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25th International Conference on Digital Image Computing: Techniques and Applications, DICTA 2024

作者： Mirza, Inzela Iqbal, Shahzaib Alhaqbani, Bandar Alshammari, Bandar Khan, Tariq Razzak, Imran Department of Computing Islamabad Pakistan Tcc Research and Development Labs Technology Control Company Riyadh Saudi Arabia Computer and Information Sciences College Jouf University Saudi Arabia School of Computer Science and Engineering University of New South Wales Sydney Australia

ISBN: (纸本)9798350379037

Over recent years, deep convolutional neural networks have advanced the field of face recognition in both verification and identification applications. In this paper, we present ShadowNets, a highly efficient and compact face recognition network. We employed multiple shadow blocks in a cascading manner where the output of each shadow block is given as the input to the next shadow block. By integrating the advantages of Focal Modulation Blocks, Shadow Block and Ghost Modules, our proposed ShadowNets achieves superior face recognition performance, optimized specifically for edge devices. This network architecture not only minimizes computational costs and storage needs but also delivers high accuracy, making it suitable for deployment in edge environments. Our extensive experiments on challenging benchmark face datasets showcase the outstanding performance by achieving accuracy 98.85% on LFW, 84.37% on CFP-FP, and 91.23% on AgeDB-30 which validates the effectiveness of ShadowNets over state-of-the-art lightweight and deep face recognition models. © 2024 IEEE.

关键词： Convolutional neural networks

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Propagation Characteristics of Partial Discharges in an Oil-Filled Power Transformer 17

Propagation Characteristics of Partial Discharges in an Oil-...

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17th IEEE International Conference on Compatibility, Power Electronics and Power engineering, CPE-POWERENG 2023

作者： Kameli, Sayed Mohammad Refaat, Shady S. Ghrayeb, Ali Abu-Rub, Haitham Guzinski, Jaroslaw Texas AandM University at Qatar Electrical and Computer Engineering Doha Qatar University of Hertfordshire School of Physics Engineering and Computer Science Department of Engineering United Kingdom Gdansk University of Technology Electrical and Control Engineering Faculty ul. Gabriela Narutowicza 11/12 Gdansk80-233 Poland

ISBN: (纸本)9798350300048

Power transformers are among the most important assets in the power transmission and distribution grid. However, they suffer from degradation and possible faults causing major electrical and financial losses. Partial discharges (PDs) are used to identify the insulation health status and their degradation level. PDs are incipient, low-magnitude faults caused by localized dielectric breakdown. Those activities emit signals in many forms, including electrical, chemical, acoustic, electromagnetic, and optical, facilitating various detection methods. This paper provides a theoretical basis for the condition evaluation of an oil-filled power transformer and clarifies the relationship between the operating voltage, void location, and electric-field intensity within the void. This was achieved by investigating the propagation characteristics of partial discharge signals in an oil-filled power transformer using a 3D finite element method (FEM) based simulation. Moreover, the characterization of simulated PD sources at different positions is investigated in this paper. The simulation results are curried out to show that air voids near the windings are subject to greatest peak electric field intensity. © 2023 IEEE.

关键词： Power transformers

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An Efficient and Secured Energy Management System for Automated Guided Vehicles

An Efficient and Secured Energy Management System for Automa...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Mrozek, Dariusz National Taiwan University Department of Computer Science and Information Engineering Taiwan Western Norway University of Applied Sciences Department of Computer Science Electrical Engineering and Mathematical Sciences Norway Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Poland

ISBN: (纸本)9781665480451

In this paper, we propose a Secure Energy Management System (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning network to simultaneously classify suppliers and predict the real supply quantities. The Q-learning decision module can then determine operating reserve and subsidies to manage the energy grid. Experimental results illustrate that the proposed anomaly detection module has an excellent performance in classifying malicious suppliers, excels at shaping supply distribution, and outperforms the existing benchmark systems. © 2022 IEEE.

关键词： Energy management

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Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 2014-2025页

作者： Xingtang Wu Mingkun Yang Wenbo Lian Min Zhou Hongwei Wang Hairong Dong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China National Research Center of Railway Safety Assessment Beijing Jiaotong UniversityBeijing 100044China

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

关键词： Delay propagation double layer network high speed rail network max-plus algebra

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DecStore: a Blockchain-based File Storage System With Autoscaling 24

DecStore: a Blockchain-based File Storage System With Autosc...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Hammoud, Obadah Tarkhanov, Ivan A. National University of Science and Technology Department of Engineering Cybernetics Moscow Russia State Academic University for the Humanities Moscow Russia Academy of Sciences Federal Research Center 'Computer Science and Control' of Russian Russia

ISBN: (纸本)9798350384307

Digital transformation requires new innovative approaches in the design of data exchange and file storage systems. The analysis of the architecture of well-known IT projects and approaches showed that each of them cannot solve one of three problems at the same time: automatic scaling, the absence of a single point of failure, and minimizing the required storage space for files and their backups. The presented architecture of DecStore, a blockchain-based peer-to-peer file storage system, solves these problems simultaneously. It reduces the total amount of disk space required by 25% through the use of erasure coding. Automatic horizontal scaling and the absence of a single point of failure are provided by a load balancer based on algorithms implemented inside the Hyperledger chaincode. DecStore can become a subsystem for secure data exchange for government-to-business and business-to-business systems for state supervision in various areas, including financial and insurance audits. © 2023 IEEE.

关键词： Autoscaling distributed storage smart contract

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Review on guidance and control of aerospace vehicles: recent progress and prospect

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Aerospace Systems 2024年第2期7卷 175-192页

作者： Wang, Zian Cai, Pengcheng Gong, Zheng Zhang, Chengxi Zhao, Shunyi Wu, Jin Dong, Peng Department of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Key Laboratory of Advanced Control for Light Industry Processes Ministry of Education Jiangnan University Wuxi214122 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China

This paper expounds on the development status and relevant works of control and guidance methods of the aerospace vehicle in recent years. The control difficulties and the solutions in the related results are introduced briefly. Moreover, the guidance methods are then expounded in detail according to the flight phases of the whole flight mission. Guidance methods are usually included in each phase, and the corresponding trajectory design theories are also introduced where necessary. In addition, the potential future development direction prospects. Based on the above, a brief conclusion is then made as a summary. © Shanghai Jiao Tong University 2024.

关键词： Space flight

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Establishment of a BOPPPS-AHP Model for Curriculum Quality Evaluation

Establishment of a BOPPPS-AHP Model for Curriculum Quality E...

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2023 China Automation Congress, CAC 2023

作者： Chen, Xiaoyu Ma, Xin Shi, Li Li, Teng Shandong Xiehe University School of Computer Science Jinan China Beijing University of Chemical Technology School of Information Science and Technology Beijing China Jinan China Shandong University School of Control Science and Engineering Jinan China

ISBN: (纸本)9798350303759

Aiming at teaching of specialized courses, this paper constructs a model for addressing both teaching and evaluation methods. Taking the bridge-in, objective, pre-assessment, participatory learning, post-assessment and summary (BOPPPS) model as a teaching objective, the curriculum evaluation system is established by using the analytic hierarchy process (AHP) scheme. As a result, the course model of BOPPPS-AHP is proposed. The AHP evaluation model is established in the form of expert judgment and questionnaire survey, three first-level indicators, and twelve second-level indicators are established. By calculating the evaluation weights of each index and consistency test, it shows that the curriculum quality evaluation system with the proposed model is feasible to the course of Sensor Principle and Application. Through the comparison between the experimental group and the control group, the BOPPPS-AHP model is conducive to enhancing students' learning interest and comprehensive ability. © 2023 IEEE.

关键词： Analytic hierarchy process

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Sampling locally, hypothesis globally: accurate 3D point cloud registration with a RANSAC variant

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Visual Intelligence 2023年第1期1卷 1-15页

作者： Cheng, Yuxin Huang, Zhiqiang Quan, Siwen Cao, Xinyue Zhang, Shikun Yang, Jiaqi School of Computer Science Northwestern Polytechnical University Xi’an 710129 China Da-Jiang Innovations ShenZhen 511464 China School of Electronic and Control Engineering Chang’An University Xi’an 710064 China

Correspondence-based six-degree-of-freedom (6-DoF) pose estimation remains a mainstream solution for 3D point cloud registration. However, the heavy outliers pose great challenges to this problem. In this paper, we propose a random sample consensus (RANSAC) variant based on sampling locally and hypothesis globally (SLHG) for 6-DoF pose estimation and 3D point cloud registration. The key novelties are efficient sampling by guiding the sampling process locally and accurate pose estimation by generating hypotheses with global information. SLHG first generates a correspondence subset via compatibility clustering on the initial set. Second, locally guided graph sampling is performed. Third, 6-DoF hypotheses are generated by incorporating global information with a voting scheme. The best hypothesis serves as the estimation result by repeating the second and third steps. Extensive experiments on four popular datasets and comparisons with state-of-the-art methods confirm that: SLHG manages to 1) achieve accurate registrations with a few iterations, and 2) yield better accuracy performance than most competitors. © The Author(s) 2023.

关键词： 3D point cloud 3D registration Pose estimation Random sample consensus

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Advancing prognostic precision in gastric cancer with an immunoinflammatory index

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World Journal of Gastroenterology 2024年第44期30卷 4754-4758页

作者： Hong-Mei Zhang Guo-Hua Wang Shan-Wen Sun Lei Yuan College of Life Science Northeast Forestry UniversityHarbin 150040Heilongjiang ProvinceChina College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040Heilongjiang ProvinceChina Department of Hepatobiliary Surgery Quzhou People’s HospitalQuzhou 324000Zhejiang ProvinceChina

Gastric cancer remains a major global health challenge with high morbidity and mortality *** advancements in immunology and inflammation research have highlighted the crucial roles that these biological processes play in tumor progression and patient *** has sparked new interest in developing prognostic biomarkers that integrate these two key biological *** this letter,we discuss the recent study by Ba et al,which proposed a novel prognostic immunoinflammatory index for patients with gastric *** underscore the importance of this research,its potential impact on medical practice,and the prospective avenues for further investigation in this rapidly emerging area of study.

关键词： Gastric cancer Immunoinflammatory index Prognostic biomarkers Inflammation Immunology

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Research on improved full-factor deep information mining algorithm

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Cognitive Robotics 2022年 2卷 30-38页

作者： Man, Yun Fei, Xu Jun, Liu Qian, Zhang School of Computer Science and Engineering Xi'an Technological University Xi'an China Engineering Laboratory The State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an China 63768 Unit of the Chinese People's Liberation Army

In the use of fire-fighting physics platform for fire alarm data correlation analysis, there are often problems such as too much data volume and insufficient accuracy of the analysis results. For such questions, this paper establishes a full-factor secondary mining mechanism for fire accidents based on the fire big data based on the correlation analysis algorithm and the clustering algorithm. The association algorithm is used to conduct full-factor primary mining on the fire-related factors in the data warehouse, and the common-sense accident attributes in the association rules are extracted. Then use the K-means clustering algorithm, where the cluster center is the relevant attribute in the fire accident record, and perform the second combined clustering of the accident elements to achieve in-depth information mining of all factors of the fire accident. Experimental results show that the improved full-factor deep information mining algorithm proposed in this paper can effectively filter 31.6% of meaningless mining results compared to the traditional single mining algorithm. It shows that the algorithm in this paper can more accurately dig out the relationship between data, and can provide more effective decision support for fire management and other work. © 2022

关键词： Fires

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