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Data Science in Applications

  • Book
  • © 2023

Overview

Editors:
  1. Gintautas Dzemyda

    1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

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  2. Jolita Bernatavičienė

    1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

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    You can also search for this editor in PubMed   Google Scholar

  3. Janusz Kacprzyk

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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  • Presents recent research on Applied Data Science
  • Overviews recent developments in Data Science and Applications
  • Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 1084)

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About this book

This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xii
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  2. Computational Thinking Design Application for STEAM Education

    • Anita Juškevičienė, Arnold Pears, Tatjana Jevsikova, Gabrielė Stupurienė
    Pages 1-26

  3. Education Data for Science: Case of Lithuania

    • Audronė Jakaitienė, Rimantas Želvys, Rita Dukynaitė
    Pages 27-42

  4. Imbalanced Data Classification Approach Based on Clustered Training Set

    • Dalia Breskuvienė, Gintautas Dzemyda
    Pages 43-62

  5. Baltic States in Global Value Chains: Quantifying International Production Sharing at Bilateral and Sectoral Levels

    • Giedrė Dzemydaitė, Brigita Šidlauskaitė-Riazanova, Darjuš Bartkevičius
    Pages 63-85

  6. The Soft Power of Understanding Social Media Dynamics: A Data-Driven Approach

    • Domnica Dzitac
    Pages 87-97

  7. Bootstrapping Network Autoregressive Models for Testing Linearity

    • Mirko Armillotta, Konstantinos Fokianos, Ioannis Krikidis
    Pages 99-116

  8. Novel Data Science Methodologies for Essential Genes Identification Based on Network Analysis

    • Mario Manzo, Maurizio Giordano, Lucia Maddalena, Mario Rosario Guarracino, Ilaria Granata
    Pages 117-145

  9. Acoustic Analysis for Vocal Fold Assessment—Challenges, Trends, and Opportunities

    • Monika Danilovaitė, Gintautas Tamulevičius
    Pages 147-166

  10. The Paradigm of an Explainable Artificial Intelligence (XAI) and Data Science (DS)-Based Decision Support System (DSS)

    • Vytautas Petrauskas, Raimundas Jasinevicius, Egidijus Kazanavicius, Zygimantas Meskauskas
    Pages 167-209

  11. Stock Portfolio Risk-Return Ratio Optimisation Using Grey Wolf Model

    • Virgilijus Sakalauskas, Dalia Kriksciuniene, Audrius Imbrazas
    Pages 211-232

  12. Towards Seamless Execution of Deep Learning Application on Heterogeneous HPC Systems

    • Li Zhong, Oleksandr Shcherbakov, Dennis Hoppe, Michael Resch, Bastian Koller
    Pages 233-252
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Editors and Affiliations

  • Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda, Jolita Bernatavičienė

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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