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Conceptual Design of Mobile Application for post-disaster Rapid Assessment of Damaged Houses

IOP Conference Series: Earth and Environmental Science 2019年第1期273卷

作者： I Setyawati K Munadi Y Idris Syamsidik S Muchallil Post Graduate of Disaster Science Program Syiah Kuala University Banda Aceh Indonesia Tsunami and Disaster Mitigation Research Center (TDMRC) Syiah Kuala University Banda Aceh Indonesia Electrical and Computer Engineering Department Syiah Kuala University Banda Aceh Indonesia Civil Engineering Department Syiah Kuala University Banda Aceh Indonesia

The current rapid assessment of post-earthquake damaged houses has been done manually. The determination of the damage level is also very subjective. Moreover, the available time during a rapid assessment and limited number of enumerators lead to ineffective decisions for responses and assistances. There are several application had appeared trying to answer the problems, but still they have many types of data that need to be input and even need a lot of time to process. The system design to be simple, more user-friendly and time efficient to be operated during the assessment. This study is aimed to develop a conceptual design of a system to collect data of houses damaged by earthquake using mobile application which propose to work both online and offline. The system will consists of five components: mobile device, user, data center (web server and database), internet, and data processing center (administrator and manager to verify and analyze the data). The application design to be integrated with Google Maps containing concise data entry to facilitate users (trained users and common users) and to shorten the time of data collection. Final collected data will be presented through the website and perform descriptive and spatial analysis.

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Implementation of Augmented Reality in Pretend Play Therapy for Children with Autism Spectrum Disorder

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Journal of Physics: Conference Series 2019年第1期1235卷

作者： M F Syahputra A P Angkasih S Purnamawati U Andayani D Abdullah S Sriadhi A Iskandar T M Rosida J Fitriany I N Sari M D Utama R F Nanuru Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30˚.

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Implementation Method CUSUM To Determine The Accident Prone Areas in Web Based

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Rozzi Kesuma Dinata Dahlan Abdullah H Hartono Cut Ita Erliana Berliana Kusuma Riasti Akbar Iskandar Ifit Novita Sari Nurmawati Ricardo Freedom Nanuru Lusi Dwi Putri Rosida Tiurma Manurung S. Sriadhi A A Saleh T Astari Muammar Khaddafi Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta. Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial & Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Aceh Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013.

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Retraction: Implementation Method CUSUM To Determine The Accident Prone Areas in Web Based (J. Phys.: Conf. Ser. 1114 012093)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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Electronic nose in differentiating and ascertaining clinical status among patients with pulmonary nontuberculous mycobacteria: A prospective multicenter study

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The Journal of infection 2023年第3期87卷 255-258页

作者： Meng-Rui Lee Hung-Ling Huang Wei-Chang Huang Shang-Yu Wu Pang-Chun Liu Jui-Ching Wu Meng-Hsuan Cheng Chau-Chyun Sheu Kea-Tiong Tang Jann-Yuan Wang Chao-Chi Ho Jin-Yuan Shih Inn-Wen Chong Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan. Department of Internal Medicine Kaohsiung Municipal Ta-Tung Hospital Kaohsiung Taiwan Division of Pulmonary and Critical Care Medicine Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan. Division of Chest Medicine Department of Internal Medicine Taichung Veterans General Hospital Taichung Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan Mycobacteria Center of Excellence Department of Internal Medicine Taichung Veterans General Hospital Taichung Taiwan School of Medicine Chung Shan Medical University Taichung 402 Taiwan Ph.D. Program in Translational Medicine National Chung Hsing University Taichung 402 Taiwan Department of Medical Technology Jen-Teh Junior College of Medicine Nursing and Management Miaoli Taiwan. Department. of Electrical Engineering National Tsing Hua University Hsinchu Taiwan. Division of Pulmonary and Critical Care Medicine Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan. Department. of Electrical Engineering National Tsing Hua University Hsinchu Taiwan. Electronic address: kttang@ee.nthu.edu.tw. Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan. Electronic address: jywang@ntu.edu.tw. Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Respiratory Therapy Kaohsiung Medical University Hospital Kaohsiung Taiwan Department of Biological Science & Technology National Chiao Tung University Hsin-Chu Taiwan.

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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