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Topology-optimized thermal metamaterials traversing full-parameter anisotropic space

npj Computational Materials 2022年第1期8卷 1717-1726页

作者： Wei Sha Run Hu Mi Xiao Sheng Chu Zhan Zhu Cheng-Wei Qiu Liang Gao State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Coal Combustion School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhan430074China School of Engineering Cardiff UniversityCardiffCF243AAUnited Kingdom Department of Electrical and Computer Engineering National University of SingaporeKent Ridge117583Republic of Singapore

It is widely adopted in thermal metamaterials that mixing different materials could conveniently result in effective thermal conductivities(ETCs)beyond naturally-occurring *** multiple materials are isotropically mixed,the ETC is a direct average governed by their filling fractions and given bulk *** could lead to an inhomogeneous and anisotropic value within the maximal and minimal thermal conductivities of constituent *** thermal metadevices rely on anisotropic thermal conductivity tensor,whose tensorial elements are frequently inter-dependent and confined within a limited parametric *** is thus nontrivial to establish a design recipe for advanced thermal metamaterials whose ETCs could cover full-parameter anisotropic *** demonstrate topological functional cells(TFCs)with copper and polydimethylsiloxane,and show that the anisotropic ETCs traverse their full-parameter *** robust scheme based on topology-optimized TFCs unlocks unexplored opportunities for functional thermal metadevices whose parameters may not be reached in previous mixing *** study also sheds light on the developments in emerging acoustic,mechanical and electromagnetic composite materials.

关键词： parameter mixing thermal

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LF-CNN:Deep Learning-Guided Small Sample Target Detection for Remote Sensing Classification

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computer Modeling in engineering & Sciences 2022年第4期131卷 429-444页

作者： Chengfan Li Lan Liu Junjuan Zhao Xuefeng Liu School of Computer Engineering and Science Shanghai UniversityShanghai200444China Key Laboratory for Digital Land and Resources of Jiangxi Province East China University of TechnologyNanchang330013China School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghai201620China School of Communication&Information Engineering Shanghai UniversityShanghai200444China

Target detection of small samples with a complex background is always difficult in the classification of remote sensing *** propose a new small sample target detection method combining local features and a convolutional neural network(LF-CNN)with the aim of detecting small numbers of unevenly distributed ground object targets in remote sensing *** k-nearest neighbor method is used to construct the local neighborhood of each point and the local neighborhoods of the features are extracted one by one from the convolution *** the local features are aggregated by maximum pooling to obtain global feature *** classification probability of each category is then calculated and classified using the scaled expected linear units function and the full connection *** experimental results show that the proposed LF-CNN method has a high accuracy of target detection and classification for hyperspectral imager remote sensing data under the condition of small *** drawbacks in both time and complexity,the proposed LF-CNN method can more effectively integrate the local features of ground object samples and improve the accuracy of target identification and detection in small samples of remote sensing images than traditional target detection methods.

关键词： Small samples local features convolutional neural network(CNN) k-nearest neighbor(KNN) target detection

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Fatigue crack propagation across grain boundary of Al-Cu-Mg bicrystal based on crystal plasticity XFEM and cohesive zone model

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Journal of Materials Science & Technology 2022年第31期126卷 275-287页

作者： Qi Zhao Magd Abdel Wahab Yong Ling Zhiyi Liu School of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China Faculty of Mechanical-Electrical and Computer Engineering School of Engineering and TechnologyVan Lang UniversityHo Chi Minh CityVietnam Soete Laboratory Faculty of Engineering and ArchitectureGhent UniversityTechnologiepark Zwijnaarde 903B-9052 ZwijnaardeBelgium School of Materials Science and Engineering Central South UniversityChangsha 410083China

In this paper,a methodology integrating crystal plasticity(CP),the eXtended finite element method(XFEM)and the cohesive zone model(CZM)is developed for an Al-Cu-Mg alloy to predict fatigue crack propagation(FCP)across grain boundary(GB)of Al-Cu-Mg alloy during stageІІ.One GB model is incor-porated into FCP constitutive law to describe grain interaction at GB.A bicrystal containing GB is built up to simulate FCP behavior through L participated *** features including GB characteristic,cumulative plastic strain(CPS)distribution and crystal slipping evidence can be *** numer-ical results are compared with published experimental data to check the accuracy of *** work demonstrates that the combination of CP containing GB constitutive laws,XFEM and CZM is a promising methodology in predicting twist angle-controlled crack deflection through GBs.

关键词： Grain boundary Twist angle Crystal plasticity Extended finite element method Fatigue crack propagation Cumulative plastic strain

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SLSNet: Weakly-Supervised Skin Lesion Segmentation Network with Self-attentions 20th

SLSNet: Weakly-Supervised Skin Lesion Segmentation Network w...

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20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Pei, Songwen Huang, Junjie School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education East China Normal University Shanghai200062 China

ISBN: (纸本)9789819970247

computer-aided skin lesion segmentation with high precision is crucial to diagnose skin cancers in the early stage. However, the lack of pixel-level labels makes the skin lesion segmentation tasks challenging. To tackle this problem, a new weakly-supervised skin lesion segmentation network with self-attentions named SLSNet is proposed. SLSNet contains two modules and uses image-level labels as supervision information. One module named Intra-image Self-attention Seed Expansion (ISE) digs intra-image self-attentions with an expansion loss and a confidence loss to expand seed areas. The other module named Inter-image Affinity-based Noise Suppression (IAS) suppresses the noise pixels in attention maps via inter-image correlations. Extensive experiments conducted on ISIC-2017 dataset show that SLSNet achieves relatively high performance while reducing human labeling efforts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Expansion

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A Survey on Indoor Visible Light Positioning Systems: Fundamentals, Applications, and Challenges

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IEEE Communications Surveys and Tutorials 2024年第3期27卷 1656-1686页

作者： Zhu, Zhiyu Yang, Yang Chen, Mingzhe Guo, Caili Cheng, Julian Cui, Shuguang Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering and Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China The University of British Columbia Faculty of Applied Science School of Engineering KelownaBCV1V 1V7 Canada 518172 Hong Kong

The growing demand for location-based services in areas like virtual reality, robot control, and navigation has intensified the focus on indoor localization. Visible light positioning (VLP), leveraging visible light communications (VLC), becomes a promising indoor positioning technology due to its high accuracy and low cost. This paper provides a comprehensive survey of VLP systems. In particular, since VLC lays the foundation for VLP, we first present a detailed overview of the principles of VLC. Then, we provide an in-depth overview of VLP algorithms. The performance of each positioning algorithm is also compared in terms of various metrics such as accuracy, coverage, and orientation limitation. Beyond the physical layer studies, the network design for a VLP system is also investigated, including multi-access technologies, resource allocation, and light-emitting diode (LED) placements. Next, the applications of the VLP systems are overviewed. Finally, this paper outlines open issues, challenges, and opportunities for the research field. In a nutshell, this paper constitutes the first holistic survey on VLP from state-of-the-art studies to practical uses. © 1998-2012 IEEE.

关键词： Resource allocation

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Sequential generation of self-starting diverse operations in all-fiber laser based on thulium-doped fiber saturable absorber

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Chinese Physics B 2022年第6期31卷 87-90页

作者： Pei Zhang Kaharudin Dimyati Bilal Nizamani Mustafa M.Najm S.W.Harun School of Electrical and Information Engineering Huaihua UniversityHuaihua 418008China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua 418008China Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Advanced Technology and Multidiscipline Airlangga UniversitySurabaya 60115Indonesia Institute of Computer Science and Digital Innovation UCSI UniversityKuala LumpurMalaysia

Self-starting Q-switching,Q-switched mode-locking and mode-locking operation modes are achieved sequentially in an all-fiber erbium-doped fiber laser with thulium-doped fiber saturable absorber for the first *** central wavelengths of Q-switching,Q-switched mode-locking and mode-locking operation modes are 1569.7 nm,1570.9 nm,and 1572 nm,*** mode-locking operation of the proposed fiber laser generates stable dark soliton with a repetition rate of 0.99 MHz and signal-to-noise ratio of 65 *** results validate the capability of generating soliton pulse by doped fiber saturable ***,the proposed fiber laser is beneficial to the applications of optical communication and signal processing system.

关键词： all-fiber laser Q-switched mode-locking dark soliton fiber saturable absorber

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Seatbelt-Embroidered Metamaterials for In-Vehicle Vital Sign Monitoring

Seatbelt-Embroidered Metamaterials for In-Vehicle Vital Sign...

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2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Zeng, Qihang Tian, Xi Nguyen, Dat T. Yang, Xin Chia, Patrick Wu, Changsheng Ho, John S. National University of Singapore Department of Electrical and Computer Engineering Singapore National University of Singapore SIA-NUS Digital Aviation Corporate Laboratory Singapore National University of Singapore Integrative Sciences & Engineering NUS Graduate School Singapore National University of Singapore Department of Materials Science and Engineering Singapore

ISBN: (纸本)9798350347647

Continuous in-vehicle physiological monitoring can improve safety through early detection of driver fatigue and drowsiness. However, developing a system capable of effective and robust physiological monitoring in practical driving scenarios is challenging due to the noisy vehicular environment in which the sensor is exposed to engine vibrations, unpredictable road conditions and random body motions. In this work, we introduce a seatbelt-integrated metamaterial sensor for unobtrusive and continuous in-vehicle respiration and heartbeat monitoring. The metamaterial sensor is fabricated by digital embroidery of conductive threads and can continuously monitor respiration and heartbeat in a contactless manner. Our sensor supports confined microwave surface waves that are modulated by subtle local physiological motions, which are sensitively transduced into changes in the phase of the transmitted signal. We developed an algorithm based on variational mode decomposition (VMD) for noise-robust extraction of respiration and heart rate. We experimentally demonstrate the embroidered metamaterial in real-life driving scenarios and show accurate heartbeat detection with a median inter-beat interval (IBI) detection error of 23.5 ms during driving. Our results highlight the potential of embroidered metamaterial sensors in driver physiological monitoring applications, especially for the unobtrusive detection of fatigue and drowsiness. © 2023 IEEE.

关键词： Surface waves

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Construction of digital Anatomy Experiment Teaching System Based on VR Technology

Construction of Digital Anatomy Experiment Teaching System B...

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2024 International Conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Yu, Penghui Li, Qiao Cai, Shichang Pan, Meisen College of Basic Medicine Hunan University of Medicine Huaihua418000 China College of Computer and Electrical Engineering Hunan University of Arts and Science Hunan Changde415000 China Huaihua Key Laboratory of Digital Anatomy 3D Printing for Clinical Translational Research Hunan Huaihua418000 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Currently, VR technology is constantly developing and widely applied in the field of medical education. Many experiments in medical courses have evolved from simple animated demonstrations to virtual simulation experiments. The current lack of intuitive clarity and ease of operation in teaching human anatomy experiments is a common problem. The 3D anatomical structure teaching model has the advantages of three-dimensional and highly simulated teaching, which can effectively reproduce the three-dimensional structure and three-dimensional entity information of tissues and organs. This article introduces the basic principles of VR technology and its application in anatomy experimental teaching. By comparing the traditional teaching methods and VR integrated teaching methods of 60 students in the anatomy course, the advantages of applying VR anatomical structure teaching mode to human anatomy experimental teaching were analyzed. As a result, the combination of VR anatomical structure teaching and traditional experimental entity specimen teaching solved many difficulties in the teaching process of this specialized course, and gave full play to their respective advantages, effectively overcame the shortcomings of traditional experimental teaching and VR anatomical structure teaching model, and greatly mobilized students' subjective initiative. Make it easier for students to master the complex knowledge of human anatomy. © 2025 SPIE.

关键词： digital elevation model

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Dynamic Scheduling of Mobile Energy Storage for Post-Disaster Power Recovery from Storm Tides: A Multi-Agent Reinforcement Learning Framework 7

Dynamic Scheduling of Mobile Energy Storage for Post-Disaste...

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7th IEEE Student Conference on Electric Machines and Systems, SCEMS 2024

作者： Liu, Fengrui Lao, Keng-Weng Guo, Haotian Zhang, Ziyao Kong, Weiming Hu, Xiaorui University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China King's College London Digital assets and media management London United Kingdom Institute of Energy Power Innovation North China Electric Power University Beijing China

ISBN: (纸本)9798350366945

Storm tide disasters may lead to extensive power outage in distribution networks. The usage of energy storage resources is necessary to ensure the power critical loads. Previous research has been designed to address typhoon disasters without considering the impact of storm tides, which reduces its effectiveness. This paper proposes a multi-agent deep reinforcement learning framework to address the issues, based on the integration of power and transportation networks, facing dynamic scheduling decisions of mobile energy storage for power supply recovery after storm tide. Firstly, to simulate the dynamic allocation of power demand and energy storage resources in various regions during storm tide disasters, a coupled transportation and power grid digital twin is constructed, ensuring that Mobile Energy Storage Systems (MESS) can efficiently transfer and distribute power resources between regions affected by storm tide. Then, the reinforcement learning method based on Multi-Agent Depth Q-Network (MADQN) is designed, and can optimize the real-time scheduling strategy of mobile energy storage resources, maximize power recovery efficiency, and minimize recovery time. Finally, a hazard assessment framework for storm tides in coastal cities is proposed. The experimental results show that this method has significantly improved recovery speed and power supply security after storm-tide disasters. © 2024 IEEE.

关键词： Reinforcement learning

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Interior Scene Intelligent Generated for Smart Homes Based on GAN-ID Algorithms

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第2期9卷 1046-1055页

作者： Zhang, Fu-Quan Ma, Lin-Juan Zhou, Jun-Xian Wang, Run-Hong Zhang, Guang-Zhen College of Computer and Control Engineering Minjiang University Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu China Fuzhou Technology Innovation Center of Intelligent Manufacturing Information System Minjiang University Fuzhou China Fujian Province University Fuzhou China School of Computer Science and Technology Beijing Institute of Technology Beijing China Minjiang University Fuzhou China Information Media School of Tianjin Technician Institute of Mechanical & Electrical Technology Tianjin China

The purpose of this paper is to present a new GAN-ID algorithm to gener-ate interior scene intelligently based on Artificial Intelligence of Things (AIoT). Although great progress has been made when GAN algorithm applied in smart homes and smart cities, the issue of the trade-off between the accuracy and the efficiency in interior scene has been overlooked. A number of experiments were performed to check the performance and it is indicated that the results of the proposed GAN-ID has great advantages in model sample generation than other common methods when generating interior scene intelligently, which is similar to state-of-the-art. It is meaningful when it can be applied in smart cities and smart homes filed based on AIoT in the future. © 2024, J. Network Intell. All rights reserved.

关键词： Automation

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