Population level neuroimaging for neuroepidemiology; A new healthcare big data frontier
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
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,
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
CMeune, FX Goudot,
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
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
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
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
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
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
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
A 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
B 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
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
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
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
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
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
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
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:
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
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
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
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
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
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
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
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
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
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
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