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Integration of Federated Learning and
Blockchain for Smart Cities

Integration of Federated Learning and Blockchain for Smart Cities

Powered by Hyperscale Computing and Next Generation Networks

AI-Driven Smart Healthcare

Green Federated Learning for Sustainable Smart Computing

This unique compendium presents the basics of the theory of computing at a level and in a manner that can be easily understood by computer science students in a large university. It offers the student a firm foundation in logical reasoning and covers many traditional topics in unconventional ways.The useful reference text benefits professionals, academics, researchers and undergraduate students in the area of theoretical computer science.

Foundation Of Computation: Languages And Machines

Art in the Age of AI

How to See Like a Machine

Medical and Technical Analysis and Signal Processing Perspectives

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AI-Powered Ergonomics

Exploring Machine and Deep Learning's Impact on Computer Vision

From Pixels to Insights

Moving Towards Fully Autonomous and Cost-Effective Surgical Robotic Systems with AI offers advanced insights into how AI can be used to optimize the design, manufacturing, and clinical application of these systems. It covers a wide range of topics, including the introduction of surgical robotic systems design and the presentation of a fully autonomous surgical robotic system for minimally invasive surgery. Advanced medical imaging techniques integrated with surgical robots are discussed to enhance surgical precision and safety. The book also highlights the application of machine learning and deep learning models in robotic-assisted surgery, with the development of novel algorithms for autonomous surgical robots. Various AI approaches for optimizing surgical robotic systems and the design considerations for manufacturing and assembly are examined. Additionally, the book includes a thorough analysis of the life cycle and economic aspects of surgical robotic systems, as well as risk assessment and evaluation methods. The final chapters address ethics considerations and explore future enhancements in the realm of fully autonomous surgical robotic systems. Overall, this book aims to contribute to the technical understanding, design aspects, and ethical dimensions of surgical robotics, promoting safer and more efficient surgical procedures.

Moving Towards Fully Autonomous and Cost-Effective Surgical Robotic Systems with AI

Shaping the Future of Cities

AI-Driven Urban Planning

This book highlights the enduring synergy between information technology and decision-making tools, showcasing how advancements in one field drive progress in the other. Featuring the discoveries of esteemed researchers from the International Journal of Information Technology and Decision Making, it provides an insightful exploration of foundational concepts and cutting-edge techniques.This review volume opens with a broad overview of fundamental concepts like the Analytic Hierarchy Process (AHP) and Threat-Oriented Person Screening Integrated System, (TOPSIS) across the past decades. Subsequent chapters explore how theoretical advances find practical application in diverse fields.In this book, techniques from fuzzy logic find usage in uncertainty modelling, followed by the use of feature selection and recommendation in machine learning. The use of advanced optimization techniques for applications in price forecasting and the Internet of Things (IoT) are also covered. Additionally, the work presents novel methods under a neutrosophic environment as well as global and local importance used for multi-criteria decision-making. The prolific research presented helps to expand the repertoire of approaches to tackle problems in business strategy, healthcare and public policy.This comprehensive resource is an essential reference for practitioners and researchers seeking to expand their expertise in decision-making and technology-driven solutions.

Innovative Approaches To Decision Making: Bridging It And Decision Science

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools-just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

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