Books in Data

Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

1st Edition
June 2, 2025
Tilottama Goswami + 2 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 3 3 0 4 4 - 5
eBook
9 7 8 - 0 - 4 4 3 - 3 3 0 4 5 - 2

As pursuit of the Sustainable Development Goals (SDGs) becomes central to our global mission, there is a growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues effectively, one should be able to measure and analyze progress. Data Driven Insights and Analytics for Measurable Sustainable Development Goals bridges the gap between qualitative and quantitative assessments, recognizing that the SDGs are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how the 5 Parts of SDGs intersect and influence each other, providing a holistic perspective on sustainable development. The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance, and thus offering valuable insights into where we stand on these critical goals. In addition, to make informed decisions and drive the SDGs forward, readers need more than just an understanding of the current situation. The book demonstrates the need for prescriptive analytics, a methodology that guides actions. Prescriptive analytics provides actionable recommendations based on data analysis, helping readers to identify specific interventions and policies that can accelerate progress. Furthermore, predictive analytics is vital in anticipating future trends and challenges. By showing how readers can forecast potential obstacles and opportunities, the book presents tools for taking proactive measures to navigate our path toward the SDGs effectively. By offering a data-driven approach, the book ensures that every action taken is based on sound analysis, making a tangible difference in building a better and safer world for all.

Advanced Machine Learning for Cyber-Attack Detection in IoT Networks

1st Edition
June 1, 2025
Dinh Thai Hoang + 3 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 9 0 3 2 - 9
eBook
9 7 8 - 0 - 4 4 3 - 2 9 0 3 3 - 6

Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems. Chapters investigate the key challenges and vulnerabilities found in IoT security, how to handle challenges in data collection and pre-processing specific to IoT environments, as well as what metrics to consider for evaluating the performance of machine learning models. Other sections look at the training, validation, and evaluation of supervised learning models and present case studies and examples that demonstrate the application of supervised learning in IoT security.

Applied Graph Data Science

1st Edition
February 1, 2025
Pethuru Raj + 4 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 9 6 5 4 - 3
eBook
9 7 8 - 0 - 4 4 3 - 2 9 6 5 5 - 0

Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques.

Computational Intelligence for Genomics Data

1st Edition
February 1, 2025
Babita Pandey + 4 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 3 0 0 8 0 - 6
eBook
9 7 8 - 0 - 4 4 3 - 3 0 0 8 1 - 3

Computational Intelligence for Genomics Data presents an overview of machine learning and deep learning techniques being developed for the analysis of genomic data and the development of disease prediction models. The book focuses on machine and deep learning techniques applied to dimensionality reduction, feature extraction, and expressive gene selection. It includes designs, algorithms, and simulations on MATLAB and Python for larger prediction models and explores the possibilities of software and hardware-based applications and devices for genomic disease prediction. With the inclusion of important case studies and examples, this book will be a helpful resource for researchers, graduate students, and professional engineers.

Data Science in the Medical Field

1st Edition
September 25, 2024
Seifedine Kadry + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 4 0 2 8 - 7
eBook
9 7 8 - 0 - 4 4 3 - 2 4 0 2 9 - 4

Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage.

Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications

1st Edition
July 13, 2024
Siddhartha Bhattacharyya + 3 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 5 5 3 3 - 8
eBook
9 7 8 - 0 - 4 4 3 - 1 5 5 3 2 - 1

Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on recent, up-to-date technologies, combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

Cognitive Science, Computational Intelligence, and Data Analytics

1st Edition
June 6, 2024
Vikas Khare + 2 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 6 0 7 8 - 3
eBook
9 7 8 - 0 - 4 4 3 - 1 6 0 7 9 - 0

Cognitive Science, Computational Intelligence, and Data Analytics: Methods and Applications with Python introduces readers to the foundational concepts of data analysis, cognitive science, and computational intelligence, including AI and Machine Learning. The book's focus is on fundamental ideas, procedures, and computational intelligence tools that can be applied to a wide range of data analysis approaches, with applications that include mathematical programming, evolutionary simulation, machine learning, and logic-based models. It offers readers the fundamental and practical aspects of cognitive science and data analysis, exploring data analytics in terms of description, evolution, and applicability in real-life problems.The authors cover the history and evolution of cognitive analytics, methodological concerns in philosophy, syntax and semantics, understanding of generative linguistics, theory of memory and processing theory, structured and unstructured data, qualitative and quantitative data, measurement of variables, nominal, ordinals, intervals, and ratio scale data. The content in this book is tailored to the reader's needs in terms of both type and fundamentals, including coverage of multivariate analysis, CRISP methodology and SEMMA methodology. Each chapter provides practical, hands-on learning with real-world applications, including case studies and Python programs related to the key concepts being presented.

Smart Spaces

1st Edition
March 18, 2024
Fatos Xhafa + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 4 6 2 - 3
eBook
9 7 8 - 0 - 4 4 3 - 1 3 4 6 3 - 0

Smart Spaces covers the latest concepts and technologies surrounding smart spaces, providing technical personnel engaged in smart space related research and industries a more in-depth understanding of smart spaces. This book can be used as a reference for practicing this emerging discipline, but it will also be useful for researchers, scientists, developers, practitioners, and graduate students working in the fields of smart spaces and artificial intelligence. It combines the study of working or living spaces with computing, information equipment, and multimodal sensing devices, and with natural and convenient interactive interfaces to support how people can easily obtain services from computer systems.People's work and life in smart spaces use computer systems; it is a process of uninterrupted interaction between people and the computer system. In this process, the computer is no longer just an information processing tool that passively executes explicit human operation commands but a collaborator with people to complete tasks – a partner to human beings. International research on smart spaces is quite extensive, which shows the important role of smart spaces in ubiquitous computing research.

Object-Oriented Analysis and Design for Information Systems

2nd Edition
March 16, 2024
Raul Sidnei Wazlawick
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 7 3 9 - 6
eBook
9 7 8 - 0 - 4 4 3 - 1 3 7 4 0 - 2

Object-Oriented Analysis and Design for Information Systems, Second Edition clearly explains real object-oriented programming in practice. Expert author Raul Sidnei Wazlawick explains concepts such as object responsibility, visibility, and the real need for delegation in detail. The object-oriented code generated by using these concepts in a systematic way is concise, organized and reusable.The patterns and solutions presented in this book are based in research and industrial applications. You will come away with clarity regarding processes and use cases and a clear understanding of how to expand a use case. Wazlawick clearly explains how to build meaningful sequence diagrams. Object-Oriented Analysis and Design for Information Systems illustrates how and why building a class model is not just placing classes into a diagram. You will learn the necessary organizational patterns so that your software architecture will be maintainable. The Second Edition includes all new content shifting the focus of the book to agile software development, including Scrum software project management, BPMN diagrams, user stories, and Python code examples.

Data Fusion Techniques and Applications for Smart Healthcare

1st Edition
March 12, 2024
Amit Kumar Singh + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 2 3 3 - 9
eBook
9 7 8 - 0 - 4 4 3 - 1 3 2 3 4 - 6

Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry, with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. The book can be used as a reference for practicing engineers, scientists, and researchers, but it will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications.Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, X-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI.

Related subjects

Coding and information theory

Data encryption

Data general

Data storage representations

Data structures

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health