In the near future, we will see an increase in the development and use of all sorts of AI applications. Some of the more promising areas will be Finance, Healthcare, IoT, Manufacturing, Journalism, and Cybersecurity. Many of these applications generate a great amount of complex information. Natural Language Understanding is one of the most clear examples. Traditional ways of visualizing complex information, namely linear text, web pages and hyperlink-based applications, have serious productivity problems. Users need a lot of time to visualize the information and have problems seeing the whole picture of the results. Mind mapping is probably the only way of reducing the problems inherent in these traditional ways of visualizing complex information. Most people have no clear idea about the advantages of mind mapping or the problems created by the traditional ways of visualizing complex information. The goal of Mind Mapping and Artificial Intelligence is to provide readers with an introduction to mind mapping and artificial intelligence, to the problems of using traditional ways of visualizing complex information and as an introduction to mind mapping automation and its integration into Artificial Intelligence applications such as NLU and others. As more applications of Artificial Intelligence are developed in the near future, the need for the improvement of the visualization of the information generated will increase exponentially. Information overload will soon also happen in AI applications. This will diminish the advantages of using AI. Author José Maria Guerrero is a long-time expert in mind mapping and visualization techniques. In this book he also introduces readers to MindManager mind mapping software, which can considerably reduce the problems associated with the interpretation of complex information generated by Artificial Intelligence software. - Provides coverage of the fundamentals of mind mapping and visualization applied to Artificial Intelligence applications - Includes coverage of the scientific bases for mind mapping for the visualization of complex information - Introduces MindManager software for mind mapping - Introduces the author's MindManager toolkit for the readers to use in development of new mind mapping applications - Includes case studies and real-world applications of MindManager for AI applications, including examples using IBM Watson NLU

Dr.S.Gandhimathi, Assistant Professor, Department of Computer Science, Valluvar College of Science and Management, Karur, Tamil Nadu, India. Dr.K.Sivakami, Associate Professor, Department of Computer Science, Nadar Saraswathi College of Arts and Science, Theni, Tamil Nadu, India. Dr.B.Senthilkumaran, Assistant Professor, Department of Computer Science and Engineering, School of Computing, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai,Tamil Nadu, India. Dr.John T Mesia Dhas, Associate Professor, Department of Computer Science and Engineering, School of Computing, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai,Tamil Nadu, India. Mrs.S.Saranya, Assistant Professor, Department of Computer Science, Valluvar College of Science and Management, Karur, Tamil Nadu, India.

This double volume book set constitutes the refereed proceedings of 4th International Conference, AI-HCI 2023, held as part of the 25th International Conference, HCI International 2023, which was held virtually in Copenhagen, Denmark in July 2023. The total of 1578 papers and 396 posters included in the HCII 2023 proceedings was carefully reviewed and selected from 7472 submissions. The first volume focuses on topics related to Human-Centered Artificial Intelligence, explainability, transparency and trustworthiness, ethics and fairness, as well as AI-supported user experience design. The second volume focuses on topics related to AI for language, text, and speech-related tasks, human-AI collaboration, AI for decision-support and perception analysis, and innovations in AI-enabled systems.

This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.

Use the universe’s most powerful thinking tool to be more creative and successful than you ever dreamed possible! • Remember anything • Pass any exam • Get promoted • Manage your time • Have great relationships • Be healthy and happy • Plan your dream future Mind Map Mastery is the most authoritative, clear and accessible guide to Mind Mapping ever published, drawing on five decades of research and development by Mind Maps inventor Tony Buzan. Developed both for those new to the Mind Map concept as well as more advanced users who would like to build on their expertise, this is the one Mind Mapping book needed on the shelf of every student, teacher, business person and creative dreamer across the world. Discover how to: • Create Mind Maps at every level, from beginner to advanced. • Use Mind Mapping in every conceivable situation, from planning your week and revising for an exam to changing your career path and improving a difficult relationship. • Learn what to do when a Mind Map goes wrong and why pseudo Mind Maps don’t work. • Explore exciting new Mind Mapping applications, including a two-person Mind Map for conflict resolution, a Mind Map for report writing, a Mind Map to apply design thinking principles and a Mind Map to help budding authors get published. A Mind Map mirrors the structure of the brain’s neural network, with branches that reach outward from the centre of the diagram and evolve through patterns of association. This structural link with the workings of the brain is one reason why Mind Mapping is so effective. Unfortunately, over the decades since its invention by Tony Buzan, this incredible thinking tool has been misunderstood by some and misrepresented by others. This book is intended to set the record straight and help all its readers achieve Mind Map mastery. If you are looking to improve your memory, organize your weekly activities, study for an exam, plan your business strategy, change your career or envision your future, this is the book for you. Packed full of Mind Map workouts and mnemonic exercises, it includes clear explanation of the Laws of Mind Mapping, and guidance on what is a Mind Map (and what is not), as well as illustrated techniques for Mind Mapping at every level, and a whole chapter of trouble-shooting advice. It also features the true stories of master Mind Mappers and experts in their fields whose lives have been radically transformed by Mind Mapping. It’s time to set out on your own Mind Mapping adventure and discover the astounding power of your brain . . .

Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world's best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy. - The future of the data republic, life within a data democracy, and our digital freedoms - An in-depth analysis of open science, open data, open source software, and their future challenges - A comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychology - The democratization of Artificial Intelligence (AI), and data issues such as: Bias, imbalance, context, and knowledge extraction - A systematic review of AI methods applied to software engineering problems

This book is an introduction to a group of techniques known as visual mapping and its application in medicine. The best known of these techniques is mind mapping (MM). Mind mapping is a very old technique that has been neglected in many professional areas. Our intention is to offer a book full of useful information to students and professionals of medicine in the application of mind mapping to their work, which we hope will stimulate greater use of this technique. We have been using mind mapping for more than twenty years in different fields, insurance, programming, banking, medicine, GIS, data visualization and, in general, in complex information analysis. Medicine is an important field where more applications are possible.

While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications.

The concept of Robotics and Artifldal Intelligence (AI) has been in practice over the years with the advent of technological progress overtime and is transforming our world in profound and unprecedented ways, with the potential to revolutionise virtually every aspect of our lives. From self-driving cars and personal assistants to medical diagnosis and financial forecasting, AI is rapidly becoming an indispensable tool for solving complex problems and unlocking new opportunities for innovation and progress. As the world becomes increasingly complex and interconnected, robotics has emerged as a critical field that is revolution ising how we live, work and interact with our environment. From manufacturing and transportation to healthcare and education, robots are transforming industries and creating new opportunities for innovation and progress. Keeping this in mind, I.C.S.E. Robotics and Artificial Intelligence for Class 9 has been designed. This book is strictly based on the latest syllabus prescribed by the Council for the Indian School Certificate Examination (CISCE) and is intended to provide a comprehensive overview of the field, exploring the fundamental principles and applications of robotics and AI technology. Based on the latest research and developments in the fields, this book offers a detailed overview of the key concepts and techniques that underpin AI, from machine learning and natural language processing to computer vision and Robotics. This book will provide you with a comprehensive and up-todate understanding of these exciting and rapidly evolving fields keeping in line with ICSE syllabus. Salient Features of this Book • As per the latest syllabus and examination pattern prescribed by the ICSE. • The book is divided into two parts: Part I deals with the Robotics portion. This part consists of three units: Introduction to Robotics, Robot as a System and Concepts in Robotics. Part II deals with the Artificial Intelligence portion. This part consists of rwe units: Introduction to Artificial Intelligence (AI), Role of Data and Information. Evolution of Computing, Introduction to Data and Programming with Python, AI Concepts and AI Project Framework, and Assignments and Laboratory Experiments. • All the concepts explained in a simple language using a step-by-step approach supported by a Lot of illustrations. Chapter-wise Features • Learning Objectives introduces you to the learning outcomes and knowledge criteria covered in the chapter. • Chapter content caters to know about the topic of the chapter which may enrich your knowledge. • Did You Know? provides an interesting piece of knowledge to get the students interested. • Activity encourages students to integrate theory with practice. • Recap sums up the key concepts given in the chapter. • Key Terms are the main terminologies that are present in the chapter. • Each chapter contains an accompanying exercise that will assess students' understanding after they have completed the entire unit by answering the questions given in the exercise. Online Support • E-books (for teachers only). Teadtvs Resource Book • Overview of the chapters • Lesson plan • Answers of the exercise We hope that this book will inspire you to explore the limitless possibilities of Robotics and AI to make meaningful contributions to this dynamic and transformative field. Thus, it is a request to our esteemed readers to share the feedback. suggestions* etc. for the improvement of the book. All your suggestions for the improvement of the book are welcome. -Author

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making. No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective. - Offers a range of data science models, engineering tools, and federal use-cases - Provides foundational observations into government data resources and requirements - Introduces experiences and examples of data openness from the US and other countries - A step-by-step guide for the conversion of government towards data-driven policy making - Focuses on presenting data models that work within the constraints of the US government - Presents the why, the what, and the how of injecting AI into federal culture and software systems