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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Automatic License Plate Detection Using information Processing system Vision and Deep Learning 2

Automatic License Plate Detection Using Information Processi...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Sharma, Avinash Dwivedi, Ishita Dawar, Divya Saxena, Rini Barua, Tarkcshwar Goyel, Parul Chandigarh Engineering Chandigarh Group of Colleges Department of information processing system Science and Engineering Mohali140307 India Mohali140307 India Roorkee Institute of Technology Computer Science & Engineering Department Roorkee India M. M. Engineering College Maharishi Markandeshwar University CSE Department Mullana Haryana Ambala133207 India

ISBN: (纸本)9798350366570

The content of this probe is to overcome the current cognitive content with ALPR playacting, with a special accent on developing a dead and impelling playacting for distinguishing License plates from video film. The study attempts to ameliorate the presentation norms of ALPR technology by utilizing the powerful accumulation of optical character identification (OCR)[20] and deep learning based object detection algorithmic program. The core of this occupation is the use of the cutting-edge YOLOv8. object distinguishing hypothesis, which has been pains taking and disciplined on an unequaled dataset premeditated with License plate detection in mind. Focusing on quality and efficiency, the YOLOv8 model accomplish an amazing 99.8 quality rate when it comes to accurately localization and categorization License plates[18] inside video frames. This occupation aims to formalize the willingness and dependability of the advisable ALPR playacting through extensive scientific research. The project aims to intensify ALPR technology and determinant the forthcoming of transport and police investigation playactings[18] by breaking through current obstruction and establishing new presentation norms. © 2024 IEEE.

关键词： Deep learning

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WebCode2M: A Real-World Dataset for Code Generation from Webpage Designs 25

WebCode2M: A Real-World Dataset for Code Generation from Web...

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34th ACM Web Conference, WWW 2025

作者： Gui, Yi Li, Zhen Wan, Yao Shi, Yemin Zhang, Hongyu Su, Yi Chen, Bohua Chen, Dongping Wu, Siyuan Zhou, Xing Jiang, Wenbin Jin, Hai Zhang, Xiangliang Huazhong University of Science and Technology Wuhan China Peking University Beijing China Chongqing University Chongqing China Hubei University of Automotive Technology Shiyan China Rabbitpre AI Shenzhen China University of Notre Dame Notre Dame United States National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster Grid Computing Lab School of Computer Science and Technology China

ISBN: (纸本)9798400712746

Automatically generating webpage code from webpage designs can significantly reduce the workload of front-end developers, and recent Multimodal Large Language Models (MLLMs) have shown promising potential in this area. However, our investigation reveals that most existing MLLMs are constrained by the absence of high-quality, large-scale, real-world datasets, resulting in inadequate performance in automated webpage code generation. To fill this gap, this paper introduces WebCode2M, a new dataset comprising 2.56 million instances, each containing a design image along with the corresponding webpage code and layout details. Sourced from real-world web resources, WebCode2M offers a rich and valuable dataset for webpage code generation across a variety of applications. The dataset quality is ensured by a scoring model that filters out instances with aesthetic deficiencies or other incomplete elements. To validate the effectiveness of WebCode2M, we introduce a baseline model based on the Vision Transformer (ViT), named WebCoder, and establish a benchmark for fair comparison. Additionally, we introduce a new metric, TreeBLEU, to measure the structural hierarchy recall. The benchmarking results demonstrate that our dataset significantly improves the ability of MLLMs to generate code from webpage designs, confirming its effectiveness and usability for future applications in front-end design tools. Finally, we highlight several practical challenges introduced by our dataset, calling for further research. © 2025 Copyright held by the owner/author(s).

关键词： Web Design

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High-Voltage SF6 Circuit Breaker Maintenance 33rd

High-Voltage SF6 Circuit Breaker Maintenance

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33rd International Conference on Organization and technology of Maintenance, OTO 2024

作者： Soldo, Luka Knežević, Goran Zovko, Mario Croatian Transmission System Operator Transmission Area Osijek Vukovarska Cesta 217 Osijek31000 Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Kneza Trpmira 2b Osijek31000 Croatia

ISBN: (纸本)9783031805967

Nowadays, the need for uninterrupted power supply is greater than ever. One of the most effective ways to ensure an uninterrupted supply of electricity is the correct selection of the method and interval of maintenance of elements in a high-voltage substation. In this way, not only is a high-quality delivery of electricity ensured, but also the possibility of equipment failure that can be dangerous for people in the substation is reduced. A high-voltage circuit breaker is a device that performs several different functions. It is used for network configuration changes, and also provides protection for equipment and personnel. High voltages and thermal (current) stresses cause aging and wear of switch parts, and through various forms of maintenance and testing, damage parts are determined and potential hazards are safely removed. This paper explains the maintenance procedures of the high-voltage SF6 circuit breaker. Using the example of a high-voltage line-bay circuit breaker, the entire 6Y circuit breaker revision procedure (revision that is carried out in six-year cycles) is presented. In addition to visual inspection, checking, cleaning and replacement of worn parts, the switch on and off times were recorded. The quality of SF6 gas was also tested by measuring the concentration of SF6 gas decomposition products and the concentration of mineral oil aerosols in SF6 gas, by measuring the dew point of the gas and controlling the volume percentage of SF6 gas. The voltage drops at the primary connections of the switches were measured, and the operation of the pressure relays was also checked. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mineral oils

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A four-dimensional model for the information storage/output of life

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Nano Research 2023年第2期16卷 2630-2634页

作者： Bo Song Lei Jiang Key Laboratory of Optical Technology and Instrument for Medicine Ministry of EducationShanghai Key Lab of Modern Optical SystemSchool of Optical-Electrical Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Key Laboratory of Bio-inspired Materials and Interfacial Science Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China

A large amount of progress has achieved in neuroscience,however,there is still a lack of reasonable model for the storage/output(S/O)of life *** cyclical motion of cardio-and pulmonary-myocyte is a typical process of the life information S/O,while the opening and closing sites of Ca^(2+)ion channels during the motion can form a genetically programmed time-dependent three-dimensional(3D)*** phenomena indicate a strong correlation of the information S/O model of these myocytes with the time-sequence 3D ***,based on the time-dependent Ca^(2+)fluorescence imaging during the motion of cardio-and pulmonary-myocyte,here we suggest a four-dimensional(4D)code of information S/O model in cell and nervous *** from the fact of pulmonary myocyte motion able to be controlled by brain,it is deduced that the 4D code in brain has a role of controlling muscles through a pathway of the central nervous system,peripheral nervous system,neuromuscular junction,and muscle *** addition,we also suggested the 4D code of non-innate skill that can be programmed by the learning/training of a long time(~3 years),such as walking,writing,painting,sports,speech,singing,and ***,this 4D S/O model is reasonable for the ultralow energy consumption of life information transmission.

关键词： four-dimensional(4D)storage/output model life information cell nervous system

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Large-scale land-sea interactions extend ozone pollution duration in coastal cities along northern China

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Environmental science and Ecotechnology 2024年第2期18卷 150-160页

作者： Yanhua Zheng Fei Jiang Shuzhuang Feng Yang Shen Huan Liu Hai Guo Xiaopu Lyu Mengwei Jia Chenxi Lou Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjing210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjing210023China School of Environment Tsinghua UniversityBeijing100084China Air Quality Studies Department of Civil and Environmental EngineeringHong Kong Polytechnic UniversityHong KongChina

Land-sea atmosphere interaction(LSAI)is one of the important processes affecting ozone(O_(3))pollution in coastal *** effects of small-scale LSAIs like sea-land breezes have been widely ***,it is not fully clear how and to what extent the large-scale LSAIs affect O_(3) *** we explored an O_(3) episode to illuminate the role of large-scale LSAIs in O_(3) pollution over the BohaieYellow Seas and adjacent areas through observations and model *** results show that the northern Bohai Sea's coastal region,influenced by the Mongolian High,initially experienced a typical unimodal diurnal O_(3) variation for three days,when O_(3) precursors from BeijingeTianjineHebei,Shandong,and Northeast China were transported to the BohaieYellow *** reactions generated O_(3) within marine air masses,causing higher O_(3) levels over the seas than coastal *** the Mongolian High shifted eastward and expanded,southerly winds on its western edge transported O_(3)-rich marine air masses toward the coast,prolonging pollution for an additional three days and weakening diurnal ***,emissions from the Korean Peninsula and marine shipping significantly affected O_(3) levels in the northern Bohai Sea(10.7%and 13.7%,respectively).Notably,Shandong's emissions played a substantial role in both phases(27.5%and 26.1%,respectively).These findings underscore the substantial impact of large-scale LSAIs driven by the Mongolian High on O_(3) formation and pollution duration in coastal *** insight helps understand and manage O_(3) pollution in northern Bohai Sea cities and broadly applies to temperate coastal cities worldwide.

关键词： Mongolian high Source apportionment WRF-CMAQ Sea-crossing transport

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Facial expression recognition under occlusion conditions based on multi-feature cross-attention

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Journal of Intelligent and Fuzzy systems 2024年第4期46卷 9841-9856页

作者： Guo, Sheng Tan, Mian Cai, Shan Zhang, Zaijun Liang, Yihui Feng, Hongxi Zou, Xue Wang, Lin School of Data Science and Information Engineering Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China School of Mathematics and Statistics Qiannan Normal University for Nationalities Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun China Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Aerospace Tianma Electromechanical Technology Co LTD Zunyi China

Although facial expression recognition (FER) has a wide range of applications, it may be difficult to achieve under local occlusion conditions which may result in the loss of valuable expression features. This issue has motivated the present study, as a part of which an effective multi-feature cross-attention network (MFCA-Net) is proposed. The MFCA-Net consists of a two-branch network comprising a multi-feature convolution module and a local cross-attention module. Thus, it enables decomposition of facial features into multiple sub-features by the multi-feature convolution module to reduce the impact of local occlusion on facial expression feature extraction. In the next step, the local cross-attention module distinguishes between occluded and unoccluded sub-features and focuses on the latter to facilitate FER. When the MFCA-Net performance is evaluated by applying it to three public large-scale datasets (RAF-DB, FERPlus, and AffectNet), the experimental results confirm its good robustness. Further validation is performed on a real FER dataset with local occlusion of the face. © 2024 – IOS Press.

关键词： Convolution

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Crafting Compelling Argumentative Writing for Undergraduates: Exploring the Nexus of Digital Annotations, Conversational Agents, and Collaborative Concept Maps

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Journal of Educational Computing Research 2024年第5期62卷 1327-1357页

作者： Sandra, Randi Proska Hwang, Wu-Yuin Zafirah, Afifah Hariyanti, Uun Engkizar, Engkizar Hadi, Ahmaddul Fauzan, Ahmad Universitas Negeri Padang West Sumatra Indonesia Graduate Institute of Network Learning Technology National Central University Taoyuan Taiwan College of Science and Engineering National Dong Hwa University Hualien Taiwan Department of Information System Faculty of Computer Science Universitas Brawijaya East Java Indonesia

Argumentative writing is a fundamental aspect of undergraduate students’ academic and scientific writing related to critical thinking and problem-solving skills. However, previous studies have shown that students face various difficulties with argumentative writing, such as unclear and illogical ideas, less-structured arguments, and unbalanced interpretation of issues, data, and evidence. This study aims to improve the argumentative writing skills of undergraduate students by integrating computer-supported argumentative writing tools, such as annotation, conversational agents (CAs), and collaborative concept maps, into an online learning management system. Since the study was conducted during the COVID-19 pandemic, these tools can support meaningful learning activities and investigation in argumentative writing. The researchers divided sixty participants into the experimental group (N = 30) and the control group (N = 30). The results showed that the experimental group’s writing achievements outperformed the control group, and the three tools effectively improved the five elements of argumentative writing, including claims, grounds, warrants, backings, and rebuttal. Furthermore, a deep analysis found that the number of annotations, valid CAs’ responses, and argument nodes on collaborative concept maps can significantly predict students’ argumentative writing development. Moreover, students perceived that the incorporated tools could effectively improve their argumentative writing skills. © The Author(s) 2024.

关键词： argumentative writing collaborative concept map conversational agents digital annotation undergraduate students

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Outage analysis of aerial semi-grant-free NOMA systems

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Digital Communications and Networks 2024年第5期10卷 1529-1541页

作者： Hongjiang Lei Chen Zhu Ki-Hong Park Imran Shafique Ansari Weijia Lei Hong Tang Kyeong Jin Kim School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Chongqing Key Lab of Mobile Communications Technology Chongqing 400065China CEMSE Division King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia James Watt School of Engineering University of GlasgowGlasgow G128QQUnited Kingdom Samsung Research America(SRA) PlanoTX75023USA

In this paper,we analyze the outage performance of Unmanned Aerial Vehicles(UAVs)-enabled downlink Non-Orthogonal Multiple Access(NOMA)communication systems with the Semi-Grant-Free(SGF)transmission scheme.A UAV provides coverage services for a Grant-Based(GB)user and one Grant-Free(GF)user is allowed to utilize the same channel resource *** analytical expressions for the exact and asymptotic Outage Probability(OP)of the GF user are *** results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users'quality of service ***,an efficient Dynamic Power Allocation(DPA)scheme is proposed to relax such data rate *** analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are ***,Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV's location and altitude on the OP of the GF user.

关键词： Unmanned aerial vehicle Non-orthogonal multiple access Semi-grant-free Outage probability

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Stacking-Enhanced Bagging Ensemble Learning for Breast Cancer Classification with CNN 3

Stacking-Enhanced Bagging Ensemble Learning for Breast Cance...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Wu, Peicheng Ma, Runze Toe, Teoh Teik Huazhong University of Science and Technology Electronics and Information Engineering Wuhan China Automation Huazhong University of Science and Technology Wuhan China Nanyang Technological University Ntu Business Ai Lab Singapore

ISBN: (纸本)9798350323511

This paper proposes a CNN classification network based on Bagging and stacking ensemble learning methods for breast cancer classification. The model was trained and tested on the public dataset of DDSM. The model is capable of fast and accurate classification of input images. According to our research results, for binary classification (presence or absence of breast cancer), the accuracy reached 98.84%, and for five-class classification, the accuracy reached 98.34%. The model also achieved a micro-average recall rate of 94.80% and an F1 score of 94.19%. In comparative experiments, we compared the effects of different values of bagging_ratio and n_models on the model, as well as several methods for ensemble bagging models. Furthermore, under the same parameter settings, our BSECNN outperformed VGG16 and ResNet-50 in terms of accuracy by 8.22% and 6.33% respectively. © 2023 IEEE.

关键词： Learning systems

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