检索结果-内蒙古大学图书馆

IEEE International Conference on Industrial Informatics (INDIN)

作者： George Georgoulas Vicente Climente-Alarcon Jose A. Antonino-Daviu Chrysostomos D. Stylios Antero Arkkio George Nikolakopoulos Control Engineering Group University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Aalto Finland Instituto Tecnologico de la Energia Universitat Politècnica de València Valencia Spain Department of Computer Engineering Laboratory of Knowledge and Intelligent Computing Kostakioi Greece

ISBN: (纸本)9781509028719

In this article a data driven approach for the classification of simultaneously occurring faults in an induction motor is presented. The problem is treated as a multi-label classification problem with each label corresponding to one specific fault, using the power-set approach. The faulty conditions examined, include the existence of a broken bar fault and the presence of mixed eccentricity with various degrees of static and dynamic eccentricity. For the feature extraction stage, the time-frequency representation, resulting from the application of the short time Fourier transform of the start-up current is exploited. The proposed approach is validated using simulation data with promising results.

关键词： Bars Time-frequency analysis Induction motors Transient analysis Principal component analysis Fault diagnosis Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

No reference video quality assessment based on 3D convolutional neural network

引用

Ruan Jian Xue Bao/Journal of Software 2016年 27卷 103-112页

作者： Wang, Chun-Feng Su, Li Zhang, Wei-Gang Huang, Qing-Ming Key Laboratory on Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology The Chinese Academy of Sciences Beijing100190 China Weihai264209 China

No reference video quality assessment (NR-VQA) measures distorted videos quantitatively without the reference of original high quality videos. Conventional NR-VQA methods are generally designed for specific types of distortions, or not consistent with human's perception. This paper innovatively introduces 3D deep convolutional neural network (3D-CNN) into VQA and proposes a 3D-CNN based NR-VQA method, which is universal for non-specific types of distortions. First, the proposed method utilizes 3D patches to learn spatio-temporal features that represent video content effectively. Second, the original 3D-CNN model is modified which is used to classify videos to make it adapt to VQA task. Experiments demonstrate that the proposed method is highly consistent with human's perception across numerous distortions and metrics. Compared with other state-of-the-art no-reference VQA methods, the proposed method runs much faster while keeping the similar performance. As a no-reference VQA method, it is even comparable with many of the state-of-the-art full-reference VQA methods, which provides the proposed method with better application prospects. © Copyright 2016, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Topic discovery of clusters from documents with geographical location

Topic discovery of clusters from documents with geographical...

引用

作者： Zhang, Li Sun, Xiaoping Zhuge, Hai Knowledge Grid Lab Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Nanjing University of Posts and Telecommunications Nanjing Jiangsu China State Key Laboratory of Software Engineering Wuhan University Wuhan Hubei China University of Chinese Academy of Sciences Beijing China

As smart phones with GPS become popular, more and more textual documents with geographical locations are published on the Web. Keyword-based location services like vehicle navigation, tour planning, nearby object querying, and location pattern discovering of spatial objects are becoming popular and important. However, processing both text and geographical locations brings more challenges to information-retrieval techniques. In this paper, we focus on the problem of finding textual topics of clusters containing spatial objects with text descriptions. The key is how to combine clustering techniques with topic-retrieval models to integrate both geo-location information and text information. We investigated methods that combine clustering methods with the Latent Dirichlet Allocation model to discover topics of clusters of documents with geo-locations. Six different methods of combination are investigated, each having outputs with different meanings, which can be further leveraged to answer different types of queries over spatial documents. Experiments are conducted on both synthetic and real data. The results show that the combination of the probabilistic topic model with clustering algorithms is an efficient and effective way to discover meaningful clusters in different facets and levels of documents with textual and geographical information. © 2015 John Wiley & Sons, Ltd.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Develop Fuzzy Cognitive Maps based on recorded data and information

Develop Fuzzy Cognitive Maps based on recorded data and info...

引用

IEEE International Conference on Fuzzy Systems

作者： Chrysostomos Stylios Voula C. Georgopoulos Knowledge and Intelligent Computing Laboratory Computer Engineering Depart. Technological Educational Institute of Epirus INTERACT Lab School of Health & Welfare Professions Technological Educational Institute of Western Greece

ISBN: (纸本)9781467374293

This work presents a novel integrated approach on how to develop Fuzzy Cognitive Maps combining human expert knowledge with existing recorded information and historical data. The proposed approach aims to extract information from unstructured data and to transform it into knowledge in the form of a FCM. The proposed approach still is dependent on experts but providing them with more information and supportive data, in the form of particular evidence-based information available in the literature in order to better justify their selections. The proposed approach is inherit to the FCM and its structure the extracted knowledge and it can be used to model a complex system such as the Medical Decision Support Systems.

关键词： Fuzzy Cognitive Maps knowledge extraction Historical data Case based Soft computing

来源：评论

学校读者我要写书评

暂无评论

Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program

arXiv

引用

arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Automatizing the broken bar detection process via Short Time Fourier Transform and two-dimensional Piecewise Aggregate Approximation representation

Automatizing the broken bar detection process via Short Time...

引用

作者： Georgoulas, George Karvelis, Petros Stylios, Chysostomos D. Tsoumas, Ioannis P. Antonino-Daviu, Jose Alfonso Climente-Alarcon, Vicente Laboratory of Knowledge and Intelligent Computing Department of Computer Engineering TEI of Epirus Artas Kostakioi47100 Greece Larges Drives R and D Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingeniería Energética Universitat Politècnica de València Valencia Spain

ISBN: (纸本)9781479956982

This work presents an automated approach for detecting broken rotor bars in induction machines using the stator current during startup operation. The currents are analyzed using the well-known Short Time Fourier Transform (STFT) producing a two-dimensional time-frequency representation. This representation contains information regarding the presence of a characteristic transient component but requires further processing before it can be fed into a standard classification algorithm. In this work, this part is performed using the two dimensional extension of Piecewise Aggregate Approximation (PAA) that can deal with the two dimensional representation of STFT. The results (with both simulated and experimental data) suggest that the method can be used for the automatic detection of broken bars and even for determining the fault severity. Moreover, its low computational burden makes it ideal for its future use in online, unsupervised systems, as well as in portable condition monitoring devices. © 2014 IEEE.

关键词： Condition monitoring

来源：评论

学校读者我要写书评

暂无评论

Principal Component Analysis Anomaly Detector for Rotor Broken Bars

Principal Component Analysis Anomaly Detector for Rotor Brok...

引用

Annual Conference of the IEEE Industrial Electronics Society

作者： Mohammed Obaid Mustafa George Georgoulas George Nikolakopoulos Control Engineering Group Department of Computer Science Electrical and Space Engineering Lulea University of Technology Laboratory of Knowledge and Intelligent Computing (KIC) Department of Computer Engineering Technological Educational Institute of Epirus

ISBN: (纸本)9781479940318

In this article a method for the detection of broken rotor bars in asynchronous machines operating under full load is presented. Unlike most Motor Current Signature Analysis (MCSA) approaches, which operate in the frequency domain, our method operates in the time domain. The scheme is based on the use of a Principal Component Analysis (PCA) fault/anomaly detector. PCA is applied on the three stator currents to subsequently calculate the Q statistic which is employed for detecting the presence/absence of a fault. The efficiency of the proposed scheme was experimentally evaluated using different fault severity levels, ranging from 1/4 of a broken bar to three broken bars. The obtained results indicate that the method can detect the caused asymmetry with a very restricted amount of data.

关键词： Principal component analysis Rotors Bars Induction motors Detectors Stators Fault detection

来源：评论

学校读者我要写书评

暂无评论

An automated thermographic image segmentation method for induction motor fault diagnosis

An automated thermographic image segmentation method for ind...

引用

作者： Karvelis, Petros Georgoulas, George Stylios, Chsysostomos D. Tsoumas, Ioannis P. Antonino-Daviu, Jose Alfonso Rodenas, Maria Jose Picazo Climente-Alarcon, Vicente Laboratory of Knowledge and Intelligent Computing Technological Educational Institute of Epirus Department of Computer Engineering Arta Greece Larges Drives Products RandD Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingeniería Energética Universitat Politècnica de València Valencia Spain Department of Electrical Engineering and Automation Aalto University Espoo Finland

ISBN: (纸本)9781479940325

Eventual failures in induction machines may lead to catastrophic consequences in terms of economic costs for the companies. The development of reliable systems for fault detection that enable to diagnose a wide range of faults is a motivation of many researchers worldwide. In this context, non-invasive condition monitoring strategies have drawn special attention since they do not require interfering with the operation process of the machine. Though the analysis of the motor currents has proven to be a reliable, non-invasive methodology to detect some of the faults (especially when assessing the rotor condition), it lacks reliability for the diagnosis of other faults (e.g. bearing faults). The infrared thermography has proven to be an excellent, non-invasive tool that can complement the diagnosis reached with the motor current analysis, especially for some specific faults. However, there are still some pending issues regarding its application to induction motor faults diagnosis, such as the lack of automation or the extraction of reliable fault indicators based on the infrared data. This paper proposes a methodology that intends to provide a solution to the first issue: a method based on image segmentation is employed to detect several failures in an automated way. Four specific faults are analyzed: bearing faults, fan failures, rotor bar breakages and stator unbalance. The results show the potential of the technique to automatically identify the fault present in the machine. © 2014 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Cognitive Map Scenario-Based Medical Decision Support Systems for Education

Fuzzy Cognitive Map Scenario-Based Medical Decision Support ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Voula C. Georgopoulos Spyridoula Chouliara Chrysostomos D. Stylios Department of Speech and Language Therapy Technological Educational Institute of Western Greece Koukouli Patras Greece MSc is an Obstetrician working for a private Obstetrician and Gynecological Clinic Artas Greece Head of the Knowledge and Intelligent Computing Laboratory Technological Educational Institute of Epirus Artas Greece

Soft computing (SC) techniques are based on exploiting human knowledge and experience and they are extremely useful to model any complex decision making procedure. Thus, they have a key role in the development of Medical Decision Support Systems (MDSS). The soft computing methodology of Fuzzy Cognitive Maps has successfully been used to represent human reasoning and to infer conclusions and decisions in a human-like way and thus, FCM-MDSSs have been developed. Such systems are able to assist in critical decision-making, support diagnosis procedures and consult medical professionals. Here a new methodology is introduced to expand the utilization of FCM-MDSS for learning and educational purposes using a scenario-based learning (SBL) approach. This is particularly important in medical education since it allows future medical professionals to safely explore extensive "what-if' scenarios in case studies and prepare for dealing with critical adverse events.

关键词： Medical diagnostic imaging Fetal heart rate Decision support systems Decision making Fuzzy cognitive maps Education Biomedical monitoring

来源：评论

学校读者我要写书评

暂无评论

Automatizing the broken bar detection process via Short Time Fourier Transform and two-dimensional Piecewise Aggregate Approximation representation

Automatizing the broken bar detection process via Short Time...

引用

IEEE Energy Conversion Congress and Exposition

作者： George Georgoulas Petros Karvelis Chysostomos D. Stylios Ioannis P. Tsoumas Jose Alfonso Antonino-Daviu Vicente Climente-Alarcon Laboratory of Knowledge and Intelligent Computing Department of Computer Engineering TEI of Epirus 47100 Artas Kostakioi Greece Larges Drives R&D Department Siemens Industry Sector - Drive Technologies Nuremberg Germany Instituto de Ingenieria Energetica Universitat Politecnica de Valencia Valencia Spain

ISBN: (纸本)9781479957774

关键词： Time-frequency analysis Bars Transient analysis Rotors Circuit faults Spectrogram Stators

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：