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IEEE Signal Processing Algorithms, Architectures, Arrangements, and Applications Conference

作者： Agnieszka Stankiewicz Tomasz Marciniak Adam Dabrowski Marcin Stopa Elzbieta Marciniak Andrzej Michalski Division of Signal Processing and Electronic Systems Chair of Control and Systems Engineering Faculty of Computing Poznan University of Technology Clinical Eye Unit and Pediatric Ophthalmology Service Heliodor Swiecicki University Hospital Poznan University of Medical Sciences

ISBN: (纸本)9781509026616

Optical coherence tomography (OCT) is the current very fast and accurate modality for noninvasive assessment of 3D retinal structure. Due to large amount of data acquired with this technique the resolution of 3D scans is limited. In this paper we present a new method for improving resolution of 3D macula scans while maintaining short acquisition time and robustness with respect to motion artifacts. Our approach is based on multi-frame super-resolution method applied to several 3D standard resolution OCT scans. Presented experiments where performed on volumetric data acquired from adult patients with the use of Avanti RTvue device. Each OCT cross-section (B-scan) was subjected to image denoising and retinal layers segmentation. The generated 3D super-resolution scans have significantly improved quality of the vertical cross-sections.

关键词： OCT Super-resolution Multi-frame Retina image segmentation

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Matrix flat splicing systems 11th

Matrix flat splicing systems

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Ceterchi, Rodica Pan, Linqiang Song, Bosheng Subramanian, K.G. Faculty of Mathematics and Computer Science University of Bucharest 14 Academiei Street Bucharest010014 Romania School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China Department of Mathematics Madras Christian College Chennai600059 India

ISBN: (纸本)9789811036101

In dealing with the problem of modelling DNA recombination, the operation of splicing on linear and circular strings of symbols was introduced. Inspired by splicing on circular strings, the operation of flat splicing on a pair of strings (u, v) was considered. This operation involves "cutting" u at a specified position and "inserting" v into it, with v having a pre-specified prefix as well as suffix defined by a flat splicing rule. In this work, we consider a well-known technique in formal language theory, known as "matrix of rules", and introduce matrix of flat splicing rules and thus define matrix flat splicing system (MFSS). Some results on the language generative power of MFSS are provided. An application of MFSS in the generation of chain code pictures is also pointed out. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Formal languages

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Development of an UAV prototype for visual inspection of aerial electrical lines

Development of an UAV prototype for visual inspection of aer...

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Argentine Conference on Embedded Systems (CASE)

作者： Walter Benitez Yessica Bogado Ariel Guerrero Mario Arzamendia Technology and Advanced Innovation (CICTIA) “Our Lady of the Assumption” Catholic University (UCA) - Hernandarias Paraguay Innovation Center in Automation and Control (CIAC) Technology Park of Itaipu (PTI) - Hernandarias Paraguay Faculty of Engineering National University of Asuncion (FIUNA) - Asuncion Paraguay

ISBN: (纸本)9781509038053

The development of an attitude and altitude control system of an unmanned aerial vehicle for visual inspection of aerial electrical lines is presented. The system was implemented using quaternions algebra and the altimeter equation for the orientation estimation with the purpose of controlling the quadcopter. The proposed system was simulated in Matlab using a Newton-Euler model and compared with the performance on a real prototype operation, obtaining similar results in both cases.

关键词： Quaternions Mathematical model Inspection Unmanned aerial vehicles Visualization control systems

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Learning of FCMs with Causal Links Represented via Fuzzy Triangular Numbers

Learning of FCMs with Causal Links Represented via Fuzzy Tri...

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IEEE International Conference on Fuzzy Systems

作者： M. Furkan Dodurka Atakan Sahin Engin Yesil Leon Urbas Istanbul Technical University Control and Automation Engineering Department Chair of Distributed Control Systems Engineering Institute of Automation Dresden University of Technology

ISBN: (纸本)9781467374293

In this paper, learning of the FCMs represented using triangular fuzzy numbers (TFNs) in their weight matrices is studied. For this aim a population based novel learning approach is proposed. In the proposed algorithm, BB-BC optimization method is preferred because of its fast convergence capability. Moreover, this proposed approach involves concept by concept (CbC) learning to increase the accuracy of the learning of FCMs. Two different tests are realized as case studies for investigating the performance of the learning approach. For the first test, the learning capability of the algorithm is examined and for the second test the performance of generalization capability is investigated. The tests, which are presented via tables and figures, show that learning approach is successful for learning of FCMs with TFNs. Furthermore, from the case study it can be seen that the uncertain information can be represented and interpreted by the proposed FCM design methodology in a more efficient way.

关键词： Fuzzy Cognitive Maps Triangular Fuzzy Numbers Causal Links Reasoning Weight Matrix. Learning Learning Fuzzy cognitive maps Reasoning fuzzy number Fuzzy

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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A simple DDS algorithm for TDS: An example 29

A simple DDS algorithm for TDS: An example

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29th European Conference on Modelling and Simulation, ECMS 2015

作者： Pekař, Libor Tomas Bata University in Zlín Faculty of Applied Informatic Department of Automation and Control Engineering Nad Stráněmi 4511 Zlín76005 Czech Republic

ISBN: (纸本)9780993244001

This paper is aimed at the presentation and simulation verification of a novel simple and fast delay dependent stability (DDS) testing algorithm for linear time-invariant time delay systems (LTI TDS). The algorithm can be used for systems with multiple delays and/or those with many controller parameters. Value ranges of delays and tunable parameters decide about the (exponential) stability of LTI TDS and the goal is to determine such ranges that might not be convex. Our numerical gridding iterative DDS algorithm is based on the finite dimensional approximation of the characteristic quasipolynomial by means of the Taylor series expansion or a Padé-like approach followed by the Regula-Falsi result enhancement. Stability regions are sought through the determination of crossing delays (or parameters) which cause the system stability switching. Numerical simulation experiments performed in MATLAB® environment prove a sufficient accuracy and the practical usability of the proposed DDS algorithm. © ECMS Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors).

关键词： MATLAB

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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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Intelligent control of uncertain switched nonlinear Plants: NFG optimum control of switched fuzzy time-delay systems revisited

Intelligent control of uncertain switched nonlinear Plants: ...

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International IEEE Conference on Intelligent Systems, IS

作者： Georgi M. Dimirovski Jinming Luo Huakua Li Jun Zhao Faculty of Electrical Eng. and Information Technologies St Cyril and St Methodius University R. Macedonia Faculty of Engineering Dogus University R. Turkey State Key Laboratory of Synthetic Automation Northeastern University of Shenyang Shenyang P.R. China Control Theory Committee of the CAA Northeastern University Shenyang Shenyang P.R. China

A solution of intelligent, optimum guaranteed-cost and robust, control for a class of uncertain switched nonlinear systems via switched fuzzy models possessing time delays and uncertainties has been developed. Following the multiple Lyapunov functions approach, a non-fragile state feedback controller and a switching law are designed such that the closed-loop system is asymptotically stable and the guaranteed cost function possesses an upper bound. Then an optimization problem of the non-fragile guaranteed cost control is solved. The considered optimum non-fragile guaranteed-cost control problem asymptotic stability of subsystems is not assumed, nonetheless the overall system is guaranteed asymptotically stable. Numerical and simulation results for an illustrative example are presented to demonstrate the feasibility and effectiveness of the proposed intelligent control design.

关键词： Switches Fuzzy systems Uncertainty Delay effects Symmetric matrices Switched systems

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Mathematic model of heat transport in materials during cutting process 26

Mathematic model of heat transport in materials during cutti...

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26th DAAAM International Symposium on Intelligent Manufacturing and automation, DAAAM 2015

作者： Janacova, Dagmar Mokrejs, Pavel Vasek, Vladimir Drga, Rudolf Liska, Ondrej Krenek, Jiri Department of Automatic and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Czech Republic Department of Polymer Engineering Faculty of Technology Tomas Bata University in Zlin Nám. T. G. Masaryka 5555 Zlín760 01 Czech Republic Department of Automation Control and Human Machine Interaction Faculty of Mechanical Engineering Technical University of Košice Letná 9 Košice042 00 Slovakia

ISBN: (纸本)9783902734075

Printed circuit boards (PCBs) that represent a significant part of electronic waste are potential sources of material and energy. In the paper we focused on study of a cutting as an alternative method of conductive ways separating from plastic board as one of stages of the printed circuit board recycling procedure. High velocity of cutting belt is connected with enormous heat production. Due to the generation of high temperatures may lead to caking of separated components of metal and plastic materials. For this reason we formulated mathematic model of the cutting process and on the base we can determine of temperature fields in PCB materials during cutting. Of courses of them we can calculate the heat intensity and consequently the critical velocity of cut ting belt without damage of PCB materials.

关键词： Printed circuit boards

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Picture array generation using flat splicing operation

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3568-3577页

作者： Pan, Linqiang Nagar, Atulya K. Subramanian, K.G. Song, Bosheng School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in a number of theoretical properties. A different kind of splicing on two words, referred to as flat splicing, has been considered recently. This operation is extended to flat splicing on picture arrays, thus defining a new model of generation of digitized pictures, which is called as array flat splicing system (AFS). Results on the generative power of AFS in comparison with certain well-known picture array defining models and certain non-closure results are obtained. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Nanoscience

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