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SMART INNOVATIONS FOR CLIMATE RESILIENCE, FOREST SUSTAINABILITY, AND GREEN ECONOMY
WHY THIS BOOK? A rapidly warming climate is stretching forests beyond historical envelopes: longer fire seasons, flashier floods, synchronized pest outbreaks, and compound extremes that make yesterday’s rules unsafe. At the same time, data and computation have leapt ahead: anyone with a laptop can access daily satellite imagery, fuse it with tower cameras and stream gauges, run open-source models, and coordinate crews using offline apps. Yet there is a gap between possibility and practice. Toolkits remain scattered across disciplines; documents assume bandwidth, budgets, or institutional capacity that field teams rarely have; and many plans underplay social license and safety—two determi...
Robotics And Automation computer science and engineering
The concept of robots may be seen as highly developed automated systems when viewed from a certain point of view. In addition, robotics may be seen as both a scientific area and a technology that has emerged from automation via the collaborative efforts of several other fields of endeavour. These are some other viewpoints about robotics. In general, an automated system requires relatively little in the way of intelligence or manipulation, yet it may be simply programmed to achieve productivity goals. This is because it is able to function without human intervention. Additionally, it is feasible for the system to do some processes more than once. Keeping in mind that the mechanical structure ...
AI APPLICATIONS IN PSYCHOLOGY
Structure and Organization The book is structured into eleven comprehensive chapters, each addressing a key thematic area where AI intersects with psychology: Chapters 1–3 introduce the foundations: the historical context, the core technologies (AI, machine learning, NLP, etc.), and the significance of AI in research and cognitive modeling. Chapters 4–7 explore domain-specific applications: clinical psychology, behavioral analysis, cognitive assessment, educational psychology, and developmental tracking. Chapter 8 focuses on AI’s role in cultural and social psychology, sentiment analysis, group behavior, and bias detection. Chapter 9 dives deep into neuropsychology and brain-computer i...
Artificial Intelligence and Sustainable Innovation
This book brings together researchers, academicians, industry professionals, and policymakers to explore the transformative role of Artificial Intelligence (AI) in addressing global sustainability challenges. With a distinct focus on the United Nations Sustainable Development Goals (SDGs), it serves as a rich repository of research on AI for energy efficiency, climate change mitigation, smart cities, healthcare, and education. This title comprises a selection of papers that reflect an emphasis on interdisciplinary research and real-world applications. It covers a broad spectrum of topics including, but not limited to, Artificial Intelligence and Sustainable Innovation in green infrastructure, industry and manufacturing, education and policy, banking, navigation, communication, security, and sustainable agriculture. It also delves into real-life applications of intelligent computing and communication techniques in congruence with SDG goals. Researchers, academicians, research scholars, persons in industry, students, entrepreneurs, and technology enthusiasts will benefit from this book.
ARTIFICIAL BRAIN AND SIMULATION
The human brain remains the most explosive enigmatic and powerful computing system ever known. Its unmatched ability to learn, adapt, reason, and generate creativity continues to inspire scientists, engineers, and philosophers across generations. With the rise of Artificial Intelligence (AI), Neuroscience, and Neuromorphic Engineering, the question once relegated to the realm of science fiction — Can we build an artificial brain? — is now a legitimate and actively explored scientific frontier. This book, Artificial Brain and Simulation, is an earnest attempt to synthesize the diverse yet interrelated domains of cognitive science, machine learning, brain simulation, neuromorphic computing...
HOW TO CRACK TECH INTERVIEWS IN THE ERA OF AI?
ROADMAP TO THIS BOOK The structure of this book is carefully crafted to guide you step-by-step through the modern interview journey: Section I: The New Landscape of Tech Hiring This section helps you understand how hiring processes have changed in the age of AI. From how resumes are parsed by ATS bots to how AI tools are used in assessments, it lays the foundation for modern-day interview expectations. Section II: Cracking the Core – Problem Solving & Data Structures This section dives into data structures and algorithms, the bedrock of technical interviews. It includes smart approaches to practicing LeetCode, pattern-based problem solving, and optimizing time/space complexity—plus a ref...
MACHINE LEARNING IN BIOINFORMATICS
Machine learning (ML) has revolutionized the field of bioinformatics, offering innovative tools and methodologies to tackle complex biological problems. In bioinformatics, data is often vast, diverse, and multidimensional, ranging from genomic sequences to protein structures, gene expressions, and clinical datasets. Machine learning techniques have proven essential in analyzing and extracting meaningful patterns from these enormous datasets. The use of ML in bioinformatics spans a broad spectrum of applications, from predicting protein structures and functions to identifying genetic variants associated with diseases. By leveraging supervised, unsupervised, and reinforcement learning algorith...
AGENTIC AI 360º FOUNDATIONS, ARCHITECTURES, AND FUTURES
ABOUT THE BOOK The World is witnessing a remarkable shift in the trajectory of Artificial Intelligence—from systems that merely react to stimuli or process data to agents capable of autonomous decision-making, goal pursuit, moral reasoning, and social interaction. This transformation calls for a new conceptual and practical framework: Agentic AI. The term denotes intelligent systems that operate as agents—autonomous entities with beliefs, desires, intentions, and the ability to act toward achieving objectives within dynamic environments. These agentic systems are not only reactive or predictive but deliberative and proactive. They can plan, adapt, collaborate, and even evolve in ways tha...
GENETIC ALGORITHM AND MACHINE LEARNING
Imagine that you own a website where you sell software that you've developed yourself and that you provide it to people who visit your site as a service. You have come to the conclusion that the best way to achieve your objective of better catering the website to the individual requirements of each user is to get started gathering data on the individuals who use the website. This data includes not only the kind of computer and operating system that visitors use, but also the web browser that they use to access the website, the nation in which they are residents, as well as the time of day that they viewed the website. Your ultimate goal is to improve the website's usefulness for each user in...
New Trends and Applications in Internet of Things (IoT) and Big Data Analytics
This book focuses on the use of The Internet of Things (IoT) and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. IoT and big data emerged from the early 2000s data boom, driven forward by many of the early internet and technology companies. The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. There are a variety of IoT-based applications being used in different sectors and have succeeded in providing huge benefits to the users. The generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends to adopt the data analytics to strengthen solutions. The success of IoT depends upon the influential association of big data analytics. New technologies like search engines, mobile devices, and industrial machines provided as much data as companies could handle—and the scale continues to grow. In a study conducted by IDC, the market intelligence firm estimated that the global production of data would grow 10x between 2015 and 2020. So, the proposed book covers up all the aspects in the field discuss above.
