检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

Modelling of Raw Hide One-Stage Washing Process

Modelling of Raw Hide One-Stage Washing Process

引用

2015 International Conference on Environmental Science and Energy engineering(ICESEE 2015)

作者： Dagmar JANACOVA Karel KOLOMAZNIK Pavel MOKREJS Vladimir VASEK Ondrej LISKA Antonin BLAHA Miloslav FIALKA Department of Automation and Control Engineering Faculty of Applied Informatics Faculty of Technology Tomas Bata University in Zlín Technical University of Ko?ice

In the last years increased application of automatic control systems in tannery *** system consists mostly in the control of equipment and metering of chemicals,according to a predetermined programme.A qualitatively higher degree of automatic control is the application of closed loop control,involving active interferences based on measured parameters of the process in *** of the ways how to achieve this is adequate technical equipment and application of control algorithms,derived from the mathematical model of the given process and his physical *** first task was the design of such *** case of raw hide washing such models are of diffusion type,describing protective component transport or models describing protective solution on the *** solution and practical verification was made under laboratory and industrial *** design or control algorithms should equally give answer to the question what is the main purpose of *** could be *** of satisfactory good quality semiproduct,environmental protection,minimization of operating costs because reduced water consumption cannot compensate the long operation time connected with power *** focused on part of soaking process—washing.

关键词： Washing Raw hide Mathematical modelling Optimization Process control

来源：评论

学校读者我要写书评

暂无评论

Geometrical Method for Increasing Precision of Machine Building Parts

引用

Procedia engineering 2016年 149卷 576-580页

作者： Pavol Božek Aleksander Lozkin Alexey Gorbushin Slovak University of Technology Faculty of Materials Science and Technology Institute of Applied Informatics Automation and Mechatronics J. Bottu 25 Trnava 91724 Slovakia Department of Software M. T. Kalashnikov Izhevsk State Technical University Studencheskaya st. 7 IIzhevsk 426069 Russia Department of Automated Data Processing and Control Systems Glazov branch of Kalashnikov Izhevsk State Technical University Kirova street 36 427622 Glazov Russia

Calculation of complex curves with high accuracy is challenging. The curve is approximated by segments of straight lines and carried out smoothing. A new method of analytic geometry to calculate the trajectories of mechatronic systems and CAD/CAM is offered. The theoretical basis of the method is symmetries in the Euclidean plane. The method can accurately calculate the trajectory for the centrally symmetric conic sections and, in some cases, arbitrary differentiable planar curves. The method gives an accurate analytical solution without using radicals. This allows you to find the formulaic dependencies for further calculations. The existence of Lissajous figures allows assuming the presence of a universal method of calculation of complex trajectories based on planar differentiable curves. Some examples of the design of the kinematic mechanisms are presents additionally.

关键词： mechatronic systems calculation of trajectory symmetries arbitrary curves.

来源：评论

学校读者我要写书评

暂无评论

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

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

Dynamics of DFIG controlled by Rotor Side Converter in wind energy

Dynamics of DFIG controlled by Rotor Side Converter in wind ...

引用

International Youth Conference on Energetics (IYCE)

作者： Péter Stumpf József Berei István Nagy István Vajk Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest MTA-BME Control Engineering Research Group

The paper is concern with the investigation of control of Doubly Fed Induction Generator (DFIG) carried out by Rotor Side Converter (RSC) applied in wind energy harvest. Throughout the paper the principle of Stator Flux Oriented Vector control (SFOVC) is applied. In the first part of the paper a general slip-torque relation is derived with three torque components: one component is derived by the stator voltage, the other one by the d component and the third one by the q component of the rotor voltage space vector. In the second part of the paper, the dynamic behavior of the algorithm controlling the stator active and reactive power is simulated in open loop and closed loop.

关键词： Rotors Torque Stators Turbines Mathematical model Microgrids Transient response

来源：评论

学校读者我要写书评

暂无评论

Multi-source information fusion model in rule-based Gaussian-shaped fuzzy control inference system incorporating Gaussian density function

Multi-source information fusion model in rule-based Gaussian...

引用

作者： Li, Zairan He, Ting Cao, Luying Wu, Tunhua McCauley, Pamela Balas, Valentina E. Shi, Fuqian Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin China Wenzhou Vocational and Technical College Wenzhou China College of Information and Engineering Wenzhou Medical University Wenzhou325035 China Department of Industrial Engineering and Management Systems University of Central Florida OrlandoFL United States Department of Automation and Applied Informatics Aurel Vlaicu University of Arad Romania

An increasing number of applications require the integration of data from various disciplines, which leads to problems with the fusion of multi-source information. In this paper, a special information structure formalized in terms of three indices (the central presentation, population or scale, and density function) is proposed. Single and mixed Gaussian models are used for single source information and their fusion results, and a parameter estimation method is also introduced. Furthermore, fuzzy similarity computing is developed for solving the fuzzy implications under a Mamdani model and a Gaussian-shaped density function. Finally, an improved rule-based Gaussian-shaped fuzzy control inference system is proposed in combination with a nonlinear conjugate gradient and a Takagi-Sugeno (T-S) model, which demonstrated the effectiveness of the proposed method as compared to other fuzzy inference systems. © 2015 - IOS Press and the authors. All rights reserved.

关键词： Fuzzy control

来源：评论

学校读者我要写书评

暂无评论

State space control of quadratic boost converter using LQR and LQG approaches

State space control of quadratic boost converter using LQR a...

引用

International Aegean Conference on Electrical Machines and Power Electronics, ACEMP

作者： Bence Kurucsó Alfréd Peschka Péter Stumpf István Nagy István Vajk Department of Automation and Applied Informatics Budapest University of Technology and Economics MTA-BME Control Engineering Research Group Budapest Hungary

The systematic design of a Linear Quadratic Regulator (LQR) state-feedback controller with an integral action is presented for a quadratic DC/DC boost converter topology. The weighting factors are selected with respect to energy considerations. By using a Kalman Filter for both filtering and state estimation purpose a Linear Quadratic Gaussian (LQG) controller is obtained. For the proper operation of the LQG controller an average state-space model of the quadratic boost converter with non ideal elements is introduced. Detailed simulation study in the discrete time-domain is presented demonstrating the robustness of both LQR and LQG. Laboratory tests results are shown for LQR.

关键词： Switches Mathematical model Steady-state Voltage control Aerospace electronics Matrix converters

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

引用

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

来源：评论

学校读者我要写书评

暂无评论

Increasing energy efficiency of a building with minimal computational demands using model predictive control

Increasing energy efficiency of a building with minimal comp...

引用

Roedunet International Conference (RoEduNet)

作者： Giorgian Neculoiu Valentin Sgarciu Alexandru Viorel Marinescu Mariana Marinescu Faculty of Automatic Control and Computers Politehnica University of Bucharest1 Bucharest Romania Laboratory of Automation and Applied Informatics Technical University of Civil Engineering of Bucharest Bucharest Romania

This work is a aggregated perspective of previous papers studying advanced control strategy applicable in intermittently heated buildings. This strategy mainly aims to optimize the energy efficiency of heating systems taking into consideration the minimization of the needful time and the computational resources necessary to this process. Model Predictive control is the control strategy used in this work and the main purpose (ensuring maximum comfort with minimum energy consumption) is satisfied by using weather forecasts and building occupancy program. Several architectures presented can be used to implement the proposed solution. The main goal is to minimize the computational requirements achieving the best performance. To solve the problems from previous studies, this paper studied the solutions implemented on a single thermal zone and multiple thermal zones.

关键词： Decision support systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：