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Population level neuroimaging for neuroepidemiology; A new healthcare big data frontier

P Matthews - Journal of the Neurological Sciences, 2017
The world's aging populations are further focusing neurologists' and psychiatrists' attentions 
on ways of delaying, preventing and treating chronic brain disorders of late life. Evidence-
based answers to questions regarding early risk stratification, prioritization of modifiable risk 
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[HTML] Considering the ethics of big data research: A case of Twitter and ISIS/ISIL

E Buchanan - PLOS ONE, 2017
This is a formal commentary, responding to Matthew Curran Benigni, Kenneth Joseph, and 
Kathleen Carley's contribution,“Online extremism and the communities that sustain it: 

Detecting the ISIS supporting community on Twitter”. This brief review reflects on the ethics  


P4898Current use and misuse of natriureticpeptides form a large cohort: results of big dataanalysis



CMeune, FX Goudot, N Garnier, N Dubois, G Copin… - European Heart Journal, 2017



Methods: We examined all biological tests performed from February 2010 to August 2015  (study period) in two districts from the west part of France,“theFrench Brittany”, covering  13,653 km 2 and corresponding to a population of 1,723,653 persons. Data from 22 






P4895Current use and misuse of troponinmeasurements form a large cohort: results of big data analysis



CMeune, FX Goudot, N Garnier, N Dubois, G Copin… - European Heart Journal, 2017



Methods: We examined all biological tests performed from February 2010 to August 2015  (study period) in two districts from the Western part of France,“theFrench Brittany”, covering  13,653 km 2 and corresponding to a population of 1,723,653 persons. Data from 22 






Bioinformatics Solutions for Big Data Analysis in Life Sciences presented by the German Network for Bioinformatics Infrastructure



APühler - 2017



Due to the rapid technological progress in analytical areas such as sequencing, omics  analyses, and imaging techniques, big data analysis is considered to belong to the leading  challenges in modern life sciences. To meet these challenges, the German Network for 






[PDF] Privacy Protection for Big Data Linking using the Identity Correlation Approach



K McCormack, M Smyth - Journal of Statistical Science and Application, 2017



Privacy protection for big data linking is discussed here in relation to the Central Statistics  Office (CSO), Ireland's, big data linking project titled the 'Structure of Earnings Survey– Administrative Data Project'(SESADP). The result of the project was the creation of datasets 






P6460Risk factors, predictors and outcomes of chronic total occlusions in ischaemic heart disease: big data from the UK ACALM registry



RPotluri, KR Bainey, PR Carter, H Uppal, RC Welsh… - European Heart Journal, 2017



Methods: Utilisingthe ACALM registry from 2000–2014, comprising of over 1.8 million  patients, we identified patients who developed a new diagnosis of IHD+/− CTO and followed  up these patients (median 7 years). ACALM uses a big data approach using ICD-10 and 






Network based model of social media big data predicts contagious disease diffusion



LS Elkin, K Topal, G Bebek - Information Discovery and Delivery, 2017



Purpose Predicting future outbreaks and understanding how they are spreading from  locationto location can improve patient care provided. Recently, mining social media big  data provided the ability to track patterns and trends across the world. In this study, we are 






Double Instrumental Variable estimation of interaction models with big data



PGagliardini, C Gouriéroux - Journal of Econometrics, 2017



Abstract The factor analysis of a (n, m)(n, m) matrix of observations YY is based on the joint  spectral decomposition of the matrix squares YY′ YY′ and Y′ YY′ Y for Principal  Component Analysis (PCA). For very large matrix dimensions nn and mm, this approach has 






[PDF] Big Data: Evolution, not revolution



WB Data, D MacDonald - 2017



This Magazine Article is brought to you for free and open access by the Centre for Management  Practice at Institutional Knowledge at SingaporeManagementUniversity. It has been accepted  for inclusion in Perspectives@SMUby an authorized administrator of Institutional Knowledge 






Do Trade Area Grades Really Affect Credit Ratings of Small Businesses? An Application of Big Data



H Pan, MS Kang, HY Ha - Management Decision, 2017



Purpose Although the study of credit ratings has focused on traditional credit bureau (CB)  resources, scholars have recently emphasized the importance of big data. We examine both  how these data affect the credit evaluations of small businesses and how financial 






Distributed Computing Patterns Useful in Big Data Analytics



JCS dos Anjos, CFR Geyer, JLV Barbosa- Distributed Computing in Big Data …, 2017



Abstract Thehistory of Distributed Computing is more than 40 years old. Throughout these  years many concepts have been created and applied in different computing models, system  architectures, and platforms for the development of distributed systems. Several Big Data 






Visualizing Big Data Outliers through Distributed Aggregation



L Wilkinson - IEEE Transactions on Visualization and Computer …, 2017



Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting 






A Framework for Effective Data Analytics for Tourism Sector: Big Data Approach



S Sinha, V Bhatnagar, A Bansal - International Journal of Grid and High Performance …, 2017



Abstract From BRICS nations, India is the second largest tourism market after China in Asia. Technological revolution has added new dimensions to the way technologies being used in  all the sectors. Also, the use of electronic gadgets leaves trail of data, which is very huge in 






[PDF] An Ensemble Random Forest Algorithm for Insurance Big Data Analysis



W Lin, Z Wu, L Lin, A Wen, J Li - IEEE Access, 2017



Due to the imbalanced distribution of business data, missing of user features and many other reasons, directly using big data techniques on realistic business data tends to deviate from the business goals. It is difficult to model the insurance business data by classification 






Location Recommendation for Enterprises by Multi-Source Urban Big Data Analysis



G Zhao, T Liu, X Qian, T Hou, H Wang, X Hou, Z Li - IEEE Transactions on Services …, 2017



Effective location recommendation is an important problem in both research and industry. Much research has focused on personalized recommendation for users. However, there are more uses such as site selection for firms and factories. In this study, we try to solve site 






Using big data to advance personality theory



W Bleidorn, CJ Hopwood, AGC Wright - Current Opinion in Behavioral Sciences, 2017



Big data has led to remarkable advances in society. One of the most exciting applications in psychological science has been the development of computer-based assessment tools to  assess human behavior and personality traits. Thus far, machine learning approaches to 






A Review of Infrastructures to Process Big Multimedia Data



J Salvador, Z Ruiz, J Garcia-Rodriguez - International Journal of Computer Vision and …, 2017



Abstract In the last years, the volume of information is growing faster than ever before,  moving from small to huge, structured to unstructured datasets like text, image, audio and  video. The purpose of processing the data is aimed to extract relevant information on trends, 






Distributed Computing in Big Data Analytics: Concepts, Technologies and Applications



S Mazumder, RS Bhadoria, GC Deka - 2017



Big data technologies are used to achieve any type of analytics in a fast and predictable  way, thus enabling better human and machine level decision making. Principles of  distributedcomputing are the keys to big data technologies and analytics. The mechanisms 






[PDF] Toward Automated Analysis of Electrocardiogram Big Data by Graphics Processing Unit for Mobile Health Application



X Fan, R Chen, C He, YCai, P Wang, Y Li - IEEE Access, 2017



With the rapid development of mobile health technologies and applications in recent years,  large amounts of electrocardiogram (ECG) signals which need to be processed timely have  been produced. Although the CPU-based sequential automated ECG analysis algorithm 






[PDF] Industrial Big Data Analysis in Smart Factory: Current Status and Research Strategies



X Xu, Q Hua - IEEE Access, 2017



Under the background of Cyber-Physical Systems (CPS) and Industry 4.0, intelligent  manufacturing has become an orientation and produced a revolutionary change. Compared  with traditional manufacturing environments, the intelligent manufacturing has the 









K Gopalakrishnan, SK Khaitan - International Journal for Traffic & Transport …, 2017



Abstract Research grant databases offer a wealth of information to study research trends,  research collaboration networks and patterns of funding over time. Natural Language  Processing (NLP) and Text Mining (TM) in combination with Machine Learning (ML) are 






[PDF] Data Imbalance and Classifiers: Impact and Solutions from a Big Data Perspective



K Madasamy, M Ramaswami - International Journal of Computational Intelligence …, 2017



Abstract Data being generated in real-time environment is prone to inconsistencies like data  imbalance and messy data with noise. Hugeness of the data also poses an additional  complexity to the prediction mechanisms. Data imbalance is an intrinsic part of the real-time 






[PDF] OP88 Assessing the potential utility of 'big data'from the private sector for health research: linking experian™ mosaic groups to deprivation indices



WM Wami, OR Molaodi, R Dundas, AH Leyland… - 2017



Background Socioeconomic circumstances are routinely measured using government-held  data eg the Index of Multiple Deprivation (IMD) for health research and service planning.  However, alternative approaches may be necessary as key datasets (eg the decennial 






Big Data beats engineering in residential energy performance assessment—a case study



G Fridgen, F Guggenmos, C Regal, M Schmidt - Computer Science-Research and …, 2017



Abstract Engineering-based energy performance assessments, eg, required for the award of  energycertificates, evoke significant effort and lack accuracy. This paper introduces the idea  of building energy performance assessment on Big Data Analytics and information on 






Efficient spark-based framework for big geospatial data query processing and analysis



IM Aljawarneh, P Bellavista, A Corradi, R Montanari… - … and Communications (ISCC …, 2017



The exponential amount of geospatial data that has been accumulated in an accelerated  pace has inevitably motivated the scientific community to examine novel parallel  technologies for tuning the performance of spatial queries. Managing spatial data for an 






[PDF] Adaptive Manycore Architectures for Big Data Computing



JR Doppa, RG Kim, M Isakov, MA Kinsy, HJ Kwon… - 2017



ABSTRACT This work presents a cross-layer design of an adaptive manycore architecture to  addressthe computational needs of emerging big data applications within the technological  constraints of power and reliability. From the circuits end, we present links with 






[HTML] The potential for big data in animal disease surveillance in Ireland



D Barrett - Frontiers in Veterinary Science, 2017



Animal Health Surveillance is the systematic collection, collation, analysis interpretation and  disseminationof animal health and welfare data from defined populations. This process is  essentially about gathering intelligence to detect either novel animal health related events or 









J Zhang, J Zhang, X Huo, W Zheng, X Zheng, M Zhang - International Archives of the …, 2017



ABSTRACT: Historic districts are a special type of cultural heritage, as living cultural  heritage, the utilization and development of historical districts is an inevitable issue. How to  accurately position the protection and utilization of districts and achieve its healthy and 






Big data and healthcare



SA Jones - Australian Nursing and Midwifery Journal, 2017



I was moved and empowered by the story as the themes of race and gender inequality were  explored in a number of ways, but I was equally drawn to reflect on the use of data and technology  – both then and today. In 1960, data was gathered, stored and reported firstly by hand and then 






Big data analytics in genomics: The point on Deep Learning solutions



F Celesti,A Celesti, L Carnevale, A Galletta, S Campo… - … and Communications (ISCC …, 2017



Nowadays, Next Generation Sequeencing(NGS) is a catch-all term used to describe  differentmodern DNA sequencing applications that produce big genomics data that can be  analysed in a faster fashion than in the past. For this reason, NGS requires more and more 






big-data layered architecture for analyzing molecular communications systems in blood vessels



L Felicetti, M Femminella, T Ivanov, P Lio, G Reali - Proceedings of the 4th ACM …, 2017



Abstract We present a novel architecture for analyzing molecular communications systems  in blood vessels for drug delivery and monitoring. This architecture leverages a big data  platformfor simultaneously using data produced by the existing simulation platforms, health 






[HTML] The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote) omics



A Brenes, V Afzal, R Kent, AI Lamond- Nucleic Acids Research, 2017



Abstract Driven by improvements in speed and resolution of mass spectrometers (MS), the  field of proteomics, which involves the large-scale detection and analysis of proteins in cells,  tissues and organisms, continues to expand in scale and complexity. There is a resulting 






Performance Tuning and Modeling for Big Data Applications in Docker Containers



K Ye, Y Ji - Networking, Architecture, and Storage (NAS), 2017 …, 2017



Docker container is experiencing a rapid development with the support from industry and  being widely used in large scale production cloud environment, due to the benefits of  speedy launching time and tiny memory footprint. However the performance of big data 






IHC Posters–Saturday and Sunday



Data, CD Element, SNH CDEs, K Gay, ML Oshinsky - Cephalalgia, 2017



Objectives The National Institute of Neurological Disorders and Stroke (NINDS) Headache  Common Data Elements (CDE) project was initiated to specifically develop data standards  for clinical research within the neurological community. The vision of this initiative is to 






Big Data Orchestration as a Service Network



X Liu, Y Liu, H Song, A Liu - IEEE Communications Magazine, 2017



This article argues that a big data network joint SDN, together with cloud and fog computing  platforms, can build a service chain network. In SDN, the purpose is to reduce a large  amount of redundant data and response time. We propose a novel Big Data Orchestration 






[PDF] Can Big Data be a panacea for business?



R Ramanathan- Journal of Contemporary Development and …, 2017



This issue features a number of interesting but varied articles on the theme of business.  There is focus on economic issues (eg, Mudaraba Financing), environmental issues (eg, BP  Oildisaster), and social issues (eg, smart education, job satisfaction and CSR) facing 






Basics of analytics and big data



U DineshKumar, R Ramanathan - 2017



In this book chapter, we introduce fundamental concepts of analytics and big data and role  ofanalytic in multi-criteria decision making. Three components of analytics, namely,  descriptive, predictive and prescriptive analytics are explained using different applications of 






A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics



Y Huang, L Du, K Liu, X Yao, SL Risacher, L Guo… - Graphs in Biomedical Image …, 2017



Abstract Mining big data in brain imaging genetics is an emerging topic in brain science. It  canuncover meaningful associations between genetic variations and brain structures and  functions. Sparse canonical correlation analysis (SCCA) is introduced to discover bi-






[PDF] Self-reported home and work stress and trying to conceive-using big data in the study of infertility



C Messerlian, B Plaku-Alakbarova, A Lange, J Yeh… - Fertility and Sterility, 2017



Objective Few studies have examined preconception stress and infertility, despite evidence  that maternal stress during pregnancy is associated with adverse outcomes including  miscarriage and preterm birth. We examined the association of self-reported home and work 






Predicting Refractive Surgery Outcome: Machine Learning ApproachWith Big Data



A Achiron, Z Gur, U Aviv, A Hilely, M Mimouni… - Journal of Refractive …, 2017



METHODS: Data from consecutive cases of patients who underwent LASIK or  photorefractivesurgeries during a 12-year period in a single center were assembled into a  single dataset. Training of machine-learning classifiers and testing were performed with a 






A Fitting Approach to Construct and Measurement Alignment: The Role of Big Data in Advancing Dynamic Theories



MM Luciano, JE Mathieu, S Park, SI Tannenbaum - Organizational Research …, 2017



Many phenomena of interest to management and psychology scholars are dynamic and  change over time. One of the primary impediments to the examination of dynamic  phenomenahas been challenges associated with collecting data at a sufficient frequency 






A Design Theory for Supply Chain Visibility in the age of Big Data



J Leung, SC Chu, W Cheung - 2017



Abstract Existing literature has extensively discussed that supply chain visibility (SCV) can  help to improve supply chain performance. Yet there is no sound approach available to  effectively operationalizeSCV. We posit that information sharing alone is not decisive for 






Big Data and Total Hip Arthroplasty: How Do Large Databases Compare?



NA Bedard, AJ Pugely, MA McHugh, NR Lux, KJ Bozic… - The Journal of Arthroplasty, 2017



Background Use of large databases for orthopaedicresearch has become extremely  popular in recent years. Each database varies in the methods used to capture data and the  population it represents. The purpose of this study was to evaluate how these databases 






On fault prediction based on industrial big data



Q Han, H Li, W Dong, YLuo, Y Xia - Control Conference (CCC), 2017 36th Chinese, 2017



Fault-free production is a basic characteristic of intelligent workshop. The existing model- based fault prediction methods depend much more on the precise models of the equipment,  whilethe data-driven ones can only use some basic state data with very limited volume. 






Impact of Organizational Factors on the Intention to Use Big Data Technologies



ASH Lee, LS Thi - 2017



Abstract Big data and technologies that analyze big data such as Hadoop and SAS Visual  Analytics have alerted many business owners and scientists to start considering whether this  is the right moment to adopt and embrace. Key factors such as investment, training, and 






[HTML] Big Building Data-a Big Data Platform for Smart Buildings



L Linder, D Vionnet, JP Bacher, J Hennebert - Energy Procedia, 2017



Abstract Future buildings will more and more rely on advanced Building Management  Systems (BMS) connected to a variety of sensors, actuators and dedicated networks. Their  objectives are to observe the state of rooms and apply automated rules to preserve or 






[HTML] Special issue on intelligent urban computing with big data



W Liu, P Cui, JK Nurminen, J Wang - 2017



The rapid proliferation of urbanization has modernized many people's lives and also  engendered critical issues, such as traffic congestion, energy consumption, and  environmental pollution. These urbanization challenges seriously deteriorate people's life 






P 136 Brain network analysis of EEG data in the service of clinical assessment–utilizing big data and prior theoretical knowledge to identify a biomarker for mTBIin …



A Reches, H Or-ly, M Weiss, Y Stern, JC Baumeister… - Clinical Neurophysiology, 2017



Mild traumatic brain injury (mTBI) in adolecents has gained increased attention in recent  years amongst parents, clinicians, and researchers due to their growing rate and hazardous  outcomes. Electroencephalography (EEG) and Event-Related Potential (ERP) have been 






A Bibliographic Network Analysis of Big Data Literature



R Hosoya, Z Ding, T Kamioka - 2017



Abstract The spread of big data utilization has made impacts on various disciplines, resulting  ina rapid increase in number of related articles. With the rapidness and high volume,  understanding the breadth of big data-related research through literature review is 






Towards an Efficient Way of Building Annotated Medical Image Collections for Big Data Studies



C Compas, T Syeda-Mahmood - … Annotation of Biomedical Data and Expert Label …, 2017



Abstract. Annotating large collections of medical images is essential for building robust  image analysis pipelines for different applications, such as disease detection. This process  involves expert input, which is costly and time consuming. Semiautomatic labeling and 






Using populations of models to navigate big data in electrophysiology: evaluation of parameter sensitivity of action potential models



CA Ledezma Rondon, B Kappler, V Meijborg… - 2017



Experimentally-calibrated populations of models (ePoM) for cardiac electrophysiology can  be used as a means to elucidate the cellular dynamics that lead to pathologies observed in  organ-level measurements, while taking into account the variability inherent to living 






What can Google and Wikipedia can tell us about a disease? Big Data trends analysis in Systemic Lupus Erythematosus



S Sciascia, M Radin - International Journal of Medical Informatics, 2017



Objective To investigate trends of Internet search volumes linked to Systemic Lupus  Erythematosus (SLE), on-going clinical trials and research developments associated to the  disease, using Big Data monitoring and data mining. Methods We performed a longitudinal 






Managing default risk under trade credit: Who should implement Big-Data analytics in supply chains?



YC Tsao- Transportation Research Part E: Logistics and …, 2017



Abstract This paper considers a supplier–retailer channel in which providing trade credit to  customers incurs default risk. Big-data analytics (BD-A) could be used to mitigate default  risk. The aim is to identify the party that should implement BD-A in the supply chain. Our 






[PDF] Design Model of Public Facilities Topology Based on Manifold Learning and Big Data Optimization



L Wang - Boletín Técnico, ISSN: 0376-723X, 2017



Abstract Topology research is a kind of flexible geometry and it is the study of a graphics in  the case of only by pure elastic change, such as stretching, squeezing, distortion or other  form may form under the continuous movement, so its research is a kind of continuity. This 






Big-Data in Climate Change Models—A Novel Approach with Hadoop MapReduce



JMC Loaiza, G Giuliani, G Fiameni - High Performance Computing & Simulation ( …, 2017



The goal of this work is to present a software package which is able to process binary  climate data through spawning Map-Reduce tasks while introducing minimum  computational overhead and without modifying existing application code. The package is 






Securing big data and IoTnetworks in smart cyber-physical environments



SK Das, H Yamana - Proceedings of the 2017 International Conference on …, 2017



I. INTRODUCTION We live in an era in which our physical and personal environments are increasingly  intertwined due to the pervasive embeddings of sensors and actuators, wireless communications  and networking, and ubiquitous computing capabilities. Indeed, our daily living depends on a 






[PDF] Scalable and Efficient Statistical Inference with Estimating Functions in the MapReduce Paradigm for Big Data



L Zhou, PXK Song - arXiv preprint arXiv:1709.04389, 2017



Abstract: The theory of statistical inference along with the strategy of divide-and-conquer for  large-scale data analysis has recently attracted considerable interest due to great popularity  of the MapReduce programming paradigm in the Apache Hadoop software framework. The 






Immunization-based redundancy elimination in Mobile Opportunistic Networks-Generated big data



J Zhang, H Huang, Y Luo, Y Fan, G Yang - Future Generation Computer Systems, 2017



Abstract Diverse sensors and smart devices are promising in facilitating to perform specific  tasks which generate massive data whilst such data transmission is challenged in the big  data era. Under some circumstances, these devices may form Mobile Opportunistic 






[PDF] Development of a Total Environment Data Science Approach in a Big Data Scale



SL Nimmagadda, T Reiners, A Rudra - 2017



Abstract We use the Big Data paradigm, as a driving mechanism of an integrated research  framework. As a case study, we consider analysing various ecological systems and their  connectivity in the framework. An unknown coexistence among different species and lack of 






Evolvable Systems for Big Data Management in Business



R McClatchey, A Branson, J Shamdasani, P Emin- High Performance Computing & …, 2017



Big Data systems are increasingly having to be longer lasting, enterprise-wide and  interoperable with other (legacy or new) systems. Furthermore many organizations operate  in an external environment which dictates change at an unforeseeable rate and requires 






A glossary for big data in population and public health: discussion and commentary on terminology and research methods



D Fuller, R Buote, K Stanley - J EpidemiolCommunity Health, 2017



The volume and velocity of data are growing rapidly and big data analytics are being  applied to these data in many fields. Population and public health researchers may be  unfamiliar with the terminology and statistical methods used in big data. This creates a 






Big Data and Theory



W Maass, J Parsons, S Purao, ARosales, VC Storey… - 2017



Big data is the buzzword du jour in diverse fields in the natural, life, social, and applied  sciences, including physics (Legger2014), biology (Howe et al. 2008), medicine (Collins  and Varmus 2015), economics (Diebold 2012), and management (McAfee and Brynjolfsson 






Hearing Aid Use and Mild Hearing Impairment: Learnings from Big Data



BHB Timmer, L Hickson, S Launer - Journal of the American Academy of Audiology, 2017



Background: Previous research, mostly reliant on self-reports, has indicated that hearing aid  (HA) use is related to the degree of hearing impairment (HI). No large-scale investigation of  the relationship between data-logged HA use and HI has been conducted to date. Purpose: 






Intelligence Science and Big Data Engineering: 7th International Conference, IScIDE 2017, Dalian, China, September 22-23, 2017, Proceedings



Y Sun, H Lu, L Zhang, J Yang, H Huang - 2017



This book constitutes the proceedings of the 7th International Conference on Intelligence  Science and Big Data Engineering, IScIDE 2017, held in Dalian, China, in September 2017.  The 48 full papers and 14 short papers presented in this volume were carefully reviewed 






What Big Data Tell Us About Trees and the Sky in the Cities



F Duarte, C Ratti - Humanizing Digital Reality, 2018



Abstract Since Google Street View (GSV) was launched in 2007, its cars have been  collecting millions of photographs in hundreds of cities around the world. In New York City  alone, there are about 100,000 sampling points, with six photographs captured in each of 






The Scalability of Volunteer Computing for MapReduce Big Data Applications



W Li, W Guo - … of Pioneering Computer Scientists, Engineers and …, 2017



Abstract Volunteer Computing (VC) has been successfully applied to many compute- intensive scientific projects to solve embarrassingly parallel computing problems. There  exist some efforts in the current literature to apply VC to data-intensive (ie big data






Baymax: A Mental-Analyzing Mobile App Based on Big Data



F Yuan, H Wang, S Tian, X Tong - … of Pioneering Computer Scientists, Engineers and …, 2017



Abstract Nowadays people are facing various psychological problems. Existing solution of  evaluation and treatment of mental illness is only to see a psychiatrist, but most of the users  has sense of resistance on psychiatrist. Meanwhile most of the existing systems are 






[PDF] An Upstream Business Data Science in a Big Data Perspective



SL Nimmagadda, T Reiners, A Rudra - 2017



Abstract The rugged geographies, geomorphologies and complex geological environments  make the explorers more challenging exploration and production (E & P). Despite  challenges, many sedimentary basins, associated oil & gas fields and E & P Ventures are 






11 Using CRM data for “big picture” research



DG Anderson - New Perspectives in Cultural Resource Management, 2017






[PDF] Big Data, the Internet of Things and Smart Cities Research: A Literature Review and Research Agenda



S Fosso Wamba, CA Messina Ntede, JBEtoa Etoa - EAI International Conference on …, 2017



Abstract. This study aims at providing a literature review of big data, the Internet of Things  andSmart cities research using SCOPUS, which is considered as the largest abstract and  citation database of peer-reviewed literature. The research identified 143 relevant papers. 






[PDF] Exploring Innovative Learning Environment (ILE): Big Data Era



M Huda, Z Haron, MN Ripin, A Hehsan, ABC Yaacob- International Journal of Applied …, 2017



Abstract The emergence of digital technology development such as smart phones, tablets  and iPadhas been widely raised to utilise among the society at large and particularly in the  higher education (HE) context. The massive amounts of data can be enhanced to provide 






Big Data Applications in Built Environment: Towards a Use Foundation Model



M Kassem, J Li - 2017



Abstract: The term big data is increasingly permeating the current debate over the  present and the future of our built environment. There are heightened expectations about the  role big data may or can play in enabling new applications and decisions across the whole 






Time-series oligonucleotide count to assign antiviral siRNAs with long utility fit in the big data era.



K Wada, Y Wada, Y Iwasaki, T Ikemura - Gene therapy, 2017



Oligonucleotides are key elements of nucleic acid therapeutics such as small interfering  RNAs (siRNAs). Influenza and Ebolavirusesare zoonotic RNA viruses mutating very rapidly,  and their sequence changes must be characterized intensively to design therapeutic 






[PDF] Machine Learning for predicting in a big data world



G Bontempi- 2017



Reductionist attitude: ML is a modern buzzword which equates to statistics plus marketing  Positive attitude: ML paved the way to the treatment of challenging problems, sometimes  overlooked by statisticians (nonlinearity, classification, pattern recognition, missing 






Big Data Analytics for Extracting Disease Surveillance Information: An Untapped Opportunity



P Amirian, T Lang, F van Loggerenberg, AThomas… - Big Data in Healthcare, 2017



Abstract Diagnostic Point of Care (POC) devices are important tools in the battle against  infectious diseases as well as other acute and chronic diseases. POC tests can usually run  faster than conventional laboratory testing and need less equipment. Combining the test 






The impact of Digitalization on Business Models: How IT Artefacts, Social Media, and Big Data Force Firms to Innovate Their Business Model



H Bouwman, M de Reuver, S Nikou - 2017



Digital technology has forced entrepreneurs to reconsider their business models (BMs).  Although research on entrepreneurial intention and business models is gaining attention,  there is still a large knowledge gap on both fields. In this paper, we specifically address the 






A Comprehensive Infrastructure for Big Data in Cancer Research: Accelerating Cancer Research and Precision Medicine



IV Hinkson, TM Davisden, JD Klemm, AR Kerlavage… - Frontiers in Cell and …, 2017



Advancements in next-generation sequencing and other-omics technologies are  acceleratingthe detailed molecular characterization of individual patient tumors, and driving  the evolution of precision medicine. Cancer is no longer considered a single disease, but 






Challenges and Benefits of Deploying Big Data Analytics in the Cloud for Business Intelligence



BM Balachandran, S Prasad - Procedia Computer Science, 2017



Abstract Cloud computing and big data analytics are, without a doubt, two of the most  importanttechnologies to enter the mainstream IT industry in recent years. Surprisingly, the  two technologies are coming together to deliver powerful results and benefits for 






Big Data DBMS Assessment: A Systematic Mapping Study



MI Ortega, M Genero, M Piattini - International Conference on Model and Data …, 2017



Abstract The tremendous prosperity of big data systems that has occurred in recent years  has made its understanding crucial for both research and industrial communities. Big Data is  expected to generate an economy of 15 billion euros over the next few years and to have 






'Big Tigers, BigData:'LearningSocial Reactions to China's Anticorruption Campaign through Online Feedback



J Zhu, H Huang, D Zhang - Public Administration Review, 2017



This study examines the effect of campaign-style anticorruption on political support using the  case of China's most recent anticorruption drive, which stands out for its harsh crackdown on  high-ranking officials, or the “big tigers.” An exploratory text analysis of over 370,000 online 






[PDF] Scoping study into Deriving Transport Benefits from Big Data and the Internet of Things in Smart Cities



N Hill, G Gibson, E Guidorzi, S Amaral, AK Parlikad… - 2017



Executive summary Big Data refers to both large volumes of data with high levels of  complexityand the analytical methods applied such data which require advanced  techniques and technologies in order to derive meaningful information and insights in real 






An Efficient Industrial Big-data Engine



P Basanta-Val - IEEE Transactions on Industrial Informatics, 2017



Current trends in industrial systems opt for the use of different big-data engines as a mean to  process huge amounts of data that cannot be processed with an ordinary infrastructure. The  number of issues an industrial infrastructure has to face is large and includes challenges 






[PDF] Internet-of-Things and big data for smarter healthcare: From device to architecture, applications and analytics



F Firouzi,A Rahmani, K Mankodiya, M Badaroglu… - Future Generation …, 2017



The technology and healthcare industries have been deeply intertwined for quite some time.  New opportunities, however, are now arising as a result of fast-paced expansion in the  areasof the Internet of Things (IoT) and Big Data. In addition, as people across the globe 






[PDF] Analysis of Big Data Maturity Stage in Hospitality Industry



N Shabani, A Munir, A Bose - arXivpreprint arXiv:1709.07387, 2017



Abstract: Big data analytics has an extremely significant impact on many areas in all  businessesand industries including hospitality. This study aims to guide information  technology (IT) professionals in hospitality on their big data expedition. In particular, the 






[HTML] Challenges and Opportunities of Big Data Analytics for Upcoming Regulations and Future Transformation of the Shipping Industry



I Zaman, K Pazouki, R Norman, S Younessi… - Procedia Engineering, 2017



Abstract Shipping is a heavily regulated industry and responsible for around 3% of global  carbonemissions. Global trade is highly dependent on shipping which covers around 90%  of commercial demand. Now the industry is expected to navigate through many twists and 






[PDF] Technology adoption in Norway: organizational assimilation of big data



T Nguyen, TE Petersen - 2017



As data permeates and drives the digital evolution, the role of Big Data becomes  increasingly essential. Big Data is making its presence known in almost every industry, and  has the potential to not only transform the business world, but society at large. Given that 






[PDF] A Comparative Quantitative Analysis of Contemporary Big Data Clustering Algorithms for Market Segmentation in Hospitality Industry



A Bose, A Munir, N Shabani - arXiv preprint arXiv:1709.06202, 2017



Abstract: The hospitality industry is one of the data-rich industries that receives huge  Volumes of data streaming at high Velocity with considerably Variety, Veracity, and  Variability. These properties make the data analysis in the hospitality industry a big data 






[HTML] Feeding Tubes and Health Care Service Utilization in Amyotrophic Lateral Sclerosis: Benefits and Limits to a Retrospective, Multicenter Study Using Big Data



KM Swetz, SM Peterson, LR Sangaralingham, RT Hurt… - INQUIRY: The Journal of …, 2017



Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurologic disorder with  predictable challenges regarding disease progression and end-of-life care. These include  need for respiratory and nutritional support. Little is known about how such choices impact 






Big data analyses for continuous evaluation of pharmacotherapy: A proof of principle with doxapramin preterm infants.



R Flint, WV Weteringen, S Völler, JA Poppe, BC Koch… - Current pharmaceutical …, 2017



BACKGROUND: Drug effect evaluation is often based on subjective interpretation of a  selection of patient data. Continuous analyses of high frequency patient monitor data are a  valuable source to measure drug effects. However, these have not yet been fully explored in 






Design Guidelines for Exploring Relationships in a Connected Big Data Environment



J Jacob, S Rao - IFIP Conference on Human-Computer Interaction, 2017



Abstract Reimagining the 'SAP Investigative Case Management'frame-work from a log- based register of events to a direct interaction environment with the possibility to search,  explore relationships between multiple entities in one or more cases/incidents. This case 












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