The idea for this text stemmed from the fruitful experience gathered during the training course of 9 Nigerian university students organized in Naples from 3 to 18 September 2008 by the team of Fondazione IDIS-Citta della Scienza under the project Science Centre Owerri. The training course turned out to be not only an educational opportunity to acquire knowledge and skills for these students, but also a real and practical tool that later led to the realization of the first Science Festival of Owerri in Nigeria in May 2009. This in turn sparked the idea of creating a highly practical handbook for those who want to face the challenge of developing new projects for the dissemination and socialization of science in developing countries. In these countries, the role of scientific education and training in schools is not sufficient to arouse scientific curiosity among young people and make the population aware of the importance of scientific knowledge in everyday life. Moreover science and technology are indispensable tools for people's empowerment and should be supported with actions that encourage curiosity about science and the intelligent use of technology to bridge the divide with developed countries. It is therefore necessary to set up activities that are carefully targeted to promote and communicate science. The text has been designed as a practical guide to be used in a variety of contexts: scientific events or more structured science festivals, training, the creation of scientific cultural associations, and the development of new science centres. Besides being an excellent tool for training and supporting the design and planning phases, the manual can also be used as a reference work for institutions and local cultural services which have to select projects of this type.
James W. C. Pennington's slave narrative tells of his time and experiences before the Civil War, when he was a slave in the South, and of the problems, oppressions, and religious aspects of slavery.
The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally.
This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning solutions for the major difficulties.
It is a valuable resource for those working in machine learning for natural language processing as well as anyone studying time in language, or involved in annotating the structure of time in documents.