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Self-Adaptive Software
The 18 revised full papers presented in this book together with an introductory survey were carefully reviewed and constitute the documentation of the Second International Workshop on Self-adaptive Software, IWSAS 2001, held in Balatonfüred, Hungary in May 2001. Self-adaptive software evaluates its own behavior and changes it when the evaluation indicates that the software does not accomplish what it is intended to do or when better functionality or better performance is possible. The self-adaptive approach in software engineering builds on well known dynamic features familiar to Lisp or Java programmes and aims at improving the robustness of software systems by gradually adding new features of self-adaption or autonomy.
Measurement and Data Science
Nowadays, all of us enjoy the worldwide revival of measurement and data science caused by the revolution of sensory devices and the amazing data transmission, storage and processing capabilities available and embedded everywhere. Thanks to the unbelievable amount of recorded information and the theoretical results of measurement and data science, a great deal of newly developed products invade our surroundings and enable previously unconceivable smart services and support. This volume consists of a number of chapters covering the scientific results of researchers working in this field at the Department of Measurement and Information Systems of the Budapest University of Technology and Economics, Hungary. The book reports research results attained by carefully combining some of the classical theories of measurement and data processing. These new approaches and methods contribute to higher quality measurement design and measured data evaluation, and provide hints to find efficient implementations for instrumentation.
Software-Enabled Control
Discusses open systems, object orientation, software agents, domain-specific languages, component architectures, as well as the dramatic IT-enabled improvements in memory, communication, and processing resources that are now available for sophisticated control algorithms to exploit. Useful for practitioners and researchers in the fields of real-time systems, aerospace engineering, embedded systems, and artificial intelligence.
Automatic Algorithm Selection for Complex Simulation Problems
To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. An automated selection of simulation algorithms supports users in setting up simulation experiments without demanding expert knowledge on simulation. Roland Ewald analyzes and discusses existing approaches to solve the algorithm selection problem in the context of simulation. He introduces a framework for automatic simulation algorithm selection and describes its integration into the open-source modelling and simulation framework James II. Its selection mechanisms are able to cope with three situations: no prior knowledge is available, the impact of problem features on simulator performance is unknown, and a relationship between problem features and algorithm performance can be established empirically. The author concludes with an experimental evaluation of the developed methods.
IMTC/99
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IMTC Proceedings
None
IEEE Instrumentation and Measurement Technology Conferencer, 1999
The conference will cover all aspects of theory and practice of metrology, measurement technologies, instrumentation, and related applications.
