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Investigation into enhancing the sensitivity method for monitoring trace erosion product concentration in the ceramic channel of a Hall thruster

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Plasma science and technology 2025年第4期27卷 95-104页

作者： Wei XI Ximing ZHU Bowen ZHENG Zhongxi NING Daren YU School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001People’s Republic of China Key Laboratory of Aerospace Plasma Propulsion Ministry of Industry and Information TechnologyHarbin 150001People’s Republic of China

An optical emission spectroscopy(OES)method with a non-invasive measurement capability,without inducing disturbance to the discharge,represents an effective method for material ***,when the OES method is employed to monitor the trace erosion product within the ceramic channel of a Hall thruster,it becomes challenging to distinguish between signal and *** this study,we propose a model filtering method based on the signal characteristics of the Hall thruster plume *** method integrates the slit imaging and spectral resolution features of the *** this method,we extract the spectral signals of the erosion product and working gas from the Hall thruster under different operating *** results indicate that our new method performs comparably to the traditional method without model filtering when extracting atom signals from strong xenon working ***,for trace amounts of the erosion product,our approach significantly enhances the signal-to-noise ratio(SNR),enabling the identification of extremely weak spectral signals even under low mass flow rate and low-voltage *** obtain boron atom concentration of 3.91×10^(-3) kg/m^(3) at a mass flow rate of 4×10^(-7) kg/s and voltage of 200 V while monitoring a wider range of thruster operating *** new method proposed in this study is suitable for monitoring other low-concentration elements,making it valuable for materials processing,environmental monitoring and space propulsion applications.

关键词： model filtering method optical emission spectroscopy Hall thruster advanced actinometry method trace erosion product concentration(Some figures may appear in colour only in the online journal)

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IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

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Computers, Materials & Continua 2024年第2期78卷 2667-2687页

作者： Xiao Luo Hao Zhu Zhenli Zhang Department of Electrical Engineering and Automation Jiangxi University of Science and TechnologyGanzhou341000China Jiangxi Provincial Key Laboratory of Maglev Technology Ganzhou341000China Graduate School of Information Production and SystemsWaseda UniversityKitakyushu-shiFukuoka808-0135Japan

Road traffic safety can decrease when drivers drive in a low-visibility *** application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of *** tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small ***,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category ***,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection *** test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only *** contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource *** the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the *** improved algorithm has shown significant advancements in balancing accuracy and computati

关键词： Traffic safety infrared image pedestrians and vehicles focal GIoU distributed shift convolution

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Research on Optimal Preload Method of Controllable Rolling Bearing Based on Multisensor Fusion

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Computer Modeling in engineering & sciences 2024年第6期139卷 3329-3352页

作者： Kuosheng Jiang Chengrui Han Yasheng Chang School of Mechanical and Electrical Engineering Anhui University of Science and TechnologyHuainan232001China School of Optical and Electronic Information Suzhou City University&Suzhou Key Laboratory of BiophotonicsSuzhou215104China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an710054China

Angular contact ball bearings have been widely used in machine tool spindles,and the bearing preload plays an important role in the performance of the *** order to solve the problems of the traditional optimal preload prediction method limited by actual conditions and uncertainties,a roller bearing preload test method based on the improved D-S evidence theorymulti-sensor fusion method was ***,a novel controllable preload system is proposed and ***,multiple sensors are employed to collect data on the bearing parameters during preload ***,a multisensor fusion algorithm is used to make predictions,and a neural network is used to optimize the fitting of the preload *** limitations of conventional preload testing methods are identified,and the integration of complementary information frommultiple sensors is used to achieve accurate predictions,offering valuable insights into the optimal preload *** results demonstrate that the multi-sensor fusion approach outperforms traditional methods in accurately measuring the optimal preload for rolling bearings.

关键词： Multi-sensor information fusion neural network preload force

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Remote entangling gate between a quantum dot spin and a transmon qubit mediated by microwave photons

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Chinese Physics B 2024年第2期33卷 52-59页

作者：朱行宇朱乐天涂涛李传锋 Key Laboratory of Quantum Information Chinese Academy of SciencesUniversity of Science and Technology of ChinaHefei 230026China School of Mechanical and Electronic Engineering Suzhou UniversitySuzhou 234000China Hefei National Laboratory University of Science and Technology of ChinaChinese Academy of SciencesHefei 230088China

Spin qubits and superconducting qubits are promising candidates for realizing solid-state quantum information *** a hybrid architecture that combines the advantages of different qubits on the same chip is a highly desirable but challenging *** we propose a hybrid architecture that utilizes a high-impedance SQUID array resonator as a quantum bus,thereby coherently coupling different solid-state *** employ a resonant exchange spin qubit hosted in a triple quantum dot and a superconducting transmon *** this hybrid system is highly tunable,it can operate in a dispersive regime,where the interaction between the different qubits is mediated by virtual *** utilizing such interactions,entangling gate operations between different qubits can be realized in a short time of 30 ns with a fidelity of up to 96.5%under realistic parameter *** utilizing this interaction,remote entangled state between different qubits can be prepared and is robust to perturbations of various *** results pave the way for exploring efficient fault-tolerant quantum computation on hybrid quantum architecture platforms.

关键词： hybrid quantum architectures circuit quantum electrodynamics entangling gate

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DFT-SPREAD COMBINED WITH PTS METHOD TO REDUCE THE PAPR IN RADCOM SYSTEM 10

DFT-SPREAD COMBINED WITH PTS METHOD TO REDUCE THE PAPR IN RA...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Zhi, Ruxin Quart, Cong Xu, Zhan Yang, Xiaolong 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 Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

In radar communication integration (RADCOM) systems based on orthogonal frequency division multiplexing (OFDM) technology, high peak to average power ratio (PAPR) is one of the main factors affecting system performance. This article analyses the PAPR probability distribution of radar communication integrated signals based on OFDM. In order to reduce the PAPR of integrated signals, the discrete Fourier transform spread spectrum (DFT Spread) technology suitable for traditional OFDM systems has been improved and combined with partial transmission sequences (PTS) to further reduce the PAPR of radar communication integrated signals. The simulation results show that compared with using DFT spread spectrum technology alone, PTS technology alone, and the original signal, the proposed DFT PTS joint algorithm based on linear interpolation reduces PAPR by 1.5 dB, 2.4 dB, and at least 4.1 dB, respectively. Obviously, the DFT-PTS joint algorithm achieved the best PAPR suppression effect. © The Institution of engineering & technology 2024.

关键词： Orthogonal frequency division multiplexing

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Deep learning-based software engineering: progress,challenges, and opportunities

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science China(information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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Lewis base multisite ligand engineering in efficient and stable perovskite solar cells

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Journal of Energy Chemistry 2024年第12期99卷 277-291页

作者： Danqing Ma Dongmei He Qing Zhu Xinxing Liu Yue Yu Xuxia Shai Zhengfu Zhang Sam Zhang Jing Feng Jianhong Yi Jiangzhao Chen Key Laboratory of Optoelectronic Technology&Systems(Ministry of Education) College of Optoelectronic EngineeringChongqing UniversityChongqing 400044China Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093YunnanChina Institute of Physical and Engineering Science/Faculty of Science Kunming University of Science and TechnologyKunming 650500YunnanChina School of Aeronautics Harbin Institute of TechnologyHarbin 150001HeilongjiangChina HIT Zhengzhou Research Institute Zhengzhou 450000HenanChina

Perovskite solar cells(PSCs) have stood out from many photovoltaic technologies due to their flexibility,cost-effectiveness and high-power conversion efficiency(PCE). Nevertheless, the further development of PSCs is greatly hindered by the trap-induced non-radiative recombination losses and poor long-term work stability. In the past decade, the huge advancements have been obtained on suppressing nonradiative recombination and enhancing device durability. Among them, the multisite ligands(MSLs) engineering plays a crucial role in precise control and directional modification of functional layers and interfaces,which contributes to markedly increased PCE and lifetimes of PSCs. In view of this, this review summarizes the advances of MSLs in PSCs. From the perspective of functional groups and chemical interaction,the modulation mechanisms of properties of different functional layers and interfaces and device performance via various MSLs are deeply investigated and revealed. Finally, the prospects for the application and development direction of MSLs in PSCs are legitimately proposed.

关键词： Perovskite solar cells Multisite ligands Defect passivation Ion migration suppression Stability

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A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1424-1437页

作者： Quanbo Ge Yang Cheng Hong Li Ziyi Ye Yi Zhu Gang Yao School of Automation Nanjing University of Information Science&TechnologyJiangsu Provincial University Key Laboratory of Big Data Analysis and Intelligent SystemsNanjing University of Information Science&Technologyand the Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Nanjing University of Information Science&TechnologyNanjing 210044China School of Department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China China Classification Society Nantong Office Nantong 226006China Chinese Flight Test Establishment Xi’an 710089China School of Mathematics Tsinghua UniversityBeijing 100084China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China Department of Logistics Engineering Shanghai Maritime UniversityShanghai 201306China IEEE

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity *** the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and *** com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

关键词： Curve similarity matching Gaussian-like noise non-parametric scheme parzen window.

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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Wireless Interference Classification with Low Complexity Multi-Branch Networks

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China Communications 2023年第4期20卷 382-394页

作者： Song Ma Yufan Cheng Ying Mou Pengyu Wang Qihang Peng Jun Wang National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

In non-cooperative communication systems,wireless interference classification(WIC)is one of the most essential ***,deep learning(DL)based WIC methods have been ***,conventional DL-based WIC methods have high computational complexity and unsatisfactory accuracy,especially when the interference-tonoise ratio(INR)is *** this end,we propose three effective ***,we introduce multibranch convolutional neural networks(CNNs)for interference *** multi-branch CNN is constructed by repeating a layer that aggregates several transformations with the same topology,and it notably improves the recognition ability for *** design avoids the carefully crafted selection of each ***,multi-branch CNNs are computationally expensive and *** this end,we further propose Low complexity multibranch networks(LCMN),which are mathematically equivalent to multi-branch CNNs but maintain low computing costs and efficient ***,we present novel loss function,which encourages networks to have consistent prediction probabilities for samples with high visual similarities,resulting in increasing recognition accuracy of *** results demonstrate the proposed methods consistently boost the classification performance of WIC without substantially increasing computational overhead compared to traditional DL-based methods.

关键词： electromagnetic interference wireless interference identification deep learning multi-branch architectures

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