检索结果-内蒙古大学图书馆

International Conference on Advanced Learning Technologies (ICALT)

作者： Athanasios Staikopoulos Ian OKeeffe Bilal Yousuf Owen Conlan Eddie Walsh Vincent Wade Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin University of Dublin Trinity College Dublin IE

A lack of appropriate engagement in online learning courses is a significant factor leading to poor performance and high dropout rates. This paper presents a framework that provides personalized motivations in the form of feedback, advices and reminders in order to enhance the engagement of students with online learning. It also describes the design, implementation and evaluation of the framework which has been used by over one hundred students. The paper focuses on how the framework by modelling and monitoring the level of engagement of students, it provides tailored motivations to stimulate and sustain their engagement. Finally, the paper compares the results from a previous student cohort (where no motivations were provided) to highlight how the framework has significantly increased the level of engagement of students.

关键词： Monitoring Engines Education Context Electronic mail Least squares approximations Portals

来源：评论

学校读者我要写书评

暂无评论

Pathological brain detection based on online sequential extreme learning machine

Pathological brain detection based on online sequential extr...

引用

IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Siyuan Lu Hainan Wang Xueyan Wu Shuihua Wang School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China State Key Lab of CAD & CG Zhejiang University Hangzhou Zhejiang China Key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin University Changchun Jilin China Key Laboratory of Statistical information technology and data mining State Statistics Bureau Chengdu Sichuan China Department of Electrical Engineering CUNY New York NY USA

ISBN: (纸本)9781509034857

Magnetic resonance imaging (MRI) is a kind of imaging modality, which offers clearer images of soft tissues than computed tomography (CT). It is especially suitable for brain disease detection. It is beneficial to detect diseases automatically and accurately. We proposed a pathological brain detection method based on brain MR images and online sequential extreme learning machine. First, seven wavelet entropies (WE) were extracted from each brain MR image to form the feature vector. Then, an online sequential extreme learning machine (OS-ELM) was trained to differentiate pathological brains from the healthy controls. The experiment results over 132 brain MRIs showed that the proposed approach achieved a sensitivity of 93.51%, a specificity of 92.22%, and an overall accuracy of 93.33%, which suggested that our method is effective.

关键词： Entropy Discrete wavelet transforms Feature extraction Pathology Training Magnetic resonance imaging Diseases

来源：评论

学校读者我要写书评

暂无评论

Learning platform: Emotional learning

Learning platform: Emotional learning

引用

Iberian Conference on Information Systems and Technologies (CISTI)

作者： Ana Raquel Faria Ana Almeida Constantino Martins Ramiro Gonçalves Computer Science Department GECAD-Knowledge Engineering and Decision Support Group Institute of Engineering - Polytechnic of Porto Porto Portugal

The purpose of this paper is to propose new model for emotional interaction that uses learning styles and student emotional state to adapt the user interface and learning path. This aims to reduce the difficulty and emotional stain that students encounter while interacting with learning platforms. To this end will be used techniques of Affective computer that can capture the student emotional state and base on that change the course parameters (flow, organization or difficulty) or even an emotional interaction in order to recapture the student attention.

关键词： Prototypes Adaptation models Education data models Computational modeling Gaussian distribution computers

来源：评论

学校读者我要写书评

暂无评论

Adaptive Control of Solar Energy Collector Systems [Book News]

引用

IEEE Industrial Electronics Magazine 2015年第2期9卷 61-62页

作者： Fernando A. Silva A*STAR Data Storage Institute Singapore Department of Computer Science & Engineering KIET Group of Institutions Ghaziabad UP India

The excellent book Adaptive Control of Solar Energy Collector Systems presents, in a rigorous and comprehensive way, the adaptive control methodologies to deal with the DCSF-specific dynamic structure. The authors are world-known specialists in intelligent control, systems identification, and decision-making technology. The textbook clearly explains the main mathematical tools to apply adaptive and predictive control to industrial plants, including power conversion and distributed renewable energy resources. It contributes to disseminate advanced control expertise while encouraging technology transfer in control engineering.

关键词： Book reviews Adaptive control Intelligent control Solar energy System identification Decision making Predictive control Industrial plants

来源：评论

学校读者我要写书评

暂无评论

A demand based unicast data dissemination scheme in VANET

A demand based unicast data dissemination scheme in VANET

引用

IEEE India Conference (INDICON)

作者： Bidisha Bhabani Atanu Mondal Sulata Mitra Department of Computer Science and Engineering Supreme Knowledge Foundation Group of Institutions Kolkata India Department of Computer Science and Engineering Camellia Institute of Technology Kolkata India Department of Computer Science and Technology Indian Institute of Engineering Science and Technology Howrah India

ISBN: (纸本)9781467365413

Vehicular ad hoc network performs crucial function in road safety, detection of traffic accidents and reduction of traffic congestions by disseminating messages among vehicles. The periodic broadcasting is an efficient approach to serve the requests of many vehicles without selecting any route between source and destination. But it degrades the network performance due to hidden node problem and broadcasting storm problem. The present work is an on demand type of unicast pull based approach of data dissemination in vehicular ad hoc network. It disseminates data in the form of response message after receiving any query message from vehicle. The performance of the proposed scheme is evaluated in terms of block of service, loss of query messages due to time out, average required time of sending response messages to the vehicles and throughput.

关键词： Vehicles Vehicular ad hoc networks Broadcasting Unicast Authentication databases

来源：评论

学校读者我要写书评

暂无评论

Temporal reasoning on Twitter streams using semantic web technologies

Temporal reasoning on Twitter streams using semantic web tec...

引用

IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： Meng Cui Wei Tai Declan O'Sullivan Trinity College Dublin School of Computer Science & Statistics Dublin Ireland Knowledge and Data Engineering Group School of Computer Science & Statistics Dublin Ireland University of Dublin Trinity College Dublin IE

There has been a significant increase in recent years in the volume and diversity of streams of data, data streams from sensors, data streams arising from the analysis of content or data mining, right through to user generated Twitter streams. There has been a corresponding increase in demand for more real-time analysis of these streams in order to spot significant events and trends of interest to an individual or business. This has resulted in an increased need to achieve efficient temporal reasoning upon the streams. In this paper, we present a novel approach to perform temporal reasoning on real time streams of data using Semantic Web Technologies so that we could derive more valuable information by taking account of the time dimension. Moreover, in order to deal with such high-frequency data, several filter mechanisms have been implemented to, significantly, improve the performance of the reasoning process. In order to illustrate and evaluate the approach, the real-time analysis of Twitter data is taken as a concrete use case for such data streams.

关键词： Cognition Resource description framework Twitter Semantics Real-time systems Filtering theory

来源：评论

学校读者我要写书评

暂无评论

First M87 event horizon telescope results. I. The shadow of the supermassive black hole

arXiv

引用

arXiv 2019年

作者： Akiyama, Kazunori Alberdi, Antxon Alef, Walter Asada, Keiichi Azulay, Rebecca Baczko, Anne-Kathrin Ball, David Baloković, Mislav Barrett, John Bintley, Dan Blackburn, Lindy Boland, Wilfred Bouman, Katherine L. Bower, Geoffrey C. Bremer, Michael Brinkerink, Christiaan D. Brissenden, Roger Britzen, Silke Broderick, Avery E. Broguiere, Dominique Bronzwaer, Thomas Byun, Do-Young Carlstrom, John E. Chael, Andrew Chan, Chi-kwan Chatterjee, Shami Chatterjee, Koushik Chen, Ming-Tang Chen, Yongjun Cho, Ilje Christian, Pierre Conway, John E. Cordes, James M. Crew, Geoffrey B. Cui, Yuzhu Davelaar, Jordy de Laurentis, Mariafelicia Deane, Roger Dempsey, Jessica Desvignes, Gregory Dexter, Jason Doeleman, Sheperd S. Eatough, Ralph P. Falcke, Heino Fish, Vincent L. Fomalont, Ed Fraga-Encinas, Raquel Freeman, William T. Friberg, Per Fromm, Christian M. Gómez, José L. Galison, Peter Gammie, Charles F. García, Roberto Gentaz, Olivier Georgiev, Boris Goddi, Ciriaco Gold, Roman Gu, Minfeng Gurwell, Mark Hada, Kazuhiro Hecht, Michael H. Hesper, Ronald Ho, Luis C. Ho, Paul Honma, Mareki Huang, Chih-Wei L. Huang, Lei Hughes, David H. Ikeda, Shiro Inoue, Makoto Issaoun, Sara James, David J. Jannuzi, Buell T. Janssen, Michael Jeter, Britton Jiang, Wu Johnson, Michael D. Jorstad, Svetlana Jung, Taehyun Karami, Mansour Karuppusamy, Ramesh Kawashima, Tomohisa Keating, Garrett K. Kettenis, Mark Kim, Jae-Young Kim, Junhan Kim, Jongsoo Kino, Motoki Koay, Jun Yi Koch, Patrick M. Koyama, Shoko Kramer, Michael Kramer, Carsten Krichbaum, Thomas P. Kuo, Cheng-Yu Lauer, Tod R. Lee, Sang-Sung Li, Yan-Rong Li, Zhiyuan Lindqvist, Michael Liu, Kuo Liuzzo, Elisabetta Lo, Wen-Ping Lobanov, Andrei P. Loinard, Laurent Lonsdale, Colin Lu, Ru-Sen National Radio Astronomy Observatory 520 Edgemont Road CharlottesvilleVA22903 United States Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road WestfordMA01886 United States National Astronomical Observator of Ja an 2-21-1 Osawa Mitaka Tok o Ja an181-8588 Japan Black Hole Initiative at Harvard Universit 20 Garden Street Cambrid eMA02138 United States Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n GranadaE-18008 Spain Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Institute of Astronomy and Astrophysics Academia Sinica 11F of Astronomy-Mathematics Building AS/NTU No. 1 Sec. 4 Roosevelt Rd Taipei10617 Taiwan Departament d’Astronomia i Astrofísica Universitat de València C. Dr. Moliner 50 Burjassot ValènciaE-46100 Spain Observatori Astronòmic Universitat de València C. Catedrático José Beltrán 2 Paterna ValènciaE-46980 Spain Steward Observatory Department of Astronomy University of Arizona 933 N. Cherry Ave TucsonAZ85721 United States Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States East Asian Observatory 660 N. A’ohoku Pl. HiloHI96720 United States PO Box 9513 Leiden2300 RA Netherlands California Institute of Technolo 1200 East California Boulevard PasadenaCA91125 United States Institute of Astronom Astro h sics Academia Sinica 645 N A’ohoku Place HiloHI96720 United States Institut de Radioastronomie Millimétri ue 300 rue de la Piscine Saint Martin d’HèresF-38406 France Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands Perimeter Institute for Theoretical Ph sics 31 Caroline Street North WaterlooONN2L 2Y5 Canada De artment of Ph sics Universit of Waterloo 200 Universit Avenue West WaterlooONN2L 3G1 Canada Waterloo Centre for Astrophysics University of Waterloo WaterlooONN2L 3G1 Canada Korea Astronomy and Space Science Institute Daedeok-daero 776 Yuseong-gu Daejeon34055 Korea

When surrounded by a transparent emission region, black holes are expected to reveal a dark shadow caused by gravitational light bending and photon capture at the event horizon. To image and study this phenomenon, we have assembled the Event Horizon Telescope, a global very long baseline interferometry array observing at a wavelength of 1.3 mm. This allows us to reconstruct event-horizon-scale images of the supermassive black hole candidate in the center of the giant elliptical galaxy M87. We have resolved the central compact radio source as an asymmetric bright emission ring with a diameter of 42 ± 3 μas, which is circular and encompasses a central depression in brightness with a flux ratio 10:1. The emission ring is recovered using different calibration and imaging schemes, with its diameter and width remaining stable over four different observations carried out in different days. Overall, the observed image is consistent with expectations for the shadow of a Kerr black hole as predicted by general relativity. The asymmetry in brightness in the ring can be explained in terms of relativistic beaming of the emission from a plasma rotating close to the speed of light around a black hole. We compare our images to an extensive library of ray-traced general-relativistic magnetohydrodynamic simulations of black holes and derive a central mass of M = (6.5 ± 0.7) × 109 Me. Our radio-wave observations thus provide powerful evidence for the presence of supermassive black holes in centers of galaxies and as the central engines of active galactic nuclei. They also present a new tool to explore gravity in its most extreme limit and on a mass scale that was so far not accessible. Copyright © 2019, The Authors. All rights reserved.

关键词： Gravitation

来源：评论

学校读者我要写书评

暂无评论

Sustainable computational science: The Rescience initiative

arXiv

引用

arXiv 2017年

作者： Rougier, Nicolas P. Hinsen, Konrad Alexandre, Frédéric Arildsen, Thomas Barba, Lorena Benureau, Fabien C.Y. Titus Brown, C. de Buyl, Pierre Caglayan, Ozan Davison, Andrew P. Delsuc, Marc André Detorakis, Georgios Diem, Alexandra K. Drix, Damien Enel, Pierre Girard, Benoît Guest, Olivia Hall, Matt G. Henriques, Rafael Neto Hinaut, Xavier Jaron, Kamil S. Khamassi, Mehdi Klein, Almar Manninen, Tiina Marchesi, Pietro McGlinn, Dan Metzner, Christoph Petchey, Owen L. Plesser, Hans Ekkehard Poisot, Timothée Ram, Karthik Ram, Yoav Roesch, Etienne Rossant, Cyrille Rostami, Vahid Shifman, Aaron Stimberg, Marcel Stachelek, Joseph Stollmeier, Frank Vaggi, Federico Viejo, Guillaume Vitay, Julien Vostinar, Anya Yurchak, Roman Zito, Tiziano INRIA Bordeaux Sud-Ouest Talence France Institut des Maladies Neurodégénératives Université de Bordeaux CNRS UMR 5293 Bordeaux France LaBRI Université de Bordeaux Bordeaux INP CNRS UMR 5800 Talence France Centre de Biophysique Moléculaire CNRS UPR4301 Orléans France Synchrotron SOLEIL Division Expériences Gif sur Yvette France Department of Electronic Systems Technical Faculty of IT and Design Aalborg University Denmark Department of Mechanical and Aerospace Engineering George Washington University WashingtonDC United States Department of Population Health and Reproduction University of California Davis DavisCA United States Instituut voor Theoretische Fysica KU Leuven Belgium Le Mans France Unité de Neurosciences Information et Complexité CNRS FRE 3693 Gif sur Yvette France Institut de Génétique et de Biologie Moléculaire et Cellulaire INSERM U964 CNRS UMR 7104 Université de Strasbourg Illkirch France Department of Cognitive Sciences University of California Irvine United States Computational Engineering and Design Faculty of Engineering and the Environment University of Southampton United Kingdom Department of Computer Science Humboldt-Universität zu Berlin Friedman Brain Institute Icahn School of Medicine Mount SinaiNY United States Institut des Systèmes Intelligent et de Robotique Sorbonne Universités UPMC Univ Paris 06 CNRS Paris France Experimental Psychology University College London United Kingdom UCL Great Ormond St Institute of Child Health University College London London United Kingdom MRC Cognition and Brain Sciences Unit Cambridge United Kingdom Department of Ecology and Evolution University of Lausanne Lausanne Switzerland Independent scholar Enschede Netherlands BioMediTech Institute and Faculty of Biomedical Sciences and Engineering Tampere University of Technology Tampere Finland Swammerdam Institute for Life Sciences Center for Neuroscience Faculty of Science University of Amsterdam Amsterdam Netherlands Depart

computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. Rescience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. Rescience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests. Copyright © 2017, The Authors. All rights reserved.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

From categorical to numerical: Multiple transitive distance learning and embedding

From categorical to numerical: Multiple transitive distance ...

引用

SIAM International Conference on data Mining 2015, SDM 2015

作者： Zhang, Kai Wang, Qiaojun Chen, Zhengzhang Marsic, Ivan Kumar, Vipin Jiang, Guofei Zhang, Jie School of Computer Science Southwest Petroleum University Chengdu Sichuan Province610500 China Institute of Data Science and Technology Alibaba Group SeattleWA98101 United States Department of Electrical and Computer Engineering Rutger-s the State University of New Jersey NJ08854 United States NEC Laboratories America Inc. PrincetonNJ08540 United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States Center for Computational Systems Biology Fudan University Shanghai200433 China

ISBN: (纸本)9781510811522

Categorical data are ubiquitous in real-world databases. However, due to the lack of an intrinsic proximity measure, many powerful algorithms for numerical data analysis may not work well on their categorical counterparts, making it a bottleneck in practical applications. In this paper, we propose a novel method to transform categorical data to numerical representations, so that abundant numerical learning methods can be exploited in categorical data mining. Our key idea is to learn a pairwise dissimilarity among categorical symbol-s, henceforth a continuous embedding, which can then be used for subsequent numerical treatment. There are two important criteria for learning the dissimilarities. First, it should capture the important "transitivity" which has shown to be particularly useful in measuring the proximity relation in categorical data. Second, the pairwise sample geometry arising from the learned symbol distances should be maximally consistent with prior knowledge (e.g., class labels) to obtain a good generalization performance. We achieve them through multiple transitive distance learning and embedding. Encouraging results are observed on a number of benchmark classification tasks against state-of-the-art. Copyright © SIAM.

关键词： Distance education

来源：评论

学校读者我要写书评

暂无评论

SimCon: A context simulator for supporting evaluation of smart building applications when faced with uncertainty

SimCon: A context simulator for supporting evaluation of sma...

引用

作者： McGlinn, Kris Hederman, Lucy Lewis, Dave Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Ireland

Smart Building Applications (SBAs) adapt their behaviour in response to context information generated by sensors present in the smart building. SBA developers must account for uncertainty in the accuracy of context information resulting from imperfection in the sensing technology and potentially complex interactions between the sensed phenomenon, the sensor and the physical environment. To address this challenge, context simulators which generate simulated context information have been developed. A number of key challenges must be addressed before such a simulation-based SBA prototyping approach can become widely used. First, any context simulator must be flexible in its approach to simulating context so that it supports evaluating different mixes of SBAs using a selection of methods most suitable to the evaluation task at hand. Second, the context simulator must support simulating uncertainty in context as uncertainty can cause an SBA to function incorrectly. Finally, the process of setting up a simulation should be efficient in use, satisfying to the developer and also, be effective in correctly evaluating the SBA behaviour. This paper presents the SimCon model which addresses these challenges by supporting simulation of context, in particular location context, with configurable levels of uncertainty for evaluating SBAs using visualisation. The SimCon model has been implemented in a simulation, configuration and visualisation tool set which has undergone a number of evaluations with SBA developers to determine and improve its level of usability, the most recent of which is presented here. © 2013 Elsevier B.V. All rights reserved.

关键词： Simulators

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：