检索结果-内蒙古大学图书馆

arXiv 2017年

作者： Abbati, Gabriele Schüffler, Peter J. Winklhofer, Sebastian Burgstaller, Jakob M. Held, Ulrike Steurer, Johann Bauer, Stefan Buhmann, Joachim M. Department of Engineering Science University of Oxford Eagle House Walton Well Road OxfordOX2 6ED United Kingdom Thomas Fuchs Lab Medical Machine Learning & Computational Pathology Memorial Sloan Kettering Cancer Center 417 E 68th St. New YorkNY10065 United States Klinik für Neuroradiologie University Hospital Zürich Rämistrasse 100 Zürich8091 Switzerland Horten Centre for Patient Oriented Research Knowledge Transfer University Hospital Zürich Pestalozzistrasse 24 Zürich8032 Switzerland Department of Computer Science ETH Zürich Universittstrasse 6 Zürich8006 Switzerland

The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis (LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the surgeon shows large variance. Thus a standardized support system is of high value for a more objective and reproducible decision. In this work, we develop an automated algorithm to localize the stenosis causing the symptoms of the patient in magnetic resonance imaging (MRI). With 22 MRI features of each of five spinal levels of 321 patients, we show it is possible to predict the location of lesion triggering the symptoms. To support this hypothesis, we conduct an automated analysis of labeled and unlabeled MRI scans extracted from 788 patients. We confirm quantitatively the importance of radiological information and provide an algorithmic pipeline for working with raw MRI scans. Copyright © 2017, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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

York University at CLEF eHealth 2015: Medical document retrieval 16

York University at CLEF eHealth 2015: Medical document retri...

引用

16th Conference and Labs of the Evaluation Forum, CLEF 2015

作者： Ghoddousi, Andia Huang, Jimmy Xiangji Information Retrieval and Knowledge Management Research Lab Department of Computer Science and Engineering School of Information Technology York University Canada

This paper presents the results for task 2 of ShAre/CLEF 2015 eHealth Evaluation Lab. We use BM25 as our base normalization method and Pseudo Relevance Feedback to retrieve information regarding patients' health and find the best results to expand the efficiency of information retrieval system. Participants in task 2 are provided with a collection of datasets focused on health web pages. We used queries and submitted 10 runs in TREC style. The runs include the top1000 documents returned for each query. The objective of task 2 is to evaluate the effectiveness of information retrieval system and develop search engines for searching on the web looking for health related documents[1].

关键词： Information retrieval

来源：评论

学校读者我要写书评

暂无评论

Efficient mining of class association rules with the itemset constraint

Efficient mining of class association rules with the itemset...

引用

作者： Nguyen, Dang Nguyen, Loan T.T. Vo, Bay Pedrycz, Witold Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City University of Technology Viet Nam College of Electronics and Information Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw Poland

Mining class association rules (CARs) with the itemset constraint is concerned with the discovery of rules, which contain a set of specific items in the rule antecedent and a class label in the rule consequent. This task is commonly encountered in mining medical data. For example, when classifying which section of the population is at high risk for the HIV infection, epidemiologists often concentrate on rules which include demographic information such as gender, age, and marital status in the rule antecedent, and HIV-Positive in the rule consequent. There are two naive strategies to solve this problem, namely pre-processing and post-processing. The post-processing methods have to generate and consider a huge number of candidate CARs while the performance of the pre-processing methods depend on the number of records filtered out. Therefore, such approaches are time consuming. This study proposes an efficient method for mining CARs with the itemset constraint based on a lattice structure and the difference between two sets of object identifiers (diffset). Firstly, a lattice structure is built to store all frequent itemsets in the dataset. To reduce memory usage, instead of the entire set of object identifiers, the diffset is used. Secondly, the lattice is traversed to generate only rules which satisfy the itemset constraint. The experimental results show that the proposed algorithm outperforms existing methods in terms of both the mining time and memory usage. © 2016 Elsevier B.V. All rights reserved.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Introduction

Lecture Notes in Computer Science (including subseries Lectu...

引用

Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9792 LNCS卷 1-8页

作者： González-Beltrán, Alejandra Osborne, Francesco Peroni, Silvio Oxford e-Research Centre University of Oxford Oxford United Kingdom Data Science Group Knowledge Media Institute The Open University Milton Keynes United Kingdom Digital and Semantic Publishing Laboratory Department of Computer Science and Engineering University of Bologna Bologna Italy

We provide the motivation and overview of the SAVE-SD workshop series and introduce the manuscripts that were accepted as part of these proceedings of the SAVE-SD 2016 edition. © Springer International Publishing...

ISBN: (纸本)9783319536361

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exponential stability assignment of inverse LQ regulator for neutral systems with time-varying delay

IEEJ Transactions on Electronics, Information and Systems

引用

IEEJ Transactions on Electronics, Information and Systems 2016年第10期136卷 1466-1472页

作者： Matsuki, Tsuyoshi Kubo, Tomohiro Oya, Hidetoshi Department of Electronics and Control Engineering National Institute of Technology Niihama College 7-1 Yagumo-cho Niihama Ehime792-8580 Japan Institute of Science and Technology Tokushima University 2-1 Minamijosanjima-cho Tokushima Tokushima770-8506 Japan Department of Computer Science Faculty of Knowledge Engineering Tokyo City University 1-28-1 Tamazutsumi Setagaya-ku Tokyo158-0087 Japan

In this paper, we propose a design method of an inverse LQ regulator for neutral systems with a time-varying delay, in which the resulting system is assured to have a pre-assigned degree of exponential stability. Using this method, the closed-loop system is asymptotically stabilized and a feedback law constructed easily is the optimal control minimizing a class of a cost functional without relation to the exponential stability assignment. In addition, the regulator promises to have a good robust stability as same as ordinary finite dimensional LQ regulators, even when a static nonlinear or a dynamic linear perturbation is inserted in the control input. Finally, the method is demonstrated by numerical examples with and without the exponential stability assignment. In the simulation, it is shown that the proposed method allows designers to seek more fast closed-loop responses by selecting two scalar parameters and the degree of exponential stability in a condition given by LMIs. © 2016 The Institute of Electrical Engineers of Japan.

关键词： Closed loop systems

来源：评论

学校读者我要写书评

暂无评论

引用

2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016

作者： Nguyen, Linh Anh Nguyen, Thi Hong Khanh Nguyen, Ngoc-Thanh Ha, Quang-Thuy Division of Knowledge and System Engineering for ICT Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Institute of Informatics University of Warsaw Banacha 2 Warsaw02-097 Poland Electric Power University 235 Hoang Quoc Viet Tu Liem Hanoi Viet Nam Department of Information Systems Faculty of Computer Science and Management Wroclaw University of Technology Poland Faculty of Information Technology VNU University of Engineering and Technology 144 Xuan Thuy Hanoi Viet Nam

ISBN: (纸本)9781509018970

We introduce comparisons with respect to information between interpretations in paraconsistent description logics and use them to define bisimilarity for such logics. As bisimilarity is a natural notion for characterizing indiscernibility in modal and description logics, it is useful for concept learning in description logics also when inconsistencies occur. We give preservation results and the Hennessy-Milner property for comparisons with respect to information in paraconsistent description logics. As consequences, we also obtain invariance results and the Hennessy-Milner property for bisimilarity in paraconsistent description logics. © 2016 IEEE.

关键词： Data description

来源：评论

学校读者我要写书评

暂无评论

Preface

Communications in Computer and Information Science

引用

Communications in computer and Information science 2017年 705卷 V-VIII页

作者： Cazenave, Tristan Winands, Mark H. M. Edelkamp, Stefan Schiffel, Stephan Thielscher, Michael Togelius, Julian LAMSADE Universitè Paris-Dauphine Paris Cedex 16 France Department of Data Science and Knowledge Engineering Maastricht University Maastricht Limburg Netherlands Institute for Artificial Intelligence Universität Bremen TAB Bremen Bremen Germany Reykjavik University Reykjavik Iceland The University of New South Wales SydneyNSW Australia Department of Computer Science and Engineering New York University BrooklynNY United States

来源：评论

学校读者我要写书评

暂无评论

SeqCluSum: Combining Sequential Clustering and Contextual Importance Measuring to Summarize Developing Events over Time 24

SeqCluSum: Combining Sequential Clustering and Contextual Im...

引用

24th Text REtrieval Conference, TREC 2015

作者： Zopf, Markus Research Training Group AIPHES Knowledge Engineering Group Department of Computer Science Technische Universität Darmstadt Hochschulstraße 10 Darmstadt64293 Germany

Unexpected events such as accidents, natural disasters and terrorist attacks represent an information situation where it is essential to give users access to important and non-redundant information as fast as possible. In this paper, we introduce SeqCluSum, a temporal summarization system which combines sequential clustering to cluster sentences and a contextual importance measurement to weight the created clusters and thereby to identify important sentences. We participated with this system in the TREC Temporal Summarization track where systems have to generate extractive summaries for developing events by publishing sentence-length updates extracted from web documents. Results show that our approach is very well suited for this task by achieving best results. We furthermore point out several improvement possibilities to show how the system can further be enhanced. © 2015 24th Text REtrieval Conference, TREC 2015 - Proceedings. All Rights Reserved.

关键词： Disasters

来源：评论

学校读者我要写书评

暂无评论

Speech emotion recognition with acoustic and lexical features 40

Speech emotion recognition with acoustic and lexical feature...

引用

40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Jin, Qin Li, Chengxin Chen, Shizhe Wu, Huimin Computer Science Department School of Information Renmin University of China Beijing China Key Lab of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing China

ISBN: (纸本)9781467369978

In this paper we explore one of the key aspects in building an emotion recognition system: generating suitable feature representations. We generate feature representations from both acoustic and lexical levels. At the acoustic level, we first extract low-level features such as intensity, F0, jitter, shimmer and spectral contours etc. We then generate different acoustic feature representations based on these low-level features, including statistics over these features, a new representation derived from a set of low-level acoustic codewords, and a new representation from Gaussian Supervectors. At the lexical level, we propose a new feature representation named emotion vector (eVector). We also use the traditional Bag-of-Words (BoW) feature. We apply these feature representations for emotion recognition and compare their performance on the USC-IEMOCAP database. We also combine these different feature representations via early fusion and late fusion. Our experimental results show that late fusion of both acoustic and lexical features achieves four-class emotion recognition accuracy of 69.2%. © 2015 IEEE.

关键词： Acoustic features Emotion lexicon Emotion recognition Lexical features Support vector machine

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：