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SSRN 2023年

作者： He, Weiguo Huo, Weijie Duan, Xinxin Gu, Jun Zhu, Kangwu School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou310024 China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Taiji Laboratory for Gravitational Wave Universe Hangzhou310024 China Shanghai Aerospace Electronic Technology Institute Shanghai201109 China Shanghai SastSpace Technology Co. Ltd Shanghai201109 China Shanghai Aerospace Control Technology Institute Shanghai201109 China

Improving the high-voltage resistance of the discharge cavity is essential to enhancing the performance of the hollow-cathode electron source. In this work, a discharge cavity of the hollow-cathode electron beam source is designed and optimized by stacking and isolating the insulating sheets. The experimental results indicate that the optimized design not only improves the overall high-voltage resistance of the device but also improves the stability of the discharge. Meanwhile, it is found that when the amplitude of the discharge breakdown voltage is increased from 12 kV to 20 kV, the resistance of the discharge cavity varies within the range of 3.8–3.7 Ω, with a slight change in the amplitude, and the inductance decreases from 356 nH to 323.1 nH. The experimental study of the high-pressure gas discharge characteristics in the discharge cavity reveals that the change in gas pressure leads to a significant change in the discharge pattern, and compared with the glow discharge, the hollow-cathode discharge significantly improves the discharge current and shortens the breakdown time of the discharge. Under the same air pressure, the breakdown voltage of the discharge decreases and then increases with the increase in cathode cavity length. © 2023, The Authors. All rights reserved.

关键词： Glow discharges

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Exploiting Active RIS in NOMA Networks with Hardware Impairments

arXiv

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arXiv 2023年

作者： Yue, Xinwei Song, Meiqi Ouyang, Chongjun Liu, Yuanwei Li, Tian Hou, Tianwei The Key Laboratory of Information and Communication Systems Ministry of Information Industry China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Electrical and Electronic Engineering University College Dublin DublinD04 V1W8 Ireland The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The 54th Research Institute of China Electronics Technology Group Corporation Hebei Shijiazhuang050081 China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Erlangen91054 Germany

Active reconfigurable intelligent surface (ARIS) is a promising way to compensate for multiplicative fading attenuation by amplifying and reflecting event signals to selected users. This paper investigates the performance of ARIS assisted non-orthogonal multiple access (NOMA) networks over cascaded Nakagami-m fading channels. The effects of hardware impairments (HIS) and reflection coefficients on ARIS-NOMA networks with imperfect successive interference cancellation (ipSIC) and perfect successive interference cancellation (pSIC) are considered. More specifically, we develop new precise and asymptotic expressions of outage probability and ergodic data rate with ipSIC/pSIC for ARIS-NOMA-HIS networks. According to the approximated analyses, the diversity orders and multiplexing gains for couple of non-orthogonal users are attained in detail. Additionally, the energy efficiency of ARIS-NOMA-HIS networks is surveyed in delay-limited and delay-tolerant transmission schemes. The simulation findings are presented to demonstrate that: i) The outage behaviors and ergodic data rates of ARIS-NOMA-HIS networks precede that of ARIS aided orthogonal multiple access (OMA) and passive reconfigurable intelligent surface (PRIS) aided OMA;ii) As the reflection coefficient of ARIS increases, ARIS-NOMA-HIS networks have the ability to provide the strengthened outage performance;and iii) ARIS-NOMA-HIS networks are more energy efficient than ARIS/PRIS-OMA networks and conventional cooperative schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy efficiency

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Adaptive Hybrid Potential Evapotranspiration (Pet) Prediction Method Based on Automatic Machine Learning

SSRN

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SSRN 2024年

作者： Zhang, Chenjia Xu, Tianxin Zhang, Yan Abdu Kaimu, Abullimiti Guo, Lirui Zhang, Yutong Ma, Daokun Xinjiang Agricultural University China College of Information and Electrical Engineering China Agricultural University Haidian District Beijing100089 China School of Yi Language and Culture Xichang University Sichaun Xichang831000 China Beijing Lianchuang Siyuan Measurement and Control Technology Co. Ltd. Beijing Beijing615000 China College of Information Engineering Yangzhou University Hanjiang District Jiangsu Yangzhou225009 China College of Resources and Environment China Agricultural University Haidian District Beijing100094 China

An adaptive hybrid model based on automatic machine learning for short-term PET prediction is proposed coupling neural network and PET formula. 105 standard weather stations in Xinjiang were used as data sets (43 of them had missing data) to test model. According to modules, networks and PET formulas used in the prediction process, corresponding labels were generated in each dataset forecast result. Ratio of training set and test set for each data set was 8:2. Grid search was used to optimize the best hyperparameter combination. In test set, the average absolute error (MAE) and average squared error (MSE) of the model prediction were 0.338mm and 0.270. We prove that the neural network applicability varies among the used data sources, and that GRU and 1 DCNN are more suitable for the selected datasets, while LSTM and MLP are not applicable. We find evidences that applicability of neural networks and PET formulas is independent of geographic region and degree of drought. In 2023, method of rolling prediction for 1-15 days is verified, PET prediction error based on neural network is significantly smaller than useing weather forecast data to calculate PET. In addition, by comparison，we determined that adaptive input length can effectively reduce the prediction error, MAE was 27.52% smaller than fixed input length, and MSE was 45.76% smaller than fixed input length. © 2024, The Authors. All rights reserved.

关键词： Statistical tests

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OFDM Signal Design Based on Electrode-based Through-the-earth Communication

OFDM Signal Design Based on Electrode-based Through-the-eart...

引用

International Conference on Ubiquitous Computing and communications and International Symposium on Cyberspace and Security (IUCC-CSS)

作者： Gan Zhang Zhan Xu Jinhui Chen Xiaowen Wen Key Laboratory of Modern Measurement and Control Technology Beijing Information Science and Technology University Beijing China School of Automation Beijing Information Science and Technology University Beijing China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781665466684

Through-the-earth (TTE) communication is of great significance to establish the information transmission with the trapped people at the first time and ensure the smooth flow of information. The complex electromagnetic environment of the terrestrial channel brings many difficulties in wireless signal transmission. This paper proposes an orthogonal frequency division multiplexing (OFDM) signal design scheme of electrode-based TTE communication. The scheme, which has intense penetration and high reliability, designs the frequency and modulation mode of the subcarrier according to the electromagnetic characteristics of earth channel and noise interference. This paper also provides the results of field experiments to show the performance of this OFDM signal.

关键词： Earth Wireless communication Frequency modulation OFDM Low-pass filters Interference Ubiquitous computing

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A TTSVD-Enhanced Fast and Accurate Channel Estimation Method for Dual-Polarized Massive MIMO Systems

A TTSVD-Enhanced Fast and Accurate Channel Estimation Method...

引用

2021 IEEE International Conference on Signal Processing, communications and Computing, ICSPCC 2021

作者： Gong, Xiao Chen, Wei Chen, Xuying Chen, Jie Ai, Bo Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing China Frontiers Science Center for Smart High-speed Railway System Beijing China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing China Northwestern Polytechinical University School of Marine Science and Technology Xi'an China

ISBN: (纸本)9781665429184

This paper aims to perform fast and accurate downlink channel estimation for dual-polarized massive multiple-input multiple-output (MIMO) systems. Considering that both ends of the link are equipped with antenna arrays, the double directional channel matrix can be represented by a higherorder tensor. Based on the low-rankness of channel tensor due to the sparse scattering nature, we propose an ESPRIT-like channel estimation method enhanced by tensor train singular value decomposition (TTSVD). The proposed estimation method is characterized by (a) small estimation errors, which benefits from employing TTSVD to reduce noise in the channel tensor;and (b) fast computational speed, which exploits Vandermonde structure of signal subspace without multiple iterations. Simulated experiments in a 5G millimeter wave scenario show the superior estimation performance of the proposed method both on accuracy and speed. It is worth noting that the proposed method is at least 12 times faster than the state-of-The-Art. © 2021 IEEE.

关键词： Singular value decomposition

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

引用

arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Microstructure and Properties of Graphene Reinforced Co-Based Composite Coating by Laser Cladding

SSRN

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SSRN 2022年

作者： Chang, Wei Xiao, Guangchun Zhang, Hui Chen, Hui Yi, Mingdong Zhang, Jingjie Chen, Zhaoqiang Xu, Chonghai School of Mechanical and Automotive Engineering Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Key Laboratory of Equipments Manufacturing and Intelligent Measurement and Control China National Light Industry Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Shandong Institute of Mechanical Design and Research Jinan250031 China

Graphene (Gr)-reinforced Co-based (Co50) composite coatings were prepared on 40Cr steel substrates by laser cladding technology. The effects of different amounts of Gr addition on the microstructure and mechanical properties of the coating were studied. The addition of a proper amount of Gr can improve the comprehensive properties of the coating, and most Gr forms carbides, such as Cr23C6 and Cr7C3, under the action of laser irradiation. The addition of Gr can significantly refine the grains and evenly distribute them. When the addition of Gr is 3 ωt%, the average grain size is the smallest in the coating, which is 5.7 μm, and the highest microhardness reaches 777.5 HV0.2, which is an increase of 270.2% compared with the substrate. The unmelted Gr remains dispersed in the coating, which can improve lubrication and reduce friction. The average friction coefficient and wear volume are decreased to 0.335 and 4.26×107 μm3, which are approximately 54.2% and 28.0% of the substrate, respectively. © 2022, The Authors. All rights reserved.

关键词： Microstructure

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Noise prediction and reduction of single electron spin by deep-learning-enhanced feedforward control

arXiv

引用

arXiv 2022年

作者： Xu, Nanyang Zhou, Feifei Ye, Xiangyu Lin, Xue Chen, Bao Zhang, Ting Yue, Feng Chen, Bing Wang, Ya Du, Jiangfeng Research Center for Quantum Sensing Zhejiang Lab Hangzhou311000 China School of Physics Hefei University of Technology Anhui Hefei230009 China CAS Key Laboratory of Microscale Magnetic Resonance University of Science and Technology of China Hefei230026 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

Noise-induced control imperfection is an important problem in applications of diamond-based nano-scale sensing, where measurement-based strategies are generally utilized to correct low-frequency noises in realtime. However, the spin-state readout requires a long time due to the low photon-detection efficiency. This inevitably introduces a delay in noise-reduction process and limits its performance. Here we introduce the deep learning approach to relax this restriction by predicting the trend of noise and compensating the delay. We experimentally implement feedforward quantum control of nitrogen-vacancy center in diamond to protect its spin coherence and improve the sensing performance against noise. The new approach effectively enhances the decoherence time of the electron spin, which enables exploring more physics from its resonant spectroscopy. A theoretical model is provided to explain the improvement. This scheme could be applied in general sensing schemes and extended to other quantum systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Magnetic resonance

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Classification of aerosols using particle linear depolarization ratio (PLDR) over seven urban locations of Asia

引用

Chemosphere 2024年 350卷 141119页

作者： Tariq, Salman Nisa, Aiman ul-Haq, Zia Mariam, Ayesha Murshed, Muntasir Sulaymon, Ishaq Dimeji Salam, Mohammed Abdus Mehmood, Usman Department of Space Science University of the Punjab Lahore Pakistan Centre for Remote Sensing University of the Punjab Lahore Pakistan Department of Economics School of Business and Economics North South University Dhaka1229 Bangladesh Department of Journalism Media and Communications Daffodil International University Dhaka Bangladesh Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing210044 China Department of Environmental Science and Disaster Management Noakhali Science and Technology University Noakhali3814 Bangladesh Department of Business Administration Bahçeşehir Cyprus University Northern Cyprus Nicosia Turkey

Active lidar remote sensing has been used to obtain detailed and quantitative information about the properties of aerosols. We have analyzed the spatio-temporal classification of aerosols using the parameters of particle linear depolarization ratio and single scattering albedo from Aerosol Robotic Network (AERONET) over seven megacities of Asia namely;Lahore, Karachi, Kanpur, Pune, Beijing, Osaka, and Bandung. We find that pollution aerosols dominate during the winter season in all the megacities. The concentrations, however, vary concerning the locations, i.e., 70–80% pollution aerosols are present over Lahore, 40–50% over Karachi, 90–95% over Kanpur and Pune, 60–70% and over Beijing and Osaka. Pure Dust (PD), Pollution Dominated Mixture (PDM), and Dust Dominated Mixture (DDM) are found to be dominant during spring and summer *** proposes that dust over Asia normally exists as a mixture with pollution aerosols instead of pure form. We also find that black carbon (BC) dominated pollution aerosols. © 2024 Elsevier Ltd

关键词： Remote sensing

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Study of photophysical properties of Cdq2 thin film

引用

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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