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Coupling analysis and loop pairing method via an information-theoretic approach

ICIC Express Letters 2016年第6期10卷 1407-1413页

作者： Zhang, Jianhua Kuai, Yamin Lin, Mingming Zhang, Ting Hou, Guolian State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University No. 2 Beinong Road Changping District Beijing102206 China School of Control and Computer Engineering North China Electric Power University No. 2 Beinong Road Changping District Beijing102206 China

It is essential to investigate coupling and loop pairing to determine control system configurations. This paper presents a new control-loop configuration criterion for multi-input multi-output (MIMO) processes based on relevant information-theoretic knowledge. Firstly, we propose a new variable pairing rule based on mutual information rate (MIR) among input and output variables. The information coupling strength is formulated in terms of mutual information rates. Then, the straightforward MIR calculation using frequency formula in MIMO linear time invariant (LTI) systems is introduced briefly under information-theoretic framework. Finally, two numerical examples are provided to demonstrate the effectiveness of the above coupling measure and the variable pairing rules. In addition, we analyze the simulation MIR results, which are consistent with RNGA method. © 2016 ISSN.

关键词： MIMO systems

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A novel method to improve low voltage ride-through capability of DFIG

A novel method to improve low voltage ride-through capabilit...

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International Conference on Renewable Power Generation, RPG 2015

作者： Wang, Y. Guo, P. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9781785610400

In order to prevent wind turbines departing from the grid when the grid fault occurs, the Crowbar circuit of the doubly-fed induction generator (DFIG) is often used to improve low voltage ride-through (LVRT) capability. Based on the analysis of the traditional Crowbar protection circuit, a modified Crowbar protection circuit with resistance in series with the capacitor was proposed. The double-fed induction wind power generator (DFIG) with the modified Crowbar protection circuit was simulated on MATLAB/Simulink platform. Compared with the traditional Crowbar protection circuit with the resistance, the modified Crowbar protection circuit not only restrains the rotor over current, but also shortens the transition process of the rotor over current. The simulation results show that the modified Crowbar protection circuit is reasonable and improves the low voltage ride-through capacity of DFIG effectively.

关键词： Wind turbines

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A Generalized Piecewise Quadratic Lyapunov Function Approach to Estimating the Domain of Attraction of a Saturated system

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IFAC-PapersOnLine 2015年第11 11期48卷 120-125页

作者： Li, Yuanlong Lin, Zongli Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia CharlottesvilleVA22904-4743 United States

This paper revisits the problem of estimating the domain of attraction of a saturated system with an algebraic loop. A piecewise quadratic Lyapunov function of an augmented state vector composing of the system state and the saturated input has been proposed for use in estimating the domain of attraction for a saturated system. Considering the relationship between the system states and the saturation function, we propose in this paper a generalized piecewise quadratic Lyapunov function, which results from adding a term that characterizes the regional sector condition of the saturated input to the piecewise quadratic Lypunov function. The matrix associated with the generalized piecewise quadratic Lyapunov function is not required to be positive definite, and thus a set of less conservative stability conditions are established, from which a larger estimate of the domain of attraction can be obtained. Simulation results indicate that the effectiveness and superiority of the proposed method. © 2015

关键词： Lyapunov functions Domain of attraction Input saturation Piece wise quadratic Lyapunov function Positive definite Saturated systems Saturation function Sector condition Stability condition

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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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Design and Implementation of Natural Language Processing with Syntax and Semantic Analysis for Extract Traffic Conditions from Social Media Data

Design and Implementation of Natural Language Processing wit...

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IEEE International Conference on system Engineering and Technology

作者： Mochamad Vicky Ghani Aziz Ary Setijadi Prihatmanto Diotra Henriyan Rifki Wijaya Control and Computer System Laboratory School of Electrical Engineering and Informatics Institut Teknologi Bandung

ISBN: (纸本)9781467367141

Traffic congestion is still a crucial issue because it has a huge impact from the waste of time, the fuel to air pollution. Search information on traffic conditions have been widely available such as through Twitter and the website of CCTV, but the rapid development of online information services resulted in the lack of time to read the complete information. By utilizing the Twitter data, then created a summary regarding the traffic, the summary can improve time efficiency and effectiveness in obtaining information about traffic conditions. However, the structure of the language of Twitter tweets unstructured and raw cause difficult to process information computer, to solve these problems then summarize it using Natural Language Processing approach the syntactic and semantic analysis to improve the structure of words and sentence parsing so that it can classify traffic conditions tweet of the sentence.

关键词： Natural language processing Syntax and semantic analysis Extract traffic condition Natural Language Processing syntax Social Media Traffic TWITTER Language Processing CLOSED CIRCUIT TELEVISION traffic congestion time efficiency Semantics

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A novel control strategy based on multi-agent for wind farm power dispatching

A novel control strategy based on multi-agent for wind farm ...

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International Conference on Renewable Power Generation, RPG 2015

作者： Xiao, Yunqi Zhang, Xiaohang Chen, Minna State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University China

ISBN: (纸本)9781785610400

Nowadays, active power reference of wind farm from power grid dispatch center should be allocated to wind turbines. In traditional way, centralized control is commonly adopted for active power allocation, in which, total power reference is dispatched to every wind turbine by a central controller. However, it has several disadvantages, such as complex computation and low flexibility, especially for wind farms with large number of wind turbines. Therefore, a Multi-Agent based collaboration control strategy for active power dispatching in wind farms is proposed to improve operation performance. Firstly, a Multi-Agent based control structure for wind farm is designed, which includes wind turbine agent, group manager agent and central manager agent. Secondly, coordination control strategy among different agents is designed in detail. Finally, a Multi-Agent control model of wind farm is established based on Java/jade platform, and simulation results verify the efficiency of strategy proposed.

关键词： Wind farm

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Author Correction: Enhancing untargeted metabolomics using metadata-based source annotation

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Nature biotechnology 2023年第11期41卷 1656页

作者： Julia M Gauglitz Kiana A West Wout Bittremieux Candace L Williams Kelly C Weldon Morgan Panitchpakdi Francesca Di Ottavio Christine M Aceves Elizabeth Brown Nicole C Sikora Alan K Jarmusch Cameron Martino Anupriya Tripathi Michael J Meehan Kathleen Dorrestein Justin P Shaffer Roxana Coras Fernando Vargas Lindsay DeRight Goldasich Tara Schwartz MacKenzie Bryant Gregory Humphrey Abigail J Johnson Katharina Spengler Pedro Belda-Ferre Edgar Diaz Daniel McDonald Qiyun Zhu Emmanuel O Elijah Mingxun Wang Clarisse Marotz Kate E Sprecher Daniela Vargas-Robles Dana Withrow Gail Ackermann Lourdes Herrera Barry J Bradford Lucas Maciel Mauriz Marques Juliano Geraldo Amaral Rodrigo Moreira Silva Flavio Protasio Veras Thiago Mattar Cunha Rene Donizeti Ribeiro Oliveira Paulo Louzada-Junior Robert H Mills Paulina K Piotrowski Stephanie L Servetas Sandra M Da Silva Christina M Jones Nancy J Lin Katrice A Lippa Scott A Jackson Rima Kaddurah Daouk Douglas Galasko Parambir S Dulai Tatyana I Kalashnikova Curt Wittenberg Robert Terkeltaub Megan M Doty Jae H Kim Kyung E Rhee Julia Beauchamp-Walters Kenneth P Wright Maria Gloria Dominguez-Bello Mark Manary Michelli F Oliveira Brigid S Boland Norberto Peporine Lopes Monica Guma Austin D Swafford Rachel J Dutton Rob Knight Pieter C Dorrestein Collaborative Mass Spectrometry Innovation Center University of California San Diego La Jolla CA USA. Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA. Beckman Center for Conservation Research San Diego Zoo Wildlife Alliance Escondido CA USA. Center for Microbiome Innovation Joan and Irwin Jacobs School of Engineering University of California San Diego La Jolla CA USA. Division of Biological Sciences University of California San Diego La Jolla CA USA. Department of Pediatrics School of Medicine University of California San Diego La Jolla CA USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Division of Rheumatology Allergy & Immunology Department of Medicine University of California San Diego La Jolla CA USA. Division of Epidemiology and Community Health School of Public Health University of Minnesota Minneapolis MN USA. Department of Integrative Physiology University of Colorado Boulder Boulder CO USA. Department of Population Health Sciences University of Wisconsin-Madison Madison WI USA. Servicio Autónomo Centro Amazónico de Investigación y Control de Enfermedades Tropicales Simón Bolívar Puerto Ayacucho Amazonas Venezuela. Department of Pediatrics Billings Clinic Billings MT USA. Department of Animal Science Michigan State University East Lansing MI USA. Department of Pharmacology Ribeirão Preto Medicinal School Center of Research in Inflammatory Diseases University of São Paulo Ribeirão Preto Sao Paolo Brazil. Multidisciplinary Health Institute Federal University of Bahia Vitória da Conquista Bahia Brazil. NPPNS Department of Biomolecular Sciences School of Pharmaceutical Sciences of Ribeirão Preto University of São Paulo Ribeirão Preto Sao Paolo Brazil. Department of Internal Medicine Ribeirão Preto Medical School Center of Research in Inflammatory Diseases University of São Paulo Ribeirão Preto Sao Paolo Brazil. Department

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A random early detection based active queue management algorithm in power optical communication network

A random early detection based active queue management algor...

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作者： Liu, Zhao Tang, Liangrui Yan, Jiangyu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Changping District Beijing China School of Control and Computer Engineering North China Electric Power University Changping District Beijing China

ISBN: (纸本)9781138028302

According to the different QoS requirements of services in power communication network, a random early detection based active queue management algorithm combined with the differentiated service model is proposed in this paper. The congested queue can take advantage of other idle queues to ensure the QoS requirement of the high priority queue. The simulation shows that the algorithm presented in this paper has better performance in reducing the overall packet loss rate and enhancing the utilization ratio of buffer. © 2015 Taylor & Francis Group, London.

关键词： Quality of service

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A generalized piecewise quadratic lyapunov function approach to estimating the domain of attraction of a saturated system

A generalized piecewise quadratic lyapunov function approach...

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1st IFAC Conference on Modelling, Identification and control of Nonlinear systems, MICNON 2015

关键词： Lyapunov functions

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A layered interconnected graph model based algorithm for traffic grooming in optical transport network

A layered interconnected graph model based algorithm for tra...

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作者： Dong, Xijie Tang, Liangrui Yan, Jiangyu A State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Changping District Beijing China B School of control and computer engineering North China Electric Power University Changping District Beijing China

ISBN: (纸本)9781138028302

In order to solve the problem of low wavelength resource utilization caused by the huge gap between the capacity need by the service and the single wavelength capacity in OTN, a Layered Interconnected Graph Model (LIGM) based algorithm for Traffic grooming is presented. The LIGM is based on the optical network physical topology, and the costs of every link represent the optical network resources. The initial solution set is calculated with the grooming path optimization selection strategy and the optimal grooming route is chosen from the set with the O/E/O number of each path. By adapting the load balancing mechanism, the algorithm can perfectly solve the problem of traffic grooming in optical networks. The simulation shows that, compared with other traffic grooming algorithms, the algorithm LIGA effectively reduces the blocking probability and makes full use of the optical network resource at the same time. © 2015 Taylor & Francis Group, London.

关键词： Fiber optic networks

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