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Information Systems Engineering and Management

Blockchain in the Tourism Industry: A
New Era of Secure and Transparent Trave

Blockchain in the Tourism Industry: A New Era of Secure and Transparent Travel Solutions

The Impact of Artificial Intelligence on Finance: Transforming Financial Technologies

Artificial General-Internet of Things (AG-IoT) for Robotics: Advanced Computer Vision Applications and Future Trends

Demystifying AI and ML for Cyber–Threat Intelligence

Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0

Revolution with Generative AI: Trends and Techniques

This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimer’s, Parkinson’s, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation.

Theoretical Insights with Practical Applications

Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises

Practices for Sustainable Manufacturing Industry, Volume 1

Engineering, Technology and Management

Human Resources Development in a Digital Age

Beyond Passwords: Protecting Healthcare with Authentication Security

Navigating the Deepfake Conundrum: A Manager's Roadmap

ICT4GS-2024

International Conference on Technology Advances for Green Solutions and Sustainable Development

Future of AI, IoT, and Sustainability

Über die Spezielle und die Allgemeine Relativitätstheorie

E = mc2

Synthesis Lectures on Computer Science

Practical Uses and Instruments for Exploring Complex Networks

Graph Mining

Intelligent Systems Reference Library

Volume 2

Computational Intelligence based Hyperspectral Image Analysis and Applications

SpringerBriefs in Applied Sciences and Technology

This open access book summarizes research being pursued within the LINCOLN project, funded by the EU community under the H2020 Blue Growth work programme, the goal of which is to design a new product service paradigm able to promote innovative business models, to open added value to the vessels and to create new market segments. It experiments and validates its approach on three new concepts of added-value specialized vessels able to run requested services for several maritime sectors in the most effective, efficient, economic valuable and eco-friendly way. The three vessels share the same lean design methodology, IoT tools and HPC simulation strategy: a lean fact-based design model approach, which combines real operative data at sea with lean methodology, to support the development and implementation of the vessel concepts; IT customized tools to enable the acquisition, processing and usage of on board and local weather data, through an IoT platform, to provide business services todifferent stakeholders; HPC simulation, providing a virtual towing tank environment, for early vessel design improvement and testing. The book demonstrates that an integrated LCC analysis and LCC strategy to guarantee sustainability to vessels concepts and the proper environmental attention inside the maritime industry.

The LINCOLN Project

Lean Innovative Connected Vessels

Springer Undergraduate Texts in Mathematics and Technology

Linear Algebra, Data Science, and Machine Learning

Lecture Notes in Computer Science

18th International Conference, ICGT 2025, Held as Part of STAF 2025, Koblenz, Germany, June 11–12, 2025, Proceedings

Graph Transformation

Lecture Notes in Networks and Systems

This book presents the latest research on Ambient Intelligence presented in the 15th International Symposium on Ambient Intelligence (ISAmI 2024). Interested researchers can find works on intelligent systems on healthcare and security scenarios; smart cities and urban environments; active intelligent mobility; Internet of Things in Industry 4.0; Ambient-Assisted Living; as well as quantum computing in economics, industrial and social applications; among others. 
The symposium was organized by the Universidade do Minho (Portugal), the Nitte Meenakshi Institute of Technology (India), the National Institute of Informatics (Japan), the Università degli Studi di Genova (Italy), the Universitat Politècnica de València, the University of Salamanca, the University of Granada, and the AIR Institute (Spain). The present edition was hosted within the Salamanca Tech Summit by the BISITE Research Group, the AIR Institute and the City Council in Salamanca, Spain, from June 26th to 28th, 2024.

Ambient Intelligence – Software and Applications – 15th International Symposium on Ambient Intelligence

Cognitive Technologies

This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over manufacturing and material science to more advanced combinations with deep learning, say, in the form of physical informed neural networks. The book is intended for those interested in modern informed machine learning for a wide range of practical applications&nbsp;where the aspect of small data sets is a challenge.Machine Learning with small amounts of data? After the recent success of Artificial Intelligence based on training with massive amounts of data, this idea may sound exotic. However, it addresses crucial needs of practitioners in industry. While many industrial applications stand to benefit from the use of AI, the amounts of data needed by current learning paradigms are often hard to come by in industrial settings. As an alternative, learning methods and models are called for which integrate other sources of knowledge in order to compensate for the lack of data. This is where the principle of “Informed Machine Learning” comes into play.Informed Machine Learning combines purely data driven learning and knowledge-based techniques to learn from both data and knowledge. This has several advantages. It reduces the need for data, it often results in smaller, less complex and more robust models, and even makes machine learning applicable in settings where data is scarce. The kind of knowledge to be incorporated into learning processes can take many different forms, for example, differential equations, analytical models, simulation results, logical rules, knowledge graphs, or human feedback which makes the approach overall very powerful and widely applicable.

Informed Machine Learning

Advances in Science, Technology & Innovation

This book explores emerging interdisciplinary themes and applications reflecting advancements in Computational Intelligence (CI) for IoT and 5G networks. It is divided into four sections:Section 1 introduces Computational Intelligence and Sustainability Solutions for Next-Gen IoT Networks. Section 2 covers Optimization and Resilience Strategies for 5G-Enabled IoT Networks. &nbsp;Section 3 delves Intelligent Resource Allocation and Service Optimization in 5G IoT Networks. Section 4 presents Case studies on Applied Computational Intelligence and 5G IoT Innovations for Industry 4.0.This comprehensive work is essential for researchers and professionals interested in leveraging CI, IoT, and 5G technologies across diverse applications.

Computational Intelligence Techniques for 5G Enabled IoT Networks

Schriftenreihe des Deutschen Instituts für Interdisziplinäre Sozialpolitikforschung (DIFIS)

Empirische Sozialpolitikforschung und evidenzbasierte Sozialpolitikberatung sind auf qualitativ hochwertige Daten sowie eine Dateninfrastruktur angewiesen, die einen einfachen Zugang zu Daten und die sichere Nutzung für die wissenschaftliche Forschung ermöglichen. Die bestehende Dateninfrastruktur steht jedoch in der Kritik. So werden unter anderem die Intransparenz des Datenökosystems, uneinheitliche Datenschutzstandards, die Anpassungsprobleme amtlicher Statistik an aktuelle Fragen und fehlende Verknüpfungsmöglichkeiten von Mikrodaten aus unterschiedlichen Quellen beanstandet. 
Dieses Buch bietet einen Überblick über die sozialpolitische Forschungsdateninfrastruktur in Deutschland mit besonderem Augenmerk auf Daten zu sozialpolitischen Leistungen. Es thematisiert Lücken und Bedarfe in der Dateninfrastruktur und entwickelt Empfehlungen zu deren Weiterentwicklung vor dem Hintergrund positiver Beispiele verschiedener europäischer Länder.

Empirische Sozialpolitikforschung und evidenzbasierte Sozialpolitikberatung sind auf qualitativ hochwertige Daten sowie eine Dateninfrastruktur angewiesen, die einen einfachen Zugang zu Daten und die sichere Nutzung für die wissenschaftliche Forschung ermöglichen. Die bestehende Dateninfrastruktur steht jedoch in der Kritik. So werden unter anderem die Intransparenz des Datenökosystems, uneinheitliche Datenschutzstandards, die Anpassungsprobleme amtlicher Statistik an aktuelle Fragen und fehlende Verknüpfungsmöglichkeiten von Mikrodaten aus unterschiedlichen Quellen beanstandet. 
Dieses Buch bietet einen Überblick über die sozialpolitische Forschungsdateninfrastruktur in Deutschland mit besonderem Augenmerk auf Daten zu sozialpolitischen Leistungen. Es thematisiert Lücken und Bedarfe in der Dateninfrastruktur und entwickelt Empfehlungen zu deren Weiterentwicklung vor dem Hintergrund positiver Beispiele verschiedener europäischer Länder.

Stand und Perspektiven

Dateninfrastrukturen für die Sozialpolitikforschung

Tourism, Hospitality & Event Management

This book provides a critical, systemic analysis of the challenge of food waste and its drivers in hospitality operations. It reviews existing approaches to mitigating food waste in catering services and highlights best practices in effective mitigation. It also discusses the determinants of the broader adoption of effective approaches to food-waste management across the sector and within the various geographical markets of out-of-home food consumption.This book is suitable for academics in the hospitality and tourism field as well as for professionals such as hotel and restaurant managers. It can also be used in undergraduate and postgraduate classes in hospitality management.

This book provides a critical, systemic analysis of the challenge of food waste and its drivers in hospitality operations. It reviews existing approaches to mitigating food waste in catering services and highlights best practices in effective mitigation. It also discusses the determinants of the broader adoption of effective approaches to food-waste management across the sector and within the various geographical markets of out-of-home food consumption.This book is suitable for academics in the hospitality and tourism field as well as for professionals such as hotel and restaurant managers. It can also be used in undergraduate and postgraduate classes in hospitality management.

Opportunities for Sustainable Management

Food Waste in Hospitality Operations

Studies in Systems, Decision and Control

This book delves into the crucial role of AI in addressing environmental challenges and driving sustainable business operations, while emphasizing the importance of incorporating robust security measures in these endeavors. Integrating Artificial Intelligence, Security for Environmental and Business Sustainability is a comprehensive guide that explores the intersection of artificial intelligence (AI), security, and sustainable practices.&nbsp;Our proposed book provides a solid foundation in AI principles and technologies relevant to environmental and business sustainability. It covers machine learning algorithms, deep learning techniques, and their applications in optimizing resources, managing risks, and enhancing decision-making processes.

Volume 1

Integrating Artificial Intelligence, Security for Environmental and Business Sustainability

Blockchain in the Tourism Industry: A New Era of Secure and ...

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Weitere Titel der Reihe: Information Systems Engineering and Management

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