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Network and Systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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Feedback stabilization of double pendulum: Application to the crane systems with time-varying rope length

arXiv

引用

arXiv 2018年

作者： Vrabel, Robert Slovak University of Technology in Bratislava Faculty of Materials Science and Technology Institute of Applied Informatics Automation and Mechatronics Bottova 25 Trnava917 01 Slovakia

In the present paper we focus our attention on the design of the feedback-based feed-forward controller asymptotically stabilizing the double-pendulum-type crane system with the time-varying rope length in the desired end position of payload (the origin of the coordinate system). In principle, we will consider two cases, in the first case, the sway angle of payload is uncontrolled and the second case, when the sway angle of payload is controlled by an external force. Mathematical modelling in the framework of Lagrange formalism and numerical simulation in the Matlab environment indicates the substantial reduction of the transportation time to the desired end position. Another principal novelty of this paper lies in deriving and analysis of a complete mathematical model without approximating the nonlinear terms and without neglecting some structural parameters of systems for the reasons described in the Remark 4.2 and Remark 5.1.93B52 93B05 Copyright © 2018, The Authors. All rights reserved.

关键词： State feedback

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Identification of disaster-implicated named entities 1

Identification of disaster-implicated named entities

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1st International Workshop on Exploitation of Social Media for Emergency Relief and Preparedness, SMERP 2017

作者： Ács, Judit Nemeskey, Dávid Márk Kornai, András Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary Computer Science and Automation Research Institute Hungarian Academy of Sciences Hungary

For disaster preparedness, a key aspect of the work is the identification, ahead of time, of potentially implicated locations (LOC), organizations (ORG), and persons (PER). Here we describe how static repositories of ... 详细信息

关键词： Disasters

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Robust training of neural network via minimizing robust estimates of the average of loss functions

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Journal of Physics: Conference Series 2019年第1期1203卷

作者： Z M Shibzukhov M A Kazakov D P Dimitrichenko Institute of applied mathematics and automation KBSC RAS Shortanova 89a Nalchik Russia Institute of mathematics and informatics MPGU Krasnoprudnaya 4 Moscow Russia

The paper suggests an extended version of principle of empirical risk minimization and principle of smoothly winsorized averages minimization for robust neural networks learning. It's based on using of M-averaging and WM-averaging functions instead of the arithmetic mean for empirical risk estimation. These approaches generalize robust algorithms based on using median and quantiles for estimation of mean losses. An iteratively reweighted schema for minimization of differentiable robust estimations of the averages of loss functions is proposed. This schema allows to use weighted version of traditional back-propagation algorithms for neural networks learning in presence of outliers.

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The role of hydro power, storage and transmission in the decarbonization of the Chinese power system

arXiv

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arXiv 2018年

作者： Liu, Hailiang Brown, Tom Andresen, Gorm Bruun Schlachtberger, David P. Greiner, Martin Department of Engineering Aarhus University Inge Lehmanns Gade 10 Aarhus C8000 Denmark Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany

Deep decarbonization of the electricity sector can be provided by a high penetration of renewable sources such as wind, solar PV and hydro power. Flexibility from hydro and storage complements the high temporal variability of wind and solar, and transmission infrastructure helps the power balancing by moving electricity in the spatial dimension. We study cost-optimal highly-renewable Chinese power systems under ambitious CO2 emission reduction targets, by deploying a 31-node hourly-resolved techno-economic optimization model supported by a validated weather-converted 38-year-long renewable power generation and electricity demand dataset. With a new realistic reservoir hydro model, we find that if CO2 emission reduction goes beyond 70%, storage facilities such as hydro, battery and hydrogen become necessary for a moderate system cost. Numerical results show that these flexibility components can lower renewable curtailment by two thirds, allow higher solar PV share by a factor of two and contribute to covering summer cooling demand. We show that expanding unidirectional high-voltage DC lines on top of the regional inter-connections is technically sufficient and more economical than ultra-high-voltage-AC-connected "One-Net" grid. Finally, constraining transmission volume from the optimum by up to 25% does not push total costs much higher, while the significant need for battery storage remains even with abundant interconnectivity. Copyright © 2018, The Authors. All rights reserved.

关键词： Wind power

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

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arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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Preliminary considerations in the design of a sensor for improving the reference trajectory calculation for the individual leg of a hexapod

Preliminary considerations in the design of a sensor for imp...

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IEEE International Symposium on Intelligent Systems and informatics

作者： Zoltan Gobor Peter Odry Annamaria R. Varkonyi-Koczy Doctoral School of Applied Informatics and Applied Mathematics Obuda University Budapest Hungary Department of Control Engineering and Information Technology University of Dunaújváros Dunaujvaros Hungary Institute of Automation Obuda University Budapest Hungary

The free-climbing robots are the alternative to wheeled vehicles, because the legged locomotion allows mobility on the steep gradients under the harsh environmental conditions. The steady progression requires coordination of leg movements for which the force sensors implemented in the joints of the robot legs are not always sufficient. Considering the previous developments in the field of robotics, the combination of the impedance and vision sensors comprises an obvious solution for providing stable and accurate contact between the individual legs and the ground. The implementation of additional, non-invasive sensor/s on all the legs of the hexapod robotic platform, for the indirect measuring and analysis of the terrain surface, is investigated. Furthermore, a method for the parametric 3D modeling of simulation assemblies is described in a mixed top-down, bottom-up and middle-out design approach. Mechanisms were created using the common origin skeletal modeling (top-down approach), allowing the context analysis and the definition of the parameters for the further numerical optimization in an early phase of the development. Finally, the applicability of the anytime approach during the optimization of the mechanical parts of the mechanism in the design process was tested.

关键词： Hexapod Parametric modeling Common origin skeletal modeling Anytime algorithm Kinematical simulation

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Electrical bioimpedance spectroscopy as a tool for non-destructive monitoring nitrogen supply in two lettuce genotypes

引用

Scientia Horticulturae 2025年 349卷

作者： Flórián Kovács Ákos Odry Zoltán Vizvári Anita Szegő Haimei Chen Enikő Papdi Ingrid Melinda Gyalai Ágnes Kun Péter Odry Katalin Juhos Department of Agro-Environmental Studies Hungarian University of Agriculture and Life Sciences Villányi str. 29-43 Budapest H-1118 Hungary Faculty of Agriculture Institute of Plant Sciences and Environmental Protection University of Szeged Hódmezővásárhely 6800 Hungary Department of Mechatronics and Automation Faculty of Engineering University of Szeged Moszkvai krt. 9 Szeged 6725 Hungary Department of Control Engineering and Information Technology University of Dunaújváros Táncsics Mihály u. 1 Dunaújváros 2400 Hungary John Von Neumann Faculty of Informatics Biomatics and Applied Artificial Intelligence Institute Óbuda University Bécsi str. 96 Budapest H-1034 Hungary Bioimpedance Technologies Research Center University Research and Innovation Center Óbuda University Bécsi str. 96 Budapest H-1034 Hungary Multidisciplinary Medical and Engineering Cellular Bioimpedance Research Group Szentagothai Research Centre University of Pecs Ifjusag str. 20 Pecs H-7624 Hungary Department of Plant Physiology and Plant Ecology Institute of Agronomy Hungarian University of Agriculture and Life Sciences Ménesi Str. 44 Budapest H-1118 Hungary Department of Floriculture and Dendrology Urban Planning and Garden Art Institute of Landscapes Architecture Hungarian University of Agriculture and Life Sciences Villányi ut 29-43 Budapest 1118 Hungary Research Center for Irrigation and Water Management Institute of Environmental Sciences Hungarian University of Agriculture and Life Sciences Anna-Liget str. 35. Szarvas H-5540 Hungary

Accurate monitoring of nutrient supply is crucial for effective plant nutrition management. This study introduces a bioimpedance spectroscopy (BIS) approach to evaluate how lettuce genotypes respond to nitrogen (N) supply, illuminating the link between BIS and N metabolism. The research consisted of two parts: a preliminary experiment focusing on extracellular fluid resistance, followed by a second experiment involving five different N treatments applied to two lettuce genotypes. BIS spectra were recorded from 1 Hz to 100 kHz, with a total of 224 measurements. Plant physiological analyses assessed total and extracellular fluid nitrate (NO 3 − ) concentrations, pigment concentration, total N content, and cell membrane stability index. In the preliminary experiment, a significant negative correlation was observed between extracellular fluid NO 3 − concentration and extracellular fluid resistance (r = – 0.67). Furthermore, the frequency range around 63 Hz (R 2 = 0.97) appeared most sensitive to NO 3 − dynamics in the ‘Kobak’ lettuce genotype. In the two lettuce genotypes exposed to the five different N treatments, extracellular fluid resistance negatively correlated with total N and NO 3 − content ( r = – 0.76 and – 0.73), while vacuole fluid resistance showed a moderate correlation ( r = – 0.51). Cell membrane capacitance was also significantly correlated with membrane stability index ( r = 0.68), indicating that low-N conditions reduce membrane charge storage. However, these correlations appeared highly genotype dependent. Heatmap-based hierarchical clustering of Z-score standardized BIS parameters further confirmed these genotype-specific patterns. Collectively, these findings suggest that BIS captures key aspects of N uptake and storage, particularly in the extracellular fluid compartment. Overall, BIS offers a robust, non-destructive method for monitoring N status and may enhance precision in nutrient management for lettuce and other crops, although the genotype-s

关键词： Extracellular fluid resistance Vacuole fluid resistance Cell membrane capacitance Nitrogen uptake

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Transfer learning versus multi-agent learning regarding distributed decision-making in highway traffic

arXiv

引用

arXiv 2018年

作者： Schutera, Mark Goby, Niklas Neumann, Dirk Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Chair for Information Systems Research University of Freiburg IT Innovation Chapter Data Science ZF Friedrichshafen AG Research and Development ZF Friedrichshafen AG

Transportation and traffic are currently undergoing a rapid increase in terms of both scale and complexity. At the same time, an increasing share of traffic participants are being transformed into agents driven or supported by artificial intelligence resulting in mixed-intelligence traffic. This work explores the implications of distributed decision-making in mixed-intelligence traffic. The investigations are carried out on the basis of an online-simulated highway scenario, namely the MIT DeepTraffic simulation. In the first step traffic agents are trained by means of a deep reinforcement learning approach, being deployed inside an elitist evolutionary algorithm for hyperparameter search. The resulting architectures and training parameters are then utilized in order to either train a single autonomous traffic agent and transfer the learned weights onto a multi-agent scenario or else to conduct multi-agent learning directly. Both learning strategies are evaluated on different ratios of mixed-intelligence traffic. The strategies are assessed according to the average speed of all agents driven by artificial intelligence. Traffic patterns that provoke a reduction in traffic flow are analyzed with respect to the different strategies. Copyright © 2018, The Authors. All rights reserved.

关键词： Multi agent systems

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Preface

Advanced Textbooks in Control and Signal Processing

引用

Advanced Textbooks in Control and Signal Processing 2019年 ix-x页

作者： Keviczky, László Bars, Ruth Hetthéssy, Jenő Bányász, Csilla Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

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