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High-Performance Modelling and Simulation for Big Data Applications

Overview of attention for book
Cover of 'High-Performance Modelling and Simulation for Big Data Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Why High-Performance Modelling and Simulation for Big Data Applications Matters
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    Chapter 2 Parallelization of Hierarchical Matrix Algorithms for Electromagnetic Scattering Problems
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    Chapter 3 Tail Distribution and Extreme Quantile Estimation Using Non-parametric Approaches
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    Chapter 4 Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges
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    Chapter 5 Big Data in 5G Distributed Applications
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    Chapter 6 Big Data Processing, Analysis and Applications in Mobile Cellular Networks
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    Chapter 7 Medical Data Processing and Analysis for Remote Health and Activities Monitoring
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    Chapter 8 Towards Human Cell Simulation
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    Chapter 9 Cloud-Based High Throughput Virtual Screening in Novel Drug Discovery
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    Chapter 10 Ultra Wide Band Body Area Networks: Design and Integration with Computational Clouds
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    Chapter 11 Survey on AI-Based Multimodal Methods for Emotion Detection
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    Chapter 12 Forecasting Cryptocurrency Value by Sentiment Analysis: An HPC-Oriented Survey of the State-of-the-Art in the Cloud Era
Attention for Chapter 5: Big Data in 5G Distributed Applications
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Chapter title
Big Data in 5G Distributed Applications
Chapter number 5
Book title
Target Identification and Validation in Drug Discovery
Published by
Springer, Cham, March 2019
DOI 10.1007/978-3-030-16272-6_5
Book ISBNs
978-1-4939-9144-0, 978-1-4939-9145-7, 978-3-03-016271-9, 978-3-03-016272-6
Authors

Valentina Nejkovic, Ari Visa, Milorad Tosic, Nenad Petrovic, Mikko Valkama, Mike Koivisto, Jukka Talvitie, Svetozar Rancic, Daniel Grzonka, Jacek Tchorzewski, Pierre Kuonen, Francisco Gortazar

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X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 9 24%
Student > Master 7 19%
Student > Bachelor 4 11%
Student > Ph. D. Student 3 8%
Student > Postgraduate 2 5%
Other 5 14%
Unknown 7 19%
Readers by discipline Count As %
Computer Science 21 57%
Engineering 5 14%
Agricultural and Biological Sciences 2 5%
Business, Management and Accounting 2 5%
Unknown 7 19%

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