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Gesamtkatalog

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Voice-related Biomarkers

Medical and Technical Analysis and Signal Processing Perspectives

Exploring Infant Cry

Concepts, Models, and Applications

Learning-Driven Game Theory for AI

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

Die Vierte Kränkung. Der Mensch im Schatten der Künstlichen Intelligenz

Digital Geographies

Purposeful Use of the Internet and Technologies

Global Digital Divides in the COVID-19 Era

Machine Learning und Künstliche Intelligenz sind mehr als nur Schlagworte – sie sind Schlüsseltechnologien, die unsere Wirtschaft und Gesellschaft nachhaltig verändern. Dennoch zögern viele Unternehmen, diese Potenziale zu nutzen. Woran liegt das? Häufig fehlt es an Know-how, Vertrauen und einem klaren Verständnis der Methoden und Einsatzmöglichkeiten.Dieses Buch vermittelt praxisnahes Know-how für Entscheider und Interessierte, die verstehen wollen, wie Machine Learning funktioniert und welchen Nutzen es für Unternehmen stiften kann. Mit der kostenlosen Programmiersprache Python als Werkzeug werden reale Business Cases wie Hauspreisprognosen (Regression), Kreditrisikobewertung (Klassifikation), Kundensegmentierung (Clustering), Cross-Selling (Empfehlungsmaschinen) und Dynamic Pricing (Bestärkendes Lernen) nachvollziehbar erklärt.Darüber hinaus werden Best Practices zur Datenvorverarbeitung sowie die grundlegende Methodik des Machine Learnings vorgestellt. So entsteht ein fundiertes Verständnis, das hilft, Vertrauen in die Technologie aufzubauen. Ein Buch für alle, die verstehen wollen, wie aus Daten echte Entscheidungen werden.Der Inhalt<ul><li>Nutzen von Machine Learning und KI</li><li>Best Practices</li><li>Python-Grundlagen</li><li>Erstellung von KI-Anwendungen</li><li>Anwendung von Machine Learning</li></ul>Der Autor Bernd Heesen ist Professor an der wirtschaftswissenschaftlichen Fakultät der Hochschule Ansbach in Bayern. Vor seiner Tätigkeit an der Hochschule war er mehr als 10 Jahre als Unternehmensberater im In- und Ausland tätig. Er berät Unternehmen auch weiterhin bezüglich der Nutzung von IT-Innovationen.

Erstellung eigener Anwendungen mit Python

Künstliche Intelligenz im Business

An authoritative deep dive into the most recent machine learning approaches to hyperspectral remote sensing image processing In Machine Learning-Based Hyperspectral Image Processing, distinguished researcher Dr. Bing Zhang delivers an up-to-date discussion of machine learning-based approaches to hyperspectral image analysis. The author comprehensively reviews machine learning approaches to hyperspectral image denoising and super-resolution tasks, offering coverage of a variety of perspectives. Dr. Zhang also explores the most recent research on machine learning hyperspectral unmixing methods and hyperspectral image classification. He explains the algorithms used for hyperspectral image target and change detection, as well. Readers will also find: <ul> <li>A thorough introduction to the novel concept of applying advanced machine learning techniques to the analysis of hyperspectral imagery</li> <li>Comprehensive explorations of the most recent developments in this technology and its applications</li> <li>Practical discussions of how to effectively process and extract valuable insights from hyperspectral data</li> <li>Complete treatments of a variety of hyperspectral remote sensing image processing tasks, including classification, target detection, and change detection.</li> </ul> Perfect for postgraduate students and research scientists with an interest in the subject, Machine Learning-Based Hyperspectral Image Processing will also benefit researchers, academicians, and students engaged in machine learning-based approaches to image analysis.

Machine Learning-Based Hyperspectral Image Processing

Digitalization implies a wide range of transformation processes at all levels of democratic societies. The political, public and academic debates about digitalization and democracy have always been controversial and still are today. Greatly intensified research activities in recent years have expanded our knowledge about the effects of digitalization, but show that debates still range from optimistic views to sceptic or even dystopian perspectives. The former emphasize the potential of the internet to drive innovation in society and to enhance democracy. Moreover, the expanding digitalization of everyday life seems as an opportunity for increasing individualism and free choice. From this perspective it is claimed that digital technologies, artificial intelligence (AI), robotics, and algorithms are to be seen as helpful tools in optimizing social life. In contrast, skeptical views highlighting the risks and even threats of digitalization for democratic values have increased recently. This finds expression in many well-researched aspects such as the growing relevance of fake news and “alternative facts” online. Algorithmic filtering promotes visibility of polarizing content and politically extreme positions. Furthermore, social media platforms can no longer be seen as neutral gathering places for rule-governed discourse. In addition, it is warned about digital technology and AI threatening autonomous decision making and the digitalization of everyday life is critically viewed as a misuse of data in terms of public surveillance and control.&nbsp;All of this makes it necessary to further research the role of digitization with regard to strengthening and preserving democracy in the digital age. This was precisely the main focus of the NRW Digital Society research network funded by the state of North Rhine-Westphalia from 2018 to 2022. The book is the central joint publication of the network and brings together the projects and disciplines of all universities and collegesparticipating in the network. The publication documents the most important project results that have not yet been published centrally and presents them for discussion not only to the academic public. At the same time, the book offers an insight into the interdisciplinary characteristics and challenges of the growing research field of digitization research.
This is an open access book.
The Editors
Mario Anastasiadis (PhD, born 1975)&nbsp;&nbsp;is managing director and scientific coordinator in the Research Program and Graduate School NRW “Digital Society” funded by the Ministry of Culture and Science of the German State of North Rhine-Westphalia. He works as research associate at the University of Bonn, Department of Media Studies, and is spokesperson of the Popular Culture and Media section of the German Media Studies Association (GfM). His main research interests include Mediatization, Online Communication, Political Communication, Digitization of the Music Industry and music related Practice in Social Media.

Interdisciplinary digitization research on the question of strengthening and preserving democracy in the digital society

Digital Society

In an era of escalating energy demands and environmental challenges, mastering the complexities of renewable power systems is essential. This open access book delivers a cutting-edge exploration of innovative modeling and control techniques tailored for the unique characteristics of renewable power systems. Designed for engineers, researchers, and sustainability advocates, this book addresses critical issues such as low inertia and high variability, offering a roadmap to ensure safe, stable, and efficient operation. This comprehensive guide introduces the fully actuated system approach, a groundbreaking method that redefines how we tackle the nonlinear dynamics inherent in renewable power systems. By presenting experimentally validated solutions on hardware microgrids, the book bridges the gap between theory and practice, making it an indispensable resource for professionals aiming to enhance system reliability and control efficiency. Key topics include predictive control for DC and AC systems, learning-based optimization, and resilience strategies against cyber threats, with advanced applications like blockchain integration for secure operations. Readers will gain actionable insights into modern control strategies, rigorous modeling techniques, and emerging technologies shaping the future of renewable power systems. Whether you’re developing advanced control technologies or navigating the challenges of modern power systems, this book equips you with the knowledge and tools to lead in the renewable energy revolution.

A Fully Actuated System Approach

Control of Renewable Power Systems

Machine Learning For Dummies

This volume provides a comprehensive introduction to computational materials science, focusing on both fundamental theory and practical applications. The book serves as an essential resource for the researchers working at the intersection of materials science and practical computational techniques. The authors present an in-depth examination of the theoretical principles that govern the behaviour and properties of materials in the context of computational analysis, providing a strong connection to the research areas of quantum mechanics, statistical mechanics, and thermodynamics. The book serves as a platform for the materials community interested in the transition to computational methodologies, detailing state-of-the-art simulation and modelling techniques like density functional theory, molecular dynamics, and finite element analysis.<ul><li>Provides an overview of recent advances in computational material science related to its energy, environment and health;</li><li>Focuses on commercial applications with case studies and practical examples of this work addressing current challenges;</li><li>Brings together a diverse range of perspectives and disciplines from a global slate of experts.</li></ul>

Theoretical and Computational Materials Science: Advances and Applications

Arbeit und Alltag

Die Praxis unternehmerischer Software-Entwicklung ist auf verschiedenen Ebenen fragil und wird von zahlreichen Fehlern oder Diskontinuitäten herausgefordert: Im Programmieren, in der ökonomischen Rahmung der Software-Arbeit sowie in der Herstellung einer stabilen Belegschaft mit kollektiver Identifikation. Diesen Bruchstellen begegnen die Beschäftigten des Software-Unternehmens, das im Rahmen einer ethnografischen Feldforschung untersucht wurde, mit Elementen der Stabilisierung: Programmier-Werkzeuge, Projektmanagement-Strukturen, detaillierte Erfassung von Arbeitszeit, partizipative Räume der Teilhabe oder das Angebot firmenweiter Werte werden hier als konnektive Strategien analysiert. Diese Elemente der Konnektivität bieten Verbindungspotenziale, über die Menschen Wissen, explizieren, aktualisieren, fixieren oder austauschen können. So praktizieren die Beschäftigten eine hochkollektivierende Form von 'New Work', in der Subjektivierung mit Identifikation verwoben wird. Stete Selbstvergewisserung durch Narrative von Expertise führt weiter dazu, dass fragile Verbindungen im Arbeitsalltag des Unternehmens stabilisiert werden - solange das gemeinschaftlich gesponnene, konnektive Netz in Praxis aufrechterhalten wird.

Erwerbsarbeit, Unternehmenskultur und Konnektivität in der Software-Entwicklung

Fragile Verbindungen

Voice-related Biomarkers

Autres titres sur ce thème