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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Álvarez-Caballero, Antonio Merelo, J.J. Sánchez, Pablo García Fernández-Ares, A. Department of Computer Architecture and Computer Technology University of Granada Spain Department of Computer Science University of Cádiz Spain

ISBN: (纸本)9789897582745

A fast and precise prediction of the outcome of a game is essential for the design of bots that play the game;it can be used either offline as a fast way to design bot strategies or online for conserving resources and conceding defeat or speed up victory, as well as evaluating the consequences of actions. The objective of this paper is predicting the winner of a StarCraft match as soon as possible. This study is done with supervised learning, because a lot of suitable data is available. The main problem of this approach is the big amount of generated data, so it has to be selected and organised properly and be treated with proper tools. A set of six learning algorithms is used, from simpler ones to more complex algorithms. Spark and MLlib are used due to their capabilities to deal with big amounts of data. With the learned models, time of matches are restricted, trying to get a time bound for predicting results. With this approach we get that it is not necessary to play a whole match to predict its winner with high accuracy: with 10 minutes we can predict the outcome with 90% of accuracy. Copyright © 2017 by SCITEPRESS - Science and technology Publications, Lda. All rights reserved.

关键词： Forecasting

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Impact of High Particle Flux in Radiation Ground Tests with Protons

Impact of High Particle Flux in Radiation Ground Tests with ...

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European Conference on Radiation and its Effects on Components and Systems (RADECS)

作者： Mohammadreza Rezaei Pedro Martí n-Holgado Yolanda Morilla Francisco J. Franco Juan Carlos Fabero Hortensia Mecha Helmut Puchner Guillaume Hubert Juan Antonio Clemente Computer Architecture Department Facultad de Inform&#x00E1 tica Universidad Complutense de Madrid (UCM) Madrid Spain Centro Nacional de Aceleradores (Universidad de Sevilla CSIC JA) Sevilla Spain EMFTEL Dep. Institute of Particle and Cosmos Physics (IPARCOS) Fac. de F&#x00ED sica Universidad Complutense de Madrid (UCM) Madrid Spain Cypress Semiconductor Technology R&#x0026 D San Jose CA USA ONERA French Aerospace Laboratory Toulouse France

This abstract presents an experimental study of the impact of using a high flux in radiation ground tests on the measured cross-section of SRAMs. Experimental results obtained with 15 MeV protons will show that using ... 详细信息

ISBN: (数字)9781665412353

ISBN: (纸本)9781665429597

关键词： Protons Sensitivity Atmospheric measurements Europe Neutrons Particle measurements

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Genetic algorithm optimized support vector machine in noma-based satellite networkswith imperfect csi

arXiv

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arXiv 2020年

作者： Yan, Xiaojuan An, Kang Wang, Cheng-Xiang Zhu, Wei-Ping Li, Yusheng Feng, Zhiqiang National Mobile Commun. Research Lab School of Info. Science and Eng. Southeast University Nanjing210096 China College of Mechanical Naval Architecture and Ocean Engineering Beibu Gulf University Qinzhou535011 China Sixty-third Research Institute National University of Defense Technology Nanjing210007 China Purple Mountain Laboratories Nanjing211111 China Department of Electrical and Computer Engineering Concordia University MontrealQCH3G 1M8 Canada

With the help of a power-domain non-orthogonal multiple access (NOMA) scheme, satellite networks can simultaneously serve multiple users within limited time/spectrum resource block. However, the existence of channel estimation errors inevitably degrade the judgment on users' channel state information (CSI) accuracy, thus affecting the user pairing processing and suppressing the superiority of the NOMA scheme. Inspired by the advantages ofmachine learning (ML) algorithms, we propose an improved support vector machine (SVM) scheme to reduce the inappropriate user pairing risks and enhance the performance of NOMA based satellite networks with imperfect CSI. Particularly, a genetic algorithm (GA) is employed to optimize the regularization and kernel parameters of the SVM, which effectively improves the classification accuracy of the proposed scheme. Simulations are provided to demonstrate that the performance of the proposed method is better than that with random user paring strategy, especially in the scenario with a large number of users. Copyright © 2020, The Authors. All rights reserved.

关键词： Genetic algorithms

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Towards spatial integration of qualitative data for urban transformation – challenges with automated geovisualization of perception of urban places

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IOP Conference Series: Earth and Environmental Science 2020年第5期588卷

作者： L Thuvander F Latino C Zangelidis M Adelfio V Naserentin A Logg Department of Architecture and Civil Engineering Chalmers University of Technology 412 96 Gothenburg Sven Hultins gata 6 Sweden Department of Mathematical Sciences Chalmers University of Technology 412 96 Gothenburg Chalmers tvärgata 3 Sweden Department of Electrical and Computer Engineering Aristotle University of Thessaloniki 54124 Thessaloniki Greece

Urban planning needs to face and integrate ecological, social, and economic aspects of city living. So far, attempts to integrate different urban simulation models into one technical platform have focused on quantitative data. The aim of this paper is to present the preparation for an automated method to spatially integrate and visualize interview-based qualitative data on the perception of urban places into a virtual platform. The Gothenburg suburb of Hammarkullen is used as a case study. Two CAQDAS software, NVivo and ***, were tested. In both software, locations and urban qualities were coded and clustered. Visualization strategies such as information tree structures, geo-coded quotations, spatial word clouds, linked to 2D maps and 3D environments were developed. Results identify the challenges to overcome and show limitations of the software in terms of creating graphs and relationships as well as automated geocoding of data to maps. The project offers a step towards the integration of qualitative (social) data into digital environments that can be scaled up. By that, it contributes with a new dimension of analysis of urban environments which is necessary for sustainable transformation of cities.

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Ranking-based deep cross-modal hashing

arXiv

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arXiv 2019年

作者： Liu, Xuanwu Yu, Guoxian Domeniconi, Carlotta Wang, Jun Ren, Yazhou Guo, Maozu College of Computer and Information Sciences Southwest University Chongqing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China Department of Computer Science George Mason University Fairfax United States SMILE Lab School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Cross-modal hashing has been receiving increasing interests for its low storage cost and fast query speed in multi-modal data retrievals. However, most existing hashing methods are based on hand-crafted or raw level features of objects, which may not be optimally compatible with the coding process. Besides, these hashing methods are mainly designed to handle simple pairwise similarity. The complex multilevel ranking semantic structure of instances associated with multiple labels has not been well explored yet. In this paper, we propose a ranking-based deep cross-modal hashing approach (RDCMH). RDCMH firstly uses the feature and label information of data to derive a semi-supervised semantic ranking list. Next, to expand the semantic representation power of hand-crafted features, RDCMH integrates the semantic ranking information into deep cross-modal hashing and jointly optimizes the compatible parameters of deep feature representations and of hashing functions. Experiments on real multi-modal datasets show that RDCMH outperforms other competitive baselines and achieves the state-of-the-art performance in cross-modal retrieval applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

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The Sequential Algorithm for Combined State of Charge and State of Health Estimation of Lithium Ion Battery based on Active Current Injection

arXiv

引用

arXiv 2019年

作者： Song, Ziyou Hou, Jun Li, Xuefeng Wu, Xiaogang Hu, Xiaosong Hofmann, Heath Sun, Jing Department of Naval Architecture and Marine Engineering University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States College of Electrical and Electronics Engineering Harbin University of Science and Technology Harbin150080 China Department of Automotive Engineering Chongqing University Chongqing400044 China

When State of Charge, State of Health, and parameters of the Lithium-ion battery are estimated simultaneously, the estimation accuracy is hard to be ensured due to uncertainties in the estimation process. To improve the estimation performance a sequential algorithm, which uses frequency scale separation and estimates parameters/states sequentially by injecting currents with different frequencies, is proposed in this paper. Specifically, by incorporating a high-pass filter, the parameters can be independently characterized by injecting high-frequency and medium-frequency currents, respectively. Using the estimated parameters, battery capacity and State of Charge can then be estimated concurrently. Experimental results show that the estimation accuracy of the proposed sequential algorithm is much better than the concurrent algorithm where all parameters/states are estimated simultaneously, and the computational cost can also be reduced. Finally, experiments are conducted under different temperatures to verify the effectiveness of the proposed algorithm for various battery *** Codes 93B99 Copyright © 2019, The Authors. All rights reserved.

关键词： State of charge

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Broadband Waveguide Cloak for Water Waves

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Physical Review Letters 2019年第7期123卷 074501-074501页

作者： Siyuan Zou Yadong Xu Razafizana Zatianina Chunyang Li Xu Liang Lili Zhu Yongqiang Zhang Guohua Liu Qing Huo Liu Huanyang Chen Zhenyu Wang College of Civil Engineering and Architecture Zhejiang University Hangzhou 310058 China Institute of Electromagnetics and Acoustics and Key Laboratory of Electromagnetic Wave Science and Detection Technology Xiamen University Xiamen 361005 China School of Physical Science and Technology and Jiangsu Key Laboratory of Thin Films Soochow University Suzhou 215006 China Ocean College Zhejiang University Zhoushan 316021 China Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA

Inspired by electromagnetic waveguide cloaks with gradient index metamaterials, we fabricated a broadband cloak with simply a gradient depth profile on the bottom and without any other structures on the top to confine water waves in a certain area for cloaking regions. The new physics of mode conversion for water waves is first found. The experimental and numerical simulation results are in good agreement and show that the presented device has a nice performance for various situations and is feasible over a broadband of working frequencies. Being easy to construct, this design is potentially of significance for port applications.

关键词： Cloaking Flow instability Hydrodynamic instabilities Thin fluid films Navier-Stokes equation

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Music, Computing, and Health: A Roadmap for the Current and Future Roles of Music technology for Health Care and Well-Being

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Music and Science 2021年 4卷

作者： Agres, Kat R. Schaefer, Rebecca S. Volk, Anja van Hooren, Susan Holzapfel, Andre Dalla Bella, Simone Müller, Meinard de Witte, Martina Herremans, Dorien Ramirez Melendez, Rafael Neerincx, Mark Ruiz, Sebastian Meredith, David Dimitriadis, Theo Magee, Wendy L. Yong Siew Toh Conservatory of Music National University of Singapore Singapore Social and Cognitive Computing Department Institute of High Performance Computing A*STAR Singapore Institute for Psychology Health Medical Neuropsychology Unit Leiden University Leiden Netherlands Leiden Institute for Brain and Cognition Leiden University Leiden Netherlands Academy of Creative and Performing Arts Leiden University Leiden Netherlands Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Faculty of Health care Department of Arts Therapies Zuyd University of Applied Sciences Heerlen Netherlands KenVaK Research Centre for the Arts Therapies and Psychomotricity Heerlen Netherlands Faculty of Psychology Open University of The Netherlands Heerlen Netherlands Division of Media Technology and Interaction Design KTH Royal Institute of Technology Stockholm Sweden International Laboratory for Brain Music and Sound Research (BRAMS) Outremont QC Canada Department of Psychology University of Montreal Montreal QC Canada Centre for Research on Brain Language and Music (CRBLM) Montreal QC Canada University of Economics and Human Sciences in Warsaw Warsaw Poland International Audio Laboratories Erlangen Friedrich-Alexander Universität Erlangen-Nürnberg Erlangen Germany HAN University of Applied Sciences Department of Arts Therapies and Psychological Studies Nijmegen Netherlands University of Amsterdam Research Institute of Child Development and Education Amsterdam Netherlands Treatment Centre for People with Mild Intellectual Disabilities and Psychiatric and Behavioral Disorders Gennep Netherlands Information Systems Technology and Design Singapore University of Technology and Design Singapore Music and Machine Learning Lab Music Technology Group Universitat Pompeu Fabra Barcelona Spain Faculty of EEMCS Interactive Intelligence Group Delft University of Technology Delft Netherlands Centre for Digital Music School of Electronic Engineerin

The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field. © The Author(s) 2021.

关键词： health care interdisciplinarity MedTech music information retrieval (MIR) music neuroscience Music psychology music technology music therapy well-being

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Network Node Resource Risk Assessment Based on Bayesian Belief Network Model

Network Node Resource Risk Assessment Based on Bayesian Beli...

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

作者： Jun Li YuQiang Liu Yan Niu Hui Zhang Department of Computer Science Hubei University of Technology Wuhan China School of Civil Engineering Architecture and Environment Hubei University of Technology Wuhan China

ISBN: (纸本)9781538676738;9781538676721

Network attacks will bring network node resource risks. In this paper, the time series of memory usage rate, network traffic and CPU utilization rate are selected as the research objects, and the network node resources are interrelated. Based on this feature, a network node resource risk assessment method based on Bayesian belief network is designed, and the single risk and total risk of network node resources are quantified. The results show that this method can effectively evaluate the network node resource risk, and fully consider the internal correlation between network node resources, and provide a new method for risk assessment of network node resources. The effect of this method is better than the traditional K-Means clustered method and decision tree method.

关键词： Risk management Bayes methods Civil engineering computer architecture Time series analysis Telecommunication traffic Correlation

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