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2023 international conference on computer science and automation technology, csat 2023

ISBN: (纸本)9798350371437

The proceedings contain 130 papers. The topics discussed include: a cloud computing based digital storage and evaluation platform for Buddhist literature;a cloud platform for data of three-product rapid detection in the development of cloud computing;a comparative analysis of image-based classification and object detection for the ocular redness grading;a demand forecasting method for high value-added agri-food based on machine learning and time series analysis;a navigation system for guiding blind people in indoor and outdoor;a no-reference image quality assessment methodology based on distortion information extraction;a study of research data and metadata standards in the field of humanities and social sciences;an android application software security protection method based on hybrid reinforcement;an edge computing-based data collection method for smart grid data acquisition system;and an effective knowledge mining method for compressor fault text data based on large language model.

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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Research on the Automatic capture Process of Import and Export Information of RPA in Hainan Free Trade Port 24

Research on the Automatic capture Process of Import and Expo...

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8th international conference on Electronic Information technology and computer Engineering, EITCE 2024

作者： Feng, Junying Zhou, Ailing Sun, Zi College of Information Engineering Hainan Vocational University of Science and Technology Hainan Haikou China

ISBN: (纸本)9798400710094

With the accelerated development of globalization, the international trade activities of Hainan Free Trade Port are becoming more frequent, and Enterprises face the challenge of processing large amounts of manifest information. Ttraditional manual inquiry processes are inefficient and have a high error rate, seriously affecting the efficiency of customs clearance and the speed of market *** this end, this research proposes a technical solution combining Robotic Process automation (RPA) and Artificial Intelligence (AI), to optimize the customs General Administration of manifest information query and processing *** using RPA to simulate the computer operations of human users, and AI technology to accurately extract key information of *** scheme significantly improves the efficiency and accuracy of data processing, reduces labor costs, and speeds up the response of enterprises to market changes. After the implementation, RPA technology improves the query efficiency by approximately six times, significantly reduces the operation time and costs, lowering error rates and enhances the competitiveness of enterprises in international trade. © 2024 Copyright held by the owner/author(s).

关键词： Wages

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Smart Vision Bot 5th

Smart Vision Bot

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5th international conference on Data science, Machine Learning and Applications

作者： Nandeshwar, Vikas J. Borse, Om Buthale, Prateek Borse, Chirayu Borhade, Bharati Borse, Sayali Vishwakarma Inst Technol Dept Engn Sci & Humanities Pune 411037 Maharashtra India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Smart vision robots have become increasingly essential in various industries and applications due to their ability to perform complex visual tasks with high precision and efficiency. This project focuses on the development of an autonomous surveillance and tracking system. The system aims to utilize computer vision algorithms for object detection and tracking. It has potential applications in security, automation, and remote monitoring. The project aims to enhance safety and efficiency in various environments through autonomous surveillance capabilities.

关键词： automation Autonomous Surveillance Bot Smart Vision Real-time

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Design and implementation of engineering integrated practical training management system under the background of engineering education 24

Design and implementation of engineering integrated practica...

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5th international conference on computer science and Management technology, ICCSMT 2024

作者： Xue, Tianbao Lan, Quanxiang School of Mathematics and Computer Science Panzhihua University Sichuan Panzhihua China

ISBN: (纸本)9798400709999

With the promotion of global economic integration, internationalised engineering education has become an important way for colleges and universities to improve their teaching quality and international competitiveness. In order to cultivate students' ability to solve complex engineering problems, many colleges and universities adopt the mode of integrated practical training projects. However, this model has the characteristics of long duration, multi-stage tasks, multi-dimensional assessment, etc. The use of traditional management methods will lead to management chaos, low teaching efficiency, and is difficult to adapt to modern teaching needs. For this reason, this paper designs and develops an intelligent, automation engineering integrated practical training management system based on B/S architecture. The system adopts SpringBoot, Vue, MySQL and Redis technologies to optimize the management process of the practical training project by automating the management of the project, marking scheme and grade analysis. In addition, the system has real-time performance analysis and feedback functions, which improves the efficiency of teaching management and provides strong support for universities to cultivate composite talents with innovative ability and comprehensive engineering literacy. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Efficiency

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Current Status and Future Prospects of Brain-Inspired Intelligence Development: A Review 24

Current Status and Future Prospects of Brain-Inspired Intell...

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5th international conference on computer science and Management technology, ICCSMT 2024

作者： Zhu, Di Zhang, Shu Zhao, Weinan Han, Junwei Zhang, Dingwen Center for Brain and Brain-Inspired Computing Research School of Computer Science Northwestern Polytechnical University Shaanxi Xi'an China School of Automation Northwestern Polytechnical University Shaanxi Xi'an China

ISBN: (纸本)9798400709999

Brain-inspired intelligence is a form of machine intelligence that mimics human brain *** machine intelligence similar to human consciousness is the ultimate task of brain-inspired intelligence and the long-term goal of *** paper provides an overview of the current status of the brain-inspired field from perspectives of core technologies, talent distribution, and industrial *** highlights current issues in brain-inspired domain such as the shortage of professional technical talent, slow industrialization processes, inadequate fundamental theoretical research, and a lack of breakthroughs in key *** paper suggests that we should focus on building a talent cultivation system for brain-inspired intelligence, integrating the concept of brain-inspired technologies into educational ***, it recommends advancing the integration of technology and application and strengthening the strategic planning of industries related to brain-inspired intelligence to play a significant role in the new round of development in human society. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Industrial research

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The Current Status, Hotspots, and Trends of Artificial Intelligence Research in Africa-A Bibliometric Analysis Based on CiteSpace from 2003 to 2023 24

The Current Status, Hotspots, and Trends of Artificial Intel...

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5th international conference on computer science and Management technology, ICCSMT 2024

作者： Dong, Miao Wu, Yuliang Zhang, Peipei Mubeen, Afzal School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Center for West African Studies University of Electronic Science and Technology of China Sichuan Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9798400709999

Based on the CiteSpace bibliometric method, 273 research papers from the Web of science Core Database from 2003 to 2023 were analyzed. This study delves into external characteristics such as publication volume, participating countries, research institutions, and authorship to uncover the key issues and evolving trends in the field of artificial intelligence (AI) research in Africa. The research shows that the number of AI studies in Africa has seen an"explosive" growth in recent years, with AI solutions being applied on a large scale. The development of AI in Africa primarily revolves around addressing practical needs in areas such as agriculture, food security, disease, and education, leading to significant achievements. However, challenges remain, including a lack of widespread international collaboration, a small core research community, and issues related to the localization of data and technology application. Looking ahead, strengthening international cooperation, enhancing local research and innovation capabilities, and addressing challenges related to data and technology application will be key to the continued growth of AI research in Africa. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Bibliographies

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Gaze2Atten: Analyzing Explainable Gaze Dynamics to Monitor Human Attention 17th

Gaze2Atten: Analyzing Explainable Gaze Dynamics to Monitor H...

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17th international conference on Intelligent Robotics and Applications

作者： Mu, Fengjun Zhang, Jingting Zou, Chaobin Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China

ISBN: (纸本)9789819607822;9789819607839

Attention monitoring is an essential task to evaluate the human cognitive status in human-computer interaction. Prior works either employ an inconvenient invasive method or struggle to provide an explainable mechanism between the original human signal and the attention monitoring results. In this paper, we present Gaze2Atten, a dynamics-based cognitive learning approach for monitoring human attention with the non-invasive gaze signal. Gaze2Atten is constructed based on the dynamic system theory, which makes our mechanism explainable in attention modeling and monitoring. The attention-related gaze dynamics model is first learned based on the cognitive dynamics characteristics of humans. Furthermore, we realize an efficient dynamic pattern-matching method to early detect abnormal attention in the humancomputer interaction process. To validate our approach, we designed a serious game to carry out a human-computer interaction behavior, and a parallel gaze data collection of subjects, the analysis shows that Gaze2Atten enables efficient and real-time human attention monitoring.

关键词： Attention Monitoring Deterministic Learning Human-computer Interface

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Diagnosability Verification and Enforcement for Unbounded Petri Nets by Online Supervisors

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IEEE TRANSACTIONS ON automation science AND ENGINEERING 2025年 22卷 9061-9074页

作者： Hu, Shaopeng Hu, Yihui Liu, Ding Fanti, Maria Pia Li, Zhiwu Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China Xian Univ Posts & Telecommun Sch Automat Xian 710121 Peoples R China Polytech Univ Bari Dept Elect & Informat Engn I-70125 Bari Italy Macau Univ Sci & Technol Inst Syst Engn Taipa Macao Peoples R China

This paper addresses the problems of diagnosability verification and enforcement of discrete event systems modeled with unbounded Petri nets. Diagnosability in such systems is critical for ensuring reliability and maintaining operational integrity, yet current methods often struggle with the complexity introduced by unboundedness and potential deadlocks. Given an unbounded labeled Petri net that may reach deadlocks, a quiescent basis coverability graph is established to verify the diagnosability of the considered system. This procedure employs a deterministic finite state automaton, called an extended verifier, derived from the proposed quiescent basis coverability graph. It is shown that an unbounded Petri net is diagnosable if and only if the verifier does not contain a class of cycles, called repetitive $F$ -cycles. This result also provides necessary and sufficient conditions for diagnosability enforcement by developing an online supervisor. Further, the designed supervisor is maximally permissive and also circumvents a plant entering deadlocks by firing non-fault sequences. Examples are presented to demonstrate the proposed method. Note to Practitioners-Fault diagnosis and diagnosability enforcement are critical for the development and operation of highly automated systems covering computer-integrated production processes, intelligent traffic, computer and communication networks, smart gird, etc. This work touches upon this problem from the perspective of discrete event systems that are modeled with unbounded labeled Petri nets. The feasibility and applicability of the reported method stem from the usage of a structurally compact representation of a considered plant such that the computational cost of a real-world system is acceptable. The graphical representation of Petri nets as well as the proposed quiescent basis coverability graph make the method easy to use and manipulate. Moreover the sufficient and necessary conditions of diagnosability enforcement can

关键词： Petri nets System recovery Fault diagnosis automation Automata Discrete-event systems Polynomials Mechanical engineering Firing Computational modeling Unbounded Petri net fault diagnosis diagnosability enforcement discrete event system

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A Recurrent Neural Network Based Bicriteria Repetitive Motion Collision Avoidance Scheme for Motion Planning of Dual Redundant Manipulators 13

A Recurrent Neural Network Based Bicriteria Repetitive Motio...

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13th international conference on Intelligent Control and Information Processing, ICICIP 2025

作者： Chen, Shirui Gao, Huanli Hu, Shaolin Zhang, Zhijun The School of Automation Science and Engineering South China University of Technology Guangzhou510640 China The School of Automation Guangdong University of Petrochemical Technology Maoming Guangzhou525000 China The Guangzhou Key Laboratory of Brain-Computer Interaction and Applications Guangzhou China The Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Guangzhou510555 China The Jiangxi Thousand Talents Plan Nanchang University Nanchang330031 China The College of Computer Science and Engineering Jishou University Jishou416000 China Guangzhou510335 China The Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Shaanxi University of Technology Hanzhong723001 China The School of Information Science and Engineering Changsha Normal University Changsha410100 China The School of Automation Science and Engineering Maoming525000 China The Institute of Artificial Intelligence and Automation Guangdong University of Petrochemical Technology Maoming525000 China

ISBN: (纸本)9798331516147

To achieve low joint-angle drift and avoid mutual collision between dual redundant manipulators (DRMs) when they are doing collaboration works, a recurrent neural network based bicriteria repetitive motion collision avoidance (BRMCA) scheme is proposed for motion planning of DRMs. By designing a combined optimization objective encompassing both repetitive motion criterion and collision avoidance criterion, the BRMCA scheme has larger feasible region and less constraint contradiction issues compared with traditional inequality constraints based method. Furthermore, by incorporating velocity-level kinematic model and physical limits of DRMs into the scheme, a time varying quadratic programming (TVQP) problem is formulated. The linear variational inequality-based primal–dual neural network (LVI-PDNN) is used to solve the proposed scheme due to the high accuracy and low computation complexity. Finally, through comparison simulations of tracking Circle-shape and C-shape trajectories between BRMCA scheme and minimum velocity norm (MVN) scheme, it exhibits that the proposed BRMCA scheme can achieve low joint-angle drift, collision avoidance and high tracking accuracy when DRMs are doing cooperative tasks. © 2025 IEEE.

关键词： Recurrent neural networks

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