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MXene Sediment-Based Poly(vinyl alcohol)/Sodium Alginate Aerogel Evaporator with Vertically Aligned Channels for Highly Efficient Solar Steam Generation

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Nano-Micro Letters 2024年第10期16卷 638-654页

作者： Tian Wang Meng Li Hongxing Xu Xiao Wang Mingshu Jia Xianguang Hou Shuai Gao Qingman Liu Qihang Yang Mingwei Tian Lijun Qu Zhenhua Song Xiaohu Wu Lili Wang Xiansheng Zhang Shandong Key Laboratory of Medical and Health Textile Materials College of Textiles and ClothingState Key Laboratory of Bio-Fibers and Eco-TextilesResearch Center for Intelligent and Wearable TechnologyQingdao UniversityQingdao 266071People's Republic of China Department of Pharmacology Qingdao University School of PharmacyQingdao UniversityQingdao 266071People's Republic of China Shandong Institute of Advanced Technology Jinan 250100People's Republic of China College of Electromechanical Engineering Qingdao University of Science and TechnologyQingdao 266061People's Republic of China

Solar-driven interfacial evaporation from seawater is considered an effective way to alleviate the emerging freshwater crisis because of its green and environmentally friendly ***,developing an evaporator with high efficiency,stability,and salt resistance remains a key ***,with an internal photothermal conversion efficiency of 100%,has received tremendous research interest as a photothermal ***,the process to prepare the MXene with monolayer is inefficient and generates a large amount of“waste”MXene sediments(MS).Here,MXene sediments is selected as the photothermal material,and a three-dimensional MXene sediments/poly(vinyl alcohol)/sodium alginate aerogel evaporator with vertically aligned pores by directional freezing method is innovatively *** vertical porous structure enables the evaporator to improve water transport,light capture,and high evaporation *** swabs and polypropylene are used as the water channel and support,respectively,thus fabricating a self-floating *** evaporator exhibits an evaporation rate of 3.6 kg m^(-2)h^(-1)under one-sun illumination,and 18.37 kg m^(-2)of freshwater is collected in the condensation collection device after 7 h of outdoor sun *** evaporator also displays excellent oil and salt *** research fully utilizes“waste”MS,enabling a self-floating evaporation device for freshwater collection.

关键词： MXene sediments Porous structure Desalination Self-floating

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User story clustering in agile development:a framework and an empirical study

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Frontiers of computer science 2023年第6期17卷 43-59页

作者： Bo YANG Xiuyin MA Chunhui WANG Haoran GUO Huai LIU Zhi JIN School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry Oriented Intelligent Information Processing National Forestry and Grassland AdministrationBeijing 100083China School of Information Science and Technology North China University of TechnologyBeijing 100144China College of Computer Science and Technology Inner Mongolia Normal UniversityHohhot 010020China Department of Computer Science and Software Engineering Swinburne University of TechnologyHawthorn VIC 3122Australia Key Laboratory of High Confidence Software Technologies(Peking University) Ministry of EducationBeijing 100871China Institute of Software School of Computer SciencePeking UniversityBeijing 100871China

Agile development aims at rapidly developing software while embracing the continuous evolution of user requirements along the whole development *** stories are the primary means of requirements collection and elicitation in the agile development.A project can involve a large amount of user stories,which should be clustered into different groups based on their functionality’s similarity for systematic requirements analysis,effective mapping to developed features,and efficient ***,the current user story clustering is mainly conducted in a manual manner,which is time-consuming and subjective to human *** this paper,we propose a novel approach for clustering the user stories automatically on the basis of natural language ***,the sentence patterns of each component in a user story are first analysed and determined such that the critical structure in the representative tasks can be automatically extracted based on the user story *** similarity of user stories is calculated,which can be used to generate the connected graph as the basis of automatic user story *** evaluate the approach based on thirteen datasets,compared against ten baseline *** results show that our clustering approach has higher accuracy,recall rate and F1-score than these *** is demonstrated that the proposed approach can significantly improve the efficacy of user story clustering and thus enhance the overall performance of agile *** study also highlights promising research directions for more accurate requirements elicitation.

关键词： user story agile development user story mapping clustering

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A bionic approach for the mechanical and electrical decoupling of an MEMS capacitive sensor in ultralow force measurement

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Frontiers of Mechanical Engineering 2023年第2期18卷 297-317页

作者： Wendi GAO Bian TIAN Cunlang LIU Yingbiao MI Chen JIA Libo ZHAO Tao LIU Nan ZHU Ping YANG Qijing LIN Zhuangde JIANG Dong SUN State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265599China State Key Laboratory of Robotics and Systems(HIT) Harbin 150006China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Department of Biomedical Engineering City University of Hong KongHong KongChina

Capacitive sensors are efficient tools for biophysical force measurement,which is essential for the exploration of cellular ***,attention has been rarely given on the influences of external mechanical and internal electrical interferences on capacitive *** this work,a bionic swallow structure design norm was developed for mechanical decoupling,and the influences of structural parameters on mechanical behavior were fully analyzed and optimized.A bionic feather comb distribution strategy and a portable readout circuit were proposed for eliminating electrostatic *** instability was evaluated,and electrostatic decoupling performance was verified on the basis of a novel measurement method utilizing four complementary comb arrays and applicationspecific integrated circuit *** electrostatic pulling experiment showed that the bionic swallow structure hardly moved by 0.770 nm,and the measurement error was less than 0.009% for the area-variant sensor and 1.118% for the gap-variant sensor,which can be easily compensated in *** proposed sensor also exhibited high resistance against electrostatic rotation,and the resulting measurement error dropped below 0.751%.The rotation interferences were less than 0.330 nm and(1.829×10^(-7))°,which were 35 times smaller than those of the traditional differential *** on the proposed bionic decoupling method,the fabricated sensor exhibited overwhelming capacitive sensitivity values of 7.078 and 1.473 pF/μm for gap-variant and area-variant devices,respectively,which were the highest among the current *** immunity to mechanical disturbances was maintained simultaneously,i.e.,less than 0.369% and 0.058% of the sensor outputs for the gap-variant and area-variant devices,respectively,indicating its great performance improvements over existing devices and feasibility in ultralow biomedical force measurement.

关键词： micro-electro-mechanical system capacitive sensor bionics operation instability mechanical and electrical decoupling biomedical force measurement

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Burst-Sensitive Traffic Forecast via Multi-Property Personalized Fusion in Federated Learning

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5598-5614页

作者： Xue, Jingjing Sun, Sheng Liu, Min Wang, Yuwei Meng, Xuying Wang, Jingyuan Zhang, JunBo Xu, Ke Chinese Academy of Sciences Institute of Computing Technology Beijing100045 China University of Chinese Academy of Sciences Beijing101408 China Zhongguancun Lab Beijing100190 China Beihang University School of Computer Science and Engineering Beijing100191 China Beihang University MIIT Key Laboratory of Data Intelligence and Management Beijing100191 China JD Technology JD iCity JD Intelligent Cities Research Beijing101111 China Tsinghua University Department of Computer Science and Technology Beijing100190 China Zhongguancun Laboratory Beijing100081 China

For distributed network traffic prediction with data localization and privacy protection, Federated Learning (FL) enables collaborative training without raw data exchange across Base Stations (BSs). Nevertheless, traffic across BSs exhibit inherently heterogeneous trend burst and smooth fluctuation properties, but existing FL methods model single-scale series from only one view, which cannot simultaneously capture diverse trend and fluctuation properties, especially distinct burst distributions. In this paper, we propose Personalized Federated Forecasting with Multi-property Self-fusion (P2FMS), which can represent multi-scale traffic properties from different views. With precise multi-property representations, a fusion-level prediction decision is learned for each client in a personalized manner to promptly sense traffic bursts and improve forecasting performance in non-IID settings. Specifically, P2FMS decomposes the traffic series into distinct time scales, based on which, we effectively extract closeness, period, and trend properties from different views. The closeness and period are embedded through global-view representations with spatial correlations, while non-stationary trends are individually fitted from the client-side view. Furthermore, a personalized combiner is designed to accurately quantify the proportion of general fluctuation raws (i.e., closeness and period) and specific trend property in predictions, which enables multi-property self-fusion for each client to accommodate heterogeneous traffic patterns and enhance prediction accuracy. Besides, an alternant training mechanism is introduced to optimize property representation and fusion modules with the convergence guarantee. Extensive experiments on real-world datasets show that P2FMS outperforms status quo methods in both prediction performance and convergence time. © 2002-2012 IEEE.

关键词： Weather forecasting

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Accurate Distinction of Weak and Strong AC Grids for Emerging Hierarchical-Infeed LCC-UHVDC systems

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CSEE Journal of Power and Energy systems 2024年第2期10卷 772-777页

作者： Hao Xiao Xianzhong Duan Yi Zhang Department of Electrical and Computer Engineering University of ManitobaWinnipeg R3T 2N2ManitobaCanada State Key Laboratory of Advanced Electromagnetic Engineering and Technology Hubei Electric Power Security and High Efficiency Key LaboratorySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074HubeiChina RTDS Technologies Inc. Winnipeg R3T 2E1ManitobaCanada

Distinction of weak and strong AC grids for emerging hierarchical-infeed LCC-UHVDC systems is important for planning and operation departments. However, accuracy of earlier distinction methods is limited as they were developed by empirical reasoning without rigorous theoretical analysis. Hence in this letter, hierarchical-infeed interactive effective short-circuit ratio (HIESCR) index is first used for strength evaluation of HIDC systems with complex inter-inverter interactions considered. Boundary HIESCR (BHIESCR) is also introduced in the proposed distinction method of weak and strong AC grids. That is, weak (or strong) AC grids are, respectively, identified when HIESCR is less (or greater) than BHIESCR. Second, it is shown BHIESCR remains almost unchanged as 3.0 versus various system parameters and rated operation variables based on rigorous theoretical analysis. This salient feature makes the proposed method more accurate than earlier methods. Finally, the proposed method is validated by simulations based on the PSCAD/EMTDC program.

关键词： Hierarchical-Infeedinteractive effective short-circuit ratio hierarchical-infeed LCC-UHVDC systems inter-inverter interactions strong AC grids weak AC grids

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Learning Probabilistic Coordinate Fields for Robust Correspondences

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2023年第10期45卷 12004-12021页

作者： Zhao, Weiyue Lu, Hao Ye, Xinyi Cao, Zhiguo Li, Xin Huazhong University of Science and Technology The Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan430074 China West Virginia University The Lane Department of Computer Science and Electrical Engineering MorgantownWV26506-6109 United States

We introduce Probabilistic Coordinate Fields (PCFs), a novel geometric-invariant coordinate representation for image correspondence problems. In contrast to standard Cartesian coordinates, PCFs encode coordinates in correspondence-specific barycentric coordinate systems (BCS) with affine invariance. To know when and where to trust the encoded coordinates, we implement PCFs in a probabilistic network termed PCF-Net, which parameterizes the distribution of coordinate fields as Gaussian mixture models. By jointly optimizing coordinate fields and their confidence conditioned on dense flows, PCF-Net can work with various feature descriptors when quantifying the reliability of PCFs by confidence maps. An interesting observation of this work is that the learned confidence map converges to geometrically coherent and semantically consistent regions, which facilitates robust coordinate representation. By delivering the confident coordinates to keypoint/feature descriptors, we show that PCF-Net can be used as a plug-in to existing correspondence-dependent approaches. Extensive experiments on both indoor and outdoor datasets suggest that accurate geometric invariant coordinates help to achieve the state of the art in several correspondence problems, such as sparse feature matching, dense image registration, camera pose estimation, and consistency filtering. Further, the interpretable confidence map predicted by PCF-Net can also be leveraged to other novel applications from texture transfer to multi-homography classification. © 1979-2012 IEEE.

关键词： Image registration

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Energy-Efficient Wireless Federated Learning: A Secrecy Oriented Design via Sequential Artificial Jamming

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IEEE Transactions on Vehicular technology 2023年第5期72卷 6412-6427页

作者： Wang, Tianshun Huang, Ning Wu, Yuan Quek, Tony Q. S. University of Macau State Key Laboratory of Internet of Things for Smart City 999078 China University of Macau Department of Computer and Information Science 999078 China University of Macau State Key Lab of Internet of Things for Smart City The Department of Computer and Information Science 999078 China Zhuhai UM Science and Technology Research Institute Zhuhai519031 China Singapore University of Technology and Design Information Systems Technology and Design Pillar 487372 Singapore National Cheng Kung University Tainan701 Taiwan

Wireless federated learning (FL) is envisioned as a promising paradigm of distributed learning in wireless networks without disclosing users' data privacy. However, radio channel leads to a potential risk of eavesdropping attack when sending the trained model data in wireless networks. To address this eavesdropping attack, in this work, we propose an energy-efficient wireless FL by using artificial jamming. Specifically, the group of wireless devices (WDs) adopt the time division multiple access (TDMA) approach to send their locally trained models to the FL server for model aggregation subject to the eavesdropping attack of a malicious node. When one of the WDs sends its local model, all the other WDs send the artificial jamming signals to interfere with the eavesdropper, which helps increase the secrecy throughput of the targeted WD for uploading its local model. Different from many existing studies using stochastic gradient descent (SGD), we adopt the stochastic average gradient (SAG) method in the local training to improve the convergence of FL and derive the corresponding lower bound of the FL convergence rate via SAG. Furthermore, we formulate an optimization problem that aims at minimizing the energy consumption of the WDs by jointly optimizing different WDs' local training time, their uploading transmission time in TDMA and the transmit-powers for providing artificial jamming, as well as the FL configurations of the local/global iterations. We also propose an efficient algorithm for solving this non-convex optimization problem. Numerical results are illustrated to validate the advantages of our design of wireless FL and the corresponding algorithms. In particular, the results demonstrate that our secrecy oriented energy-efficient FL can significantly outperform the other heuristic FL schemes. © 1967-2012 IEEE.

关键词： Energy efficiency

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GM2RC: Graph-based Multitask Modality Refinement and Complement for Multimodal Sentiment Analysis 7

GM2RC: Graph-based Multitask Modality Refinement and Complem...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Shi, Jiandong Chen, Yuting Zhou, Siwei Li, Ming Zhejiang Normal University Department of Computer Science Jinhua China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application Jinhua China Zhejiang Institute of Optoelectronics Jinhua China

ISBN: (纸本)9798350363173

Multimodal sentiment analysis has emerged as a critical research area, aiming to analyze complex emotional states using data from multiple sources. While conventional approaches focus on sophisticated fusion techniques to integrate multimodal information, they often struggle with distributional variances among modalities. Bridging this modal distribution gap and optimizing the utilization of modality-sensitive information are crucial challenges. In response, our study presents GM2RC, an innovative framework designed to enhance modality representations for improved multimodal fusion efficacy. GM2RC adopts a two-step approach: intra-modal refinement and intermodal complementation. In the first step, it enhances distinct features within each modality, while the second step fosters the assimilation of shared information across modalities through pairwise learning, thus mitigating inter-modal disparity. This comprehensive approach leads to more accurate sentiment analysis by creating more robust multimodal representations. Further rigorous experiments demonstrate significant boosts of 1.59% in accuracy and 2.03% in w-F1 on the IEMOCAP dataset, and 1.65% in accuracy and 2.73% in w-F1 on the MELD dataset, showcasing the superiority of our proposed GM2RC model. © 2024 IEEE.

关键词： Sentiment analysis

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Effects of Initialization Methods on the Performance of Multi-Objective Evolutionary Algorithms

Effects of Initialization Methods on the Performance of Mult...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Gong, Cheng Pang, Lie Meng Nan, Yang Ishibuchi, Hisao Zhang, Qingfu City University of Hong Kong Department of Computer Science Kowloon Tong Hong Kong Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China

ISBN: (纸本)9798350337020

Population initialization is always needed in evolutionary multi-objective optimization (EMO) algorithms. Intuitively, a well-designed initialization method can help facilitate the evolutionary process and improve the performance of EMO algorithms. However, very few studies have investigated the effects of initialization methods on the performance of EMO algorithms. Many existing EMO algorithms randomly generate an initial population to start the evolutionary process. To fill this research gap and attract more attention from EMO researchers to this important yet under-explored issue, in this paper, we examine the effects of various initialization methods that may become promising alternatives to the commonly-used random initialization method. Each initialization method is evaluated through computational experiments on test problems of various sizes with 5-1000 decision variables. Experimental results clearly demonstrate the advantage of well-designed initialization methods over the random initialization method. This study provides useful insights into EMO algorithm design and motivates further research on population initialization. © 2023 IEEE.

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Efficient learning of robust quadruped bounding usingpretrained neural networks

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IET Cyber-systems and Robotics 2022年第4期4卷 331-338页

作者： Zhicheng Wang Anqiao Li Yixiao Zheng Anhuan Xie Zhibin Li Jun Wu Qiuguo Zhu Institute of Cyber-Systems and Control Zhejiang UniversityZhejiangChina Intelligent Robot Research Center Zhejiang LabZhejiangChina Department of Computer Science University College LondonLondonUK State Key Laboratory of Industrial Control Technology Zhejiang UniversityZhejiangChina

Bounding is one of the important gaits in quadrupedal locomotion for negotiating *** authors proposed an effective approach that can learn robust bounding gaits more efficiently despite its large variation in dynamic body *** authors first pretrained the neural network(NN)based on data from a robot operated by conventional model-based controllers,and then further optimised the pretrained NN via deep reinforcement learning(DRL).In particular,the authors designed a reward function considering contact points and phases to enforce the gait symmetry and periodicity,which improved the bounding *** NN-based feedback controller was learned in the simulation and directly deployed on the real quadruped robot Jueying Mini successfully.A variety of environments are presented both indoors and outdoors with the authors’*** authors’approach shows efficient computing and good locomotion results by the Jueying Mini quadrupedal robot bounding over uneven *** cover image is based on the Research Article Efficient learning of robust quadruped bounding using pretrained neural networks by Zhicheng Wang et al.,https://***/10.1049/csy2.12062.

关键词： legged locomotion reinforcement learning robot learning

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