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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Jishun Ma Weikai Lu Changen Zhou Shenghua Teng Zuoyong Li College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

Syndrome classification is an important step in Traditional Chinese Medicine (TCM) for diagnosis and treatment. In this paper, we propose a multi-graph attention network (MGAT) based method to simulate TCM doctors to infer the syndromes. Specifically, the complex relationships between symptoms and state elements are aggregated using graph attention networks (GAT) and syndromes are classified by a multilayer perceptron (MLP). To verify the effectiveness of the model, extensive experiments are conducted on the Treatise on Febrile Diseases dataset. The experimental results show that the proposed method outperforms several typical methods in terms of accuracy, precision, recall, and F1-score. The MGAT model has high accuracy in syndrome classification and has practical application value.

关键词： Computational modeling Education Medical services Multilayer perceptrons Feature extraction Computer aided diagnosis Information technology

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Measuring the distance and orientation of a planar surface using nonstructured lighting

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SYSTEMS AND COMPUTERS IN JAPAN 1996年第8期27卷 83-92页

作者： Tsukiyama, T Member Electrotechnical Laboratory Tsukuba Japan 305 Tosbifumi Tsukiyama:graduated in 1972 from the Biological Engineering Department Osaka University where he also received his Dr. of Eng. degree. He joined Electrotechnical Laboratory Ministry of Tread and Industry (Japan) in 1972. At present he is Senior Researcher at Computer Vision Section Intelligent Systems Division ETL. He was a Visiting Researcher at University of Illinois during 1984–1985. He has been interested in vision system for mobile robots and image processing architectures. He is a member of the Society of Instrumental and Control Engineers Japan Robotics Society of Japan and Information Processing Society of Japan.

This paper proposes a method of 3-dimensional measurement of a planar surface by using two fixed light sources and a TV camera. A set of two images is recorded by the camera switching on each light alternately. The peak of the luminance distribution in each image is detected, and the orientation and distance of the planar surface are calculated. The position of the peak of a luminance distribution can be estimated accurately by using an image processing. The light sources can be conventional apparatus with no particular structure. The method is simple and suitable for a vision system on an indoor mobile robot.

关键词： distance to surface orientation of planar surface point light source luminance distribution ring light

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system Computer vision Motion detection

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Sensor-based Multi-agent Coverage control with Spatial Separation in Unstructured Environments

arXiv

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arXiv 2024年

作者： Wang, Xinyi Xu, Jiwen Gao, Chuanxiang Chen, Yizhou Zhang, Jihan Wang, Chenggang Ding, Yulong Chen, Ben M. Department of Mechanical and Automation Engineering The Chinese University of Hong Kong N.T. Shatin Hong Kong Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai200240 China Department of Control Science and Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education China

Multi-robot systems have increasingly become instrumental in tackling coverage problems. However, the challenge of optimizing task efficiency without compromising task success still persists, particularly in expansive, unstructured scenarios with dense obstacles. This paper presents an innovative, decentralized Voronoi-based coverage control approach to reactively navigate these complexities while guaranteeing safety. This approach leverages the active sensing capabilities of multi-robot systems to supplement GIS (Geographic Information System), offering a more comprehensive and real-time understanding of environments like post-disaster. Based on point cloud data, which is inherently non-convex and unstructured, this method efficiently generates collision-free Voronoi regions using only local sensing information through spatial decomposition and spherical mirroring techniques. Then, deadlock-aware guided map integrated with a gradient-optimized, centroid Voronoi-based coverage control policy, is constructed to improve efficiency by avoiding exhaustive searches and local sensing pitfalls. The effectiveness of our algorithm has been validated through extensive numerical simulations in high-fidelity environments, demonstrating significant improvements in task success rate, coverage ratio, and task execution time compared with others. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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Predictive protocol of flocks with small-world connection pattern

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Physical Review E 2009年第1期79卷 016113-016113页

作者： Hai-Tao Zhang Michael Z. Q. Chen Tao Zhou The Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 People's Republic of China Department of Engineering University of Cambridge Cambridge CB2 1PZ United Kingdom Department of Engineering University of Leicester Leicester LE1 7RH United Kingdom Department of Electronic Engineering City University of Hong Kong Kowloon Hong Kong SAR People's Republic of China Department of Modern Physics University of Science and Technology of China Hefei 230026 People’s Republic of China Department of Physics University of Fribourg Chemin du Muse 3 Fribourg CH-1700 Switzerland

By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from the leader to a few distant agents, namely, pseudoleaders. The leader can directly affect the pseudoleaders, thereby influencing all the other agents through them efficiently. Moreover, these pseudoleaders are able to predict the leader’s motion several steps ahead and use this information in decision making towards coherent flocking with more stable formation. It is shown that drastic improvement can be achieved in terms of both the consensus performance and the communication cost. From the engineering point of view, the current protocol allows for a significant improvement in the cohesion and rigidity of the formation at a fairly low cost of adding a few long-range links embedded with predictive capabilities. Significantly, this work uncovers an important feature of flocks that predictive capability and long-range links can compensate for the insufficiency of each other. These conclusions are valid for both the attractive and repulsive swarm model and the Vicsek model.

关键词： pattern formation protocols random processes 3-DIMENSIONAL LATTICE MODEL DYNAMICAL COMPLEX NETWORKS REPULSIVE INTERACTIONS STABILITY ANALYSIS ATTRACTIVE FORCES SENSOR NETWORKS ANIMAL GROUPS AGENTS TRANSITIONS CONSENSUS

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A new scheme for evaluation of air-trapping in CT images

A new scheme for evaluation of air-trapping in CT images

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Iranian Machine Vision and image processing (MVIP)

作者： M. Parsa Hosseini Hamid Soltanian-Zadeh Shahram Akhlaghpoor Alireza Behrad Department of Electrical Engineering Science and Research Branch Islamic Azad University Tehran Iran Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA Department of Radiology Sina Hospital Tehran University of Medical Sciences Tehran Iran Department of Electrical Engineering Shahed University Tehran Iran

Air trapping is an abnormal retention of air that occurs after expiration state in the lungs, observed in all types of bronchiolar and obstructive lung diseases such as chronic obstructive pulmonary disease (COPD), asthma, and bronchiolitis obliterans syndrome. Air trapping is often incidentally diagnosed on computed tomography (CT) scanning but this method needs doctors so it is subjective and depends on their experience. In this paper, we present a novel method for evaluation of air trapping in the lungs for detection of COPD in CT images. The proposed method finds volumetric variations of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared and the volumetric variations are used to classify the subjects. In the evaluated cases, the proposed method is able to estimate air trapping in the lungs from CT images without human intervention. This method may assist radiologists to measure and evaluate air trapping for detection of COPD as a computer aided diagnosis (CAD) system.

关键词： Lungs Computed tomography Charge carrier processes Diseases image segmentation Biomedical imaging

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A noninvasive, remote and precise method for temperature and concentration estimation using magnetic nanoparticles

A noninvasive, remote and precise method for temperature and...

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2012上海市研究生学术论坛暨第三届上海交通大学医(理)工研究生学术论坛

作者： Jing Zhong Wenzhong Liu Zhongzhou Du Paulo C′esar de Morais Qing Xiang Qingguo Xie Department of Control Science and Engineering Huazhong University of Science and TechnologyWuhan 430074People''s Republic of China Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074People''s Republic of China Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074People''s Republic of China Universidade de BrasiliaInstituto de FisicaNucleo de Fisica AplicadaBrasilia DF 70910-900Brazil School of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074People''s Republic of China

is study describes an approach for remote measuring of on-site temperature and particleconcentration using magnetic nanoparticles (MNPs) via simulation and also *** sensor model indicates that under different applied magnetic fields, the magnetizationequation of the MNPs can be discretized to give a higher-order nonlinear equation in twovariables that consequently separates information regarding temperature and particleconcentration. As a result, on-site tissue temperature or nanoparticle concentration can bedetermined using remote detection of the magnetization. In order to address key issues in thehigher-order equation we propose a new solution method of the first-order model from theperspective of the generalized inverse matrix. Simulations for solving the equation, as well asto optimize the solution of higher equations, were carried out. In the final section we describea prototype experiment used to investigate the measurement of the temperature in which weused a superconducting magnetometer and commercial MNPs. The overall error after ninerepeated measurements was found to be less than 0.57 K within 310–350 K, with acorresponding root mean square of less than 0.55 K. A linear relationship was also foundbetween the estimated concentration of MNPs and the sample’s mass.

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RETRACTED: Dual-mode predictive flexible rotor control for active magnetic bearings with input constraints

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Journal of Vibration and control 2016年第20期23卷 NP2页

作者： Yue Wu Jie Zhao Hai-Tao Zhang Ming-Can Fan Xi Yu Guangdong HUST Industrial Technology Research Institute Guangdong Province Key Lab of Digital Manufacturing Equipment ChinaKey Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Department of Mathematics Huizhou University China School of Electrical and Information Engineering Xi'an Technology University China

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Robust filtering for networked systems with random transmission delays and packet dropouts

Robust filtering for networked systems with random transmiss...

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作者： Cai, Yunze Wang, Hua O. Tanaka, Kazuo Xu, Xiaoming Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing 800 Dongchuan Rd. Shanghai 200240 China Department of Mechanical Engineering Boston University Boston MA 02215 United States Department of Mechanical Systems and Intelligent Systems University of Electro-Communications Tokyo 182-8585 Japan Department of Automation Shanghai Jiao Tong University 800 Dongchuan Rd. Shanghai 200240 China University of Shanghai for Science and Technology 16 Jun Gong Rd. Shanghai 200093 China

ISBN: (纸本)9781457700804

This paper addresses a robust H∞ filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by employing random series with Bernoulli distributions. A sufficient condition for robust stability with H∞ constraints is derived for the filtering error system. The robust filter is designed in terms of the feasibility of a linear matrix inequality (LMI). The numerical examples are provided to show the effectiveness of the data transmission model and the proposed filtering method. © 2011 AACC American Automatic control Council.

关键词： Linear matrix inequalities

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Dual-Stream Fusion Network With Multi-Head Self-Attention for Multi-Modal Fake News Detection

SSRN

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SSRN 2024年

作者： Yang, Yimei Liu, Jinping Yang, Yujun Cen, Lihui School of Mathematics and Statistics Hunan Normal University Changsha410081 China Huaihua University Hunan Huaihua418000 China College of Information Science and Engineering Hunan Normal University Changsha China School of Automation Central South University Changsha410083 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing Application in Hunan Province Universities Hunan Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Hunan Huaihua418000 China

With the rapid development of social media platforms such as Weibo, WeChat, and other new media, as well as the rise of deepfake technologies, the identification and containment of fake information have posed significant challenges, becoming one of the key challenges faced by society and governmental institutions. Therefore, the development of intelligent and efficient methods for detecting fake news has become a top priority in combating misinformation. Addressing challenges in current fake news detection techniques, such as cross-lingual issues, data imbalance, and multimodal information fusion, this paper aims to propose a dual-stream fusion network model (DSF-MHSA) based on deep learning for detecting fake news across web pages, images, and text. The model combines the deep learning models ERNIE-M, AlexNet, ShuffleNet, and three multi-head self-attention mechanisms to extract and classify features from multilingual text and images. By utilizing two separate multi-head self-attention mechanisms to process extracted textual and image information, the model captures long-range dependencies among texts to better understand contextual information and captures global information among images to enhance object recognition and localization capabilities. Finally, a single multi-head self-attention mechanism is employed to integrate textual and image information to capture cross-modal correlations, thereby strengthening the model's understanding and identification capabilities of news content. This dual-stream fusion network architecture ensures the model's ability to detect multimodal news scenarios in both English and Chinese short texts and images. Experimental evaluations conducted on three publicly available datasets - Twitter, Weibo, and IKCEST-2023 dataset, which contains real online news data collected from domestic and international social media platforms - demonstrate superior performance of the proposed model in news detection tasks, achieving an accuracy rate

关键词： Network architecture

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