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arXiv 2024年

作者： Cheng, Ming Lin, Jun Dong, Xintong Lu, Shaoping Zhong, Tie College of Instrumentation and Electrical Engineering Jilin University Jilin Changchun130026 China School of Earth Sciences and Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Zhuhai519000 China Guangdong Provincial Key Lab of Geodynamics and Geohazards Sun Yat-sen University Guangdong Guangzhou510275 China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Jilin132012 China Department of Communication Engineering College of Electric Engineering Northeast Electric Power University Jilin132012 China

Distributed optical fiber acoustic sensing (DAS) is a rapidly-developed seismic acquisition technology with advantages of low cost, high resolution, high sensitivity, and small interval, etc. Nonetheless, consecutively missing cases often appear in real seismic data acquired by DAS system due to some factors, including optical fiber damage and inferior coupling between cable and well. Recently, some deep-learning seismic interpolation methods based on convolutional neural network (CNN) have shown impressive performance in regular and random missing cases but still remain the consecutively missing case as a challenging task. The main reason is that the weight sharing makes it difficult for CNN to capture enough comprehensive features. In this paper, we propose a transformer-based interpolation method, called seismic interpolation transformer (SIT), to deal with the consecutively missing case. This proposed SIT is an encoder-decoder structure connected by some U-shaped swin-transformer blocks. In encoder and decoder part, the multi-head self-attention (MSA) mechanism is used to capture global features which is essential for the reconstruction of consecutively missing traces. The U-shaped swin-transformer blocks are utilized to perform feature extraction operations on feature maps with different resolutions. Moreover, we combine the loss based on structural similarity index (SSIM) and L1 norm to propose a novel loss function for SIT. In experiments, this proposed SIT outperforms U-Net and swin-transformer. Moreover, ablation studies also demonstrate the advantages of new network architecture and loss function. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical fibers

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Detecting Submicron-Scale Continuous Variation in Phase of AC Magnetic Field Around Micro-Circuit With Diamond Quantum Sensor

Detecting Submicron-Scale Continuous Variation in Phase of A...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Fuki Otsubo Takumi Mikawa Yuichiro Matsuzaki Norio Tokuda Norikazu Mizuochi Junko Ishi-Hayase School of Fundamental Science and Technology Keio University Kanagawa Japan Center for Spintronics Research Network Keio University Kanagawa Japan Department of Electrical Electronic and Communication Engineering Faculty of Science and Engineering Chuo University Tokyo Japan Nanomaterials Research Institute Kanazawa University Ishikawa Japan Institute for Chemical Research Kyoto University Kyoto Japan Center for Spintronics Research Network Kyoto University Kyoto Japan International Center for Quantum-field Measurement System for Studies of the Universe and Particles High Energy Accelerator Research Organization Ibaraki Japan

Magnetic field distribution is significant information for LSI failure analysis. In this study, we detected continuous change in phase of AC magnetic field as well as amplitude utilizing RF -dressed states of electron... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Radio frequency Failure analysis Diamonds Lasers and electrooptics Large scale integration Magnetic fields Quantum sensing

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A dulcimer keys positioning method based on improved Roberts operator

A dulcimer keys positioning method based on improved Roberts...

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2021 China Automation Congress, CAC 2021

作者： Tang, De Zhang, Ziying Chen, Xin Xiao, Zhe Qin, Mengxi School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China School of Arts and Communication China University of Geosciences Wuhan430074 China

ISBN: (纸本)9781665426473

It is important for the dulcimer robot to obtain the spatial coordinates of the dulcimer phonemes. However, the traditional manual positioning method is both inefficient and does not meet the intelligence requirements of modern robot. A visual positioning method based on improved Roberts operator is proposed in this paper on account of solving these problems, which can obtain the 3D coordinates of the dulcimer keys in a short time. First, an improved Roberts edge detection operator is designed, which fully detects the edge information of the target by transforming the scale. Further, this paper proposes a dulcimer keys positioning method by fusing RGB and depth image information. This method has a better positioning effect for dulcimer keys with complex background and small size. The experimental results show that the visual positioning method proposed in this paper can effectively identify and locate the dulcimer keys, and it has better robustness to the lighting environment. © 2021 IEEE

关键词： Binocular vision

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Study of photophysical properties of Cdq2 thin film

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Materials Today: Proceedings 2022年 66卷 202-204页

作者： Lougdali, M. El Kouari, Y. Anoua, R. Zazoui, M. El Oudghiri-Idrissi, I. Abboud, Y. Zawadzka, A. Sahraoui, B. Laboratory of Materials Energy and Control System Faculty of Sciences and Technology Hassan II University of Casablanca Mohammedia B.P 146 Morocco Department of Automatic and Measurement Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland Laboratory of Engineering Sciences for Energy National School of Applied Sciences of El Jadida El Jadida BP 1166 Morocco Faculty of Sciences Ben M'sik University of Hassan II of Casablanca Casablanca Morocco Centre for Modern Interdisciplinary Technologies Nicolaus Copernicus University Wilenska 4 Torun 87-100 Poland MOLTECH-Anjou UMR 6200 CNRS UNIV Angers 2 bd Lavoisier Angers 49045 France

In this work, the morphological and optical properties of the cadmium (II) bis(8-hydroxyquinoline) (Cdq2) thin film are presented. The film was elaborated by physical deposition technique. The Atomic Force Microscopy (AFM) image shows a homogenous surface. The transmittance was measured in the range of 300–1200 nm with UV–visible spectroscopy. The emission of the film was characterized via the photoluminescence spectroscopy, a strong luminescence has been found. The measurements done at low temperatures show a decrease of the intensity of luminescence in the temperature range of 77–300 K. © 2022

关键词： Thin films

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Towards non-uniform shadow removal using shadow adaptive normalization

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Digital Signal Processing 2025年 166卷

作者： Xinjie Li Yang Zhao Yuan Chen Dong Wang Li Cao Xiaoping Liu School of Computer Science and Information Engineering Hefei University of Technology Hefei Anhui 230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei Anhui 230009 China School of Internet Anhui University Hefei Anhui 230039 China

Image shadow removal has received increasing attention in recent years. Existing deep learning-based shadow removal methods usually rely on the assumption of globally uniform illumination or employ simplified multiplicative illumination models to estimate parameters related to shadow-free image reconstruction. However, the shading process often contains non-uniform, diverse, and complex shadow patterns, substantially reducing the robustness of current shadow removal techniques and limiting their performance. To address this issue, this paper revisits the traditional shadow degradation model and introduces a pixel-wise adaptive non-uniform illumination model. Building upon this model, a shadow adaptive normalization (SAN) module is designed to estimate the parameter maps of the illumination model and rectify the shadow features within the latent space. The proposed SAN dynamically performs attentive normalization on shadow region features, which can align the statistical distributions of shadow and non-shadow regions. To enhance the efficiency of the SAN module, this paper introduces an intra-module complexity reduction strategy to reduce computational complexity while improving the stability of the training process. In addition, to mitigate the color deviation between paired training data, this paper introduces a Poisson-function-based loss to achieve color robustness. Extensive experiments on image shadow triplet dataset (ISTD), adjusted image shadow triplet dataset (ISTD+), and shadow removal dataset (SRD) validate the superiority of the proposed method over other state-of-the-art (SOTA) approaches.

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Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach

arXiv

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arXiv 2022年

作者： Li, Yuanzheng He, Shangyang Li, Yang Ge, Leijiao Lou, Suhua Zeng, Zhigang School of Artificial Intelligence and Automation Key Laboratory on Image Information Processing and Intelligent Control of Ministry of Education Huazhong University of Science and Technology Wuhan430074 China China-Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering Northeast Electric Power University Jilin 132012 China The Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin 300072 China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China

The electric vehicle (EV) and electric vehicle charging station (EVCS) have been widely deployed with the development of large-scale transportation electrifications. However, since charging behaviors of EVs show large uncertainties, the forecasting of EVCS charging power is non-trivial. This paper tackles this issue by proposing a reinforcement learning assisted deep learning framework for the probabilistic EVCS charging power forecasting to capture its uncertainties. Since the EVCS charging power data are not standard time-series data like electricity load, they are first converted to the time-series format. On this basis, one of the most popular deep learning models, the long short-term memory (LSTM) is used and trained to obtain the point forecast of EVCS charging power. To further capture the forecast uncertainty, a Markov decision process (MDP) is employed to model the change of LSTM cell states, which is solved by our proposed adaptive exploration proximal policy optimization (AePPO) algorithm based on reinforcement learning. Finally, experiments are carried out on the real EVCSs charging data from Caltech, and Jet Propulsion Laboratory, USA, respectively. The results and comparative analysis verify the effectiveness and outperformance of our proposed framework. Copyright © 2022, The Authors. All rights reserved.

关键词： Markov processes

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Research on Space-Time Block Code technology in MIMO System

Research on Space-Time Block Code Technology in MIMO System

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International Conference on Computer and communications (ICCC)

作者： Conglin Pan Si Chen Wei Wu Jiachuan Qian Lijun Wang Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of CETC Jiaxing China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781665409513

MIMO technology has been widely used in the telecommunication systems nowadays, and the space-time coding is a key part of MIMO technology. A good coding scheme can exploit the spatial diversity to correct the error which is generated in transmission, and increase the normalized transfer rate with low decoding complexity. On the Basis of the research on different Space-Time Block Codes, this essay proposes a new STBC, Diagonal Block Orthogonal Space-Time Block Code. Then we will compare it with other STBCs in the performance of bit error rate, transfer rate, decoding complexity and peek-to-average power ratio, the final result will prove the superiority of DBOAST.

关键词： Spatial diversity Bit error rate Encoding Decoding Complexity theory Telecommunications Block codes

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Spreading dynamics of information on online social networks

arXiv

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arXiv 2025年

作者： Meng, Fanhui Xie, Jiarong Sun, Jiachen Xu, Cong Zeng, Yutian Wang, Xiangrong Jia, Tao Huang, Shuhong Deng, Youjin Hu, Yanqing School of Systems Science and Engineering Sun Yat-sen University Guangzhou510275 China Center for Computational Communication Research Beijing Normal University Zhuhai519087 China School of Journalism and Communication Beijing Normal University Beijing100875 China School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Department of Statistics and Data Science College of Science Southern University of Science and Technology Shenzhen518055 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China College of Computer and Information Science Chongqing Normal University Chongqing401331 China College of Computer and Information Science Southwest University Chongqing400715 China Institute of Neuroscience Technical University of Munich Munich80802 Germany Department of Modern Physics University of Science and Technology of China Hefei230026 China MinJiang Collaborative Center for Theoretical Physics College of Physics and Electronic Information Engineering Minjiang University Fuzhou350108 China Center for Complex Flows and Soft Matter Research Southern University of Science and Technology Shenzhen518055 China

Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.45 billion users, we uncover a ubiquitous mechanism that the information spreading dynamics are basically driven by the interplay of social reinforcement and social weakening effects. Accordingly, we propose a concise equation, which, surprisingly, can well describe all the empirical large-scale spreading trajectories. Our theory resolves a number of controversial claims and satisfactorily explains many phenomena previously observed. It also reveals that the highly clustered nature of social networks can lead to rapid and high-frequency information bursts with relatively small coverage per burst. This vital feature enables social media to have a high capacity and diversity for information dissemination, beneficial for its ecological development. © 2025, CC BY.

关键词： Tweets

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Groundwater resources survey of tongchuan city using the audio magnetotelluric method

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Applied Geophysics 2020年第5期17卷 660-671,900页

作者： Xu Zhi-min Tang Jing-tian Li Guang Xin Hui-Cui Xu Zhang-jian Tan Xin-ping LI Jin Heibei Instrument&Meter Engineering Technology Research Center Chengde Petroleum CollegeChengde 067000China School of Geosciences and Info-Physics Central South UniversityChangsha 410083China Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education(Central South University)Changsha 410083China Northwest Research Institution of Engineering Investigations and Design Xi’an 710003China School of Geophysics and Measurement-control Technology Nanchang 330013China College of Information Science and Engineering Hunan Normal UniversityChangsha 410081China

The development of Tongchuan City,Shaanxi Province,located in the northwestern region of China,is restricted by water *** direct current resistivity and induced polarization sounding methods are typically applied in finding urban *** methods,however,are not effective due to their complicated topography and geological *** application practice shows that the audio magnetotelluric(AMT)method has a large depth of exploration,high work effi ciency,and high lateral *** investigate the distribution of groundwater resources,we deployed three audio-frequency magnetotelluric profiles in the city *** impedance tensor information of AMT data is obtained using *** data dimension analysis reveals that the two-dimensional structural features of the observation area are *** main structure of the observation area is about 45°northeast,as indicated by structural trend analysis.A shallow two-dimensional electrical profile of 1 km in Tongchuan City is obtained by two-dimensional nonlinear conjugate gradient ***,combined with regional geological information,the geological structure characteristics reflected by the electrical profile were obtained along with the detailed characteristics of water-rich structures in the *** infl uence of the structure on the groundwater distribution was analyzed,and the water-rich areas were identifi *** work contributes to the prospective development of Tongchuan City.

关键词： urban geology audio magnetotelluric sounding method electrical structure groundwater resources

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Hierarchical Convolutional Features Fusion for Visual Tracking 2

Hierarchical Convolutional Features Fusion for Visual Tracki...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Zhang, Fan Chang, Shuo Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100101 China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China Beijing University of Posts and Telecommunications Beijing100081 China

Hierarchical convolutional features have different impact on the tracking performance, as the higher convolutional layers encode the semantic information of targets and earlier convolutional layers are more precise to localize targets. In this paper, we propose a novel scheme for hierarchical convolutional features fusion for visual tracking. In the proposed scheme, hierarchical convolutional features are first concatenated to form the cascading feature at the feature level, and then a convolutional layer is added to reduce the feature dimension. Discriminative correlation filter (DCF) is finally utilized to obtain the target location, which is treated as a differentiable layer in the neural network. The experimental results demonstrate that our proposed scheme achieves superior performances on the visual tracking benchmark. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Convolution

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