This proceedings volume focuses on new methods of image and signal analysis in a wide range of energies (from radio to gamma ray astronomy) and advanced methodologies regarding problems and solutions in information fusion and retrieval, statistical pattern recognition, vision and advances in computing technology.A special section is devoted to the BeppoSAX mission (Satellite per Astronomia X) launched on April 30 1996, inside a program of the Italian Space Agency (ASI) and the Netherlands Agency for Aerospace Programs (NIVR).

Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.

This volume contains papers presented at the 5th International Conference on Image Analysis and Processing. It covers the most important topics of current interest in the field, presenting a large collection of recent results achieved by leading academic and industrial research groups from several countries. It contains invited lectures and research papers dealing with theoretical and applicative aspects of Image Processing. It is a valuable and updated reference source for the Image Processing community. It contains advanced architectural concepts and describes new frontiers for applicants.

A world list of books in the English language.

For effusive volcanoes in resource-poor regions, there is a pressing need for a crisis response-chain bridging the global scientific community to allow provision of standard products for timely humanitarian response. As a first step in attaining this need, this Special Publication provides a complete directory of current operational capabilities for monitoring effusive eruptions. This volume also reviews the state-of-the-art in terms of satellite-based volcano hot-spot tracking and lava-flow simulation. These capabilities are demonstrated using case studies taken from well-known effusive events that have occurred worldwide over the last two decades at volcanoes such as Piton de la Fournaise, Etna, Stromboli and Kilauea. We also provide case-type response models implemented at the same volcanoes, as well as the results of a community-wide drill used to test a fully-integrated response focused on an operational hazard-GIS. Finally, the objectives and recommendations of the ‘Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters’ working group are laid out in a statement of community needs by its members.

The goal of the project is to provide the polish scientific community with an IT platform based on grid computer clusters, enabling e-science research in various fields. The created infrastructure is both compatible and interoperable with existing european and worldwide grid frameworks. The system ensures scalability and enables the integration of additional local clusters, belonging to universities, research institutions and technology platforms. This state-of-the-art survey describes the experience and the scientific results obtained by project partners as well as the outcome of research and development activities carried out within the Polish Infrastructure for Information Science Support in the European Research Space PL-Grid (PL-Grid 2011), held in December 2011 in Krakow, Poland. The 26 papers are organized in topical sections on: eclipse parallel tools platform integrated with QosCosGrid, the migrating desktop, science gateways based on the vine toolkit, the gridspace experiment platform, and the InSilico-Lab environment.

"Astronomy and Astrophysics Abstracts" appearing twice a year has become oneof the fundamental publications in the fields of astronomy, astrophysics andneighbouring sciences. It is the most important English-language abstracting journal in the mentioned branches. The abstrats are classified under more than a hundred subject categories, thus permitting a quick survey of the whole extended material. The AAA is a valuable and important publication for all students and scientists working in the fields of astronomy and related sciences. As such it represents a necessary ingredient of any astronomical library all over the world.

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.