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E-Health and Bioengineering Conference (EHB)

作者： M. Caramihai N. Radu M. Bostan G. Ion A. A. Chirvase M. Constantin M. Doni N. Babeanu Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Biotechnology Department University of Agronomic Sciences and Veterinary Medicine of Bucharest Romania Immunology Center of IVN S. Nicolau Bucharest Romania Biotechnology Department National Institute of Chemistry and PetrochemistryR&D of Bucharest Romania

Behavior evaluation of tumor and normal cell lines, under the influence of mixture between cytostatic and immunomodulatory compounds represents a challenge in oncologic research, because it is expected that in the presence of immunomodulatory compound, the normal cells will be less affected and the tumor cells will be destroyed much more. The aim of this paper is to predict the behavior of tumor cell line (FaDu) and normal cell line (HUVEC) under the influence of cytostatic compound named Cisplatin (CisPt) and under the influence of immunomodulatory compound named Curcumin (CR), in order to obtain an optimal mixing ratio between these two compounds. Based on the results obtained in Lab regarding the response of the two cell lines evolution vs. the treatment with each reagent in the concentration range of (0-100μM/mL), it was tried to model the behavior of the system in presence of these two compounds, using a fuzzy prediction. The obtained results were compared with predictions resulted from fuzzy simulation. Analyzing the numeric values, the best results were obtained in the case of prediction regarding HUVEC behavior with a fuzzy simulation.

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A luminaire with variable light distribution 7

A luminaire with variable light distribution

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7th Conference SOLINA Sustainable Development: Architecture - Building Construction - Environmental Engineering and Protection Innovative Energy-Efficient Technologies - Utilization of Renewable Energy Sources, SOLINA 2018

作者： Lesko, Marcin Rózowicz, Antoni Baran, Krzysztof Wachta, Henryk Rzeszow University of Technology Faculty of Electrical and Computer Engineering al. Powstańców Warszawy 12 Rzeszów35-959 Poland Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science al. Tysiaclecia Państwa Polskiego 7 Kielce25-314 Poland

Industrial facilities such as production and storage halls are a specific environment, which is usually characterized by a large usable area, which is managed in a way that brings together in the given area many functional zones for various purposes. Frequent changes in the management of industrial halls gives a need to change the lighting method. In such a situation, a lighting solution that enables the photometric characteristics of the luminaires to be adapted to variable development of the facility, covering not only the quantitative regulation of the luminous flux, but also the direction of its radiation into the environment, can be a helpful solution. The article presents an innovative concept of a luminaire, which makes it possible to change the light distribution without the need to replace optical elements. Simulation tests were carried out for the developed luminaire in order to check the possibility of obtaining the assumed distribution and shapes of light spots on the working plane. Thanks to the application of this solution in an environment where there is a need for frequent changes in the development of usable space requiring changes in lighting conditions, it is possible to dynamically adjust the characteristics of the installed system to new environmental conditions. © The Authors, published by EDP sciences, 2018.

关键词： Lighting

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A Data-Driven Framework for Identifying Tropical Wetland Model

A Data-Driven Framework for Identifying Tropical Wetland Mod...

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UKACC International Conference on control (control)

作者： Angesh Anupam David J. Wilton Sean R. Anderson Visakan Kadirkamanathan Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Computer Science The University of Sheffield Sheffield United Kingdom

A wetland is a land area that is saturated with water. Most of the wetlands exhibit seasonal variations because of soil characteristics, climate variables and orography of a site. This study applies the orthogonal least square (OLS) algorithm under the system identification methodology for the identification of a nonlinear dynamic model structure of the tropical wetlands, using a remotely sensed dataset. Despite the availability of data from the multiple tropical sites, a single dynamic-model structure is able to explain the underlying processes, governing the wetland extents of the tropics. The model is validated against a fresh data set, derived using the similar remote sensing technique. Overall, this study is a novel application of the systems identification for obtaining a single model structure of a category of wetlands, enabling some understanding about their dynamics. The model can also be employed for the assessment of future wetlands in the advent of climate change.

关键词： Wetlands Mathematical model Brain modeling Meteorology Data models Remote sensing

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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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Closed Loop Fault Detectability Based on a Gap-Metric 2

Closed Loop Fault Detectability Based on a Gap-Metric

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2nd IEEE Conference on control Technology and Applications, CCTA 2018

作者： Sekunda, Andre Ding, Steven Kjolstad Poulsen, Niels Niemann, Henrik Department of Electrical Engineering Automation and Control Tech. University of Denmark Kgs. LyngbyDk-2800 Denmark Dept. of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany Dept. of Applied Mathematics and Computer Science Tech. University of Denmark Kgs. LyngbyDk-2800 Denmark

ISBN: (纸本)9781538676981

Systems are often controlled using feedback loops. Fault diagnosis schemes are usually designed assuming that there is no feedback loop. Therefore fault diagnosis methods need to accommodate for the feedback loop. One such method is active fault diagnosis based on a fault signature system. This method is derived using the YJBK parametrisation, named after Youla, Jabr, Bongiorno and Kucera. It uses the derived fault signature system to determine the detectability of possible faults in the system. Deriving the fault signature system requires knowledge about the controller. This paper demonstrates the possibility of estimating the detectability of faults in the fault signature system using a gap-metric. The gap-metric has the advantage of only requiring knowledge about the plant. By using the gap-metric it is possible to estimate the detectability of faults without using information about the controller. © 2018 IEEE.

关键词： Fault detection

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Semantic Annotation of Arabic Web Documents using Deep Learning

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Procedia computer science 2018年 130卷 589-596页

作者： Saeed Albukhitan Ahmed Alnazer Tarek Helmy Information and Computer Science Department College of Computer Science & Engineering King Fahd University of Petroleum & Minerals Dhahran 31216 Mail Box 413 Saudi Arabia On leave from College of Engineering Department of Computers & Automatic Control Tanta University Egypt

The vision of Semantic Web is to have a Web of things instead of Web of documents in a form that can be processed by machines. This vision could be achieved on the existing Web using semantic annotation based on common and public ontologies. Due to exponential growth and the huge size of the Web sources, there is a need to have fast and automatic semantic annotation of Web documents. Arabic language received less attention in semantic Web research as compared to Latin languages especially in the field of semantic annotation. The aim of this paper is to investigate the feasibility of using word embeddings from deep learning algorithms for semantic annotation of Arabic Web documents. To evaluate the performance of the proposed framework, food, nutrition, and health ontologies were used to annotate some related Web documents. For a given set of Arabic documents and ontologies, the framework produces annotations of these documents using different output formats. The initial results show a promising performance which will support the research in the Semantic Web with respect to Arabic language. The proposed framework could be used for building semantic Web application and semantic search engines for Arabic Language.

关键词： Deep Learning Semantic Annotation Arabic Language Ontology

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control of discrete-time nonlinear systems via finite-step control Lyapunov functions

arXiv

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arXiv 2019年

作者： Noroozi, Navid Geiselhart, Roman Grüne, Lars Wirth, Fabian R. Otto-von-Guericke University of Magdeburg Laboratory for Systems Theory and Automatic Control Magdeburg39106 Germany University of Ulm Institute of Measurement Control and Microtechnology Albert-Einstein-Allee 41 Ulm89081 Germany University of Bayreuth Mathematical Institute Universitätsstraße 30 Bayreuth95440 Germany University of Passau Faculty of Computer Science and Mathematics Innstraße 33 Passau94032 Germany

In this work, we establish different control design approaches for discrete-time systems, which build upon the notion of finite-step control Lyapunov functions (fs-CLFs). The design approaches are formulated as optimization problems and solved in a model predictive control (MPC) fashion. In particular, we establish contractive multi-step MPC with and without reoptimization and compare it to classic MPC. The idea behind these approaches is to use the fs-CLF as running cost. These new design approaches are particularly relevant in situations where information exchange between plant and controller cannot be ensured at all time instants. An example shows the different behavior of the proposed controller design approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Model predictive control

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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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Algorithms and performance analysis for stochastic wiener system identification

arXiv

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arXiv 2018年

作者： Wahlberg, Bo Ljung, Lennart Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Automatic Control Linköping University LinköpingSE-581 83 Sweden

We analyze the statistical performance of identification of stochastic dynamical systems with non-linear measurement sensors. This includes stochastic Wiener systems, with linear dynamics, process noise and measured by a non-linear sensor with additive measurement noise. There are many possible system identification methods for such systems, including the Maximum Likelihood (ML) method and the Prediction Error Method (PEM). The focus has mostly been on algorithms and implementation, and less is known about the statistical performance and the corresponding Cramér-Rao Lower Bound (CRLB) for identification of such non-linear systems. We derive expressions for the CRLB and the asymptotic normalized covariance matrix for certain Gaussian approximations of Wiener systems to show how a non-linear sensor affects the accuracy compared to a corresponding linear sensor. The key idea is to take second order statistics into account by using a common parametrization of the mean and the variance of the output process. This analysis also leads to a ML motivated identification method based on the conditional mean predictor and a Gaussian distribution approximation. The analysis is supported by numerical simulations. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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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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