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2nd Nommensen International Conference on Technology and engineering, NICTE 2018

作者： Iskandar, Akbar Fahlepi Tuasamu, Muhammad Resa Syamsu, Suryadi Mansyur, M. Listyorini, Tri Sallu, Sulfikar Supriyono, S. Saddhono, Kundharu Napitupulu, Darmawan Rahim, Robbi Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Negeri Makassar Makassar Indonesia Informatics Engineering Universitas Maria Kudus Central Java Indonesia Computer Information Systems Universitas Sembilan Belas November Kolaka Indonesia Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia Indonesian Language Education Departement Faculty of Teacher Training and Education Universitas Sebelas Maret Surakarta Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia Sekolah Tinggi Ilmu Manajemen Sukma Medan Indonesia

computer and web security system is an attempt to avoid attacks from crackers because a form and method of crime on internet network can not be predicted. Therefore, we just keep trying to use various methods in securing the system that is running. It is the same in web testing that can be accessed online by people who are not responsible from along distance to change and remove the test results or even damage the web testing system. So, the purpose of this paper is to design and implement web security testing system by using semantic comparison method to avoid structured query language injection (SQLI) attack and to do security on web testing application using Message Digest 5 encryption (MD5). Research data were obtained by using direct observation and documentation and literature review. After the design and application of the system, it can be obtained that by using semantic comparison method in web testing can prevent the occurrence of SQL injection attacks and can secure account from web testing users by using MD5. © Published under licence by IOP Publishing Ltd.

关键词： Semantics

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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Towards an algorithm and communication cost model for the parallel particle swarm optimization 29th

Towards an algorithm and communication cost model for the pa...

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29th International Conference on architecture of Computing systems, ARCS 2016

作者： Shuka, Romeo Niemann, Sebastian Brehm, Jürgen Müller-Schloer, Christian Institute of Systems Engineering System and Computer Architecture Leibniz Universität Hannover Hannover Germany

ISBN: (纸本)9783800741571

The adaptation of sequential algorithms for High Performance Computing (HPC) systems is determined by a tradeoff between algorithmic effectiveness (software) and communication frequency (hardware) of the parallel implementation (efficiency). To get a better understanding of the correlation, we define simple models for both, software and hardware, in order to dynamically find the best mapping parameters for the execution of the algorithm on the parallel system. For the evaluation of our method we look at population-based algorithms like the Particle Swarm Optimization Algorithm (PSO) for the solution of optimization problems. Different goals like best quality of the solution of the optimization problem for a given execution time or best execution time to find the optimum are defined by the user. Our method enables us to find the best parameters for the mapping which then results in an efficient and effective parallel implementation to achieve the user-defined goals on a High Performance Computing Cluster (HPCC). © VDE VERLAG GMBH.

关键词： Mapping

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Hearing loss prevalence and years lived with disability, 1990-2019: Findings from the Global Burden of Disease Study 2019

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The Lancet 2021年第10278期397卷 996-1009页

作者： Haile, Lydia M. Kamenov, Kaloyan Briant, Paul Svitil Orji, Aislyn U. Steinmetz, Jaimie D. Abdoli, Amir Abdollahi, Mohammad Abu-Gharbieh, Eman Afshin, Ashkan Ahmed, Haroon Rashid, Tarik Ahmed Akalu, Yonas Alahdab, Fares Alanezi, Fahad Mashhour Alanzi, Turki M. Al Hamad, Hanadi Ali, Liaqat Alipour, Vahid Al-Raddadi, Rajaa M. Amu, Hubert Arabloo, Jalal Arab-Zozani, Morteza Arulappan, Judie Ashbaugh, Charlie Atnafu, Desta Debalkie Babar, Zaheer-Ud-Din Baig, Atif Amin Banik, Palash Chandra Bärnighausen, Till Winfried Barrow, Amadou Bender, Rose G. Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bibi, Sadia Bijani, Ali Burkart, Katrin Cederroth, Christopher R. Charan, Jaykaran Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Dagnew, Amare Belachew Dagnew, Baye Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Desalew, Assefa Dhamnetiya, Deepak Dhimal, Mandira Lamichhane Dhimal, Meghnath Doyle, Kerrie E. Duncan, Bruce B. Ekholuenetale, Michael Filip, Irina Fischer, Florian Franklin, Richard Charles Gaidhane, Abhay Motiramji Gaidhane, Shilpa Gallus, Silvano Ghamari, Farhad Ghashghaee, Ahmad Ghozali, Ghozali Gilani, Syed Amir Glǎvan, Ionela-Roxana Golechha, Mahaveer Goulart, Barbara Niegia Garcia Gupta, Veer Bala Gupta, Vivek Kumar Hamidi, Samer Hammond, Billy Randall Hay, Simon I. Hayat, Khezar Heidari, Golnaz Hoffman, Howard J. Hopf, Kathleen Pillsbury Hosseinzadeh, Mehdi Househ, Mowafa Hussain, Rabia Hwang, Bing-Fang Iavicoli, Ivo Ibitoye, Segun Emmanuel Ilesanmi, Olayinka Stephen Irvani, Seyed Sina Naghibi Islam, Sheikh Mohammed Shariful Iwagami, Masao Jacob, Louis Jayapal, Sathish Kumar Jha, Ravi Prakash Jonas, Jost B. Kalhor, Rohollah Al-Salihi, Nawzad Kameran Kandel, Himal Kasa, Ayele Semachew Kayode, Gbenga A. Khalilov, Rovshan Khan, Ejaz Ahmad Khatib, Mahalaqua Nazli Kosen, Soewarta Koyanagi, Ai Kumar, G. Anil Landires, Ivan Lasrado, Savita Lim, Stephen S. Liu, Xuefeng Lobo, Stany W. Lugo, Alessandra Makki, Alaa Mendoza, Walter Mersha, Amanual Getnet Mihretie, Kebadnew Mulatu Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Noncommunicable Diseases World Health Organization (WHO) Geneva Switzerland Department of Parasitology and Mycology Jahrom University of Medical Sciences Jahrom Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran University of Medical Sciences Tehran Iran School of Pharmacy Tehran University of Medical Sciences Tehran Iran Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Department of Biosciences COMSATS Institute of Information Technology Islamabad Pakistan Department of Computer Science and Engineering University of Kurdistan Hewler Erbil Iraq Department of Medical Physiology University of Gondar Gondar Ethiopia Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Health Information Management and Technology Department Dammam Saudi Arabia Geriatric and Long Term Care Department Hamad Medical Corporation Doha Qatar Rumailah Hospital Hamad Medical Corporation Doha Qatar Department of Biological Sciences National University of Medical Sciences (NUMS) Rawalpindi Pakistan Health Management and Economics Research Center Tehran Iran Department of Community Medicine King Abdulaziz University Jeddah Saudi Arabia Department of Population and Behavioural Sciences University of Health and Allied Sciences Ho Ghana Social Determinants of Health Research Center Birjand University of Medical Sciences Birjand Iran Department of Maternal and Child Health Sultan Qaboos University Muscat Oman Department of Health System and Health Economics Bahir Dar University Bahir Dar Ethiopia Department of Pharmacy University of Huddersfield Huddersfield United Kingdom Unit of Biochemistry Universiti

Background: Hearing loss affects access to spoken language, which can affect cognition and development, and can negatively affect social wellbeing. We present updated estimates from the Global Burden of Disease (GBD) study on the prevalence of hearing loss in 2019, as well as the condition's associated disability. Methods: We did systematic reviews of population-representative surveys on hearing loss prevalence from 1990 to 2019. We fitted nested meta-regression models for severity-specific prevalence, accounting for hearing aid coverage, cause, and the presence of tinnitus. We also forecasted the prevalence of hearing loss until 2050. Findings: An estimated 1·57 billion (95% uncertainty interval 1·51–1·64) people globally had hearing loss in 2019, accounting for one in five people (20·3% [19·5–21·1]). Of these, 403·3 million (357·3–449·5) people had hearing loss that was moderate or higher in severity after adjusting for hearing aid use, and 430·4 million (381·7–479·6) without adjustment. The largest number of people with moderate-to-complete hearing loss resided in the Western Pacific region (127·1 million people [112·3–142·6]). Of all people with a hearing impairment, 62·1% (60·2–63·9) were older than 50 years. The Healthcare Access and Quality (HAQ) Index explained 65·8% of the variation in national age-standardised rates of years lived with disability, because countries with a low HAQ Index had higher rates of years lived with disability. By 2050, a projected 2·45 billion (2·35–2·56) people will have hearing loss, a 56·1% (47·3–65·2) increase from 2019, despite stable age-standardised prevalence. Interpretation: As populations age, the number of people with hearing loss will increase. Interventions such as childhood screening, hearing aids, effective management of otitis media and meningitis, and cochlear implants have the potential to ameliorate this burden. Because the burden of moderate-to-complete hearing loss is concentrated in countries with low health-ca

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PHP: Power hungry pattern generation at higher abstraction level

PHP: Power hungry pattern generation at higher abstraction l...

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East-West Design & Test Symposium (EWDTS)

作者： Rohini Gulve Anshu Goel Virendra Singh Computer Architecture and Dependable Systems Lab Electrical Engineering Indian Institute of Technology Bombay India

The Performance, area, and power are most essential factors to be considered and optimize at every step in the design cycle. Design engineers often need to learn about these factors in order make right decisions on design strategies. Power analysis at lower levels of abstraction can provide more accurate analysis than higher levels. Worst case power can be estimated through high activity pattern generation. However, generation of such power hungry patterns (PHP) become challenging as the number of modules or design components increases. This process can be accelerated at higher abstraction levels by utilizing the available information. In this paper, we generate PHP by at higher abstraction level with significant speed up. A genetic algorithm is implemented to find out the global maximum power of designs. An experiment indicates that the process implemented is much faster and it finds about 10 % more power demanding PHP than random samples generated.

关键词： Mathematical model Genetic algorithms Integrated circuit modeling Logic gates Power demand Optimization Libraries

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Publisher Correction: Deep neural networks for automated detection of marine mammal species

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Scientific reports 2020年第1期10卷 11000页

作者： Yu Shiu K J Palmer Marie A Roch Erica Fleishman Xiaobai Liu Eva-Marie Nosal Tyler Helble Danielle Cholewiak Douglas Gillespie Holger Klinck Center for Conservation Bioacoustics Cornell Lab of Ornithology Cornell University Ithaca NY 14850 USA. ys587@cornell.edu. Department of Computer Science San Diego State University San Diego CA 92182 USA. Department of Fish Wildlife and Conservation Biology Colorado State University Fort Collins CO 80523 USA. Department of Ocean and Resources Engineering University of Hawai'i at Mānoa Honolulu HI 96822 USA. US Navy Space and Naval Warfare Systems Command System Center Pacific San Diego CA 92152 USA. Northeast Fisheries Science Center National Marine Fisheries Service National Oceanic and Atmospheric Administration Woods Hole MA 02543 USA. Sea Mammal Research Unit Scottish Oceans Institute University of St. Andrews St Andrews Fife KY16 8LB Scotland. Center for Conservation Bioacoustics Cornell Lab of Ornithology Cornell University Ithaca NY 14850 USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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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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Erratum to: Search for heavy Higgs bosons decaying to a top quark pair in proton-proton collisions at s = 13 TeV

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Journal of High Energy Physics 2022年第3期2022卷 1-21页

作者： Sirunyan, A. M. Tumasyan, A. Adam, W. Ambrogi, F. Bergauer, T. Brandstetter, J. Dragicevic, M. Erö, J. Escalante Del Valle, A. Flechl, M. Frühwirth, R. Jeitler, M. Krammer, N. Krätschmer, I. Liko, D. Madlener, T. Mikulec, I. Rad, N. Schieck, J. Schöfbeck, R. Spanring, M. Spitzbart, D. Waltenberger, W. Wulz, C.-E. Zarucki, M. Drugakov, V. Mossolov, V. Suarez Gonzalez, J. Darwish, M. R. De Wolf, E. A. Di Croce, D. Janssen, X. Lauwers, J. Lelek, A. Pieters, M. Rejeb Sfar, H. Van Haevermaet, H. Van Mechelen, P. Van Putte, S. Van Remortel, N. Blekman, F. Bols, E. S. Chhibra, S. S. D’Hondt, J. De Clercq, J. Lontkovskyi, D. Lowette, S. Marchesini, I. Moortgat, S. Moreels, L. Python, Q. Skovpen, K. Tavernier, S. Van Doninck, W. Van Mulders, P. Van Parijs, I. Beghin, D. Bilin, B. Brun, H. Clerbaux, B. De Lentdecker, G. Delannoy, H. Dorney, B. Favart, L. Grebenyuk, A. Kalsi, A. K. Luetic, J. Popov, A. Postiau, N. Starling, E. Thomas, L. Vander Velde, C. Vanlaer, P. Vannerom, D. Cornelis, T. Dobur, D. Khvastunov, I. Niedziela, M. Roskas, C. Trocino, D. Tytgat, M. Verbeke, W. Vermassen, B. Vit, M. Zaganidis, N. Bondu, O. Bruno, G. Caputo, C. David, P. Delaere, C. Delcourt, M. Giammanco, A. Lemaitre, V. Magitteri, A. Prisciandaro, J. Saggio, A. Vidal Marono, M. Vischia, P. Zobec, J. Alves, F. L. Alves, G. A. Correia Silva, G. Hensel, C. Moraes, A. Rebello Teles, P. Belchior Batista Das Chagas, E. Carvalho, W. Chinellato, J. Coelho, E. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. De Oliveira Martins, C. Fonseca De Souza, S. Huertas Guativa, L. M. Malbouisson, H. Martins, J. Matos Figueiredo, D. Medina Jaime, M. Melo De Almeida, M. Mora Herrera, C. Mundim, L. Nogima, H. Prado Da Silva, W. L. Sanchez Rosas, L. J. Santoro, A. Sznajder, A. Thiel, M. Tonelli Manganote, E. J. Torres Da Silva De Araujo, F. Vilela Pereira, A. Ahuja, S. Bernardes, C. A. Calligaris, L. Fernandez Perez Tomei, T. R. Gregores, E. M. Lemos, D. S. Mercadante, P. G. Novaes, S. F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Vienna University of Technology Vienna Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Federal de Pelotas Pelotas Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of NRC ‘Kurchatov Institute’ Moscow Russia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Joint Institute for Nuclear Research Dubna Russia Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Cairo University Cairo Egypt Academy of Scientific Research and Technolog

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A Pattern Division Multiple Access Scheme with Low Complexity Iterative Receiver for 5G Wireless Communication systems

A Pattern Division Multiple Access Scheme with Low Complexit...

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IEEE Vehicular Technology Conference

作者： Kai Zhang Jin Xu Changchuan Yin Chunyu Pan Weiqiang Tan Guixian Xu Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing 100876 P. R. China Zhengzhou University of Light Industry School of Computer and Communication Engineering Zhengzhou 450001 P. R. China Guangzhou University School of Computer Science and Educational Software Guangzhou 510006 P. R. China Aalborg University Department of Electronic Systems Aalborg 9400 Denmark

ISBN: (纸本)9781538663592;9781538663585

Non-orthogonal multiple access schemes with higher spectral efficiency and the capability of accessing more users than orthogonal multiple access (OMA) scheme is preferred for the fifth generation (5G) wireless networks. In this work, a non-orthogonal transmission scheme called pattern division multiple access (PDMA) is proposed for the 5G wireless communication systems. Two pattern matrices are proposed for 150% and 200% overloaded PDMA systems. Then, a low complexity symbol-wise belief propagation iterative detection and decoding (BPIDD) algorithm for multiple user detection is proposed. Numerical results and analysis provided by utilizing extrinsic information transfer chart show that the proposed scheme outperforms the traditional OMA systems significantly, and the performance of the proposed scheme is better than that of the existing schemes up to 1 dB. Finally, simulation results show that the proposed scheme is superior to the existing schemes and the proposed BPIDD algorithm is better than that of the BP algorithm over 0.5 dB.

关键词： 5G mobile communication iterative decoding matrix algebra multi-access systems multiuser detection Multi access systems matrix algebra Multiuser detection Iterative decoding multiple access Wireless communication systems Scheme iterative receiver spectral efficiency Information Transfer

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Model-driven deep learning for physical layer communications

arXiv

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arXiv 2018年

作者： He, Hengtao Jin, Shi Wen, Chao-Kai Gao, Feifei Li, Geoffrey Ye Xu, Zongben National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan State Key Lab of Intelligent Technologies and Systems Tsinghua University Department of Automation Tsinghua University Beijing China School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Institute for Information and System Sciences Xian Jiaotong University Xi'an710049 China

Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and demonstrated an impressive performance improvement in recent years. However, most of the existing works related to DL focus on data-driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, modeldriven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model-driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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