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4th International Conference on Information Science and Education, ICISE-IE 2023

作者： Chen, Xiaopan Li, Boyuan Zhu, Xiaoke Zhang, Tao School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology Henan University Kaifeng China Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China

ISBN: (纸本)9798350394610

This paper aims to enhance the efficiency of teaching and learning by leveraging computer vision technology for automated analysis of student behavior in the classroom. We propose a feature-enhanced method for recognizing student behavior, which integrates an Upsampling module (UPS) and a convolutional block layer (CBL) module into the YOLOv5 model. This innovative approach significantly improves the detection and feature extraction capabilities for student targets, effectively addressing challenges associated with small-sized targets and lowresolution images. Through algorithm optimization, it achieves a balance in sample diversity, enhancing the model's adaptability and generalizability in complex classroom environments. Building upon these technological advancements, we have developed a Classroom Student Posture Perception System (CSP2S). This system integrates functions for data collection, student behavior detection, and result visualization. The CSP2S operates in realtime by capturing and analyzing students' behavioral dynamics while providing teachers with immediate feedback. Experimental results demonstrate that this system substantially reduces teachers' workload in student assessment, offering significant potential to improve teaching effectiveness. These robust technical advancements provide strong support for future applications in real educational environments. © 2023 IEEE.

关键词： Students

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Research on Weld Detection Based on Weighted Feature Fusion Network 23

Research on Weld Detection Based on Weighted Feature Fusion ...

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15th International Conference on Digital Image Processing, ICDIP 2023

作者： Wang, Mengxue Ma, Xing Mu, Chunyang Hou, Bing College of Electronic and Information Engineering North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing North Minzu University Yinchuan China

ISBN: (纸本)9798400708237

Weld seam grinding is a crucial process for welding cast products. Not only are the polished welds more attractive and durable, but they also have superior stress effects. However, the workplace is harsh and can significantly impact health. The first task for automated weld grinding is weld detection. This paper, a pyramid feature fusion network (YOLOv5-BiCA) learning model with embedded coordinate attention as a weighting condition that fully utilizes the shallow and deep network information. An online data augmentation strategy employing Mosaic+Mixup is proposed to address the problem of insufficient sample size. We use Focal Loss to enhance the classification function and increase the positive influence of positive samples on the loss function during the training process to address the problem of an imbalance between positive and negative sample. Our proposed YOLOv5-BiCA performs better in weld detection, mAP improves by 3.5%, and recall improves by 7.97%, according to experimental results based on homegrown datasets. © 2023 ACM.

关键词： Welds

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Oriented Object Detection in Aerial Images with Double Midpoint Vectors 9

Oriented Object Detection in Aerial Images with Double Midpo...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Zhu, Xiaoke Hu, Qi Chen, Xiaopan Yuan, Caihong Li, Minghao Henan University School of Computer and Information Engineering Kaifeng China Henan University Henan Engineering Research Center of Intelligent Technology and Application China Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China

ISBN: (纸本)9798350317251

In recent years, oriented object detection technology has made significant progress. Most oriented object detectors represent oriented bounding boxes by adding additional angle information to the horizontal bounding box representation, which leads to serious angle periodicity issues. To address these issues, this paper proposes double midpoint vectors (DMvectors) to represent oriented objects. For any oriented bounding box, we align the center point with the origin in the Cartesian coordinate system, and evenly distribute the midpoints of the box edges across the four quadrants. We use the midpoint of the first and second quadrants, as well as the width and height of the box, to represent the oriented bounding box. DMvectors solve the periodic problem of angles by implicitly including angle information in vectors. To demonstrate the effectiveness of our proposed method, we conducted extensive experiments on two common remote sensing datasets (DOTA and HRSC2016), and our method achieved competitive results. © 2023 IEEE.

关键词： Object detection

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Research on Ultra-wide Bandwidth Low-frequency Signal Channelization for Xinjiang 110m Radio Telescope

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Research in Astronomy and Astrophysics 2023年第12期23卷 263-274页

作者： Hai-Long Zhang Ya-Zhou Zhang Meng Zhang Jie Wang Jian Li Xin-Chen Ye Xin Pei Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Radio Astronomy Chinese Academy of SciencesNanjing 210008China National Astronomical Data Center Beijing 100101China School of Cyber Science and Engineering Qufu Normal UniversityQufu 273165China

Aiming at the subband division of ultra-wide bandwidth low-frequency(UWL)signal(frequency coverage range:704–4032 MHz)of the Xinjiang 110 m QiTai radio Telescope(QTT),a scheme of ultra-wide bandwidth signal is ***,we analyze the effect of different window functions such as the Hanning window,Hamming window,and Kaiser window on the performance of finite impulse response(FIR)digital filters,and implement a critical sampling polyphase filter bank(CS-PFB)based on the Hamming window FIR digital ***,we generate 3328 MHz simulation data of ultra-wideband pulsar baseband in the frequency range of 704–4032 MHz using the ultra-wide bandwidth pulsar baseband data generation algorithm based on the 400 MHz bandwidth pulsar baseband data obtained from Parkes CASPSR ***,we obtain 26 subbands of 128 MHz based on CS-PFB and the simulation data,and the pulse profile of each subband by coherent dispersion,integration,and ***,the phase of each subband pulse profile is aligned by non-coherent dedispersion,and to generate a broadband pulse profile,which is basically the same as the pulse profile obtained from the original data using *** experimental results show that the scheme for the QTT UWL receiving system is feasible,and the proposed channel algorithm in this paper is effective.

关键词： pulsars general-methods data analysis-techniques miscellaneous

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Enhancing Programming Course Quality through Human Posture Recognition and Screen Content Detection 4

Enhancing Programming Course Quality through Human Posture R...

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4th International Conference on Information Science and Education, ICISE-IE 2023

作者： Chen, Xiaopan Bai, Haiyang Zhu, Xiaoke Dong, Lingyuan School of Computer and Information Engineering Henan University Kaifeng China Henan Engineering Research Center of Intelligent Technology Henan University Kaifeng China Henan University Henan Key Laboratory of Big Data Analysis and Processing Kaifeng China

ISBN: (纸本)9798350394610

The evaluation of programming course instruction is a key component of educational management. However, relying solely on supervising teachers for assessment poses challenges in comprehensive evaluation and providing feedback on students' classroom learning status. Additionally, a significant amount of monitoring video data from programming courses in Chinese universities remains underutilized. To address these challenges, this paper combines traditional educational management with artificial intelligence and proposes an intelligent algorithm for detecting students' learning status in programming courses. We first establish a dual YOLO network model to analyze students' postures and screen content in programming classroom monitoring videos, thereby identifying their behaviors. Subsequently, we develop a Programming Classroom Student Behavior Recognition System (PCSBS) that integrates data collection, student behavior detection, and result visualization functionalities. Experimental results demonstrate that the system can accurately provide feedback on students' programming course learning status, offering graded results that assist supervising teachers in their classroom instructional evaluation tasks to enhance educational management efficiency. © 2023 IEEE.

关键词： Students

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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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Gray-scale transformation for traffic classification: leveraging local and global features in flow data 3

Gray-scale transformation for traffic classification: levera...

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3rd International Conference on Electronic Information engineering, Big data, and Computer Technology, EIBDCT 2024

作者： Xia, Yuchao Xue, Mutian Li, Wei Network and Data Security Key Laboratory of Sichuan Province School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China University of Electronic Science and Technology of China Chengdu China Sichuan University of Media and Communications Chengdu China

ISBN: (纸本)9781510680449

The rapid expansion and diversification of internet traffic pose a pressing demand for accurate classification of diverse application streams in network management and security monitoring. This paper introduces a deep learning-based method for precise classification of diverse internet application streams in network. By transforming raw traffic data into grayscale images and utilizing Convolutional Neural Networks (CNNs) and the Swin-Transformer framework, critical information is extracted at both local and global feature levels. The core of this method is offering a visual representation of the structure and content of traffic data. This visual representation enables subsequent feature extraction and classification. Through experimentation across various applications including email, Skype, YouTube, Vimeo, FTP, and Facebook, the proposed method in traffic classification is demonstrated to be effective. This approach boosts traffic classification accuracy, offers innovation in network management and security monitoring, and holds vital importance in optimizing network performance and security. Additionally, it sets the stage for future research in networking data processing and security methodologies. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Network security

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Fault Estimation for Nonlinear Systems with Disturbance Based on Reinforcement Iterative Learning Strategy 13

Fault Estimation for Nonlinear Systems with Disturbance Base...

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13th IEEE data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Chen, Zhengquan Huang, Ruirui Zhang, Zhiheng Hou, Yandong Henan University School of Computer and Information Engineering Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China School of Artificial Intelligence Henan University Zhengzhou450000 China

ISBN: (纸本)9798350361674

This paper addresses the problem of low fault estimation accuracy in Lipschitz nonlinear systems with external disturbances, presenting an innovative strategy based on a Reinforcement Iterative Learning (RIL) framework. Initially, we conducted precise mathematical modeling, comprehensively considering the impact of Lipschitz non-linearity and external disturbances. Subsequently, an iterative learning fault observer was designed, and the optimization problem for its parameters was reformulated into a reinforcement learning task, clearly defining the states, actions, and reward functions. Employing the Advantage Actor-Critic (A2C) reinforcement learning method, we optimized the gain parameters of the iterative learning fault estimator to approximate non-linearity. Simultaneously, with the increase in iteration count, the neural network weights were continually optimized, achieving accurate fault estimation. Experimental results demonstrate a significant improvement in fault estimation using the proposed method. © 2024 IEEE.

关键词： Adversarial machine learning

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Low-cost surface modification of a biomedical Zr-2.5Nb alloy fabricated by electron beam melting

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Journal of Materials Science & Technology 2023年第12期143卷 178-188页

作者： Caixu Wang Xiaoli Zhao Shujun Li Lu Liu Deliang Zhang Mitsuo Niinomi School of Materials Science and Engineering Northeastern UniversityShenyang 110819China Shi-changxu Innovation Center for Advanced Materials Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China Tianjin Key Laboratory of Bone Implants Interface Functionalization and Personalization Tianjin 300190China Institute for Materials Research Tohoku UniversitySendaiMiyagi 9808577Japan Division of Materials and Manufacturing Science Graduate School of EngineeringOsaka UniversityOsaka 565-0871Japan Department of Materials Science and Engineering Graduate School of Science and TechnologyMeijo UniversityNagoya 468-8502Japan Faculty of Chemistry Materials and BioengineeringKansai UniversityOsaka 564-860Japan

The Zr-2.5Nb alloy with a fine microstructure consisting ofαlaths was successfully prepared by electron beam melting(EBM).The thermal oxidation behaviors and kinetics of the as-built,and the EBM-built and hot isostatically pressed(HIPed)Zr-2.5Nb materials in a temperature range of 450-600°C were in-vestigated and compared with those of the alloy prepared by conventional casting and *** was found that the oxidation kinetics of the as-built and the forged materials followed the parabolic rate law during isothermal oxidation at 550°C,but the HIPed materials exhibited a parabolic-to-linear kinetic transition,suggesting that the larger grain sizes enhanced the *** oxide layers of all materials were composed of a large fraction of monoclinic zirconia phase(m-ZrO_(2))and a small fraction of tetrago-nal zirconia phase(t-ZrO_(2)),and transformed from t-ZrO_(2)to m-ZrO_(2)with increasing oxidation *** surface hardness of the as-built,the forged and the HIPed materials increased from 215,204,and 188 HV before oxidation to 902,1070,and 1137 HV after oxidation,*** cross-sections of the materi-als showed the presence of micropores and microcracks inside the oxide layers with thicknesses ranging from 4 to 8μ*** the oxidation temperature of 600°C and oxidation time duration of 3 h,a dense black m-ZrO_(2)oxide layer with smooth surface and 902 HV hardness was obtained on the EBM as-built Zr-2.5Nb materials.

关键词： Zr-2.5Nb alloy Electron beam melting Thermal oxidation Oxidation behaviors and kinetics Grain size

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Optimization of boron-containing acceptors towards high-efficiency TADF emitters:sky-blue OLEDs with external quantum efficiency of 32.6%

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Science china Materials 2024年第11期67卷 3537-3542页

作者： Xu Gong Wei Yang He Zhang Weimin Ning Shaolong Gong Xiang Gao Chuluo Yang Department of Chemistry Renmin Hospital of Wuhan UniversityHubei Key Lab on Organic and Polymeric Optoelectronic MaterialsWuhan UniversityWuhan 430072China Department of Pharmacy Renmin Hospital of Wuhan UniversityWuhan 430060China Shenzhen Key Laboratory of New Information Display and Storage Materials College of Materials Science and EngineeringShenzhen UniversityShenzhen 518060China

Two new thermally activated delayed fluorescence(TADF)molecules,13-(2,12-di-tert-butyl-5,9-dioxa-13bboranaphtho[3,2,1-de]anthracen-7-yl)-5,5-dimethyl-5,13-dihydrobenzo[4,5]thieno[3,2-c]acridine(BOBT)and 13-(4-(dimesitylboranyl)-3,5-dimethylphenyl)-5,5-dimethyl-5,13-dihydrobenzo[4,5]thieno[3,2-c]acridine(BPBT),are constructed via connecting the 5,5-dimethyl-5,13-dihydrobenzo[4,5]thieno[3,2-c]acridine(BTDMAC)donor(D)with triarylboron or oxygen-bridged cyclized boron acceptors(A),*** comparison with the photoluminescence quantum yield(PLQY)of 84%for BPBT,BOBT shows a higher PLQY of 100%,due to the multi-resonance effect of the boron-oxygen *** addition,the D-A-type molecular structural characteristic endows the boron-containing BOBT emitter with a fast reverse intersystem crossing rate on the order of 106 s^(-1).The sky-blue organic light-emitting diode(OLED)employing the BOBT emitter achieves state-of-the-art device performances with a high external quantum efficiency of 32.6%.

关键词： organic light-emitting diodes thermally activated delayed fluorescence boron-containing acceptor

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