Books in the Artificial Intelligence and Soft Computing for Industrial Transformation series

The world is experiencing an unprecedented period of change and growth through all the electronic and technilogical developments and everyone on the planet has been impacted. What was once 'science fiction', today it is a reality.This book explores the world of many of once unthinkable advancements by explaining current technologies in great detail. Each chapter focuses on a different aspect - Machine Vision, Pattern Analysis and Image Processing - Advanced Trends in Computational Intelligence and Data Analytics - Futuristic Communication Technologies - Disruptive Technologies for Future Sustainability. The chapters include the list of topics that spans all the areas of smart intelligent systems and computing such as: Data Mining with Soft Computing, Evolutionary Computing, Quantum Computing, Expert Systems, Next Generation Communication, Blockchain and Trust Management, Intelligent Biometrics, Multi-Valued Logical Systems, Cloud Computing and security etc. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

Die Nutzung von KI bei der Umgestaltung von Unternehmensprozessen betrifft sowohl die Managementmethoden als auch die Computertechnologie. In diesem Werk geht es darum, wie sich künstliche Intelligenz auf verschiedene Berufe auswirkt und welche Bedeutung die Algorithmen und Technologien des maschinellen Lernens haben. Vor dem Hintergrund der Anwendung von KI bei der Neugestaltung von Geschäftsprozessen werden in erster Linie neue Geschäftsmodelle sowie die Einsatzreife und -bereitschaft der KI auf organisatorischer, technologischer, finanzieller und kultureller Ebene betrachtet. Das Buch informiert ausführlich und detailliert über maschinelles Lernen und die entsprechenden Anwendungen in den Bereichen Robotik, Blockchain und Internet der Dinge. Zudem wird der Einfluss der KI auf Strategien und Verfahren im Finanzbereich, menschliche Fähigkeiten und Werte, innovative Beschaffungsstrategien, innovative Produktionsmethoden sowie beim Einsatz auf Marketing- und Verkaufsplattformen erörtert.

BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVALThis book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications.Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient's data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients' biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients.AudienceResearchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Covering the concepts and fundamentals of efficient energy systems, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple industries, for both the engineer and the student.There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these "game changers," governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society.This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation.The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.This outstanding new volume: Handles the fundamentals of system design including the concept of energy saving aspects at different levelsIs useful for all engineering students for learning the fundamentals of system design and automation with machine learning and IoTWill be helpful for researchers and designers to find out key parameters for future projects and current applicationsAudience: Engineers and scientists across many fields, including petroleum and process engineers, chemical engineers, electrical engineers working with power systems, and students at the university and post-graduate level studying energy topics

FUZZY INTELLIGENT SYSTEMSA comprehensive guide to Expert Systems and Fuzzy Logic that is the backbone of artificial intelligence.The objective in writing the book is to foster advancements in the field and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and those in education and research covering a broad cross section of technical disciplines.Fuzzy Intelligent Systems: Methodologies, Techniques, and Applications comprises state-of-the-art chapters detailing how expert systems are built and how the fuzzy logic resembling human reasoning, powers them. Engineers, both current and future, need systematic training in the analytic theory and rigorous design of fuzzy control systems to keep up with and advance the rapidly evolving field of applied control technologies. As a consequence, expert systems with fuzzy logic capabilities make for a more versatile and innovative handling of problems. This book showcases the combination of fuzzy logic and neural networks known as a neuro-fuzzy system, which results in a hybrid intelligent system by combining a human-like reasoning style of neural networks.AudienceResearchers and students in computer science, Internet of Things, artificial intelligence, machine learning, big data analytics and information and communication technology-related fields. Students will gain a thorough understanding of fuzzy control systems theory by mastering its contents.

Dieses Werk, das sich umfassend mit der Einführung von maschinellem Lernen, KI und dem IoT im Gesundheitswesen beschäftigt, richtet sich an Forschende, Fachkräfte im Gesundheitswesen, Wissenschaftler und Technologen.Die Nutzung von maschinellem Lernen und künstlicher Intelligenz im Internet der Dinge (IoT) für Anwendungen im Gesundheitswesen sowie die damit einhergehenden Herausforderungen werden ausführlich erörtert.Das IoT erzeugt gewaltige Datenmengen von unterschiedlicher Qualität. Die intelligente Verarbeitung und Analyse dieser Datenmengen sind der Schlüssel zur Entwicklung intelligenter IoT-Anwendungen, wodurch Raum für die Nutzung des maschinellen Lernens (ML) geschaffen wird. Mit ihren Recheninstrumenten, die bei der Erledigung bestimmter Aufgaben die menschliche Intelligenz ersetzen können, macht es die künstliche Intelligenz (KI) möglich, dass Computer aus Erfahrung lernen, sich an neue Eingaben anpassen und bisher von Menschen durchgeführte Aufgaben übernehmen. Da IoT-Plattformen eine Schnittstelle bieten, um Daten von unterschiedlichen Geräten zusammenzutragen, lassen sie sich leicht mit AI/ML-Systemen verbinden. Vor diesen Hintergrund besteht der Wert der KI in ihrer Fähigkeit, schnell Erkenntnisse aus Daten zu gewinnen, automatisch Muster zu erkennen und Anomalien in den von intelligenten Sensoren und Geräten erzeugten Daten zu erkennen ? aus Angaben zu Temperatur, Druck, Luftfeuchtigkeit, Luftqualität, Schwingungen und Geräuschen ? die für eine schnelle Diagnose extrem hilfreich sein können.