Advances in Data Science: Methodologies and Applications

1. Front Matter

   Pages i-xvii

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2. Introduction to Big Data and Data Science: Methods and Applications

   • Gloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain

   Pages 1-11

3. Towards Abnormal Behavior Detection of Elderly People Using Big Data

   • Giovanni Diraco, Alessandro Leone, Pietro Siciliano

   Pages 13-33

4. A Survey on Automatic Multimodal Emotion Recognition in the Wild

   • Garima Sharma, Abhinav Dhall

   Pages 35-64

5. “Speech Melody and Speech Content Didn’t Fit Together”—Differences in Speech Behavior for Device Directed and Human Directed Interactions

   • Ingo Siegert, Julia Krüger

   Pages 65-95

6. Methods for Optimizing Fuzzy Inference Systems

   • Iosif Papadakis Ktistakis, Garrett Goodman, Cogan Shimizu

   Pages 97-116

7. The Dark Side of Rationality. Does Universal Moral Grammar Exist?

   • Nelson Mauro Maldonato, Benedetta Muzii, Grazia Isabella Continisio, Anna Esposito

   Pages 117-123

8. A New Unsupervised Neural Approach to Stationary and Non-stationary Data

   • Vincenzo Randazzo, Giansalvo Cirrincione, Eros Pasero

   Pages 125-145

9. Fall Risk Assessment Using New sEMG-Based Smart Socks

   • G. Rescio, A. Leone, L. Giampetruzzi, P. Siciliano

   Pages 147-166

10. Describing Smart City Problems with Distributed Vulnerability

    • Stefano Marrone

    Pages 167-188

11. Feature Set Ensembles for Sentiment Analysis of Tweets

    • D. Griol, C. Kanagal-Balakrishna, Z. Callejas

    Pages 189-208

12. Supporting Data Science in Automotive and Robotics Applications with Advanced Visual Big Data Analytics

    • Marco Xaver Bornschlegl, Matthias L. Hemmje

    Pages 209-249

13. Classification of Pilot Attentional Behavior Using Ocular Measures

    • Kavyaganga Kilingaru, Zorica Nedic, Lakhmi C. Jain, Jeffrey Tweedale, Steve Thatcher

    Pages 251-276

14. Audio Content-Based Framework for Emotional Music Recognition

    • Angelo Ciaramella, Davide Nardone, Antonino Staiano, Giuseppe Vettigli

    Pages 277-292

15. Neuro-Kernel-Machine Network Utilizing Deep Learning and Its Application in Predictive Analytics in Smart City Energy Consumption

    • Miltiadis Alamaniotis

    Pages 293-307

16. Learning Approaches for Facial Expression Recognition in Ageing Adults: A Comparative Study

    • Andrea Caroppo, Alessandro Leone, Siciliano Pietro

    Pages 309-333

Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.

    

• Intelligent Systems
• Data Science
• Big Data
• Data Analytics
• Deep Neural Networks
• Augmented Reality
• Cyber-Physical Systems

“The book is useful to both the specialized researcher seeking information on specific sub-areas within Data Science or to the new-comer who seeks to get involved in Data Science. I am confident that both types of readers will benefit greatly from the book. … the editors are warmly congratulated for their superb work. Their book is highly and unreservedly recommended to professors, graduate students, practitioners and other specialists ins Data Science and to general readers … .” (George A. Tsihrintzis, Intelligent Decision Technologies, Vol. 15 (2), 2021)

• Loyola University Maryland, Baltimore, USA

  Gloria Phillips-Wren

• Dipartimento di Psicologia, Università della Campania “Luigi Vanvitelli”, Caserta, Italy

  Anna Esposito

• Centre for Artificial Intelligence, University of Technology Sydney Broadway,, Sydney, Australia

  Lakhmi C. Jain

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