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2017 International MultiConference of Engineers and computer Scientists, IMECS 2017

作者： Sakaguchi, Ayumu Nohara, Shoji Saga, Ryosuke Department of Knowledge and Information Systems School of Sustainable System Sciences Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai Osaka Japan Department of the Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai Osaka Japan

ISBN: (纸本)9789881404732

Given that reviews are difficult to score, predicting evaluation values automatically can be useful. The evaluation value depends on users who buy certain products with known information that meet expectations. Numerous studies have already predicted the evaluation value from reviews. However, many of these studies only paid attention to user reviews, and the opinions of product providers were not considered. In this paper, we will comment about the keywords of reviews and explanations, create a co-occurrence network showing keywords, and perform multiple regression analysis using the features of the network. As a result, we can acquire results of high accuracy from multiple regression analysis to predict the value of products based on the reviews and explanations to the service.

关键词： Forecasting

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Corrections to “Toward Near-Ground Localization: Modeling and Applications for TOA Ranging Error” [Oct 17 5658-5662]

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IEEE Transactions on Antennas and Propagation 2018年第2期66卷 1052-1052页

作者： Cheng Xu Jie He Xiaotong Zhang Po-Hsuan Tseng Shihong Duan School of Computer and Communication Engineering University of Science and Technology Beijing and the Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan

The authors of [1] would like to make the following corrections.

关键词： Antennas Distance measurement Time of arrival estimation Cramer-Rao bounds

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MRI-based surgical planning for lumbar spinal stenosis 20th

MRI-based surgical planning for lumbar spinal stenosis

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20th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2017

作者： Abbati, Gabriele Bauer, Stefan Winklhofer, Sebastian Schüffler, Peter J. Held, Ulrike Burgstaller, Jakob M. Steurer, Johann Buhmann, Joachim M. Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science ETH Zürich Zürich Switzerland Neuroradiology University Hospital Zürich Zürich Switzerland Computational Pathology Memorial Sloan Kettering Cancer Center New York United States Horten Centre for Patient Oriented Research and Knowledge Transfer University of Zürich Zürich Switzerland

ISBN: (纸本)9783319661780

The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis (LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the surgeon show large variance. Thus a standardized support system is of high value for a more objective and reproducible decision. In this work, we develop an automated algorithm to localize the stenosis causing the symptoms of the patient in magnetic resonance imaging (MRI). With 22 MRI features of each of five spinal levels of 321 patients, we show it is possible to predict the location of lesion triggering the symptoms. To support this hypothesis, we conduct an automated analysis of labeled and unlabeled MRI scans extracted from 788 patients. We confirm quantitatively the importance of radiological information and provide an algorithmic pipeline for working with raw MRI scans. Both code and data are provided for further research at ***. © Springer International Publishing AG 2017.

关键词： Magnetic resonance imaging

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Taxonomy of digital forensics: Investigation tools and challenges

arXiv

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arXiv 2017年

作者： Rana, Nikita Sansanwal, Gunjan Khatter, Kiran Singh, Sukhdev Department of Computer Science and Engineering Manav Rachna International University Faridabad121004 India Accendere Knowledge Management Services Pvt. Ltd India

In today's world of computers, any kind of information can be made available within few clicks for different endeavours. The information may be tampered by changing the statistical properties and can be further used for criminal activities. These days, Cybercrimes are happening at a very large scale, and possess big threats to the security of an individual, firm, industry and even to developed countries. To combat such crimes, law enforcement agencies and investment institutions are incorporating supportive examination policies, procedures and protocols to address the complete investigation process. The paper entails a detailed review of several cybercrimes followed by various digital forensics processes involved in the cybercrime investigation. Further various digital forensics tools with detail explanation are discussed with their advantages, disadvantages, challenges, and drawbacks. A comparison among all the selected tools is also presented. Finally the paper recommends the need of training programs for the first responder and judgement of signature based image authentication. Copyright © 2017, The Authors. All rights reserved.

关键词： Electronic crime countermeasures

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Correction to: Investigation of convective nanomaterial flow and exergy drop considering CVFEM within a porous tank

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Journal of Thermal Analysis and Calorimetry 2019年第3期139卷 2351-2351页

作者： Abdulrahman A. Alrobaian Ali Sulaiman Alsagri Jagar A. Ali Samir Mustafa Hamad Ahmad Shafee Truong Khang Nguyen Zhixiong Li Mechanical Engineering Department College of Engineering Qassim University Buraydah Saudi Arabia Mechanical Engineering Department College of Engineering - Unaizah Qassim University Unaizah Saudi Arabia Department of Petroleum Engineering Faculty of Engineering Soran University Soran Iraq Department of Petroleum Engineering College of Engineering Knowledge University Erbīl Iraq Computer Department Cihan University-Erbil Erbil Iraq Scientific Research Centre Soran University Soran Iraq Division of Computational Physics Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Vietnam Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Vietnam School of Engineering Ocean University of China Qingdao China School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong Australia

Unfortunately in the original publication of the article, the fifth affiliation was incorrectly published. The corrected affiliation is given in this Correction article.

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

arXiv

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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

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Addressing Societal Issues Through MOOCs in Southeast Asia

Addressing Societal Issues Through MOOCs in Southeast Asia

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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

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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

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

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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

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Online tool condition monitoring based on parsimonious ensemble

arXiv

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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

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