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American control Conference

作者： Simone Baldi Elias B. Kosmatopoulos Andreas Pitsillides Marios Lestas Petros A. Ioannou Yiming Wan Delft Center of Systems and Control Netherlands Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Computer Science Department University of Cyprus (UCY) Nicosia Cyprus Department of Electrical Engineering Frederick University Nicosia Cyprus Department of Electrical Engineering University of Southern California Los Angeles USA

ISBN: (纸本)9781467386838

An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal control problem exploits an adaptive optimization algorithm aiming at adaptively minimizing a suitable approximation of the Hamilton-Jacobi-Bellman equation associated with the optimal control problem. Simulations results, obtained by using a fluid flow based model of the communication network and a common network topology, show improvement with respect to the Random Early Detection strategy. Besides, it is shown that the performance of the proposed decentralized solution is comparable with the performance obtained with a centralized strategy, which solves the optimal control problem via a central unit that maintains the flow states of the entire network.

关键词： Protocols Communication networks Optimal control Mathematical model Delays Optimization networks(communications) Optimal control rotation management adaptive optimization protocols Mathematical Model Telecommunications Tritolyl Phosphates tactical command post Network topology delay Residual Volume fluid flow

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Proposed Document Frequency technique for minimizing dataset in Web crawler

Proposed Document Frequency technique for minimizing dataset...

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International Conference on computer engineering and Systems

作者： Amany M. Sarhan Ghada M. Hamissa Heba E. Elbehiry Computer &Automatic Control Dept. Tanta University Egypt Electrical Engineering Dept. KFS University Egypt

The explosive growth of webpage number on the Web has brought up some problems in the search process. One of these problems is that the general purpose search engines often return too many irrelevant results when users are searching for specific information on a given topic. Another problem is the massive increase in the number of pages to be indexed by Web search systems. In this research, two steps for Web Crawling are used to decrease these difficulties. First step is the feature selection for the datasets used. A proposed algorithm of feature selection, which uses the Document Frequency technique for the term in the category, is presented. Second step is Web page classification. Two famous techniques of Web page classification are used: (i) Support Vector Machine and (ii) Naïve Bayes Classifier. It is concluded that the proposed algorithm, using Document Frequency technique, reduces the redundancy during feature selection and increases accuracy during Web page classification. Complete evaluation is performed, in JAVA, to indicate the effectiveness of our proposed algorithm.

关键词： Classification algorithms Web pages Support vector machines Training Standards Kernel Search problems

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Feature Selection algorithms based on HTML tags importance

Feature Selection algorithms based on HTML tags importance

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International Conference on computer engineering and Systems

作者： Amany M. Sarhan Ghada M. Hamissa Heba E. Elbehiry Computer & Automatic Control Dept. Tanta University Egypt Electrical Engineering Dept. KFS University Egypt

Traditionally in Web crawling, the required features are extracted from the whole contents of HTML pages. However, the position which a word is located inside the HTML tags indicates its importance in the web page. This research proposes two ideas concerning the Feature Selection stage in HTML web pages. The first idea reduces the features by simply extracting them from the important tags in an HTML page in order to achieve faster classification. The second idea gives weights for each of the important tags. Two algorithms are presented in this paper based on these ideas: i) Important HTML tags only algorithm, ii) Weighted Important HTML tags only algorithm. The selected features are classified using two famous classifiers in the literature: Support Vector Machine (SVM) and Naïve Bayes classifier (NBC). The accuracy of each algorithm is computed. Comparison between the accuracies of traditional feature selection method, which uses the whole contents of HTML page, and the proposed algorithms is performed. Complete evaluation is performed which indicates the effectiveness of using our technique. The experimental results show improved precision and recall with the proposed algorithms with respect to keyword-based search. The algorithms are implemented in JAVA and its extended packages.

关键词： Web pages HTML Classification algorithms Support vector machines Feature extraction Search engines Crawlers

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Attitude estimation algorithms using low cost IMU

International Journal of Control and Automation

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International Journal of control and Automation 2015年第11期8卷 113-126页

作者： Quoc, Dung Duong Sun, Jinwei Le, Van Nhu Dept. of Automatic test and control Harbin Institute of Technology Harbin China Research center for Space Optics Engineering Harbin Institute of Technology China Le Qui Don Technical University Cau Giay Ha Noi Viet Nam

Attitude estimation has a wide range of applications including aerial (UAVs for example), underwater (ROVs for instance), navigation systems, robotics, games, augmented reality system, industrial and so on. Extensive research over decades in this field resulted in a number of powerful estimators;complex like Kalman based algorithms as well as simple such as complementary filters & the kinds. For applications where computational simplicity is of prime concern, complementary filters have proven efficiency. This paper presents a comparative study of computationally simple algorithms naming Explicit Complementary Filter (ECF) and Gradient Descent based Complementary Filter (GDCF) along with computationally demanding extended Kalman filter-a de-facto standard for attitude estimation so far, regarding attitude estimation based on MEMS IMU. An alternative would be the variants of complementary filter;sufficiently efficient and simple scheme to avoid computational *** of these estimators is evaluated for Euler angle estimation using both simulated data from Matlab and experimental data from MPU6050 IMU. The assessment is based on the root mean square error computation for these algorithms. Moreover, the algorithms adjustable parameters were exploited for a range of values in the hunt for perfection. © 2015 SERSC.

关键词： Data fusion

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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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Robust decentralized control of large-scale systems via H∞theory and using descriptor system representation

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International Journal of Systems Science 2016年第12-13期34卷 705-715页

作者： Labibi, B. Lohmann, B. Sedigh, A. Khaki Maralani, P. Jabedar Control Department Electrical Engineering Faculty K. N. Toosi University of Technology Seyyed Khandan Bridge Shariati Street 16314 Iran Dept. of System Dynamics and Control University of Bremen Otto-Hahn-Allee/NW1 28359 Bremen Germany Electrical and Computer Eng. Dept. Faculty of Engineering University of Tehran North Karegar Street Building No. 2 Tehran Iran

In this paper, a method for design of linear decentralized robust controllers for a class of uncertain large-scale systems in general form is presented. For a given large-scale system, an equivalent descriptor system in input-output decentralized form is defined. Using this representation, closed-loop diagonal dominance sufficient conditions are derived. It is shown that by appropriately minimizing the weighted sensitivity function of each isolated subsystem, these conditions are achieved. Solving the appropriately defined H∞local problem for each isolated uncertain subsystem, the interactions between the subsystems are reduced, and the overall stability and robust performance are achieved in spite of uncertainties. The designs are illustrated by a practical example.

关键词： control system synthesis

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Online policy iterations for optimal control of input-saturated systems

Online policy iterations for optimal control of input-satura...

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American control Conference

作者： Simone Baldi Giorgio Valmorbida Antonis Papachristodoulou Elias B. Kosmatopoulos Delft Center for Systems and Control Delft University of Technology 2628CD The Netherlands Department of Engineering Science Control Group University of Oxford Parks Road OX1 3PJ U.K. Dept. of Electrical and Computer Engineering Democritus University of Thrace Xanthi 67100 Greece

ISBN: (纸本)9781467386838

This work proposes an online policy iteration procedure for the synthesis of sub-optimal control laws for uncertain Linear Time Invariant (LTI) Asymptotically Null-controllable with Bounded Inputs (ANCBI) systems. The proposed policy iteration method relies on: a policy evaluation step with a piecewise quadratic Lyapunov function in both the state and the deadzone functions of the input signals;a policy improvement step which guarantees at the same time close to optimality (exploitation) and persistence of excitation (exploration). The proposed approach guarantees convergence of the trajectory to a neighborhood around the origin. Besides, the trajectories can be made arbitrarily close to the optimal one provided that the rate at which the the value function and the control policy are updated is fast enough. The solution to the inequalities required to hold at each policy evaluation step can be efficiently implemented with semidefinite programming (SDP) solvers. A numerical example illustrates the results.

关键词： Optimal control Linear systems Convergence Asymptotic stability Lyapunov methods Estimation Trajectory trajectory Optimal control Lyapunov methods asymptotic stability region Linear system Converge iterative methods control strategy Policies

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An adaptive dynamic inversion-extremum seeking control approach for constrained robotic motion tasks

An adaptive dynamic inversion-extremum seeking control appro...

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European control Conference

作者： Vasiliki Koropouli Azwirman Gusrialdi Dongheui Lee Automatic Control Engineering Technische Universitat Munchen Dept. of Electrical Engineering and Computer Science University of Central Florida

ISBN: (纸本)9781467371605

In this paper, an adaptive control approach is proposed for performance of constrained robot end-effector movements in presence of uncertainty. In real-world scenarios, complex physical phenomena occuring at the place of interaction may introduce nonlinearities in the system dynamics, which have to be taken into account for proper system control. We currently propose an Extremum Seeking (ES) Model Reference Adaptive control (MRAC) approach for state tracking of multiple-input multiple-output systems which enclose nonlinearities in their dynamics and involve parametric uncertainty by employing Adaptive Dynamic Inversion (ADI). According to ADI, system nonlinearities are assumed known and are taken into account in the design of the system control law. The proposed scheme is based on MRAC and ADI while the unknown controller parameters are adapted by ES control. The system is shown to achieve global and asymptotic reference state tracking under the proposed control law by performing Lyapunov and averaging analysis. The approach is evaluated in simulation and in an experimental robot task.

关键词： MIMO Adaptation models Robots Tracking Dynamics Adaptive control Nonlinear dynamical systems

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controller synthesis for autonomous systems interacting with human operators 15

Controller synthesis for autonomous systems interacting with...

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6th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2015

作者： Feng, Lu Wiltsche, Clemens Humphrey, Laura Topcu, Ufuk Dept. of Computer and Information Science University of Pennsylvania United States Dept. of Computer Science University of Oxford United Kingdom Control Science Center of Excellence AFRL United Kingdom Dept. of Electrical and Systems Engineering University of Pennsylvania United States

ISBN: (纸本)9781450334556

We propose an approach to synthesize control protocols for autonomous systems that account for uncertainties and imperfections in interactions with human operators. As an illustrative example, we consider a scenario involving road network surveillance by an unmanned aerial vehicle (UAV) that is controlled remotely by a human operator but also has a certain degree of autonomy. Depending on the type (i.e., probabilistic and/or nondeterministic) of knowledge about the uncertainties and imperfections in the operator- Autonomy interactions, we use abstractions based on Markov- decision processes and augment these models to stochastic two-player games. Our approach enables the synthesis of operator-dependent optimal mission plans for the UAV, highlighting the effects of operator characteristics (e.g., workload. proficiency, and fatigue) 011 UAV mission performance;it can also provide informative feedback (e.g., Pareto curves showing the trade-offs between multiple mission objectives), potentially assisting the operator in decision-making.

关键词： Markov processes

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Isolated/non-isolated quad-inverter configuration for multilevel symmetrical/asymmetrical dual six-phase star-winding converter

Isolated/non-isolated quad-inverter configuration for multil...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Sanjeevikumar Padmanaban Michael R. Hontz Raghav Khanna Patrick William Wheeler Frede Blaabjerg Joseph Olorunfemi Ojo Power Electronics Division Ohm Technologies Chennai India Electrical Engineering & Computer Science Dept. University of Toledo Toledo Ohio USA Power Electronics Machines and Control Group (PEMC) Nottingham University UK Center for Reliable Power Electronics (CORPE) Aalborg University Denmark University of KwaZulu-Natal Durban South Africa Dept. of Electrical & Computer Engg. Tennessee Technological University USA

This article presents the developments of a novel isolated/non-isolated quad inverter configuration for multilevel dual six-phase (twelve-phase) star-winding converter. The modular circuit consists of four standard voltage source inverters (VSIs). Each VSI is incorporated with one bi-directional switch (MOSFET/IGBT) per phase and links with the neutral line through two capacitors which allows symmetrical and asymmetrical operations. A modified single carrier five-level modulation (MSCFM) algorithm is developed and modulates each 2-level VSI as a 5-level output multilevel inverter. The entire AC converter is numerically modeled using Matlab/PLECS simulation software and the predicted behavior of the system is analyzed and presented. Good agreement is obtained between these results and the theoretical analysis. Suitable applications for the converter include (low-voltage/high-current) medium power systems, electrical vehicles, AC tractions, and `More-Electric Aircraft' propulsion systems.

关键词： Inverters Windings Standards Switches Modulation Reliability Capacitors

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