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arXiv 2018年

作者： Tanaka, Ken'ichiro Sugihara, Masaaki Department of Mathematical Informatics Graduate School of Information Science and Technology University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Physics and Mathematics College of Science and Engineering Aoyama Gakuin University 5-10-1 Fuchinobe Chuo-ku Sagamihara-shi Kanagawa252-5258 Japan

We propose a simple and effective method for designing approximation formulas for weighted analytic functions. We consider spaces of such functions according to weight functions expressing the decay properties of the functions. Then, we adopt the minimum worst error of the n-point approximation formulas in each space for characterizing the optimal sampling points for the approximation. In order to obtain approximately optimal sampling points, we consider minimization of a discrete energy related to the minimum worst error. Consequently, we obtain an approximation formula and its theoretical error estimate in each space. In addition, from some numerical experiments, we observe that the formula generated by the proposed method outperforms the corresponding formula derived with sinc approximation, which is near optimal in each *** Codes 41A25, 41A50, 65D05, 65D15, 65E05 Copyright © 2018, The Authors. All rights reserved.

关键词： Functions

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Separated Contrastive Learning for Organ-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation

arXiv

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arXiv 2021年

作者： Wang, Jiacheng Li, Xiaomeng Han, Yiming Qin, Jing Wang, Liansheng Qichao, Zhou Department of Computer Science School of Informatics Xiamen University China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Peking University China Center for Smart Health School of Nursing The Hong Kong Polytechnic University Hong Kong Manteia Technologies Co. Ltd. United States

Automatic delineation of organ-at-risk (OAR) and gross-tumor-volume (GTV) is of great significance for radiotherapy planning. However, it is a challenging task to learn powerful representations for accurate delineation under limited pixel (voxel)-wise annotations. Contrastive learning at pixel-level can alleviate the dependency on annotations by learning dense representations from unlabeled data. Recent studies in this direction design various contrastive losses on the feature maps, to yield discriminative features for each pixel in the map. However, pixels in the same map inevitably share semantics to be closer than they actually are, which may affect the discrimination of pixels in the same map and lead to the unfair comparison to pixels in other maps. To address these issues, we propose a separated region-level contrastive learning scheme, namely SepaReg, the core of which is to separate each image into regions and encode each region separately. Specifically, SepaReg comprises two components: a structure-aware image separation (SIS) module and an intra- and inter-organ distillation (IID) module. The SIS is proposed to operate on the image set to rebuild a region set under the guidance of structural information. The inter-organ representation will be learned from this set via typical contrastive losses cross regions. On the other hand, the IID is proposed to tackle the quantity imbalance in the region set as tiny organs may produce fewer regions, by exploiting intra-organ representations. We conducted extensive experiments to evaluate the proposed model on a public dataset and two private datasets. The experimental results demonstrate the effectiveness of the proposed model, consistently achieving better performance than state-of-the-art approaches. Code is available at https://***/jcwang123/Separate CL. Copyright © 2021, The Authors. All rights reserved.

关键词： Pixels

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Middle East and North African Health informatics Association (MENAHIA): Building Sustainable Collaboration

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Yearbook of Medical informatics 2018年第1期27卷 286-291页

作者： Najeeb Al-Shorbaji Mowafa Househ Adel Taweel Abdullah Alanizi Bennani Othmani Mohammed Haitham Abaza Hala Bawadi Hamayon Rasuly Khalid Alyafei Luis Fernandez-Luque Mohamed Shouman Osama El-Hassan Rada Hussein Riyad Alshammari Salah Mandil Sarah Shouman Shahrad Taheri Tamer Emara Wasmiya Dalhem Zaid Al-Hamdan Zineb Serhier eHealth and Knowledge Management Consultant Retired Director of Knowledge Ethics and Research Department WHO/HQ Amman Jordan Department of Health Informatics College of Public Health and Health Informatics King Saud Bin Abdulaziz University for Health Sciences Ministry of National Guard-Health Affairs Riyadh Saudi Arabia Department of Computer Science BirZeit University Ramallah Palestine Head of Medical Informatics Unit 20 August Hospital Ibn Rochd University Hospital Casablanca Head of Casablanca Medical Informatics Laboratory Medical Faculty of Casablanca Morocco Department of Biomedical Engineering Misr University for Science & Technology Cairo Egypt Associate Professor College of Nursing University of Jordan Amman Jordan eHealth Program Coordinator Bamyan Provincial Hospital Bamyan City Afghanistan Chief Medical Informatics Officer (CMIO) - SIDRA Assistant Professor Clinical Pediatrics at Weill Cornell Medicine Qatar Qatar Computing Research Institute Hamad Bin Khalifa University Doha Qatar Faculty of Medicine Ain Shams University Cairo Egypt Vice-Chair of Emirates Health Informatics Society Head of eHealth Section at Dubai Health Authority Dubai United Arab Emirates Founder and Former Director of the Biomedical Informatics Center of Excellence (BMICoE) Information Technology Institute (ITI) Ministry of Communications and Information Technology (MCIT) Egypt President of Saudi Association for Health Informatics Riyadh Saudi Arabia Senior Consultant on eStrategies and eHealth to WHO and ITU Geneva Switzerland Department of Medicine Weill Cornell Medical College in Qatar Qatar Foundation Doha Qatar Executive Director of Nursing Informatics Hamad Medical Corporation Qatar Associate Professor of Nursing Management Faculty of Nursing Jordan University of Science and Technology Irbid Jordan Professor at Medical Informatics Laboratory Faculty of Medicine and Pharmacy Hassan II University Casablanca Morocco

There has been a growing interest in Health informatics applications, research, and education within the Middle East and North African Region over the past twenty years. People of this region share similar cultural and religious values, primarily speak the Arabic language, and have similar health care related issues, which are in dire need of being addressed. Health informatics efforts, organizations, and initiatives within the region have been largely under-represented within, but not ignored by, the International Medical informatics Association (IMIA). Attempts to create bonds and collaboration between the different organizations of the region have remained scattered, and often, resulted in failure despite the fact that the need for a united health informatics collaborative within the region has never been more crucial than today. During the 2017 MEDINFO, held in Hangzhou, China, a new organization, the Middle East and North African Health informatics Association (MENAHIA) was conceived as a regional non-governmental organization to promote and facilitate health informatics uptake within the region endorsing health informatics research and educational initiatives of the 22 countries represented within the region. This paper provides an overview of the collaboration and efforts to date in forming MENAHIA and displays the variety of initiatives that are already occurring within the MENAHIA region, which MENAHIA will help, endorse, support, share, and improve within the international forum of health informatics.

关键词： eHealth Middle East and North Africa Health informatics collaboration MENAHIA Universal Health Coverage Bioinformatics International Medical informatics Association

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Control Approaches for Complicated Self-Unstable Plants with Applications for Two-Wheel Mobile System

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IFAC Proceedings Volumes 2013年第9期46卷 609-613页

作者： Alexey A. Bobtsov Alexandr S. Borgul Konstantin A. Zimenko Anton A. Pyrkin Department of Control Systems and Informatics Saint Petersburg National Research University of Information Technologies Mechanics and Optics Saint Petersburg Russia Laboratory “Control of Complex Systems” Institute for Problems of Mechanical Engineering Bolshoy pr. V.O. 61 St.Petersburg 199178 Russia Department of Engineering Cybernetics Norwegian University of Science and Technology Trondheim NO-7491 Norway

In this paper a model of autonomous mobile robot “Motobot” is described. There is the model of two-wheeled motorbike. The mathematical model of motion of two-wheeled single-track robot on the horizontal flat is analyzed and the automatic control algorithms are designed. Problem can be solved by controlling the steering wheel and the speed of the driving wheel.

关键词： Mobile robots autonomous bike unstable systems output control educational robots

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments 6

Deep Reinforcement Learning-based Obstacle Avoidance for Rob...

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6th IEEE International Conference on Civil Aviation Safety and Information technology, ICCASIT 2024

作者： Li, Keqin Chen, Jiajing Yu, Dezhi Dajun, Tao Qiu, Xinyu Lian, Jieting Ji, Ryan Zhang, Shengyuan Wan, Zhenyu Sun, Baiwei Hong, Bo Ni, Fanghao Han, Jiaqi Ama University Department of Computer Science Quezon Philippines Courant Institute New York University 251 Mercer St New YorkNY10012 United States University of California Berkeley University Avenue and Oxford St School of Information BerkeleyCA94720 United States Carnegie Mellon University Master of Science in Mechanical Engineering School of Engineering 5000 Forbes Avenue PittsburghPA United States Northeastern University College of Engineering Seattle United States School of Professional Studies New York University Master of Science in Database Technology 50 West 4th Street New YorkNY United States Cornell University College of Engineering 616 Thurston Ave IthacaNY14853 United States Cornell University Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science 616 Thurston Ave IthacaNY United States Independent Researcher Beijing China University of California Irvine Master of Computer Science Donald Bren School of Information and Computer Sciences 510 Aldrich Hall IrvineCA United States Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350389418

This paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot's obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments. © 2024 IEEE.

关键词： Deep reinforcement learning

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Forward and backward bellman equations improve the efficiency of the EM algorithm for DEC-POMDP

arXiv

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arXiv 2021年

作者： Tottori, Takehiro Kobayashi, Tetsuya J. Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo Tokyo113-8654 Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering The University of Tokyo Tokyo113-8654 Japan Institute of Industrial Science The University of Tokyo Tokyo153-8505 Japan Universal Biology Institute The University of Tokyo Tokyo113-8654 Japan

Decentralized partially observable Markov decision process (DEC-POMDP) models sequential decision making problems by a team of agents. Since the planning of DEC-POMDP can be interpreted as the maximum likelihood estimation for the latent variable model, DEC-POMDP can be solved by the EM algorithm. However, in EM for DEC-POMDP, the forward-backward algorithm needs to be calculated up to the infinite horizon, which impairs the computational efficiency. In this paper, we propose the Bellman EM algorithm (BEM) and the modified Bellman EM algorithm (MBEM) by introducing the forward and backward Bellman equations into EM. BEM can be more efficient than EM because BEM calculates the forward and backward Bellman equations instead of the forward-backward algorithm up to the infinite horizon. However, BEM cannot always be more efficient than EM when the size of problems is large because BEM calculates an inverse matrix. We circumvent this shortcoming in MBEM by calculating the forward and backward Bellman equations without the inverse matrix. Our numerical experiments demonstrate that the convergence of MBEM is faster than that of EM. Copyright © 2021, The Authors. All rights reserved.

关键词： Markov processes

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Glucose-mediated mitochondrial reprogramming by cholesterol export at TM4SF5-enriched mitochondria-lysosome contact sites

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Cancer Communications 2024年第1期44卷 47-75页

作者： Ji Eon Kim So-Young Park Chulhwan Kwak Yoonji Lee Dae-Geun Song Jae Woo Jung Haesong Lee Eun-Ae Shin Yangie Pinanga Kyung-hee Pyo Eun Hae Lee Wonsik Kim Soyeon Kim Chang-Duck Jun Jeanho Yun Sun Choi Hyun-Woo Rhee Kwang-Hyeon Liu Jung Weon Lee Department of Pharmacy College of PharmacySeoul National UniversitySeoulRepublic of Korea Research Institute of Pharmaceutical Sciences College of PharmacySeoul National UniversitySeoulRepublic of Korea BK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit College of Pharmacy and Research Institute of Pharmaceutical SciencesKyungpook National UniversityDaeguRepublic of Korea Department of Chemistry Seoul National UniversitySeoulRepublic of Korea College of Pharmacy Chung-Ang UniversitySeoulRepublic of Korea Natural Product Informatics Research Center Korea Institute of Science and Technology(KIST)Gangneung-siGangwon-doRepublic of Korea School of Life Sciences Gwangju Institute of Science and Technology(GIST)GwangjuRepublic of Korea Department of Biochemistry College of MedicineDong-A UniversityBusanRepublic of Korea Global AI Drug Discovery Center College of Pharmacy and Graduate School of Pharmaceutical SciencesEwha Womans UniversitySeoulRepublic of Korea Interdisciplinary Program in Genetic Engineering Seoul National UniversitySeoulRepublic of Korea

Background:Transmembrane 4 L six family member 5(TM4SF5)translocates subcellularly and functions metabolically,although it is unclear how intracellu-lar TM4SF5 translocation is linked to metabolic *** is thus of interests to understand how the traffic dynamics of TM4SF5 to subcellular endosomal membranes are correlated to regulatory roles of ***:Here,we explored the metabolic significance of TM4SF5 localization at mitochondria-lysosome contact sites(MLCSs),using in vitro cells and in vivo animal systems,via approaches by immunofluorescence,proximity labelling based proteomics analysis,organelle reconstitution ***:Upon extracellular glucose repletion following depletion,TM4SF5 became enriched at MLCSs via an interaction between mitochondrial FK506-binding protein 8(FKBP8)and lysosomal *** labeling showed molecular clustering of phospho-dynamic-related protein I(DRP1)and certain mitophagy receptors at TM4SF5-enriched MLCSs,leading to mitochondrial fis-sion and ***4SF5 bound NPC intracellular cholesterol transporter 1(NPC1)and free cholesterol,and mediated export of lysosomal cholesterol to mitochondria,leading to impaired oxidative phosphorylation but intact tri-carboxylic acid(TCA)cycle andβ-*** mouse models,hepatocyte Tm4sf5 promoted mitophagy and cholesterol transport to mitochondria,both with positive relations to liver ***:Our findings suggested that TM4SF5-enriched MLCSs regu-late glucose catabolism by facilitating cholesterol export for mitochondrial reprogramming,presumably while hepatocellular carcinogenesis,recapitulating aspects for hepatocellular carcinoma metabolism with mitochondrial repro-gramming to support biomolecule synthesis in addition to glycolytic energetics.

关键词： cholesterol fluorescent imaging glucose catabolism hepatocellular carcinogenesis mem-brane contact sites mitochondria function mitophagy oxidative phosphorylation protein-protein interaction tetraspanin

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A novel modular climbing caterpillar using low-frequency vibrating passive suckers

A novel modular climbing caterpillar using low-frequency vib...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： H. X. Zhang J. Gonzalez-Gomez S.Y. Chen W. Wang R. Liu D. Li J. W. Zhang Institute of Technical Aspects of Multimodal Systems Department of Computer Science University of Hamburg Hamburg Germany School of Engineering Universidad Autonoma de Madrid Spain Department of Informatics University of Hamburg Germany College of Information Engineering Zhejiang University of Technology Hangzhou China Robotics Institute School of Mechanical Engineering and Automation Beijing Aeronautics and Astronautics University Beijing China

This paper presents a novel modular climbing caterpillar named ZC-I. After a related survey on the topic, a systematical summarizing on basic functions provided by this system is given. ZC-I features fast-building mechanical structure and low-frequency vibrating passive attachment principle. Active joints actuated by RC servos endow the connecting modules with the ability of changing shapes in two dimensions. After that the discussion focuses on the various locomotion capabilities. Linear movement, turning movement, lateral movement, rotating and rolling movement are achieved based on an inspired control model to produce rhythmic motion. In the end a conclusion and future work are given.

关键词： Climbing robots Prototypes Kinematics Servomechanisms Joining processes Shape Adhesives Electromagnetic forces Electromagnets Mobile robots

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E3-Net: Event-Guided Edge-Enhancement Network for UAV-based Crack Detection

E3-Net: Event-Guided Edge-Enhancement Network for UAV-based ...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Ran Duan Bo Wu Hao Zhou Haobo Zuo Zhengshu He Chenxi Xiao Changhong Fu Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic University Hong Kong China Department of Computer Science University of Hong Kong Hong Kong China MOE Key Laboratory of Transportation Tunnel Engineering Southwest Jiaotong University Chengdu China School of Information Science and Technology ShanghaiTech University Shanghai China School of Mechanical Engineering Tongji University Shanghai China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Buildings, bridges, and other exteriors of infrastructure are commonly susceptible to damages that may reduce safety and longevity. When left unattended, small cracks can cause catastrophic failures. However, crack inspection is a challenging process that requires significant human effort and can expose inspectors to risks. To address this challenge, the use of Unmanned Aerial Vehicles (UAVs) has emerged as an approach to survey areas that are difficult to reach. However, the cracks are small and may blend into background textures, making them difficult to discriminate. Furthermore, the motion of quadrotors can potentially cause motion blur, increasing the difficulty of crack detection. To address these challenges, we propose a neural network designed to detect cracks robustly. Our neural network architecture includes two stages. First, a V2E (Video-to-Event) model transforms the image data into Dynamic Vision Sensor (DVS) events. This procedure aims to make the output crack feature identifiable in the presence of motion blur. Then, an edge-enhancement net that combines UNet and non-local block net is designed to augment the crack feature and suppress the background texture concurrently. The background texture suppression is achieved by training on our annotated crack dataset using a triplet loss. Lastly, these proposed cracks can be highlighted by the YOLOv8n-seg network. Experimental results demonstrate that the proposed network can effectively detect small wall cracks in the presence of diverse background patterns.

关键词： Training Surveys Image edge detection Neural networks Transforms Inspection Vision sensors Safety Voltage control Vehicle dynamics

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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