Marina Zanella – författare

This monograph describes an innovative prototyping framework for data and knowledge intensive systems. The proposed approach will prove especially useful for advanced and research-oriented projects that aim to develop a traditional database perspective into fully-fledged advanced database approaches and knowledge engineering technologies. The book is organised in two parts. The first part, comprising chapters 1 to 4, provides an introduction to the concept of prototyping, to database and knowledge-based technologies, and to the main issues involved in the integration of data and knowledge engineering. The second part, comprising chapters 5 to 12, illustrates the proposed approach in technical detail. Audience: This volume will be of interest to researchers in the field of databases and knowledge engineering in general, and for software designers and knowledge engineers who aim to expand their expertise in data and knowledge intensive systems.

This book is a comprehensive work on model-based diagnosis of a broad class of discrete-event systems, called active systems. The diagnostic approach, developed over several years by the authors, is surveyed along with introductory elements and related contributions. Each subject is dealt with both informally and formally, so that, based on a variety of examples, the reader can understand the basic ideas at an intuitive level first, while possibly delving into formal details afterwards.

This book is an up-to-date self-contained compendium of the research carried out by the authors on model-based diagnosis of a class of discrete-event systems called active systems. After defining the diagnosis problem, the book copes with a variety of reasoning mechanisms that generate the diagnosis, possibly within a monitoring setting. The book is structured into twelve chapters, each of which has its own introduction and concludes with bibliographic notes and itemized summaries. Concepts and techniques are presented with the help of numerous examples, figures, and tables, and when appropriate these concepts are formalized into propositions and theorems, while detailed algorithms are expressed in pseudocode. This work is primarily intended for researchers, professionals, and graduate students in the fields of artificial intelligence and control theory.

This book is an up-to-date self-contained compendium of the research carried out by the authors on model-based diagnosis of a class of discrete-event systems called active systems. After defining the diagnosis problem, the book copes with a variety of reasoning mechanisms that generate the diagnosis, possibly within a monitoring setting. The book is structured into twelve chapters, each of which has its own introduction and concludes with bibliographic notes and itemized summaries. Concepts and techniques are presented with the help of numerous examples, figures, and tables, and when appropriate these concepts are formalized into propositions and theorems, while detailed algorithms are expressed in pseudocode. This work is primarily intended for researchers, professionals, and graduate students in the fields of artificial intelligence and control theory.

This book is about model-based diagnosis of a class of discrete-event systems called active systems. Roughly, model-based diagnosis is the task of finding out the faulty components of a physical system based on the observed behavior and the system model. An active system is the abstraction of a physical artefact that is modeled as a network of com­ municating automata. For example, the protection apparatus of a power transmission network can be conveniently modeled as an active system, where breakers, protection devices, and lines are naturally described by finite state machines. The asynchronous occurrence of a short circuit on a line or a bus-bar causes the reaction of the protection devices, which aims to isolate the shorted line. This reaction can be faulty and several lines might be eventually isolated, rather than the shorted line only. The diagnostic problem to be solved is uncovering the faulty devices based the visible part of the reaction. Once the diagnosis task has been on accomplished, the produced results are exploited to fix the apparatus (and also to localize the short circuit, in this sample case). Interestingly, the research presented in this book was triggered a decade ago by a project 011 short circuit localization, conducted by ENEL, the Italian electricity board, along with other industrial and academic European partners.

This monograph describes an innovative prototyping framework for data and knowledge intensive systems. The proposed approach will prove especially useful for advanced and research-oriented projects that aim to develop a traditional database perspective into fully-fledged advanced database approaches and knowledge engineering technologies. The book is organised in two parts. The first part, comprising chapters 1 to 4, provides an introduction to the concept of prototyping, to database and knowledge-based technologies, and to the main issues involved in the integration of data and knowledge engineering. The second part, comprising chapters 5 to 12, illustrates the proposed approach in technical detail. Audience: This volume will be of interest to researchers in the field of databases and knowledge engineering in general, and for software designers and knowledge engineers who aim to expand their expertise in data and knowledge intensive systems.

This monograph describes an innovative prototyping framework for data and knowledge intensive systems. The proposed approach will prove especially useful for advanced and research-oriented projects that aim to develop a traditional database perspective into fully-fledged advanced database approaches and knowledge engineering technologies. The book is organised in two parts. The first part, comprising chapters 1 to 4, provides an introduction to the concept of prototyping, to database and knowledge-based technologies, and to the main issues involved in the integration of data and knowledge engineering. The second part, comprising chapters 5 to 12, illustrates the proposed approach in technical detail. Audience: This volume will be of interest to researchers in the field of databases and knowledge engineering in general, and for software designers and knowledge engineers who aim to expand their expertise in data and knowledge intensive systems.