Data Science and Emerging Technologies: Proceedings of DaSET 2022

The book presents selected papers from the International Conference on Data Science and Emerging Technologies (DaSET 2022), highlighting the importance of data science and emerging technologies in achieving Sustainable Development Goals and their applications in various domains. It emphasizes the grand challenge of combining computational and social-behavioral sciences to improve well-being, emergency response, sustainability, and civic engagement in a data-driven society.

Format: Hardback
Length: 548 pages
Publication date: 01 April 2023
Publisher: Springer Verlag, Singapore

The book presents a collection of selected papers from the International Conference on Data Science and Emerging Technologies (DaSET 2022), which was held virtually at UNITAR International University, Malaysia, from December 20 to 21, 2022. This comprehensive volume seeks to showcase the latest research and practical applications in the fields of data science and emerging technologies. The deployment of data science and these cutting-edge technologies plays a crucial role in achieving the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies, such as artificial intelligence and blockchain, have wide-ranging applications across various domains, including marketing, healthcare, finance, banking, environmental conservation, and agriculture.

One of the significant grand challenges in data science revolves around integrating advancements in computational and social-behavioral sciences to enhance well-being, emergency response, sustainability, and civic engagement in a data-driven society. This book addresses a range of topics within these fields, including but not limited to:

Artificial Intelligence: The study and development of intelligent systems that can mimic human cognitive abilities, such as perception, reasoning, and learning.

Big Data Technology: The management, analysis, and processing of large and complex data sets, often using advanced computing techniques and machine learning algorithms.

Machine and Deep Learning: The use of neural networks and deep learning models to analyze and understand data, enabling tasks such as image recognition, speech recognition, and natural language processing.

Data Mining: The extraction of valuable insights and patterns from large datasets through techniques such as clustering, classification, and regression analysis.

Optimization Algorithms: The design and analysis of algorithms that optimize complex systems, such as logistics, scheduling, and resource allocation.

Blockchain: A distributed ledger technology that enables secure and transparent transactions and data storage, with applications in finance, supply chain management, and other industries.

Internet of Things (IoT): The network of physical devices, vehicles, and objects that can communicate and exchange data, enabling the development of smart cities, smart homes, and industrial automation.

Cloud Computing: The provision of computing resources and services over the internet, enabling scalable and flexible infrastructure for data storage, processing, and analysis.

Computer Vision: The field of computer science that focuses on enabling computers to interpret and understand visual data, with applications in autonomous vehicles, medical imaging, and surveillance systems.

Cybersecurity: The protection of computer systems, networks, and data from unauthorized access, theft, and damage, with an emphasis on developing robust security measures and protocols.

Augmented and Virtual Reality: The simulation of real-world environments and objects using computer-generated imagery and sensory feedback, with applications in entertainment, education, and training.

Cryptography: The study of secure communication and data encryption techniques, with applications in secure messaging, digital signatures, and online security.

Statistical Learning: The use of statistical methods and machine learning algorithms to analyze and predict data, with applications in data mining, machine learning, and predictive analytics.

In conclusion, this book provides a valuable resource for researchers, practitioners, and students interested in the latest developments in data science and emerging technologies. It showcases the interdisciplinary nature of these fields and their potential to address complex societal challenges and drive innovation across various industries. By presenting a diverse range of research and applications, this book contributes to the advancement of knowledge and understanding in these critical areas and lays the foundation for future research and development.

Weight: 1016g
Dimension: 235 x 155 (mm)
ISBN-13: 9789819907403
Edition number: 1st ed. 2023