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Black-hole-inspired thermal trapping with graded heat-conduction metadevices

National science Review 2023年第2期10卷 131-138页

作者： Liujun Xu Jinrong Liu Peng Jin Guoqiang Xu Jiaxin Li Xiaoping Ouyang Ying Li Cheng-Wei Qiu Jiping Huang Department of Physics State Key Laboratory of Surface Physics and Key Laboratory of Micro and Nano Photonic Structures (MOE) Fudan University Department of Electrical and Computer Engineering National University of Singapore Graduate School of China Academy of Engineering Physics School of Materials Science and Engineering Xiangtan University Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang University International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University

The curved space-time produced by black holes leads to the intriguing trapping *** far,metadevices have enabled analogous black holes to trap light or sound in laboratory ***,trapping heat in a conductive environment is still challenging because diffusive behaviors are *** by black holes,we construct graded heat-conduction metadevices to achieve thermal trapping,resorting to the imitated advection produced by graded thermal conductivities rather than the trivial solution of using insulation materials to confine thermal *** experimentally demonstrate thermal trapping for guiding hot spots to diffuse towards the *** heat-conduction metadevices have advantages in energy-efficient thermal regulation because the imitated advection has a similar temperature field effect to the realistic advection that is usually driven by external energy *** results also provide an insight into correlating transformation thermotics with other disciplines,such as cosmology,for emerging heat control schemes.

关键词： thermal trapping graded metadevices imitated advection

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Data-induced learning control for unknown nonlinear systems with full-tracking performances

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science China(information sciences) 2025年

作者： Changxin LU Deyuan MENG Hongyi LI School of Automation Science and Electrical Engineering Beihang University (BUAA) State Key Laboratory of CNS/ATM Seventh Research Division Beihang University (BUAA) College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest University

In tackling the challenge of achieving high control accuracy while refining control effort in unknown nonlinear systems, this paper presents a novel data-induced learning control (DiLC) method. The DiLC method marks the inaugural use of operational data to iteratively update controller parameters for unknown nonlinear systems, thereby achieving full-tracking performances over the entire operation time interval. The DiLC method enriches the traditional iterative learning control(ILC) paradigm by integrating a feedback control-based approach. This integration enables exploratory trials during the initial iteration process and facilitates the online collection and iterative utilization of operational data from actual operations,thus gradually enhancing control accuracy. Furthermore, it offers a significant advantage over prevalent finite/fixed-time and prescribed performance methods in repeatable tasks. Inspired by leveraging operational data, it effectively mitigates the constraints imposed on the system and adjustment parameters by existing methods, hence providing a more flexible and efficient solution. The efficiency of the DiLC method in accuracy evolution is proven through error reduction profiles,confirming its prospect for full-tracking performances in unknown nonlinear systems.

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Accelerated glacier mass loss in the mid-latitude Eurasia from 2019 to 2022 revealed by ICESat-2

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Advances in Climate Change Research 2024年第5期15卷 815-829页

作者： Gen-Yu WANG Chang-Qing KE Yu-Bin FAN Xiao-Yi SHEN Yu CAI Vahid NOURANI Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China Collaborative Inovation Centerof Novel Sofiware Technology and Industrialization Nanjing 20023China Collaborative Innovation Center of South China Sea Studies Nanjing 210023China School of Earth Sciences and Engineering Hohai UniversityNanjing 210024.China Center of Excellence in Hydroinformatics and Faculty of Civil Engineering University of TabrizTabriz 51368Iran Faculty of Civil and Environmental Engineering Near East UniversityNicosia 99138Turkey

The dynamics of glaciers serve as one of the most important indicators of climate *** current research has primarily concentrated on long-term interannual glacier mass balance and its response to climate change,glaciers may respond more rapidly to climate change,highlighting the urgent need for intra-annual mass balance *** seasonal or short-term variations in glacier mass balance not only enhances our understanding of the interactions between glaciers and the climate system but also provides crucial data for water resource management and ecological *** ICESat-2 and NASADEM datasets were used to estimate the inter-and intra-annual glacier mass balance changes in the mid-latitude Eurasia from 2019 to ***,the response of glacier mass balance to regional air temperature and precipitation values was analysed using ERA5-Land data and multiple regression analysis,*** 2019 to 2022,glacier mass loss in mid-latitude Eurasia reached-45.02±34.21 Gt per year,contributing to a global sea-level rise of 0.12±0.09 mm per *** glacier melt rate in the study area from 2019 to 2022 was 2.33 times higher than that from 2000 to *** the exception of the Western Kunlun region,which experienced a weak accumulation rate of 0.04±0.35 m *** year,all other areas experienced ablation *** mass balance responds differently to temperature and precipitation variations across seasons:higher temperatures in different seasons lead to more negative mass balances,while increased winter and spring precipitation can slow down glacier *** temperature dominates the glacier mass balance changes in the study *** intense heat in 2022 raised average glacier temperatures by 1.04°C compared to 2019-2021,resulting in a more negative mass balance and an increased ice loss of-0.34±1.01 m *** year(-35.07±103.22 Gt per year).This analysis indicates that glacier mass balance is highly sensitive to climate chan

关键词： Glacier mass balance ICESat-2 NASADEM The mid-latitude Eurasia Temperature

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Adaptive energy-preserving algorithms for guiding center system

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Plasma science and technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

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A Preliminary Study of Frequency Shift Mechanism in Magnetic Resonance Coupled Human Body Communication

A Preliminary Study of Frequency Shift Mechanism in Magnetic...

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2023 Cross Strait Radio science and Wireless technology Conference, CSRSWTC 2023

作者： Chen, Lina Wang, Jiamei Wei, Ziliang Pun, Sio Hang Vai, Mang I. Gao, Yueming College of Physics and Information Engineering Fuzhou University China Fuzhou University The International Joint Laboratory on Health Intelligent Monitoring Systems China University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI China University of Macau Faculty of Science and Technology China

ISBN: (纸本)9798350358971

The Magnetic Resonance-Coupled Human Body Communication (MR-HBC) method presents advantages such as high path gain and enhanced information security, rendering it particularly suitable for establishing wireless body area networks. The optimal operation of MR-HBC relies on functioning at resonance frequency. However, owing to the intricate dielectric properties of human tissues and individual differences, the resonance frequency of communication systems frequently experiences varying degrees of deviation. To delve into the intrinsic mechanism behind frequency shifts, this paper establishes a finite element model based on the genuine dielectric properties and geometric structure of the human body. It investigates the augmentation effects of human tissue on MR-HBC, examines the influence of distinct tissue electrical properties on the electromagnetic field distribution of MR-HBC, and analyzes the inherent connection between frequency shifts and human tissue electrical characteristics. The results reveal that the electrical properties of human tissues stand as the primary factor affecting frequency shifts, with the extent of frequency deviation contingent upon the proportional composition of different tissues. © 2023 IEEE.

关键词： Electromagnetic simulation MR-HBC Resonance Frequency Shift

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Dual-mimic learning for occluded pedestrian detection 1

Dual-mimic learning for occluded pedestrian detection

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1st International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2023

作者： Pan, Xiaofeng Han, Shoudong Ding, Huilin Wang, Yukun National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Engineering and Applied Science Columbia University NY10027 United States

It is still a great challenge to detect pedestrians in crowded scenes. Recent works mainly focus on enhancing the feature representation of the visible region. Although this strategy is effective, it fails to fully exploit the appearance information contained in the full-body region. To this end, we propose a Dual-Mimic learning model, which consists of the occluded to unoccluded (Occ-Unocc) and the full-body to visible (Full-Vis) mimic learning branches. Both branches can reduce the intra-class feature variances of pedestrians by different mimicking strategies. Besides, we define an occlusion attribute to describe the occlusion pattern of each detection. Based on the occlusion attribute, we propose the Occlusion-aware NMS (Occ-NMS), which can effectively remain the occluded instance with low confidence. We conduct extensive experiments on standard benchmarks of CityPersons and Caltech, and our method achieves a new state-of-the-art performance at 36.34% MR-2 and 25.07% MR-2 on heavy occlusion sets. © Published under licence by IOP Publishing Ltd.

关键词： Benchmarking

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List-Serial Pipelined Hardware Architecture for SCL Decoding of Polar Codes

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China Communications 2023年第3期20卷 175-184页

作者： Zhongxiu Feng Cong Niu Zhengyu Zhang Jiaxi Zhou Daiming Qu Tao Jiang Research Center of 6G Mobile Communications School of Cyber Science and Engineeringand Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China Institute of Space Integrated Ground Network Hefei 230094China The 38th Research Institute of China Electronics Technology Group Corporation Hefei 230088China School of Electronics Information and Communications Huazhong University of Science and TechnologyWuhan 430074China

For polar codes,the performance of successive cancellation list(SCL)decoding is capable of approaching that of maximum likelihood ***,the existing hardware architectures for the SCL decoding suffer from high hardware complexity due to calculating L decoding paths simultaneously,which are unfriendly to the devices with limited logical resources,such as field programmable gate arrays(FPGAs).In this paper,we propose a list-serial pipelined hardware architecture with low complexity for the SCL decoding,where the serial calculation and the pipelined operation are elegantly combined to strike a balance between the complexity and the ***,we employ only one successive cancellation(SC)decoder core without L×L crossbars,and reduce the number of inputs of the metric sorter from 2L to L+***,the FPGA implementations show that the hardware resource consumption is significantly reduced with negligible decoding performance loss.

关键词： successive cancellation list decoding po-lar codes hardware implementation pipelined archi-tecture

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Cross-Modal Recipe Retrieval With Fine-Grained Prompting Alignment and Evidential Semantic Consistency

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IEEE Transactions on Multimedia 2025年 27卷 2783-2794页

作者： Huang, Xu Liu, Jin Zhang, Zhizhong Xie, Yuan Tang, Yongqiang Zhang, Wensheng Cui, Xiaohui Wuhan University School of Computer Science Wuhan430072 China Ministry of Education Wuhan430062 China East China Normal University School of Computer Science and Technology Shanghai200062 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China

Alignment between the food images and the corresponding recipes is an emerging cross-modal representation learning task. In this task, the recipes are composed of three components, i.e., food title, ingredient lists, and cooking instructions, which require a fine-grained alignment between the features of the two modalities. Existing methods usually aggregate the recipes into global embeddings and then align them with the global image embeddings. Meanwhile, semantic classification is frequently used in these methods to regularize the embeddings of the two modalities. While these methods are efficient, there remain two problems. (1) Forcing the alignment between the global images and recipes embeddings may result in losing the component-specific information. (2) The high diversity of food appearance leads to high uncertainty in the semantic classification of food images and recipes. To solve these problems, we propose a Fine-grained Prompting and Alignment (FPA) model to enhance the feature extraction and bring more component-specific information for fine-grained alignment. Furthermore, to regularize the semantic information contained in the cross-modal features, we design an Evidential Semantic Consistency (ESC) loss to keep the cross-modal semantic consistency. We have conducted comprehensive experiments on the benchmark dataset Recipe1M and the state-of-the-art results on the cross-modal recipe retrieval task demonstrate the effectiveness of our method. © 1999-2012 IEEE.

关键词： Alignment

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Precipitation Retrieval of FY-3D MWHTS and MWRI Data Based on Light Gradient Boosting Model

Precipitation Retrieval of FY-3D MWHTS and MWRI Data Based o...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yanfang Lv Lanjie Zhang Yifan Zhang Biao Zhang Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

As an essential component of the earth system, precipitation plays a crucial role in the regional and global water cycle. This paper uses observations from the Fengyun-3D microwave humidity and temperature sounder and microwave radiation imager, as well as Integrated Multi-satellite Retrievals for GPM (IMERG), to establish a precipitation retrieval model based on the light gradient boosting model (LGBM). Using IMERG as the comparison data, the performance of precipitation identification with the LGBM-based precipitation retrieval model is as follows: accuracy is 0.9302, probability of detection is 0.7683, false alarm rate is 0.3529, and critical success index is 0.5414. The performance of precipitation estimation is also evaluated, with a correlation coefficient of 0.7536, a mean absolute error of 0.9119, and a mean squared error of 3.9506. In summary, this study achieves good performance in precipitation identification and estimation by the LGBM model.

关键词： Earth Correlation coefficient Precipitation Estimation Humidity Boosting Data models

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M³FuNet: An Unsupervised Multivariate Feature Fusion Network for Hyperspectral Image Classification

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IEEE Transactions on Geoscience and Remote Sensing 2024年 62卷 1-15页

作者： Chen, Huayue Long, Haoyu Chen, Tao Song, Yingjie Chen, Huiling Zhou, Xiangbing Deng, Wu Key Laboratory of Optimization Theory and Applications at China West Normal University of Sichuan Province School of Computer Science China West Normal University Nanchong637002 China China West Normal University School of Geographical Science Nanchong637002 China Shandong Technology and Business University School of Computer Science and Technology Yantai264005 China Wenzhou University Computer Science Department Wenzhou325035 China Sichuan Tourism University School of Information and Engineering Chengdu610100 China Civil Aviation University of China School of Electronic Information and Automation Tianjin300300 China

Hyperspectral image (HSI) spectral-spatial joint feature (FE) extraction methods generally suffer from low feature retention and weak spatial-spectral dependence, which will lead to single-class feature confrontation (SCFC). To solve this problem, an unsupervised multivariate feature fusion network (M3FuNet) is developed in this article. In M3FuNet, multiscale supervector matrix correction (MSMC) and multiscale random convolution dispersion (MRCD) are used as the spectral and spatial feature extraction method, and the feature retention of spectral and spatial features is improved to achieve feature calibration by feature fusion and decision fusion, called 'multivariate feature fusion.' The MSMC is employed to correct the supervector matrix to reduce the intraclass variance in superpixel homogeneous regions and overcome the phenomenon of supervector block drift (SvBD). The MRCD uses random convolution and Gaussian smoothing to extract deep spatial features. Because of the similar feature representation ability of the MSMC and MRCD, the obtained spectral-spatial joint features have high feature retention and strong spectral-spatial dependence. Finally, this M3FuNet is used for realizing the classification of HSI. Three common HSI datasets are used to validate the effectiveness of the M3FuNet. The experiment results show that the M3FuNet has a superior performance compared with several state-of-the-art (SOTA) HSI classification methods. The code of the proposed M3FuNet is available at https://***/aichou233/M3FuNet. © 1980-2012 IEEE.

关键词： Convolution

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