Unveiling insights, unleashing potential: Navigating the depths of big data and analytics for a data-driven tomorrow Key Features β Learn about big data and how it helps businesses innovate, grow, and make decisions efficiently. β Learn about data collection, storage, processing, and analys
Applications of Big Data Analytics
β Scribed by Mohammed M. Alani, Hissam Tawfik, Mohammed Saeed, Obinna Anya
- Publisher
- Springer International Publishing
- Year
- 2018
- Tongue
- English
- Leaves
- 219
- Edition
- 1st ed.
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.
Topics and features:
- Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing
- Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants
- Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios
- Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders
- Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices
- Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment
β¦ Table of Contents
Front Matter ....Pages i-xii
Big Data Environment for Smart Healthcare Applications Over 5G Mobile Network (Mohammed Dighriri, Gyu Myoung Lee, Thar Baker)....Pages 1-29
Challenges and Opportunities of Using Big Data for Assessing Flood Risks (Ahmed Afif Monrat, Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson)....Pages 31-42
A Neural Networks Design Methodology for Detecting Loss of Coolant Accidents in Nuclear Power Plants (David Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik)....Pages 43-61
Evolutionary Deployment and Hill Climbing-Based Movements of Multi-UAV Networks in Disaster Scenarios (D. G. Reina, T. Camp, A. Munjal, S. L. Toral, H. Tawfik)....Pages 63-95
Detection of Obstructive Sleep Apnea Using Deep Neural Network (Mashail Alsalamah, Saad Amin, Vasile Palade)....Pages 97-120
A Study of Data Classification and Selection Techniques to Diagnose Headache Patients (Ahmed J. Aljaaf, Conor Mallucci, Dhiya Al-Jumeily, Abir Hussain, Mohamed Alloghani, Jamila Mustafina)....Pages 121-134
Applications of Educational Data Mining and Learning Analytics Tools in Handling Big Data in Higher Education (Santosh Ray, Mohammed Saeed)....Pages 135-160
Handling Pregelβs Limits in Big Graph Processing in the Presence of High-Degree Vertices (Mohamad Al Hajj Hassan, Mostafa Bamha)....Pages 161-175
Nature-Inspired Radar Charts as an Innovative Big Data Analysis Tool (J. Artur Serrano, Hamzeh Awad, Ronny Broekx)....Pages 177-183
Search of Similar Programs Using Code Metrics and Big Data-Based Assessment of Software Reliability (Svitlana Yaremchuck, Vyacheslav Kharchenko, Anatoliy Gorbenko)....Pages 185-211
Back Matter ....Pages 213-214
β¦ Subjects
Computer Science; Big Data; Pattern Recognition; Information Storage and Retrieval; Computer Communication Networks; Algorithm Analysis and Problem Complexity; Big Data/Analytics
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