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An objective, dynamic and physically justified concept of information is elaborated starting from Shannon's concept of entropy and applied to information technology, artificial intelligence (consciousness) and thermodynamics. The justification of an information conservation theorem acquires practical significance in information technology, especially as it moves into the quantum realm (photonics/quantum computing). The unconditional dynamics of information and its objectivity are critically examined and are the foundations of the considerations. We live in the information age, but the concept of information is still not defined objectively and physically. This book defines a dynamic concept of information that results in a conservation of information principle. Just as the principle of conservation of energy is essential to understanding energy, the principle of conservation of information leads to a deeper understanding of information. Information is strongly related to entropy, always in motion, cannot disappear, and is independent of subjects.

In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles.

This book treats various methods for stability analysis and controller design of local model networks (LMNs). LMNs have proved to be a powerful tool in nonlinear dynamic system identification. Their system architecture is more suitable for controller design compared to alternative approximation methods. The main advantage is that linear controller design methods can be, at least locally, applied and combined with nonlinear optimization to calibrate stable state feedback as well as PID controller. The calibration of stable state-feedback controllers is based on the closed loop stability analysis methods. Here, global LMIs (Linear Matrix Inequalities) can be derived and numerically solved. For LMN based nonlinear PID controllers deriving global LMIs is not possible. Thus, two approaches are treated in this book. The first approach works iteratively to get LMIs in each iteration step. The second approach uses a genetic algorithm to determine the PID controller parameters where for each individual the stability is checked. It allows simultaneous enhancement of (competing) optimization criteria.

Fabian Lorig develops a procedure model for hypothesis-driven simulation studies which supports the design, conducting, and analysis of simulation experiments. It is aimed at facilitating the execution of simulation studies with regard to the replicability and reproducibility of the results. In comparison to existing models, this approach is based on a formally specified hypothesis. Each step of the simulation study can be adapted to the central hypothesis and performed in such a way that it can optimally contribute to the verification and thus to the confirmation or rejection of the hypothesis.

Trustworthiness is a key success factor in the acceptance and adoption of cyber-physical systems. The author first discusses various existing definitions of trust and trustworthiness and extends them to cyber-physical systems. A comprehensive framework is proposed, including methods that cover all phases of development: requirements engineering, system design, trustworthiness evaluation, run-time maintenance, and evidence-based assurance. To support a smooth integration of the methods into development projects, these methods are provided in the form of so-called capability patterns. A running example from the ambient assisted living domain is used to demonstrate the application of the methods.About the Author:Nazila Gol Mohammadi is currently working as an associate researcher at paluno – The Ruhr Institute for Software Technology in Essen, Germany. Her research interests include software engineering, requirements engineering, digitalization, cloud computing, cyber-physical systems, and trustworthiness of software systems.

Dieser Herausgeber-Band bietet eine umfassende Einführung in das Gebiet Big Data. Neben einer Markteinschätzung und grundlegenden Konzepten (semantische Modellbildung, Anfragesprachen, Konsistenzgewährung etc.) werden wichtige NoSQL-Systeme (Key/Value Store, Column Store, Document Store, Graph Database) vorgestellt und erfolgreiche Anwendungen aus unterschiedlichen Perspektiven erläutert. Eine Diskussion rechtlicher Aspekte und ein Vorschlag zum Berufsbild des Data Scientist runden das Buch ab. Damit erhält die Leserschaft Handlungsempfehlungen für die Nutzung von Big-Data-Technologien im Unternehmen.