Building on the recent initiative to truly globalize the field of international relations, this book provides an innovative interrogation of regionalism. The book applies a globalizing framework to the study of regional worlds in order to move beyond the traditional conception of regionalism, which views regions as competing blocs dominated by great powers. Bringing together a wide range of case studies, the book shows that regions are instead dynamic configurations of social and political identities in which a variety of actors, including the less powerful, interact and partake in regionalization processes and have done so through the centuries.

This book constitutes the refereed proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2007, held in Chengdu, China in April 2007. Coverage includes crime analysis, emergency response and surveillance, intrusion detection, network security, data and text mining, cybercrime and information access and security, intrusion detection, network security, terrorism informatics and crime analysis.

This book introduces current perspectives on Rasch measurement theory with an emphasis on developing Rasch-based scales. Rasch measurement theory represents a paradigm shift in measurement theory away from classical test theory and creates a framework for scaling that can yield invariant measurement. Rasch Models for Solving Measurement Problems: Invariant Measurement in the Social Sciences is a broadly accessible text. Authors George Engelhard Jr and Jue Wang introduce Rasch measurement theory step by step, with chapters on scale construction, evaluation, maintenance, and use. Points are illustrated and techniques are demonstrated through an extended example: The Food Insecurity Experience (FIE) Scale. The Rasch analyses in the book are run using the Facets computer program. Facets syntax, and R code for the ERMA program created by the authors to obtain parameter estimates and to examine model-data fit, together with sample data sets are all available on a website for the book.

To thrive, every living cell must continuously gauge and respond to changes in its environment. These changes are ultimately implemented by modulating gene expression, a process that relies on transcription by Nature's most multivalent molecular machine, the RNA polymerase. This book covers progress made over the past decade understanding how this machine functions to compute the cellular state, from the atomistic structural level responsible for chemistry to the integrative level at which RNA polymerase interacts with the other key molecular machineries of the cell.

Separating foreground objects from natural images and video plays an important role in image and video editing tasks. Despite extensive study in the last two decades, this problem still remains challenging. In particular, extracting a foreground object in a static image involves determining both full and partial pixel coverage, also known as extracting a matte, which is a severely under-constrained problem. Segmenting spatio-temporal video objects from a video sequence is even harder since extracted foregrounds on adjacent frames must be both spatially and temporally coherent. Previous approaches usually require a large amount of user input and still suffer from inaccurate results and low computational efficiency. This book demonstrates efficient and accurate foreground extraction methods and systems by combining advanced computational algorithms with novel user interfaces. Our systems are capable of extracting high quality foreground objects from images and video with a limited amount of user input such as a few paint strokes of the mouse. We also demonstrate a variety of applications with the extracted foreground objects.

Data Mining is a tool that extracts useful and novel patterns from great amounts of data. It usually involves 4 tasks: Classification, Clustering, Association Rule Learning, and Regression. Two major branches of research are addressed in this book. In the first chapter several Classification methods are applied on a real-world data set, the Mars crater data set. The goal of this case study is to improve the accuracy of the crater detection on the remote sensing images of Mars. In the second chapter Sammon's Mapping method is studied and improved. Sammon's Mapping is a projection method which simulates the high-dimension space to a low- dimension one. The motivation of this project is to visualize the internal struture of a data set and facilitate the clustering operation on the data set. After the low-dimension Sammon's Mapped space has been created the number of clusters can be observed. An external measurement of the Clustering result is also implemented in the project. This measurement objectively shows the accuracy of Clustering. With all the steps to implement the Sammon's Mapping, a pipeline is established.

The role of universities in supporting economic development has been explored in studies emphasizing the mechanisms of technology transfer and knowledge spillover. However, in addition to intellectual capital, university scientists bring other resources into research collaboration and contribute to firm partnerships in both direct and indirect ways. This book develops the concept of resource spillover, which captures the various ways in which firms can benefit from collaborations with university scientists. The study categorizes the resources possessed by university scientists into intellectual capital, social capital, and positional capital, and tests the impact of each on the performance of firms. Using a sample of new nanotechnology-based firms in the United States, the study finds that firms benefit from research collaboration in terms of both increased research capability and research output and improved public relations and research credibility. The work contributes to the university-industry technology transfer literature and is useful to managers and policy scientists who are developing research partnership programs or intermediary organizations.