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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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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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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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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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Mathematical Modelling of Electrically Controlled Filters of Microwave, subTHz and THz–bands on the Base of Grapheneand-Dielectric Multilayer Structure

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Journal of Physics: Conference Series 2020年第1期1443卷

作者： Smirnov, I A Cherckesova, L V Zhebrun, E A Kleimenkin, D V Department of Cybersecurity of Information Systems Don State Technical University Gagarin Sq. 1 Rostov–on–Don 344000 Russia Department of Cybersecurity of Information Systems Don State Technical University Gagarin Sq. 1 Rostov–on–Don 344000 Russia Department of Mathematics and Computer Sciences Don State Technical University Gagarin Sq. 1 Rostov–on–Don 344000 Russia Joint Stock Company “Research Institute of Microelectronic Equipment” “Progress” Cherepanov passage 54 Moscow 125183 Russia Information System and Radio engineering Department Don State Technical University Gagarin Sq. 1 Rostov–on–Don 344000 Russia

Report is devoted to investigations of graphene meta–surfaces for the transmission of radiation induced by plasmons in subTHz and THz ranges, cell of which consists of structures based on graphene ring and graphene nano–tape. It create regimes of radiation transmission – transparency windows induced by electric dipole resonances. Resonant frequency of transparency window can be dynamically tuned in wide band of subTHz and THz bands by changing the chemical potential (Fermi energy) of graphene by applying external electric field (gating) instead of re–fabricating of structures. Questions of possibilities of electronic controlled filters creating of subTHz and THz bands grounded on different configurations of graphene meta–surfaces are discussed; their characteristics and frequency dependencies are investigated. Mathematical modelling and electrodynamic calculation of the filters characteristics of subTHz and THz bands grounded on multilayer structures of “graphene–dielectric” type are carried out. From results of mathematical modelling it follows that periodic layered microstructures “graphene–dielectric” type can be used for creation of subTHz and THz bands broadband filters of planar construction, controlling by electric field and fast tuning at small changes in Fermi energy level of graphene.

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Motivation and Requirements for Quasi-Static Time Series (QSTS) for Distribution system Analysis

Motivation and Requirements for Quasi-Static Time Series (QS...

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IEEE Power and Energy Society General Meeting

作者： Matthew J. Reno Jeremiah Deboever Barry Mather Electric Power Systems Research Sandia National Laboratories School of Electrical and Computer Engineering Georgia Institute of Technology Power System Engineering Center National Renewable Energy Laboratory

ISBN: (纸本)9781538622131;9781538622124

Distribution system analysis with ever increasing numbers of distributed energy resources (DER) requires quasistatic time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system. Previous literature has demonstrated the benefits of QSTS, but there is limited information available for the requirements and standards for performing QSTS simulations. This paper provides a novel analysis of the QSTS requirements for the input data time-resolution, the simulation time-step resolution, and the length of the simulation. Detailed simulations quantify the specific errors introduced by not performing yearlong high-resolution QSTS simulations.

关键词： Photovoltaic systems Switches Time series analysis Indexes Distributed power generation

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A bilinear identification-modeling framework from time domain data

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PAMM 2019年第1期19卷

作者： Dimitrios S. Karachalios Ion Victor Gosea Athanasios C. Antoulas Max Planck Institute for Dynamics of Complex Technical Systems Data-Driven System Reduction and Identification (DRI) group Sandtorstraße 1 Magdeburg 39106 Rice University Houston Electrical and Computer Engineering Department 6100 Main St. Houston TX 77005 Baylor College of Medicine 1 Baylor Plaza Houston TX 77030

An ever-increasing need for improving the accuracy includes more involved and detailed features, thus inevitably leading to larger-scale dynamical systems [1]. To overcome this problem, efficient finite methods heavily rely on model reduction. One of the main approaches to model reduction of both linear and nonlinear systems is by means of interpolation. The Loewner framework is a direct data-driven method able to identify and reduce models derived directly from measurements. For measured data in the frequency domain, the Loewner framework is well established in linear case [2] while it has already extended to nonlinear [6]. On the other hand in the case of time domain data, the Loewner framework was already applied for approximating linear models [3]. In this study, an algorithm which uses time domain data for nonlinear (bilinear) system reduction and identification is presented.

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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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Hybrid cryptography and steganography method to embed encrypted text message within image

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Journal of Physics: Conference Series 2019年第1期1339卷

作者： Khider Nassif Jassim Ahmed Khudhur Nsaif Asama Kuder Nseaf Al Hamidy Hazidar Bagus Priambodo Emil Naf'an Mardhiah Masril Inge Handriani Zico Pratama Putra Department of Statistics. Faculty of Management and Economics Wasit University Al-Kut Iraq Department of Electrical Electronic & Systems Engineering Faculty of Engineering & Built Environment Universiti Kebangsaan Malaysia Malaysia Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia Malaysia Information System Faculty of Computer Science Universitas Mercu Buana Jl. Raya Meruya Selatan Kembangan Jakarta 11650 Universitas Putra Indonesia YPTK Padang 25221 Indonesia School of Electronic Engineering and Computer Science Queen Mary University of London

The businesses in various fields use the online communication application to gather their data and information with local and global sources. The gathered data may sensitive such as the financial and businesses development information. The hackers or online thief try to stole the valuable data i.e. credit card numbers. The organizations looking for secure online channels in order to transfer their data efficiently and avoid the data thieving. One of the most applicable methods that developed to secure the online transferred data is the cryptography which transfers the original data or information to encrypted formulation. Cryptography still has many drawbacks such as stole and decrypts the original texts using automatic decryption counter. The main aim of this research is to improve the cryptography securing level using supportive method which is Steganography. The Steganography is the processes of hide the data or information in media files such as video, images and audio files. There are four stages represent the methodology of this paper; (1) encrypt the original texts using RSA algorithm, (2) hide the encrypted texts in Image files, (3) extract the encrypted texts from Image files, and (4) decrypt the original texts using decryption key of RSA algorithm. It is expected to improve the security level of the online transferred textual data. The performance of the final results will be evaluated through compare the Image files quality before and after hide the data in these files. The quality of the original and stego Image files need to be same or near in order to maximize the difficulty of detect that there data hide in these files.

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Coarse-to-Fine Learning for Single-Image Super-Resolution

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IEEE Transactions on Neural Networks and Learning systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

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