الصفحة 3
الصفحة 3
Algebra and Coalgebra in Computer Science; First International Conference, CALCO 2005, Swansea, UK, September 3-6, 2005, Proceedings
CALCO, the Conference on Algebra and Coal-gebra in Computer Science, was created to bring together researchers and practitio-ners to exchange new results related to foundational aspects, and both traditional and emerging uses of algebras and coalgebras in computer science. CALCO 2005 was the first instance of this new conference. The interest that it generated in the scientific community suggests that it will not be the last. Indeed, it attracted as many as 62 submissions covering a wide range of topics roughly divided into two areas: Algebras and Coalgebras as Mathematical Objects: Automata and languages; categorical semantics; hybrid, probabilistic, and timed systems; inductive and coin-ductive methods; modal logics; relational systems and term rewriting.
AI, data, and digitalization : First International Symposium, SAIDD 2023, Sogndal, Norway, May 9–10, 2023, Revised Selected Papers
Artificial Intelligence, Big Data and Digitalization allow us more than ever beforeto make use of the data our society and public and private sectors generate every day.Institutions around the world are increasingly turning to such methods and technologiesto help them solve complex problems, promote efficiency and improve performance anddecision-making.
Advances in Mass Data Analysis of Signals and Images in Medicine, Biotechnology and Chemistry ; International Conference, MDA 2006/2007, Leipzig, Germany, July 18, 2007, Selected Papers
The automatic analysis of images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers, and other sensors have found their way into wide fields of medicine, biotechnology, economy, and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which generate automatically the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analyses on the basis of classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. The goals of this: Provide a forum for identifying important contributions and opportunities for research on mass data analysis on microscopic images Promote the systematic study of how to apply automatic image analysis and interpretation procedures to that field Show case applications of mass data analysis in biology, medicine, and chemistry Topics of interest include (but are not limited to): Techniques and developments of signal and image producing procedures Object matching and object tracking in microscopic and video microscopic images 1D, 2D, and 3D shape analysis and description
Advances in Artificial Economics : The Economy as a Complex Dynamic System
Perceiving the economy as a complex dynamic system, generates a need for new tools for its study. As a constructive simulation method, Agent-Based Computational Economics (ACE) has in recent years proven its strength and extensive applicability. Fields of study are widely spread within economics, with a cluster around financial markets. This book is based on communications given at AE’2006 (Aalborg, Denmark) – the second symposium on Artificial Economics, and covers both wellknown questions of economics, like the existence of market efficiency, as well as new questions raised by the new tools, for example questions related to networks of social interaction.
3-D Shape Estimation and Image Restoration : Exploiting Defocus and Motion-Blur
Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene—as well as its radiance properties—and which in turn can be used to generate novel images with better quality. 3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.
