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作者： Nebojsa U. Pjevalica Nenad S. Petrovic Milos M. Nikolic the University of Novi Sad Faculty of Technical sciences Computing and control engineering dept. Trg Dositeja Obradovica 6 21000 Novi Sad Serbia the School of Electrical Engineering Stari grad Visokog Stevana 37 11000 Belgrade Serbia RT-RK Computer based systems Narodnog fronta 23a 21000 Novi Sad Serbia

ISBN: (纸本)9781509000562

Inductance is a basic electrical element that couples magnetic flux and current. In many applications the linear approximation of inductance provides sufficiently good results of analysis. In the presence of an additional DC bias magnetic field H_(DC), the observed B-H curve is forced to be moved from its unbiased state and an asymmetric nonlinearity of the targeted inductance is produced. Diagnostic method is proposed, which couples voltage harmonic phases and the direction of H_(DC) bias field by means of the LT Spice simulation. An experimental verification of the proposed technique is successfully accomplished, along with the settlement of the further research.

关键词： harmonic component DC bias hysteresis curve inductance nonlinear inductance

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Stabilizing Transmission Intervals and Delays for Nonlinear Networked control Systems: The Large Delay Case

Stabilizing Transmission Intervals and Delays for Nonlinear ...

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IEEE Annual Conference on Decision and control

作者： Domagoj Tolic Sandra Hirche University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 10000 Zagreb Croatia Institute for Information-oriented Control Technische Universitat Munchen Arcisstrasse 21 D-80290 Munchen Germany

ISBN: (纸本)9781467360890

This paper proposes a methodology for computing Maximally Allowable Transfer Intervals (MATIs) that provably stabilize nonlinear Networked control Systems (NCSs) in the presence of disturbances and signal delays. Accordingly, given a desired level of system performance (in terms of L_p-gains), quantitative MATI vs. delay trade-offs are obtained. By combining impulsive delayed system modeling with Lyapunov-Razumikhin type of arguments, we are able to consider even the so-called large delays. Namely, the computed MATIs can be smaller than delays existent in NCSs. In addition, our stability results are provided for the class of Uniformly Globally Exponentially Stable (UGES) scheduling protocols. The well-known Round Robin (RR) and Transmit-Once-Discard (TOD) protocols are examples of UGES protocols. Apart from the inclusion of large delays, another salient feature of our methodology is the consideration of corrupted data. To that end, we propose the notion of L_p-stability with bias. Furthermore, the Zeno-free property of our methodology is demonstrated. Finally, a comparison with the state-of-the-art work is provided utilizing the benchmark problem of batch reactor.

关键词： Networked control systems System performance Benchmark testing delay corrupted data Systems modelling batch reactor Stabilising

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Event-triggered Scheduling for Stochastic Multi-loop Networked control Systems with Packet Dropouts

Event-triggered Scheduling for Stochastic Multi-loop Network...

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IEEE Annual Conference on Decision and control

作者： Mohammad H. Mamduhi Domagoj Tolic Adam Molin Sandra Hirche Institute for Information-oriented Control Technische Universitat Munchen Arcisstrasse 21 D-80290 Munchen Germany University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 10000 Zagreb Croatia

ISBN: (纸本)9781467360890

In this paper, we study event-triggered data scheduling for stochastic multi-loop control systems communicating over a shared network with communication uncertainties. We introduce a novel dynamic scheduling scheme which allocates the channel access according to an error-dependent policy. The proposed scheduler deterministically excludes sub-systems with lower error values from the medium access competition in favor of those with larger errors. Subsequently, the scheduler probabilistically allocates the communication resource to the eligible entities. We model the overall network-induced error as a homogeneous Markov chain and show its boundedness in expectation over a multi time-step horizon. In addition, analytical upper bound for the associated average cost is derived. Furthermore, we show that our proposed policy is robust against packet dropouts. Numerical results demonstrate a significant performance improvement in terms of error level in comparison with periodic and random scheduling policies.

关键词： Markov processes Upper bound Communication channels Probabilistic logic Covariance matrices Protocols

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Maximum Likelihood Estimator, FFT Estimator and Cramer-Rao Bounds of the Laser Doppler Frequency The effect of a particle trajectory through the measurement volume

Maximum Likelihood Estimator, FFT Estimator and Cramer-Rao B...

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IEEE International Instrumentation and Measurement Technology Conference

作者： Lu Zhang Janusz Kulon Yong Yan School of Computer and Control Engineering North China Electric Power University 2 Beinong Road Beijing 102206 China Faculty of Computing Engineering and Science University of South Wales Pontypridd CF37 1DL UK School of Engineering and Digital Arts University of Kent Canterbury Kent CT2 7NT UK

ISBN: (纸本)9781479961153

This paper addresses the problem of estimating the Doppler frequency in Laser Doppler Velocimetry (LDV) systems by taking into account the effect of the particle trajectory via the measurement volume. The dependency of the burst length on the Cramer-Rao lower bound (CRLB) and the Doppler frequency estimation is investigated by employing the 2D model of the Doppler Burst Signal with the Gaussian envelope. The Maximum Likelihood Estimator (MLE) equations are solved for estimates of the Doppler frequency for LDV systems operating in one particle scattering mode. The numerical examples show the performance of the MLE and FFT with various parameter configurations compared with the derived CRLB. The numerical results confirm the validity of the analysis in terms of the relative effect of the particle trajectory, relative measurement time, size of the volume and signal-to-noise ratio on the accuracy of the estimation.

关键词： Cramer-Rao bound Laser Doppler Velocimetry frequency estimation maximum likelihood estimation Fast Fourier Transform

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One implementation of extendable application for collecting EPG data from internet sources

One implementation of extendable application for collecting ...

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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Stefan Pejić Helena Peić Tukuljac Milan Knežević Ištvan Papp Univerzitet u Novom Sadu Novi Sad Vojvodina RS Control and Computing Department Faculty of Technical Sciences Novi Sad Serbia RT-RK Computer Based Systems Novi Sad Serbia

This paper presents one solution for a extendable application which is used to collect EPG (Electronic Program Guide) data from various internet sources. The aim of the software is to complement or replace incomplete EPG information received from DTV (Digital television) stream with Internet data. The acquired data is processed and forwarded to remote server which further stores it to a database.

关键词： Internet Servers Digital video broadcasting Digital TV Data mining XML Data acquisition

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Electric power distribution system visualization with graph partitioning

Electric power distribution system visualization with graph ...

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IEEE AFRICON 2013

作者： Kovačev, Nemanja Lendák, Imre Čapko, Darko Erdeljan, Aleksandar Computing and control department Faculty of technical sciences University of Novi Sad Novi Sad Serbia

ISBN: (纸本)9781467359405

This paper presents an electric power distribution system (EPDS) visualization algorithm which performs graph partitioning before generating the visual representations, i.e. one line diagrams. The proposed algorithm is different from similar algorithms as it performs graph partitioning to reduce the solution space. The partitioning step is necessary because modern EPDS can consist of thousands of distribution transformers, pole switches and line segments. After the partitioning step, in its second phase, the algorithm lays out the subgraphs and then combines the drawings into complete one-line diagrams. During the experiments, the partitioning and layout phases were performed with various combinations of the genetic and branch and bound algorithm. The algorithm was tested on partial, real life electric power distribution systems of up to 150 objects and it generated visually pleasing one-line diagrams. © 2013 IEEE.

关键词： Visualization

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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A derivative-free algorithm for finding least squares solutions of quasi-linear and linear systems

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Journal of computing and Information Technology 2013年第2期21卷 125-135页

作者： Hlupíc, Nikica Beroš, Ivo Basch, Danko Department of Applied Computing Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb 10000 Croatia Department of Applied Mathematics and Computer Science VERN' University of Applied Sciences Trg bana J. Jelačíca 3 Zagreb Croatia Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb 10000 Croatia

A novel derivative-free algorithm for solving quasilinear systems is presented. It resembles "classical" optimization approach but greatly simplifies computation, resulting in fast execution and numerical stability. Though the global convergence cannot be guaranteed, it turns out that the presented algorithm finds a solution as successfully as other commonly accepted methods. The algorithm is clearly developed and mathematically founded, and its properties are examined by comparisons with other methods.

关键词： Linear systems

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Autonomous marine robots assisting divers

Autonomous marine robots assisting divers

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14th International Conference on Computer Aided Systems Theory, EUROCAST 2013

作者： Miskovic, Nikola Vukic, Zoran Vasilijevic, Antonio Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 10000 Zagreb Croatia

ISBN: (纸本)9783642538612

Research related to diver safety, navigation and monitoring has been identified as crucial for advancing diving activities. These issues are usually dealt with by pairing up divers and adopting well defined rules for diving operations to reduce the chance of accidents. However, during more challenging dives (such as technical dives) these procedures may not be sufficient to ensure almost accident-free operations, for the divers must manoeuvre in complex 3D environments, carry cumbersome equipment, and focus attention on operational details. In this work it is stated that research and technological development in the area of cognitive robotics can significantly contribute to the effectiveness and safety of diving operations. The current research performed in LABUST is based on an autonomous surface platform for following divers and transmitting GPS signal to the underwater. Future envisioned applications include the development of a cognitive autonomous diving buddy consisting of both the surface platform and an underwater vehicle that will serve as diving "guide", "slave" and "observer". © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Accidents

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