检索结果-内蒙古大学图书馆

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Robert Demeter Attila Kovari Jozsef Katona Ilona Heldal Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania CogInfoCom Based LearnAbility Research Team Institute of Engineering Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Babes-Bolyai University Cluj-Napoca Romania Donders Centre for Cognition Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Netherland

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

The continued development of ICT technologies has led to new ways of information communication. As is well known, the success of any new training or communication technology incorporates disseminating information, timeliness and efficiency and often incorporates simulation and virtual reality technologies. This paper presents the results of a quantitative study showing that simulation-based training strategies are more effective than traditional methods. The current case is for applying didactic teaching methodologies for learning ICT concepts for complex systems. The paper also compares the results of this study with previous studies and recommends strategies for using virtual reality elements to streamline learning process of engineering students.

关键词： computer networks Software Tools Education Hardware Intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

The Data Mining OPtimization Ontology

SSRN

引用

SSRN 2018年

作者： Keet, C. Maria Lawrynowicz, Agnieszka d’Amato, Claudia Kalousis, Alexandros Nguyen, Phong Palma, Raul Stevens, Robert Hilario, Melanie Department of Computer Science University of Cape Town South Africa Institute of Computing Science Poznan University of Technology Poland Department of Computer Science University of Bari Italy Department of Business Informatics University Of Applied Sciences Switzerland Department of Computer Science University of Geneva Switzerland Poznan Supercomputing and Networking Center Poland School of Computer Science University of Manchester United Kingdom Artificial Intelligence Laboratory University of Geneva Switzerland

The Data Mining OPtimization Ontology (DMOP) has been developed to support informed decision-making at various choice points of the data mining process. The ontology can be used by data miners and deployed in ontology-driven information systems. The primary purpose for which DMOP has been developed is the automation of algorithm and model selection through semantic meta-mining that makes use of an ontology-based meta-analysis of complete data mining processes in view of extracting patterns associated with mining performance. To this end, DMOP contains detailed descriptions of data mining tasks (e.g., learning, feature selection), data, algorithms, hypotheses such as mined models or patterns, and workflows. A development methodology was used for DMOP, including items such as competency questions and foundational ontology reuse. Several non-trivial modeling problems were encountered and due to the complexity of the data mining details, the ontology requires the use of the OWL 2 DL profile. DMOP was successfully evaluated for semantic meta-mining and used in constructing the Intelligent Discovery Assistant, deployed at the popular data mining environment RapidMiner. © 2018, The Authors. 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

Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

引用

NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

来源：评论

学校读者我要写书评

暂无评论

Quantum computing for High-Energy Physics State of the Art and Challenges Summary of the QC4HEP Working Group

arXiv

引用

arXiv 2023年

作者： Di Meglio, Alberto Jansen, Karl Tavernelli, Ivano Alexandrou, Constantia Arunachalam, Srinivasan Bauer, Christian W. Borras, Kerstin Carrazza, Stefano Crippa, Arianna Croft, Vincent de Putter, Roland Delgado, Andrea Dunjko, Vedran Egger, Daniel J. Fernández-Combarro, Elias Fuchs, Elina Funcke, Lena González-Cuadra, Daniel Grossi, Michele Halimeh, Jad C. Holmes, Zoë Kühn, Stefan Lacroix, Denis Lewis, Randy Lucchesi, Donatella Martinez, Miriam Lucio Meloni, Federico Mezzacapo, Antonio Montangero, Simone Nagano, Lento Radescu, Voica Ortega, Enrique Rico Roggero, Alessandro Schuhmacher, Julian Seixas, Joao Silvi, Pietro Spentzouris, Panagiotis Tacchino, Francesco Temme, Kristan Terashi, Koji Tura, Jordi Tüysüz, Cenk Vallecorsa, Sofia Wiese, Uwe-Jens Yoo, Shinjae Zhang, Jinglei GenevaCH-1211 Switzerland CQTA Deutsches Elektronen-Synchrotron DESY Platanenallee 6 Zeuthen15738 Germany Computation-based Science and Technology Research Center The Cyprus Institute 20 Constantinou Kavafi str. Nicosia2121 Cyprus IBM Quantum IBM Research – Zurich Rüschlikon8803 Switzerland Department of Physics University of Cyprus PO Box 20537 Nicosia1678 Cyprus IBM Quantum IBM Research 1101 Kitchawan Rd Yorktown HeightsNY United States Physics Division LBNL - M/S 50A5104 1 Cyclotron Rd BerkeleyCA United States Deutsches Elektronen-Synchrotron DESY Notkestrasse 85 Hamburg22607 Germany RWTH Aachen University Templergraben 55 Aachen52062 Germany TIF Lab Dipartimento di Fisica Università degli Studi di Milano INFN Sezione di Milano Milan Italy Institut für Physik Humboldt-Universität zu Berlin Newtonstr. 15 Berlin12489 Germany haQaLi Applied Quantum Algorithms Leiden Netherlands Physics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Computer Science Facultad de Ciencias University of Oviedo Asturias33007 Spain Institute of Theoretical Phyiscs Leibniz University Hannover Hannover30167 Germany Physikalisch-Technische Bundesanstalt Braunschweig38116 Germany University of Bonn Nußallee 14-16 Bonn53115 Germany Institute for Theoretical Physics University of Innsbruck Innsbruck6020 Austria Institute for Quantum Optics and Quantum Information the Austrian Academy of Sciences Innsbruck6020 Austria Department of Physics Arnold Sommerfeld Center for Theoretical Physics Ludwig-Maximilians-Universität München Germany Munich Center for Quantum Science and Technology Germany LausanneCH-1015 Switzerland Paris-Saclay University CNRS IN2P3 IJCLab Orsay91405 France Department of Physics and Astronomy York University TorontoONM3J 1P3 Canada Department of Physics and Astronomy Università di Padova V. Marzolo 8 PadovaI-35131 Italy INFN - Sezione di Padova Via Marzolo 8 Padova35131 Italy Ni

Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage, namely a significant (in some cases exponential) speed-up of numerical simulations. The rapid development of hardware devices with various realizations of qubits enables the execution of small scale but representative applications on quantum computers. In particular, the high-energy physics community plays a pivotal role in accessing the power of quantum computing, since the field is a driving source for challenging computational problems. This concerns, on the theoretical side, the exploration of models which are very hard or even impossible to address with classical techniques and, on the experimental side, the enormous data challenge of newly emerging experiments, such as the upgrade of the Large Hadron Collider. In this roadmap paper, led by CERN, DESY and IBM, we provide the status of high-energy physics quantum computations and give examples for theoretical and experimental target benchmark applications, which can be addressed in the near future. Having the IBM 100 100 challenge in mind, where possible, we also provide resource estimates for the examples given using error mitigated quantum computing. © 2023, CC BY-SA.

关键词： High energy physics

来源：评论

学校读者我要写书评

暂无评论

Fairly allocating many goods with few queries

arXiv

引用

arXiv 2018年

作者： Oh, Hoon Procaccia, Ariel D. Suksompong, Warut Computer Science Department Carnegie Mellon University United States School of Engineering and Applied Sciences Harvard University United States School of Computing National University of Singapore Singapore

We investigate the query complexity of the fair allocation of indivisible goods. For two agents with arbitrary monotonic utilities, we design an algorithm that computes an allocation satisfying envy-freeness up to one good (EF1), a relaxation of envy-freeness, using a logarithmic number of queries. We show that the logarithmic query complexity bound also holds for three agents with additive utilities, and that a polylogarithmic bound holds for three agents with monotonic utilities. These results suggest that it is possible to fairly allocate goods in practice even when the number of goods is extremely large. By contrast, we prove that computing an allocation satisfying envy-freeness and another of its relaxations, envy-freeness up to any good (EFX), requires a linear number of queries even when there are only two agents with identical additive utilities. Copyright © 2018, The Authors. All rights reserved.

关键词： Additives

来源：评论

学校读者我要写书评

暂无评论

Matrix Factorization Based Collaborative Filtering with Resilient Stochastic Gradient Descent

Matrix Factorization Based Collaborative Filtering with Resi...

引用

International Joint Conference on Neural Networks

作者： Ashraf M. Abdelbar Islam Elnabarawy Khalid M. Salama Donald C. Wunsch Department of Mathematics and Computer Science Brandon University Brandon Manitoba Canada Applied Computational Intelligence Laboratory Missouri University of Science and Technology Rolla Missouri USA School of Computing University of Kent Canterbury UK

One of the leading approaches to collaborative filtering is to use matrix factorization to discover a set of latent factors that explain the pattern of preferences. In this paper, we apply a resilient stochastic gradient descent approach that uses only the sign of the gradient, similar to the R-Prop algorithm in neural network training, to matrix factorization for collaborative filtering. We evaluate the performance of our approach on the MovieLens 1M dataset, and find that test set accuracy markedly improves compared to standard gradient descent. As a follow-up experiment, we apply clustering to the learned item-factor matrix in factor space, and attempt to manually characterize each cluster of movies.

关键词： Motion pictures Collaboration Training Neural networks Standards Measurement Stochastic processes

来源：评论

学校读者我要写书评

暂无评论

Author Correction: Greengenes2 unifies microbial data in a single reference tree

引用

Nature biotechnology 2024年第5期42卷 813页

作者： Daniel McDonald Yueyu Jiang Metin Balaban Kalen Cantrell Qiyun Zhu Antonio Gonzalez James T Morton Giorgia Nicolaou Donovan H Parks Søren M Karst Mads Albertsen Philip Hugenholtz Todd DeSantis Se Jin Song Andrew Bartko Aki S Havulinna Pekka Jousilahti Susan Cheng Michael Inouye Teemu Niiranen Mohit Jain Veikko Salomaa Leo Lahti Siavash Mirarab Rob Knight Department of Pediatrics University of California San Diego School of Medicine La Jolla CA USA. Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Department of Computer Science and Engineering University of California San Diego La Jolla CA USA. School of Life Sciences Arizona State University Tempe AZ USA. Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA. Biostatistics & Bioinformatics Branch Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA. Halicioglu Data Science Institute University of California San Diego La Jolla CA USA. Australian Centre for Ecogenomics School of Chemistry and Molecular Biosciences The University of Queensland St Lucia Queensland Australia. Department of Obstetrics and Gynecology Columbia University New York NY USA. Department of Chemistry and Bioscience Aalborg University Aalborg Denmark. Department of Informatics Second Genome Brisbane CA USA. Center for Microbiome Innovation Jacobs School of Engineering University of California San Diego La Jolla CA USA. Finnish Institute for Health and Welfare Helsinki Finland. Institute for Molecular Medicine Finland FIMM-HiLIFE Helsinki Finland. Division of Cardiology Brigham and Women's Hospital Boston MA USA. Cedars-Sinai Medical Center Los Angeles CA USA. Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Victoria Australia. Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care University of Cambridge Cambridge UK. Division of Medicine Turku University Hospital and University of Turku Turku Finland. Sapient Bioanalytics LLC San Diego CA USA. Department of Computing University of Turku Turku Finland. Department of Pediatrics Uni

来源：评论

学校读者我要写书评

暂无评论

Prediction of cardiac arrest in intensive care patients through machine learning 3rd

Prediction of cardiac arrest in intensive care patients thro...

引用

3rd International Conference on Biomedical and Health Informatics, ICBHI 2017

作者： Akrivos, E. Papaioannou, V. Maglaveras, N. Chouvarda, I. Lab of Computing Medical Informatics and Biomedical Imaging Technologies Medical School Aristotle University of Thessaloniki Thessaloniki Greece Department of Internal Medicine 424 Military Hospital of Thessaloniki Thessaloniki Greece Alexandroupolis University Hospital/Intensive Care Unit Alexandroupoli Greece McCormick School of Engineering & Applied Sciences Department of Electrical Engineering & Computer Science Northwestern University EvastonIL60201 United States

ISBN: (纸本)9789811074189

Cardiac arrest is a critical health condition characterized by absence of traceable heart rate, patient’s loss of consciousness as well as apnea, with inhospital mortality of ~80%. Accurate estimation of patients at high risk is crucial to improve not only the survival rate, but also the quality of life as patients who survived from cardiac arrest have severe neurological effects. Existing research has focused on demonstrating static risk scores without taking account patient’s physiological condition. In this study, we are implementing an integrated model of sequential contrast patterns using Multichannel Hidden Markov Model. These models can capture relations between exposure and control group and offer high specificity results, with an average sensitivity of 78%, and have the ability to identify patients in high risk. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Examination of Gaze Fixations Recorded during the Trail Making Test

Examination of Gaze Fixations Recorded during the Trail Maki...

引用

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Attila Kovari Jozsef Katona Ilona Heldal Carsten Helgesen Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Robert Demeter CogInfoCom Based LearnAbility Research Team Institute of Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Faculty of Psychology and Educational Sciences Babes-Bolyai University Cluj-Napoca Romania Donders Centre for Cognition Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Netherland Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

The continuous visual tracking of activity performed in perception and action activities requires continuous eye motion. The visual computer monitoring, recording and evaluation of human motion provides many opportunities in the development of human-computer interfaces. In most activities performed by humans, eye-hand coordination plays a significant role. From the eye-hand coordination aspect, the fixation's direction is an essential factor, since before touching an object, the look is aimed at the object to be touched for a longer period. In this paper, the fixation playing a major role in eye-hand coordination is being analyzed during the Trail Making Test. The test primarily aims to measure visual searching or scanning, visual-spatial sequencing; however, the eye-hand coordination's speed plays a key role in the quick and accurate execution of the test. During the test, eye motion parameters were recorded and determined, where further analyses make certain human cognitive factors indirectly able to be analyzed.

关键词： Tracking Task analysis Conferences Visualization Software Testing Cognition

来源：评论

学校读者我要写书评

暂无评论

The use of cognitive maps in product development

The use of cognitive maps in product development

引用

International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Robert Demeter Attila Kovari Jozsef Katona Ilona Heldal Cristina Costescu Adrian Rosan Andrea Hathazi Serge Thill Department of Automation and Information Technology Faculty of Electrical Engineering and Computer Science Transilvania University of Brasov Brasov Romania CogInfoCom Based LearnAbility Research Team Institute of Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Computing Mathematics and Physics Western Norway University of Applied Sciences Bergen Norway Special Education Department Faculty of Psychology and Educational Sciences Babes-Bolyai University Cluj-Napoca Romania Donders Centre for Cognition Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Netherland

ISBN: (数字)9781728147932

ISBN: (纸本)9781728147949

The aim of this study is to view product traceability using graph-based simulation software, which gives us a cognitive map of a product's path. In this paper, we present a method for manufacturers to efficiently and automatically visualize all components of their products, allowing for multiple changes or fault event in the supply chain.

关键词： Conferences Cognition Education Tools Product development Informatics

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：