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Natural language processing: State of the art, current trends and challenges

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arXiv 2017年

作者： Khurana, Diksha Koli, Aditya Khatter, Kiran Singh, Sukhdev Department of Computer Science and Engineering Manav Rachna International University Faridabad121004 India Accendere Knowledge Management Services Pvt. Ltd. India

Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. The paper distinguishes four phases by discussing different levels of NLP and components of Natural Language Generation (NLG) followed by presenting the history and evolution of NLP, state of the art presenting the various applications of NLP and current trends and challenges. Copyright © 2017, The Authors. All rights reserved.

关键词： Natural language processing systems

Addressing Societal Issues Through MOOCs in Southeast Asia

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Addressing Societal Issues Through MOOCs in Southeast Asia

Learning With MOOCS (LWMOOCS)

作者： Armin Weinberger Carlos Alario-Hoyos Poline Bala Dennis Batangan Carlos Delgado Kloos Narayanan Kulathuramaiyer John Carlo Navera Josenh Palis Alwin Melkie Sambul Peter Sy Tat-Chee Wan Department of Educational Technology and Knowledge Management Universität des Saarlandes Saarbrücken Germany Department of Telematics Engineering Universidad Carlos III de Madrid Madrid Spain Department of Anthropology and Sociology Universiti Malaysia Sarawak Kota Samarahan Malaysia Institute of Philippine Culture Ateneo de Manila University Quezon City Philippines Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Kota Samarahan Malaysia School of Library and Information Studies University of the Philippines Quezon City Philippines Department of Geography University of the Philippines Quezon City Philippines Faculty of Engineering Universitas Sam Ratulangi Manado Indonesia Department of Philosophy University of the Philippines Quezon City Philippines School of Computer Sciences Universiti Sains Malaysia Penang Malaysia

ISBN: (纸本)9781538665343

This Paper explores the current use of Massive Open Online Courses (MOOCs) as a means of educational outreach among identified remote populations in Southeast Asia. Often excluded from traditional educational outreach, these groups are targeted through the COMPETEN-SEA Project, a Capacity Building in Higher Education project funded by the Erasmus+ programme of the European Commission and implemented in partnership with European and Southeast Asian universities. It is hoped that the Project will aid participating Southeast Asian countries address societal needs and attain national development goals.

关键词： Education Asia Sociology Urban areas Statistics Europe Buildings

Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, 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 Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Event-based structural change detection in urban-scale contact network 31

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Event-based structural change detection in urban-scale conta...

31st AAAI Conference on Artificial Intelligence, AAAI 2017

作者： Bai, Yuan Yang, Bo Eggo, Rosalind M. Du, Zhanwei College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China London School of Hygiene and Tropical Medicine LondonWC1E7HT United Kingdom Department of Integrative Biology University of Texas at Austin Austin78705 United States

ISBN: (纸本)9781577357865

The detection of structural changes is an important task in analyzing network evolution, especially for interactions between people, that may be driven by external events. Existing work relies on snapshot data and misses out some key functions of networks. Here, we study contact network evolution where no snapshot data are available. In spite of the challenge, this study demonstrates how contact networks can be used to predict and control infectious disease epidemics. We first model structural changes in contact networks during the 2009 influenza pandemic in Hong Kong, and then present a probabilistic framework to address it, aiming to answer when and how the underlying structure changes, utilizing multiple data sources including demographic data, and epidemic surveillance data. The efficacy and public health utility of the method are demonstrated using both synthetic and real data. © 2017, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Disease control

Online tool condition monitoring based on parsimonious ensemble

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arXiv 2017年

作者： Pratama, Mahardhika Dimla, Eric Lughofer, Edwin Pedrycz, Witold Tjahjowidodo, Tegoeh School of Computer Science and Engineering Nanyang Technological University Mechanical Engineering Department Faculty of Engineering Boulder University Teknologi Brunei Brunei Department of Knowledge-Based and Mathematical Systems Johanes Kepler University Department of Electrical and Computer Engineering University of Alberta Canad Canada School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore

Tool condition monitoring plays a vital role to reduce maintenance cost in manufacturing industry. It generates information about possible unsafe states of machining process before they occur such that faults of component can be predicted early to support management of its life-cycle. The faults could be isolated to minimize catastrophic effects leading to a complete shutdown of overall production process. Accurate diagnosis of tool wear in metal turning process remains an open challenge for both scientists and industrial practitioners because of inhomogeneities in work-piece material, non-stationary machining settings to suit production requirements, and non-linear relations between measured variables and tool wear. Common methodologies for tool condition monitoring still rely on batch approaches which cannot cope with a fast sampling rate of metal cutting process. Furthermore they require a retraining process to be completed from scratch when dealing with a new set of machining parameters. This paper presents an online tool condition monitoring approach based on Parsimonious Ensemble+ (pENsemble+). The unique feature of pENsemble+ lies in its highly flexible principle where both ensemble structure and base-classifier structure can automatically grow and shrink on the fly based on the characteristics of data streams. Moreover, the online feature selection scenario is integrated to actively sample relevant input attributes. The paper presents advancement of a newly developed ensemble learning algorithm, pENsemble, where online active learning scenario is incorporated to reduce operator’s labelling effort. The ensemble merging scenario is proposed which allows reduction of ensemble complexity while retaining its diversity. Experimental studies utilising real-world manufacturing data streams and comparisons with well-known algorithms were carried out. Furthermore, the efficacy of pENsemble+ was examined using benchmark concept drift data streams. It has been found tha

关键词： Condition monitoring

A network approach to quantifying radiotherapy effect on cancer: radiosensitive gene group centrality

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arXiv 2018年

作者： Yao, Yu-Xiang Bing, Zhi-Tong Huang, Liang Huang, Zi-Gang Lai, Ying-Cheng School of Physical Science and Technology Lanzhou University Lanzhou730000 China Evidence Based Medicine Center School of Basic Medical Science of Lanzhou University Lanzhou730000 China Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province Lanzhou730000 China Department of Computational Physics Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China Key Laboratory of Biomedical Information Engineering of Ministry of Education National Engineering Research Center of Health Care and Medical Devices Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs Institute of Health and Rehabilitation Science School of Life Science and Technology Xi’an Jiaotong University Xi’an710049 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Radiotherapy plays a vital role in cancer treatment, for which accurate prognosis is important for guiding sequential treatment and improving the curative effect for patients. An issue of great significance in radiotherapy is to assess tumor radiosensitivity for devising the optimal treatment strategy. Previous studies focused on gene expression in cells closely associated with radiosensitivity, but factors such as the response of a cancer patient to irradiation and the patient survival time are largely ignored. For clinical cancer treatment, a specific pre-treatment indicator taking into account cancer cell type and patient radiosensitivity is of great value but it has been missing. Here, we propose an effective indicator for radiosensitivity: radiosensitive gene group centrality (RSGGC), which characterizes the importance of the group of genes that are radiosensitive in the whole gene correlation network. We demonstrate, using both clinical patient data and experimental cancer cell lines, which RSGGC can provide a quantitative estimate of the effect of radiotherapy, with factors such as the patient survival time and the survived fraction of cancer cell lines under radiotherapy fully taken into account. Our main finding is that, for patients with a higher RSGGC score before radiotherapy, cancer treatment tends tobe more effective. The RSGGC can have significant applications in clinical prognosis, serving as a key measure to classifying radiosensitive and radioresistant patients. Copyright © 2018, The Authors. All rights reserved.

关键词： Radiotherapy

Web science 2024: Conference Chairs' Welcome Message

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Proceedings of the 16th ACM Web Science Conference, WebSci 2...

Proceedings of the 16th ACM Web science Conference, WebSci 2024 2024年 III-X页

作者： Staab, Steffen Aiello, Luca Maria Mejova, Yelena Seneviratne, Oshani Sindermann, Cornelia Hagendorff, Thilo Brandes, Simone Rohlmann, Juliane Spaniol, Marc Kinder-Kurlanda, Katharina Faleńska, Agnieszka Heiberger, Raphael Sun, Jun Kaiser, Sierra De Choudhury, Munmun Weber, Matthew De Francisci Morales, Gianmarco Dunn, Adam Gadiraju, Ujwal Gaito, Sabrina Hooper, Silas Javarone, Marco Alberto Kalimeri, Kyriaki Kwak, Haewoon Maity, Suman Kalyan Mashhadi, Afra Mustafaraj, Eni Purohit, Hemant Rossetti, Giulio Sastry, Nishanth Srinivasa, Srinath Vaz-De-Melo, Pedro Weal, Mark Weber, Ingmar Weninger, Tim Withing, Mark Zubiaga, Arkaitz Ahlers, Dirk Tamime, Reham Al Alam, Sawood Alhoori, Hamed Andriotis, Panagiotis Bär, Dominik Bernstein, Mark Boratto, Ludovico Camargo, Chico Capozzi, Arthur Chelmis, Charalampos Vieira, Carolina Coimbra De Meo, Pasquale Dinh, Ly Dividino, Renata Doerfel, Stephan Farahbakhsh, Reza Ferreira, Carlos H.G. Flores-Saviaga, Claudia Florio, Komal Galdeman, Alessia Guo, Cheng Hakimov, Sherzod Rad, Radin Hamidi Helic, Denis Hohmann, Marilena Horawalavithana, Sameera Horne, Benjamin Ibanez-Gonzalez, Luis Jiang, Julie Jones, Shawn Kamdar, Maulik R. Kao, Hsien-Te Kassa, Yonas Mitike Kastrin, Andrej Kazama, Kazuhiro Kelly, Mat Khanday, Akib Khatua, Aparup Khudabukhsh, Ashiqur Krüger, Frank Kumari, Neha Lai, Mirko Lamba, Hemank Lee, Roy Ka-Wei Lee, Eun Liao, Yiming Lin, Wenqing Magelinski, Thomas Magnani, Matteo Hill, Benjamin Mako Manikonda, Lydia Masud, Sarah Mekouar, Soufiana Møller, Anders Giovanni Muthiah, Sakthi Ni, Congning Nishimura, Joel Nwala, Alexander Pera, Arianna Piao, Guangyuan Piccardi, Tiziano Pierri, Francesco Porcaro, Lorenzo Ramasco, Jose J. Reelfs, Jens Rezapour, Rezvaneh Salminen, Joni Šćepanović, Sanja Shahi, Gautam Kishore Sinha, Priyanka Smaragdakis, Georgios Smirnova, Inna Song, Melodie Yun-Ju Sosnovik, Vera Truong, Bao Tran Tsugawa, Sho Vasarhelyi, Orsolya D'Aurelio, Davide Vega Vekaria, Yash Vilella, Salvatore Viviani, Marco Wang, Yichen Wu, Siqi Yang, Kaicheng Zeng, Yilei Zha University of Stuttgart Germany IT University of Copenhagen Denmark ISI Foundation Italy Rensselaer Polytechnic Institute United States Université de Caen Normandie France University of Klagenfurt Austria University of Washington United States GESIS Germany Georgia Tech United States IIIT Bangalore India Rutgers University United States CENTAI Italy University of Sydney Australia Delft University of Technology Netherlands University of Milan Italy Canada Centro Ricerche Enrico Fermi UCL CBT Italy Indiana University Bloomington United States Northwestern University United States UW United States Wellesley College United States George Mason University United States CNRS France King's College London United Kingdom International Institute of Information Technology Bangalore India UFMG Brazil University of Southampton United Kingdom Saarland University Germany University of Notre Dame United States UPenn United States Queen Mary University of London United Kingdom Norwegian University of Science and Technology Norway Internet Archive United States Northern Illinois University United States University of the West of England United Kingdom LMU Munich Germany Eastgate Systems Inc. United States University of Cagliari Italy University of Exeter United Kingdom University of Turin Italy University at Albany State University of New York United States Max Planck Institute for Demographic Research Germany Vrije Universiteit Amsterdam Netherlands University of South Florida United States Brock University Canada Kiel University of Applied Sciences Germany Institut Mines-Télécom Télécom SudParis France Universidade Federal de Ouro Preto Brazil Northeastern University United States Università di Torino Dipartimento di Informatica Italy Clemson University Google United States TIB - Leibniz Information Centre for Science and Technology Germany Ryerson University Canada Graz University of Technology Austria University of Copenhagen Denmark Pacific Northwest National La

LifeTime and improving European healthcare through cell-based interceptive medicine (vol 587, pg 377, 2020)

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NATURE 2021年第7852期592卷 E8-E8页

作者： Rajewsky, Nikolaus Almouzni, Genevieve Gorski, Stanislaw A. Aerts, Stein Amit, Ido Bertero, Michela G. Bock, Christoph Bredenoord, Annelien L. Cavalli, Giacomo Chiocca, Susanna Clevers, Hans De Strooper, Bart Eggert, Angelika Ellenberg, Jan Fernandez, Xose M. Figlerowicz, Marek Gasser, Susan M. Hubner, Norbert Kjems, Jorgen Knoblich, Jurgen A. Krabbe, Grietje Lichter, Peter Linnarsson, Sten Marine, Jean-Christophe Marioni, John C. Marti-Renom, Marc A. Netea, Mihai G. Nickel, Dorthe Nollmann, Marcelo Novak, Halina R. Parkinson, Helen Piccolo, Stefano Pinheiro, Ines Pombo, Ana Popp, Christian Reik, Wolf Roman-Roman, Sergio Rosenstiel, Philip Schultze, Joachim L. Stegle, Oliver Tanay, Amos Testa, Giuseppe Thanos, Dimitris Theis, Fabian J. Torres-Padilla, Maria-Elena Valencia, Alfonso Vallot, Celine van Oudenaarden, Alexander Vidal, Marie Voet, Thierry Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany Charité-Universitätsmedizin Berlin Germany Berlin Institute of Health (BIH) Berlin Germany German Center for Cardiovascular Research (DZHK) Partner Site Berlin Berlin Germany Institute for Biology Humboldt University of Berlin Berlin Germany Cardiovascular and Metabolic Sciences Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany Department of Pediatric Oncology/Hematology Charité-Universitätsmedizin Berlin Berlin Germany Institut Curie CNRS PSL Research University Sorbonne Université Nuclear Dynamics Unit Equipe Labellisée Ligue contre le cancer Paris France VIB Center for Brain and Disease Research Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Department of Neurosciences KU Leuven Leuven Belgium UK Dementia Research Institute at UCL University College London London UK Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK Department of Immunology Weizmann Institute of Science Rehovot Israel Centre for Genomic Regulation (CRG) Barcelona Institute of Science and Technology Barcelona Spain CNAG-CRG Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain Universitat Pompeu Fabra Barcelona Spain ICREA Barcelona Spain CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria Department of Laboratory Medicine Medical University of Vienna Vienna Austria Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases Vienna Austria Department of Medical Humanities Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Institute of Human Genetics UMR 9002 CNRS and University of Montpellier Montpellier France Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy Department of Oncology and Hemato

Aadhaar Card: Challenges and Impact on Digital Transformation

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arXiv 2017年

作者： Raju, Raja Siddharth Singh, Sukhdev Khatter, Kiran Department of Computer Science Engineering Manav Rachna International University FaridabadHaryana121004 India Accendere Knowledge Management Services Pvt. Ltd Chennai600101 India

Objectives: This paper presents a brief review on Aadhaar card, and discusses the scope and advantages of linking Aadhaar card to various systems. Further we present various cases in which Aadhaar card may pose security threats. The observations of Supreme Court of India are also presented in this paper followed by a discussion on the loopholes in the existing system. Methods: We conducted literature survey based on the various research articles, leading newspapers, case studies and the observations of Supreme Court of India, and categorized the various cases into three categories. Findings: Aadhaar project is one of the significant projects in India to bring the universal trend of digital innovation. The launch of this project was focused on the inter-operability of various e-governance functionalities to ensure the optimal utilization of Information, Communication and Technology Infrastructure. Towards this Government of India has recently made Aadhaar card mandatory for many government applications, and also has promoted Aadhaar enabled transactions. Improvements: There are many issues related to security and privacy of the Aadhaar data need to be addressed. This paper highlights such cases. Copyright © 2017, The Authors. All rights reserved.

关键词： Data privacy