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14th International Computer engineering Conference, ICENCO 2018

作者： Hussein, Mohammed A. Ali, Ahmed S. Elmisery, F.A. Mostafa, R. Electronics Technology Dept. Beni-Suef University Faculty of Industrial Education Beni-Suef Egypt Mechanical Engineering Dept. Assuit University Faculty of Engineering Assuit Egypt Electrical Dept. Beni-Suef University Faculty of Engineering Beni-Suef Egypt Automatic Control Dept. Beni-Suef University Faculty of Industrial Education Beni-Suef Egypt

ISBN: (纸本)9781538651179

the interest in robots and their applications has increased recently, and one of the most important applications is using robots in medical applications. This paper shows a prototype robotic system for robot-aided radiologists in their work, especially radiologists whom using ultrasound devices. The system includes master device, slave robot and a computer control system that lets the operator remotely position the ultrasound probe on the patient, Master device is available with the operator;Slave robot is located in the patient's location with an ultrasound *** proposed system composed of a new design of master device and slave robot;both designs were designed based on the shape, size and movements that radiologists used to do during an ultrasound examination, the master device is used to control the movement of ultrasound probe, the ultrasound probe is fixed inside the slave robot and its contacted to the patient body through a hole in the base at end of design. Movement accuracy between master device and slave robot was achieved. Ultrasound examination was tested by homemade gelatin model. © 2018 IEEE.

关键词： Computer control systems

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Heat Transfer Optimization of end Winding Rotor Generator by the Use of Modified Axial Spacer: A Case Study

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Journal of Physics: Conference Series 2021年第1期1845卷

作者： Y Baskoro I Jaya A Glowacz M Sulowicz W Caesarendra PT Indonesia Power Indonesia Department of Automatic Control and Robotics AGH University of Science and Technology 30-059 Kraków Poland Institute of Electromechanical Energy Conversion Faculty of Electrical and Computer Engineering Cracow University of Technology Warszawska 24 31-155 Cracow Poland Faculty of Integrated Technologies Universiti Brunei Darussalam Jalan Tungku Link Gadong BE1410 Brunei Darussalam

This paper presents a case study of a rotor fault occurring in the rotor generator of a steam power plant located in Lontar, Banten Province, Indonesia. The steam power plant has 3 x 315 MV capacity and uses hydrogen in the cooling system. The issue arising during the operation was caused by heat transfer exceeding the normal level. The grounding of the rotor occurred through rising vibration and temperature, tripping the generator unit. During repairs, the axial spacer was replaced with a new model, where it is longer than the original, adding a bar spacer at a previously unavailable position and creating a cooling track profile. This is a case study on the replacement of the axial spacer model aimed at preventing the expansion of the winding, so as not to touch with each other, through the installation of a longer axial spacer and the addition of the spacer bar, and lastly adding the track profile to the cooling hydrogen gas flow thereby maximizing the cooling process from the end winding rotor generator. Heat transfer is an analysed parameter related to the model change of the axial spacer. The addition of a track cooling gas flow has been able to maximize the heat transfer process, which is simulated in this paper. The performance of the rotor generator increased through several parameters after the replacement of the axial spacer model.

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Heat distribution in the deep drawing device components working by high temperatures 10

Heat distribution in the deep drawing device components work...

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10th International Conference Machine and Industrial Design in Mechanical engineering, KOD 2018

作者： Tropp, M. Brumerčík, F. Šteininger, J. Weis, P. Glowacz, A. Univerzity of Žilina Faculty of Mechanical Engineering Department of Design and Mechanical Elements Univerzitná 1 Žilina010 26 Slovakia AGHUniversity of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Al. A. Mickiewicza 30 Kraków30-059 Poland

The subject of the article is a simulation of heat affected components of a device for deep drawing by extreme conditions in vacuum by high temperatures required for forming of crystallization containers made from thin molybdenum sheets. The simulation is focused on the distribution of heat in particular components in relation with their shape. There are presented the design of working components and the boundary conditions of transient thermal simulations with the results. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Deep drawing

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

arXiv

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arXiv 2024年

作者： de la Rosa, Ezequiel Reyes, Mauricio Liew, Sook-Lei Hutton, Alexandre Wiest, Roland Kaesmacher, Johannes Hanning, Uta Hakim, Arsany Zubal, Richard Valenzuela, Waldo Robben, David Sima, Diana M. Anania, Vincenzo Brys, Arne Meakin, James A. Mickan, Anne Broocks, Gabriel Heitkamp, Christian Gao, Shengbo Liang, Kongming Zhang, Ziji Siddiquee, Md Mahfuzur Rahman Myronenko, Andriy Ashtari, Pooya Van Huffel, Sabine Jeong, Hyun-Su Yoon, Chi-Ho Kim, Chulhong Huo, Jiayu Ourselin, Sebastien Sparks, Rachel Clèrigues, Albert Oliver, Arnau Lladó, Xavier Chalcroft, Liam Pappas, Ioannis Bertels, Jeroen Heylen, Ewout Moreau, Juliette Hatami, Nima Frindel, Carole Qayyum, Abdul Mazher, Moona Puig, Domenec Lin, Shao-Chieh Juan, Chun-Jung Hu, Tianxi Boone, Lyndon Goubran, Maged Liu, Yi-Jui Wegener, Susanne Kofler, Florian Ezhov, Ivan Shit, Suprosanna Hernandez Petzsche, Moritz R. Menze, Bjoern Kirschke, Jan S. Wiestler, Benedikt Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Informatics Technical University Munich Germany Icometrix Leuven Belgium ARTORG Center for Biomedical Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Switzerland University of Bern Bern Switzerland Chan Division of Occupational Science and Occupational Therapy University of Southern California Los AngelesCA United States Stevens Neuroimaging and Informatics Institute Department of Neurology Keck School of Medicine University of Southern California United States University Institute of Diagnostic and Interventional Neuroradiology Inselspital Bern Switzerland University Institute of Diagnostic and Interventional Neuroradiology University Hospital Bern Inselspital University of Bern Bern Switzerland Department of Diagnostic and Interventional neuroradiology University Medical Center Hamburg-Eppendorf Hamburg Germany Department of Medical Imaging Radboud University Medical Center Institute for Health Sciences Nijmegen Netherlands Deepwise AI Lab Beijing China Beijing University of Posts and Telecommunications Bejing China School of Computing and Augmented Intelligence Arizona State University TempeAZ United States NVIDIA Santa ClaraCA United States STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Pohang Korea Republic of School of Biomedical Engineering & Imaging Sciences King’s College London United Kingdom Institute of Computer Vision and Robotics University of Girona Spain Wellcome Centre for Human Neuroimaging University College London London United Kingdom Laboratory of Neuro Imaging Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles United States KU Leuven Leuven Belgium CREATIS Université Lyon1 CNRS UMR5220 INSERM U1206 INSA-Lyon Villeurbanne696

Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a novel ensemble algorithm derived from the 2022 Ischemic Stroke Lesion Segmentation (ISLES) challenge. ISLES’22 provided 400 patient scans with ischemic stroke from various medical centers, facilitating the development of a wide range of cutting-edge segmentation algorithms by the research community. By assessing them against a hidden test set, we identified strengths, weaknesses, and potential biases. Through collaboration with leading teams, we combined top-performing algorithms into an ensemble model that overcomes the limitations of individual solutions. Our ensemble model combines the individual algorithms’ strengths and achieved superior ischemic lesion detection and segmentation accuracy (median Dice score: 0.82, median lesion-wise F1 score: 0.86) on our internal test set compared to individual algorithms. This accuracy generalized well across diverse image and disease variables. Furthermore, the model excelled in extracting clinical biomarkers like lesion types and affected vascular territories. Notably, in a Turing-like test, neuroradiologists consistently preferred the algorithm’s segmentations over manual expert efforts, highlighting increased comprehensiveness and precision. Validation using a real-world external dataset (N=1686) confirmed the model’s generalizability (median Dice score: 0.82, median lesion-wise F1 score: 0.86). The algorithm’s outputs also demonstrated strong correlations with clinical scores (admission NIHSS and 90-day mRS) on par with or exceeding expert-derived results, underlining its clinical relevance. This study offers two key findings. First, we present an ensemble algorithm that detects and segments ischemic stroke lesions on DWI across diverse scenarios on par with expert (neuro)rad

关键词： Diagnosis

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Vision-based Navigation Using Deep Reinforcement Learning

arXiv

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arXiv 2019年

作者： Kulhánek, Jonáš Derner, Erik de Bruin, Tim Babuška, Robert Cognitive Robotics Faculty of 3mE Delft University of Technology Delft2628 CD Netherlands Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague16636 Czech Republic Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague16627 Czech Republic

— Deep reinforcement learning (RL) has been successfully applied to a variety of game-like environments. However, the application of deep RL to visual navigation with realistic environments is a challenging task. We propose a novel learning architecture capable of navigating an agent, e.g. a mobile robot, to a target given by an image. To achieve this, we have extended the batched A2C algorithm with auxiliary tasks designed to improve visual navigation performance. We propose three additional auxiliary tasks: predicting the segmentation of the observation image and of the target image and predicting the depth-map. These tasks enable the use of supervised learning to pre-train a large part of the network and to reduce the number of training steps substantially. The training performance has been further improved by increasing the environment complexity gradually over time. An efficient neural network structure is proposed, which is capable of learning for multiple targets in multiple environments. Our method navigates in continuous state spaces and on the AI2-THOR environment simulator outperforms state-of-the-art goal-oriented visual navigation methods from the literature. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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A first course in feedback, dynamics and control: findings from an online pilot survey for the IFAC community

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IFAC-PapersOnLine 2019年第9期52卷 298-305页

作者： J.A. Rossiter K. Zakova M. Huba A. Serbezov A. Visioli Department of Automatic Control and Systems Engineering University of Sheeld Sheeld S1 3JD UK Slovak University of Technology in Bratislava Faculty of Electrical Engineering and Information Technology Institute of Automotive Mechatronics Ilkovicova 3 SK-812 19 Bratislava Slovakia Rose-Hulman Institute of Technology 5500 Wabash Avenue Terre Haute IN 47803-3999 Department of Mechanical and Industrial Engineering University of Brescia Italy

Undergraduate students in many engineering programs around the world take only one control course. The IFAC Educational Committee has developed and piloted to a limited audience a comprehensive survey for the topics to be included in such course. This issue is relevant to both academia and industry. The paper discusses the initial findings related to the design of the survey as well as the responses of the participants. The findings will be used to refine the survey and distribute it in the near future to the global control community.

关键词： control curriculum

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Scalability through Decentralization: A Robust control Approach for the Energy Management of a Building Community

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IFAC-PapersOnLine 2017年第1期50卷 14314-14319页

作者： Darivianakis, Georgios Georghiou, Angelos Eichler, Annika Smith, Roy S. Lygeros, John Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Switzerland Desautels Faculty of Management McGill University Montreal Canada

Recent studies in the literature have shown that cooperative energy management of an aggregation of buildings may lead to substantial energy savings. These approaches typically assume the existence of a central operator that is capable of formulating and solving, within a reasonable amount of time, a centralized optimization problem. However, this requirement may be unrealizable in cases of large scale districts, and it also fails to address privacy concerns of the building occupants. In this paper, we deal with these issues by proposing a decentralized control scheme which only requires the individual buildings to communicate bounds on their energy demands. The proposed method partly alleviates concerns on privacy since this limited communication scheme does not reveal the exact characteristics of the energy usage within each building. In addition, it enables a distributed computation of the solution, making our method highly scalable. We demonstrate through a numerical study the efficacy of the proposed approach, which leads to solutions that closely approximate those obtained by the centralized formulation only at a fraction of the computational effort. © 2017

关键词： Decentralized control Buildings Convex optimization Energy conservation Energy management Robust control Building energy managements Centralized optimization Computational effort Cooperative energies Distributed computations Limited communication Predictive control Robust controller synthesis

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An Adaptive Filter for IMU/Encoder Data Fusion for Acceleration Estimation in Robot Arms

An Adaptive Filter for IMU/Encoder Data Fusion for Accelerat...

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2018 International Conference on System Science and engineering, ICSSE 2018

作者： Cong Khoa, Nguyen Xuan Minh, Phan Faculty of Automation Technology Thai Nguyen University University of Information and Communication Technology Thai Nguyen Viet Nam Hanoi University of Science and Technology Hanoi Viet Nam Department of Automatic Control School of Electrical Engineering Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9781538662854

This paper develops an adaptive filter for fusing the noisy and biased measurement data from MEMS-based inertial measurement units and encoders for estimation of acceleration in robot arms. A discrete-time second-order model is derived for designing an adaptive Kalman filter (AKF). The output of the AKF is an unbiased but noisy estimate of the acceleration. To cancel the noise, a recursive least square filter is designed to filter the output of the designed AKF. It is shown that the resulting filtered signal is unbiased and noise-cancelled. Experimental results demonstrating the effectiveness of the developed adaptive filter are presented. © 2018 IEEE.

关键词： Adaptive filters

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Algorithms for robust production scheduling with energy consumption limits

arXiv

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arXiv 2018年

作者： Modos, Istvan Sucha, Premysl Hanzalek, Zdenek Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Czech Institute of Informatics Robotics and Cybernetics Czech Technical University

In this work, we consider a scheduling problem faced by production companies with large electricity consumption. Due to the contract with the electric utility, the production companies are obligated to comply with the total energy consumption limits in the specified time intervals (usually 15-minutes long);otherwise, the companies pay substantial penalty fees. Although it is possible to design production schedules that consider these limits as hard constraints, uncertainties occurring during the execution of the schedules are usually not taken into account. This may lead to situations in which the unexpected delays of the operations cause the violations of the energy consumption limits. Our goal is to design robust production schedules pro-actively guaranteeing that the energy consumption limits are not violated for the given set of uncertainty scenarios. We consider scheduling on one machine with release times of the operations and total tardiness as the objective function. To tackle this problem, we first propose a pseudo-polynomial algorithm for finding the optimal robust schedule for the given permutation of the operations. This algorithm is then utilised in three different algorithms for finding the optimal permutation: Two exact (Branch-and-Bound and logic-based Benders decomposition) and one heuristic algorithm (tabu search). All the algorithms were experimentally evaluated on random instances with different sizes of the uncertainty scenarios set. Using the tabu search algorithm, we are able to solve large instances within one minute. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric power utilization

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Methodology of Calculating Electric Energy Losses in Distribution Networks for the Needs of Assessment of Investment Needs and Effectiveness of Operation of Distribution Companies

Methodology of Calculating Electric Energy Losses in Distrib...

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International Conference on the European Energy Market

作者： Barbara Kaszowska Andrzej Wloczyk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

Liberalization of the electric energy market needs to involve the determination of strategic goals which will enable distribution enterprises to operate in a competitive market, which means that they have to achieve satisfactory economic results. It is imperative to determine the costs of energy distribution, which are significantly influenced by the amount of energy loss. Therefore, the calculation of the energy losses forms very important aspects in exploitation distribution networks and investment. The paper discusses a model of the distribution network and the energy losses calculation method. The potential for the application of the method in assessing the operation of distribution enterprises is presented, which leads to recommendation for the investments strategy.

关键词： Distribution networks Electric energy losses

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