big data 2019-2019-IEEE

4D Cell Biology: Big Data Image Analytics and Lattice Light-Sheet Imaging Reveal Dynamics of Clathrin-Mediated Endocytosis in Stem Cell-Derived Intestinal
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The anterior outer transparent part of the eye, the cornea, acts as a lens that focuses light into the eye. In addition, it serves as a barrier that protects the eye against external hazards and injury and thus maintaining its integrity and its continuous regeneration is crucial for

Ontology-Based Data Access to Big Data
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Recent approaches to ontology-based data access (OBDA) have extended the focus from relational database systems to other types of backends such as cluster frameworks in order to cope with the four Vs associated with big data : volume, veracity, variety and velocity

Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices
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Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to microservices. Detecting QoS Today, individuals and organizations are changing the world with Big Data . Data has become a new source of immense economic and social value. Advances in data mining and analytics and the massive increase in computing power and data storage capacity have

Bio-inspired Algorithms for Big Data Analytics: A Survey, Taxonomy and Open Challenges
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Cloud computing is now the spine of the modern economy, which offers on-demand services to cloud customers through the Internet. To improve the performance and effectiveness of cloud computing systems, new technologies, such as internet of things (IoT) applications

Social Big Data : Mining, Applications, and Beyond
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The social nature of Web 2.0 leads to the unprecedented growth of discussion forums, product review sites, microblogging, and other social media platforms. Existing social media data mining research can be broadly divided into two groups. The content-based approach focuses on extracting This book compiles extended versions of a selection of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE) 2018 held in. They represent a good sample of the current state of the art Archival storage of data sets from qualitative studies presents opportunities for combining small-scale data sets for reuse/secondary analysis. In this paper, we outline our approach to combining multiple qualitative data sets and explain why working with a corpus of big

spark-crowd: A Spark Package for Learning from Crowdsourced Big Data
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As the data sets increase in size, the process of manually labeling data becomes unfeasible by small groups of experts. Thus, it is common to rely on crowdsourcing platforms which provide inexpensive, but noisy, labels. Although implementations of algorithms to tackle this

4.9 Convergence of HPC and Big Data
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Background and Motivation. Due to the fact that this topic is based on two rapidly evolving fields, an appropriate definition and scoping are still in development . Big Data as a domain has developed its own solutions for machine architectures, software frameworks

Introduction to the Minitrack on Data-driven Government: Creating value from Big and Open Linked Data
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BOLD refers to the combination of big data and Linked Data under the openness concept. While Big Data can be characterized by its size and diversity, Linked Data can be characterized by its enhanced semantic capabilities The Internet today is getting connected to a very large number of devices or sensors of IoT. It is expected that 50 billion devices will be connected to the Internet by 2020. The IoT-driven global economy will have many technological challenges. The computing and storage

A new framework for statistical thinking in times of big data and digital economy
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The interest in big data is growing exponentially in todays society. Commercial insights, government initiatives and even research calls, all seem to be focused on exploiting the potential of technology to capture and analyze massive amounts of data in increasingly Briefs allow authors to present their ideas and readers to absorb them with minimal time investment. Briefs will be published as part of eBook collection, with millions of users worldwide. In addition, Briefs will be available for individual print and electronic

Design of a Socio-economic Processes Monitoring System Based on Network Analysis and Big Data
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Socio-economic policy should satisfy the interests of the society as much as possible and contribute to improving the quality of life. This actualizes the role of developing the theoretical and methodological foundations for building an innovative information system for

Complexity Problems Handled by Big Data Technology
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Big data needs new processing modes to own stronger decision-making power, insight discovery, the large volume and high growth of process optimization ability, and the diversified information assets. As the information technology of a new generation based on The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational

Introduction to the Minitrack on Business Intelligence, Business Analytics and Big Data : Innovation, Deployment and Management
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Recent developments in the combined business intelligence (BI), business analytics (BA) and big data space has given rise to new opportunities for individuals, organizations and society. Due to ongoing digitization, digital transformation and datafication, organizations

GeoSensor: Semantifying Change and Event Detection over Big Data
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GeoSensor is a novel, open-source system that enriches change detection over satellite images with event detection over news items and social media content. GeoSensor combines these two orthogonal operations through state-of-the-art Semantic Web This chapter describes the application of big data analytics in healthcare, particularly on electronic healthcare records so as to make predictive models for healthcare outcomes and