The dynamics of Latin American sovereign international bonds

This thesis investigated the behavioural dynamics of emerging market sovereign international bonds issued by key Latin American economies. The study allows deeper insights into the complex behaviour of an important segment of international bond markets in a single, comprehensive and penetrative study.

Identity as radical alterity : critiques of Eurocentrism, coloniality and subjectivity in contemporary Australian and Latin American poetry.

This article presents a comparative analysis of Australian and Latin American contemporary poetry which is informed by theories of Eurocentrism derived from contemporary Latin American critical thought.

On the automated interpretation and indexing of American football

This work combines natural language understanding and image processing with incremental learning to develop a system that can automatically interpret and index American Football. We have developed a model for representing spatio-temporal characteristics of multiple objects in dynamic scenes in this domain. Our representation combines expert knowledge, domain knowledge, spatial knowledge and temporal knowledge. We also present an incremental learning algorithm to improve the knowledge base as well as to keep previously developed concepts consistent with new data. The advantages of the incremental learning algorithm are that is that it does not split concepts and it generates a compact conceptual hierarchy which does not store instances.

Using camera motion to identify different types of American football plays

This paper presents a method that uses camera motion parameters to recognise 7 types of American football plays. The approach is based on the motion information extracted from the video and it can identify short and long pass plays, short and long running plays, quarterback sacks, punt plays and kickoff plays. This method has the advantage that it is fast and it does not require player or ball tracking. The system was trained and tested using 782 plays and the results show that the system has an overall classification accuracy of 68%.