspective. The high cost of high-resolution lidar sensors is a major obstacle to the widespread adoption of connected and autonomous vehicles (CAVs). To reduce the cost, this study investigates the use of low-cost sensors in conjunction with super-resolution algorithms. Unlike previous studies that approach this problem with centralized solutions, this work employs federated learning to leverage private lidar data from different autonomous vehicles under different environmental conditions, resulting in more robust and diverse deep learning model. Extensive experiments on a real-world lidar odometry dataset highlight the merits and applicability of the proposed lidar super-resolution method with federated learning. © 2023 IEEE.

关键词： Optical radar

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A survey for light field super-resolution

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High-Confidence Computing 2024年第1期4卷 118-129页

作者： Mingyuan Zhao Hao Sheng Da Yang Sizhe Wang Ruixuan Cong Zhenglong Cui Rongshan Chen Tun Wang Shuai Wang Yang Huang Jiahao Shen State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Key Laboratory of Data Science and Intelligent Computing International Innovation InstituteBeihang UniversityHangzhou 311115China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Compared to 2D imaging data,the 4D light field(LF)data retains richer scene’s structure information,which can significantly improve the computer’s perception capability,including depth estimation,semantic segmentation,and LF ***,there is a contradiction between spatial and angular resolution during the LF image acquisition *** overcome the above problem,researchers have gradually focused on the light field super-resolution(LFSR).In the traditional solutions,researchers achieved the LFSR based on various optimization frameworks,such as Bayesian and Gaussian *** learning-based methods are more popular than conventional methods because they have better performance and more robust generalization *** this paper,the present approach can mainly divided into conventional methods and deep learning-based *** discuss these two branches in light field spatial super-resolution(LFSSR),light field angular super-resolution(LFASR),and light field spatial and angular super-resolution(LFSASR),***,this paper also introduces the primary public datasets and analyzes the performance of the prevalent approaches on these ***,we discuss the potential innovations of the LFSR to propose the progress of our research field.

关键词： Light field super-resolution Convolutional neural network Transformer Sub-aperture image Epipolar-plane image

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A Survey on Privacy-Enhancing Techniques in the Era of Artificial Intelligence 4th

A Survey on Privacy-Enhancing Techniques in the Era of A...

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4th International Conference on Novel and Intelligent Digital systems, NiDS 2024

作者： Dritsas, Elias Trigka, Maria Mylonas, Phivos Athena Research and Innovation Center Industrial Systems Institute Patras Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (纸本)9783031733437

In the era of Big Data and Artificial Intelligence (AI), the unprecedented scale and complexity of data collection, processing, and analysis pose significant privacy challenges. This paper presents a survey, providing a comprehensive and focused overview of privacy-enhancing technologies (PETs) designed to mitigate these challenges and ensure the protection of sensitive information. We explore cryptographic and non-cryptographic techniques including differential privacy (DP), homomorphic encryption (HE), secure multi-party computation (SMPC), and federated learning (FL). Each of these techniques is examined in terms of its basic principles and advantages. Also, some key challenges and ethical issues for implementing PETs are briefly discussed. Finally, we conclude the survey by denoting our future research directions in the field. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Federated learning

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An Improved Semi-Supervised Learning-Based U-Net for Underwater Image Enhancement 5

An Improved Semi-Supervised Learning-Based U-Net for Underwa...

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5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024

作者： Han, Jiqun Liu, Xinyu Tan, Dongxu Zhu, Jiehui School of Computer Science and Engineering Northeastern University Shenyang China Guangdong Institute of Intelligent Unmanned System Technology Research and Development Department Guangzhou China

ISBN: (纸本)9798350385557

The attenuation and scattering of light in underwater environments often lead to degradation issues such as image blurring, color cast, and low contrast. Due to the lack of high-quality paired datasets, the performance of deep learning-based methods is limited. To address these challenges, we propose an improved U-Net architecture based on semi-supervised learning for underwater image enhancement. First, a multi-scale input-level fusion module is proposed to allow our network to fully exploit global spatial information from input images, natural light fields, and depth maps. Second, a multi-branch hybrid convolutional attention residual block is designed to improve the network's feature extraction capability and focus on important spatial and channel information in underwater images. Finally, a semi-supervised learning approach is used to fully exploit unpaired datasets, improving the generalization ability of the network model. Through qualitative and quantitative analysis, the proposed network achieves satisfactory image enhancement results in various underwater scenarios. © 2024 IEEE.

关键词： Image enhancement

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Diving into Continual Ultra-fine-grained Visual Categorization

Diving into Continual Ultra-fine-grained Visual Categorizati...

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Zhang, Pengcheng Yu, Xiaohan Bai, Xiao Zheng, Jin Wu, Xiaoyu Gao, Yongsheng Beihang University School of Computer Science and Engineering State Key Laboratory of Software Development Environment Jiangxi Research Institute Beijing China Griffith University Institute for Integrated and Intelligent Systems Nathan4111 Australia

ISBN: (纸本)9798350382204

Recent advance in ultra-fine-grained visual categorization (ultra-FGVC) has significantly boosted the capability of deep neural networks for ultra-FGVC tasks. However, building models for continually learning to recognize increasing ultra-fine-grained categories is still under-explored. This limits the application of ultra-FGVC techniques in real-world production. To this, we take the first attempt for continual ultra-FGVC. By evaluating existing continual learning methods on the constructed continual ultra-FGVC benchmark, we observe that the main bottleneck lies in the limited model plasticity for incrementally adapting to new tasks. This can be caused by excessive anti-forgetting constraints as the difficult ultra-FGVC task requires substantial update of parameters, and over-fitting on early tasks given that the ultra-fine-grained categories are with very few training samples. To tackle these problems, we propose a joint self-supervised learning and prompting model. The prompt-based continual learning framework offers proper anti-forgetting operation by fixed pretrained vision transformer and adaptive prompt selection. By jointly optimizing the learnable prompts with an adversarial self-supervised loss, the over-fitting on each continual learning task is mitigated. Extensive experiments demonstrate that the proposed method outperforms existing continual learning methods on the challenging continual ultra-FGVC problem. © 2023 IEEE.

关键词： Deep neural networks

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Cross-city insights on sustainable consumption:consistency and disparities in willingness to buy and pay for green air conditioners

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Frontiers of Environmental Science & engineering 2025年第4期19卷 169-185页

作者： Jiachao Ke Shujie Zhao Yaozhong Guo Qingbin Song Ni Sheng Jinhui Li National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao SAR 999078China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao SAR 999078China 3.School of EnvironmentTsinghua UniversityBeijing 100084China The Institute for Sustainable Development Macao University of Science and TechnologyMacao SAR 999078China School of Business Macao University of Science and TechnologyMacao SAR 999078China

The intensification of climate change action has made air conditioners a key target for emission *** study examines the factors influencing residents’willingness to buy(WTB)and willingness to pay(WTP)for green air conditioners across six cities in the Pearl River Delta(PRD)region,aiming to understand consumer behavior and inform targeted market *** a novel Contingent Valuation Method(CVM),this study surveyed 1732 residents through online and face-to-face *** logistic and ordered logistic regression analyses identified key factors affecting WTB and WTP,including gender,income,education,knowledge of green air conditioners,and confidence in their emission reduction ***,the study reveals significant regional disparities in WTP and payment amounts through the Kruskal-Wallis H and Mann-Whitney U *** results also highlight Shenzhen has significant difference and highest payment value than other *** findings provide valuable insights into regional disparities and common factors in green consumption,offering guidance for market strategies and policy development aimed at promoting green air conditioners.

关键词： Contingent valuation method Green air conditioners WTB and WTP Influence factors Consistency and difference

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Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun Zhang MengChu Zhou ChenXi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain *** transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each *** one party refuses to do so,the channel is unstable.A stable channel is thus *** nodes may show uncooperative behavior,they may have a negative impact on the stability of such *** order to address this issue,this work proposes a dynamic evolutionary game model based on node *** model considers various defense strategies'cost and attack success ratio under *** can dynamically adjust their strategies according to the behavior of attackers to achieve their effective *** equilibrium stability of the proposed model can be *** proposed model can be applied to general channel *** is compared with two state-of-the-art blockchain channels:Lightning network and Spirit *** experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable *** its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

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Review of Market Power Assessment and Mitigation in Reshaping of Power systems

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Journal of Modern Power systems and Clean Energy 2022年第5期10卷 1067-1084页

作者： Nan Shang Yi Ding Wenqi Cui Energy Development Research Institute.China Southern Power Grid GuangzhouChina College of Electrical Engineering Zhejiang UniversityHangzhouChina Department of Electrical and Computer Engineering University of WashingtonSeattleUSA

The deregulation of the power industry requires avoiding market power abuse to maintain the market competitiveness. To this end, a sequence of assessment measurements or mitigation mechanisms is required. Meanwhile, the increasing renewable energy resources(RESs) and flexible demand response resources(DRSs) are changing the behaviors of market participants and creating new cases of market power *** new circumstances bring the new evaluation and control methods of market power to the forefront. This paper provides a comprehensive review of market power in the reshaping of power systems due to the increasing RES and the development of DRS. The market power at the supply side, demand side,and in the multi-energy system is categorized and reviewed. In addition, the applications of market power supervision measures in the US, the Nordics, UK, and China are ***, the unsolved issues, possible key technologies,and potential research topics on market power are discussed.

关键词： Market power renewable energy source(RES) flexible demand response source(DRS) assessment mitigation

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