Digital preservation is an issue faced by practitioners in Ross Harveythe library and recordkeeping professions, yet most professionalshave little time to keep up with the latest techniquesand standards. This invaluable work provides a single-volume introduction to the principles, strategies and practices currently applied by librarians and recordkeepers to the preservation of digital information and will assist them to make informed decisions about the role of digital information in their care. The book is presented in four parts: Why do we preserve? What do we preserve? How do we preserve? and How do we manage digital preservation? Each part covers the area in detail and addresses current issues in a clear and informative manner. The terminology of the field is explained clearly throughout the book. Each chapter includes a range of case studies from institutionsat the forefront of digital object preservation. An index facilitates quick access. This book will be essential as a professional reference tool for all librarians, recordkeepers and archivists with preservation responsibilities as well as being a definitive source of information for the whole profession including students.

Automatic learning is a complex, multidisciplinary field of research and development, involving theoretical and applied methods from statistics, computer science, artificial intelligence, biology and psychology. Its applications to engineering problems, such as those encountered in electrical power systems, are therefore challenging, while extremely promising. More and more data have become available, collected from the field by systematic archiving, or generated through computer-based simulation. To handle this explosion of data, automatic learning can be used to provide systematic approaches, without which the increasing data amounts and computer power would be of little use. Automatic Learning Techniques in Power Systems is dedicated to the practical application of automatic learning to power systems. Power systems to which automatic learning can be applied are screened and the complementary aspects of automatic learning, with respect to analytical methods and numerical simulation, are investigated. This book presents a representative subset of automatic learning methods - basic and more sophisticated ones - available from statistics (both classical and modern), and from artificial intelligence (both hard and soft computing). The text also discusses appropriate methodologies for combining these methods to make the best use of available data in the context of real-life problems. Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field.

Le développement spectaculaire d’internet, des réseaux sociaux, de la technologie mobile et la multiplication des capteurs provoquent une croissance exponentielle des données à laquelle les entreprises doivent faire face : c’est le phénomène du Big Data. Ses enjeux sont considérables. Au-delà de la simple question technique du stockage, il offre la possibilité de tirer profit du contenu de ces nouvelles sources d’information. Les solutions décisionnelles classiques laissent progressivement place au Business Analytics et aux méthodes prédictives, transformant l’avalanche de données en valeur ajoutée. La technologie est aujourd’hui disponible, les bases de données traditionnelles ont évolué et les solutions dédiées à l’exploitation des données massives, telles que Hadoop, sont désormais opérationnelles. S’appuyant sur différents cas pratiques, Enjeux et usages du Big Data met l’accent sur les méthodes, les techniques et les ressources nécessaires pour permettre aux entreprises d’entrer avec succès dans l’ère de l’information à grande échelle.

Artificial Intelligence in Real-Time Control documents the proceedings of the IFAC Workshop held in Clyne Castle, Swansea, UK, 21-23 September 1988. It includes two keynote addresses that discussed architectural issues for expert systems in real-time control; the problem of representing knowledge and reasoning; and the problems encountered in obtaining such information. Other papers contained in these proceedings are representative of the major research bodies active throughout the world in the application of AI techniques in real-time control, although it was inevitable that a Europe-based conference would highlight the work of the European groups. While AI is clearly still in the process of establishing itself, it is undoubtedly a major new area of engineering endeavor. Practical experience is still relatively limited, and many of the results discussed at this event were obtained through simulation or, in a few cases, from reduced practical experience. The importance, though, lies in the fact that many countries are pouring extensive resources into the attempt to control difficult processes by using AI techniques. The wide cross section of interest was demonstrated by the fact that many diverse industries were represented at the workshop—ranging from power-systems control to telecommunications, and into the steel industry.

Et si l’intelligence artificielle nous était contée ? Intelligence artificielle – Défis & perspectives a été conçu comme une invitation à découvrir cette révolution technologique et intellectuelle dont les avatars ne sont ni entièrement connus ni sans doute proprement maîtrisés. Si le concept a d’ores et déjà intégré l’imaginaire commun sous bien des formes, il soulève de véritables enjeux juridiques, éthiques et sociétaux que cet ouvrage collectif se propose d’aborder de façon non totalement linéaire, préférant au jardin à la française les arrangements subtilement décalés des espaces verts d’outre-Manche. Tout en permettant d’initier le lecteur à des domaines d’application variés et novateurs et de montrer combien l’intelligence artificielle fait désormais partie de notre quotidien, cet ouvrage apporte des réflexions prospectives sur les évolutions attendues ou souhaitées dans son domaine d’élection. Il reste à espérer qu’à sa lecture, le lecteur voudra bien adhérer à l’idée que l’intelligence artifi cielle peut rester un formidable outil au service du progrès et non constituer une création susceptible à terme de détruire son humanité.

With the idea of “deep learning” having now become the key to this new generation of solutions, major technological players in the business intelligence sector have taken an interest in the application of Big Data. In this book, the author explores the recent technological advances associated with digitized data flows, which have recently opened up new horizons for AI. The reader will gain insight into some of the areas of application of Big Data in AI, including robotics, home automation, health, security, image recognition and natural language processing.

Dams are part of human achievements that induce great benefits for society but also bear a potential risk to people, property and the natural environment. The risk of a dam rupture is extremely low and diffi cult to quantify accurately. The aim of ‘Dam surveillance’ (ICOLD Bulletin 158), is to help reduce these risks by early detection of an undesirable event. The objective of dam surveillance is to make a precise and timely diagnosis of the behavior of dams, in order to prevent undesirable consequences. Both the monitoring system and surveillance program has to be designed and should be able to detect any abnormal behaviour. ‘Dam surveillance’ (ICOLD Bulletin 158), emphasizes the following aspects: • Routine visual inspection • Special inspection • Checking and testing of Hydro-electromechanical equipment • Monitoring parameters and devices • Automation • Maintenance of ageing monitoring systems • Re-instrumentation of existing dams • Recent developments • Data management • Dam documentation management • Assessment of dam condition and behaviour • Assessment of routine dam safety monitoring programme • Prioritization of maintenance, remedial and upgrading works.