Publications

It goes without saying that agriculture is a form of colonisation of nature by society. In the course of history the articulation of natural and societal features gave rise to a wide variety of agrosystems within the boundaries of Europe which were embedded in supra-regional political and economic contexts at least from the High Middle Ages onwards. By following an integrative approach, this volume defines agrosystems as production systems based on the ecological and socioeconomic relations involved in the reproduction of rural societies at multiple levels. The authors explore the articulation of natural and societal factors through the prism of labour relations. The structural and practical organization of labour is seen as the crucial link between rural production and reproduction. Accordingly, the contributions focus on the rural household as the basic unit of production and reproduction in different temporal and spatial contexts. Therefore, the question arises if the changes in ecosystems and social systems have so fundamentally altered European agriculture up to now that peasant family farming will disappear (if it is no longer sustained by state intervention).

This Symposium was hosted by the Universidad Politécnica de Madrid as an initiative of Working Group 5 of COST Action 924. The earlier Model-IT were organised in The Netherlands, New Zealand nad Leuven, and their results and publications by ISHS have shown that the tradition that started ten years ago is still attractive. For proper chain management, good and realiable predictive models covering all aspects of the food chain are necessary to control and optimise the food chain, going from farm to fork, with respect to quality and safety. This wide range was mirrored by the expertises displayed in the various conference contributions. Furthermore, the symposium offered the participants four workshops specially prepared for this occasion. We hope that these proceedings will be a source of inspiration to students and reserachers in industry and academia.

This volume provides a total of 24 peer reviewed papers as an overview of the work performed within COST Action G8 “Non-Destructive Testing and Analysis of Museum Objects” which ran from 2001 to 2006. This book is intended for all those interested in the benefit of non-destructive techniques, especially conservators, restorers, and art historians who will find examples of the applications of various analytical methods to art objects, ranging from metal artefacts through paintings and drawings to ceramics and stone.
The content will also be of interest to scientists working in research institutions who, whilst not having themselves a background in art or archaeology, often come face-to-face with issues related to cultural heritage which need specific scientific input to resolve particular problems. It is, over all, aimed at helping to bridge the gaps between the numerous players in this emerging multi-disciplinary field.

COST-TIST covers all COST research activities in the field of Telecommunications and Information technologies, services and applications. COST Actions in this area have successfully contributed to the aims of the European Research Area by brining a large set of national, industrial and university research activities in the field together into a common framework of research objectives.

– The book aims to describe how soft computing and statical methods can be used together to improve data analysis

– Advances research in soft computing and statical methods for data analysis

– Written by leading experts in the field

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasise different aspects of data analysis.

Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasises the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.

Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analysing the possible situations and their (relative) likelihood. It emphasises the need for mathematical methods and tools to assess solutions and guarantee performance.

Combining the two fields enhances the robustness and generalisability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.