检索结果-内蒙古大学图书馆

AIFORCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. an Italian multicentre study

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Soda, Paolo D’Amico, Natascha Claudia Tessadori, Jacopo Valbusa, Giovanni Guarrasi, Valerio Bortolotto, Chandra Akbar, Muhammad Usman Sicilia, Rosa Cordelli, Ermanno Fazzini, Deborah Cellina, Michaela Oliva, Giancarlo Callea, Giovanni Panella, Silvia Cariati, Maurizio Cozzi, Diletta Miele, Vittorio Stellato, Elvira Carrafiello, Gian Paolo Castorani, Giulia Simeone, Annalisa Preda, Lorenzo Iannello, Giulio Bue, Alessio Del Tedoldi, Fabio Alì, Marco Sona, Diego Papa, Sergio Unit of Computer Systems and Bioinformatics Department of Engineering University Campus Bio-Medico of Rome Via Alvaro del Portillo 21 Rome00128 Italy Department of Diagnostic Imaging and Stereotactic Radiosurgey Centro Diagnostico Italiano S.p.A. Via S. Saint Bon 20 Milan20147 Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Via Morego 30 Genoa16163 Italy Bracco Imaging S.p.A. Via Caduti di Marcinelle 13 Milan20134 Italy Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Radiology Institute Fondazione IRCCS Policlinico San Matteo Viale Golgi 19 Pavia27100 Italy Department of Naval Electrical Electronic and Telecommunications Engineering - University of Genova Via All’Opera Pia 11 A Genoa16145 Italy Radiology Department ASST Fatebenefratelli Sacco Piazza Principessa Clotilde 3 Milan20121 Italy Diagnostic and interventional radiology unit ASST Santi Paolo e Carlo - San Paolo Hospital Via Antonio di Rudinì 8 Milan20142 Italy Department of Advanced Diagnostic Technologies - Therapeutic Diagnostic and Radiology Units ASST Santi Paolo e Carlo - San Paolo Hospital Via Antonio di Rudinì 8 Milan20142 Italy Department of Emergency Radiology Careggi University Hospital Largo Piero Palagi 1 Florence50139 Italy Operative Unit of Radiology Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan Via della Commenda 10 Milan20122 Italy Department of Health Sciences Univeristy of Milan Via Festa del Perdono 7 Milan20122 Italy Diagnostic Imaging Postgraduate Medical School University of Foggia Via Antonio Gramsci 89 Foggia71122 Italy Department of Diagnostic Imaging IRCCS Ospedale Casa Sollievo della Sofferenza Viale Cappuccini 1 San Giovanni Rotondo71013 Italy Radiology Unit Department of Clinical Surgical Diagnostic and Pediatric Sciences University of Pavia Corso Str. Nuova 65 Pavia27100 Italy Neuroinformatics Laboratory Fondazione Bru

Recent epidemiological data report that worldwide more than 53 million people have been infected by SARS-CoV-2, resulting in 1.3 million deaths. The disease has been spreading very rapidly and few months after the identification of the first infected, shortage of hospital resources quickly became a problem. In this work we investigate whether chest X-ray (CXR) can be used as a possible tool for the early identification of patients at risk of severe outcome, like intensive care or death. CXR is a radiological technique that compared to computed tomography (CT) it is simpler, faster, more widespread and it induces lower radiation dose. We present a dataset including data collected from 820 patients by six Italian hospitals in spring 2020 during the first COVID-19 emergency. The dataset includes CXR images, several clinical attributes and clinical outcomes. We investigate the potential of artificial intelligence to predict the prognosis of such patients, distinguishing between severe and mild cases, thus offering a baseline reference for other researchers and practitioners. To this goal, we present three approaches that use features extracted from CXR images, either handcrafted or automatically by convolutional neuronal networks, which are then integrated with the clinical data. Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources. © 2020, CC BY-NC-ND.

关键词： Deep learning

Information-theoretic active contour model for microscopy image segmentation using texture 1

学校读者我要写书评

暂无评论

13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2016

作者： Biga, Veronica Coca, Daniel Faculty of Biology Medicine and Health The University of Manchester Oxford Rd ManchesterM13 9PL United Kingdom Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

ISBN: (数字)9783319678344

ISBN: (纸本)9783319678337

High throughput technologies have increased the need for automated image analysis in a wide variety of microscopy techniques. Geometric active contour models provide a solution to automated image segmentation by incorporating statistical information in the detection of object boundaries. A statistical active contour may be defined by taking into account the optimisation of an information-theoretic measure between object and background. We focus on a product-type measure of divergence known as Cauchy-Schwartz distance which has numerical advantages over ratio-type measures. By using accurate shape derivation techniques, we define a new geometric active contour model for image segmentation combining Cauchy-Schwartz distance and Gabor energy texture filters. We demonstrate the versatility of this approach on images from the Brodatz dataset and phase-contrast microscopy images of cells. © Springer International Publishing AG 2017.

关键词： Image segmentation

Robust nonovershooting tracking control for linear multivariable systems

学校读者我要写书评

暂无评论

Robust nonovershooting tracking control for linear multivari...

Annual Conference of Industrial Electronics Society

作者： Nithin Xavier Bijnan Bandyopadhyay Robert Schmid Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India Department of Electrical and Electronic Engineering University of Melbourne VIC Australia

This paper presents a multivariable state feedback tracking control with integral sliding mode which can achieve the output tracking of a reference step signal without any overshoot by rejecting the disturbances. The control designed is able to completely reject the matched-bounded disturbances by using the integral sliding mode technique. The multivariable feedback controller is capable of achieving arbitrarily small rise time without any overshoot for square multivariable system under some mild assumptions. The proposed control is verified using a numerical example of quadruple-tank setup.

关键词：

Distributed Least Squares Solver for Network Linear Equations

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Yang, Tao George, Jemin Qin, Jiahu Yi, Xinlei Wu, Junfeng State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China U.S. Army Research Laboratory AdelphiMD20783 United States Department of Automation University of Science and Technology of China Hefei230027 China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden College of Control Science and Engineering Zhejiang University Hangzhou310027 China

In this paper, we study the problem of finding the least square solutions of over-determined linear algebraic equations over networks in a distributed manner. Each node has access to one of the linear equations and holds a dynamic state. We first propose a distributed least square solver over connected undirected interaction graphs and establish a necessary and sufficient on the step-size under which the algorithm exponentially converges to the least square solution. Next, we develop a distributed least square solver over strongly connected directed graphs and show that the proposed algorithm exponentially converges to the least square solution provided the step-size is sufficiently small. Moreover, we develop a finite-time least square solver by equipping the proposed algorithms with a finite-time decentralized computation mechanism. The theoretical findings are validated and illustrated by numerical simulation examples. Copyright © 2018, The Authors. All rights reserved.

关键词： Linear equations

Final-state constrained optimal control via a projection operator approach

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Notarnicola, Ivano Bayer, Florian A. Notarstefano, Giuseppe Allgöwer, Frank Department of Engineering Università del Salento Lecce Italy Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70550 Germany

In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's method for Trajectory Optimization (PRONTO), which was proposed by Hauser for unconstrained optimal control problems. While in the standard method final-state constraints can be only approximately handled by means of a terminal penalty, in this work we propose a methodology to meet the constraints exactly. Moreover, our method guarantees recursive feasibility of the final-state constraint. This is an appealing property especially in realtime applications in which one would like to be able to stop the computation even if the desired tolerance has not been reached, but still satisfy the constraints. Following the same conceptual idea of PRONTO, the proposed strategy is based on two main steps which (differently from the standard scheme) preserve the feasibility of the final-state constraints: (i) solve a quadratic approximation of the nonlinear problem to find a descent direction, and (ii) get a (feasible) trajectory by means of a feedback law (which turns out to be a nonlinear projection operator). To find the (feasible) descent direction we take advantage of final-state constrained Linear Quadratic optimal control methods, while the second step is performed by suitably designing a constrained version of the trajectory tracking projection operator. The effectiveness of the proposed strategy is tested on the optimal state transfer of an inverted pendulum. Copyright © 2017, The Authors. All rights reserved.

关键词： Numerical methods

Laman graphs are generically bearing rigid in arbitrary dimensions

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Zhao, Shiyu Sun, Zhiyong Zelazo, Daniel Trinh, Minh-Hoang Ahn, Hyo-Sung Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom Research School of Engineering Australian National University Australia Faculty of Aerospace Engineering Technion-Israel Institute of Technology Israel Distributed Control & Autonomous Systems Lab Gwangju Institute of Science and Technology

This paper addresses the problem of constructing bearing rigid networks in arbitrary dimensions. We first show that the bearing rigidity of a network is a generic property that is critically determined by the underlying graph of the network. A new notion termed generic bearing rigidity is defined for graphs. If the underlying graph of a network is generically bearing rigid, then the network is bearing rigid for almost all configurations;otherwise, the network is not bearing rigid for any configuration. As a result, the key to construct bearing rigid networks is to construct generically bearing rigid graphs. The main contribution of this paper is to prove that Laman graphs, which can be generated by the Henneberg construction, are generically bearing rigid in arbitrary dimensions. As a consequence, if the underlying graph of a network is Laman, the network is bearing rigid for almost all configurations in arbitrary dimensions. Copyright © 2017, The Authors. All rights reserved.

关键词： Graphic methods

Modeling and MPPT control of a Tidal stream generator

学校读者我要写书评

暂无评论

Modeling and MPPT control of a Tidal stream generator

International Conference on control, Decision and Information Technologies (CoDIT)

作者： Khaoula Ghefiri Soufiene Bouallègue Joseph Haggège Izaskun Garrido Aitor J. Garrido Department of Automatic Control and Systems Engineering Automatic Control Group - ACG Bilbao Spain University of Tunis El Manar Laboratory of Research in Automatic Control - LA.R.A Tunis Tunisia Universidad del Pais Vasco Bilbao PaÃs Vasco ES

This paper deals with the design, modeling and control of a Tidal Stream Generator (TSG) system including a tidal turbine, a rotor shaft and a Doubly Fed Induction Generator (DFIG). Below high tidal speed the system is regulated so that for every tidal velocity reaches the maximum power. A rotational speed control based-Maximum Power Point Tracking (MPPT) for a TSG is investigated to provide the suitable rotational speed to the system in order to track the maximum power and thus keeping the pitch angle null. Two study cases were proposed to test the performance of the control strategy. The obtained results show that the proposed control provide satisfactory tracking of the MPPT reference.

关键词： Turbines Velocity control Rotors Tides Maximum power point trackers

Estimating models with high-order noise dynamics using semi-parametric weighted null-space fitting

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Galrinho, Miguel Rojas, Cristian R. Hjalmarsson, Håkan Automatic Control Department School of Electrical Engineering and Data Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

Standard system identification methods often provide inconsistent estimates with closed-loop data. With the prediction error method (PEM), this issue is solved by using a noise model that is flexible enough to capture the noise spectrum. However, a too flexible noise model (i.e., too many parameters) increases the model complexity, which can cause additional numerical problems for PEM. In this paper, we consider the weighted null-space fitting (WNSF) method. With this method, the system is first modeled using a non-parametric ARX model, which is then reduced to a parametric model of interest using weighted least squares. In the reduction step, a parametric noise model does not need to be estimated if it is not of interest. Because the flexibility of the noise model is increased with the sample size, this will still provide consistent estimates in closed loop and asymptotically efficient estimates in open loop. In this paper, we prove these results, and we derive the asymptotic covariance for the estimation error obtained in closed loop, which is optimal for an infinite-order noise model. For this purpose, we also derive a new technical result for geometric variance analysis, instrumental to our end. Finally, we perform a simulation study to illustrate the benefits of the method when the noise model cannot be parametrized by a low-order model. Copyright © 2017, The Authors. All rights reserved.

关键词： Parameter estimation

Enhanced chaotic spiral dynamic algorithm with application to controller design 6

学校读者我要写书评

暂无评论

Enhanced chaotic spiral dynamic algorithm with application t...

6th IEEE International Conference on Power and Energy, PECON 2016

作者： Hashim, M.R. Tokhi, M.O. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781509025473

This paper present an enhanced chaotic spiral dynamic algorithm (ECSDA) for optimization problems and their application in single link flexible manipulator system (SLFMS). The algorithm is developed by integrating logistic chaotic pattern into the original spiral dynamic algorithm (SDA). The artificial bee colony optimization (ABC) searching method is also adopted in ECSDA to increase its capability to find the best possible local optimum solution. This hybrid technique reduces the probability of ECSDA getting trapped at local optimum. ECSDA is used to optimize the PD controller parameters of a single link flexible manipulator system (SLFMS). The results show that the ECSDA outperforms the SDA with improved search capability and escaping local optima and is able to tune the PD controller of SLFMS for the desired output. © 2016 IEEE.

关键词： Flexible manipulators