What do we mean by the term "inflammation"? A contemporary basic science update for sports medicine

Most practicing sports medicine clinicians refer to the concept of "inflammation" many times a day when diagnosing and treating acute and overuse injuries. What is meant by this term? Is it a "good" or a "bad" process? The major advances in the understanding of inflammation in recent years are summarised, and some clinical implications of the contemporary model of inflammation are highlighted.

The body, mind and soul of AFL footballers: tales of identity from the global sports entertainment industry

The paper discusses some of the findings of a research project funded by the Australian Football League (AFL) titled: Getting the Balance Right: Professionalism, Performance, Prudentialism and Playstations in the Life of AFL Footballers. The research explored the emergence and evolution of a professional identity for AFL footballers – an identity that has many facets including the ideas that a professional leads a balanced life, and has a prudent orientation to the future, to life after football. The AFL is a high profile, sports entertainment business in which brand relationships between the industry and its sponsors generate substantial income for the League, for Clubs, and for Coaches and players. In addition the AFL’s equalisation policies tightly regulate the ways in which Clubs can recruit, maintain and develop playing lists. In this context various tools of analysis are used to identify and characterise the particular Body, Mind and Soul elements of the young men who might be recruited to a Club; who might have significant time, money and effort invested in their development (as players, as persons); who might develop an identity as an AFL footballer. Drawing on Foucault’s work on the care of the self we argue that in this situation, narratives of identity necessarily involve a struggle for the Body, Mind and Soul of these young men.

Towards universal and statistical-driven heuristics for automatic classification of sports video events

Researchers worldwide have been actively seeking for the most robust and powerful solutions to detect and classify key events (or highlights) in various sports domains. Most approaches have employed manual heuristics that model the typical pattern of audio-visual features within particular sport events To avoid manual observation and knowledge, machine-learning can be used as an alternative approach. To bridge the gaps between these two alternatives, an attempt is made to integrate statistics into heuristic models during highlight detection in our investigation. The models can be designed with a modest amount of domain-knowledge, making them less subjective and more robust for different sports. We have also successfully used a universal scope of detection and a standard set of features that can be applied for different sports that include soccer, basketball and Australian football. An experiment on a large dataset of sport videos, with a total of around 15 hours, has demonstrated the effectiveness and robustness of our
aIlgorithms.

Extensible detection and indexing of highlight events in broadcasted sports video

Content-based indexing is fundamental to support and sustain the ongoing growth of broadcasted sports video. The main challenge is to design extensible frameworks to detect and index highlight events. This paper presents: 1) A statistical-driven event detection approach that utilizes a minimum amount of manual knowledge and is based on a universal scope-of-detection and audio-visual features; 2) A semi-schema-based indexing that combines the benefits of schema-based modeling to ensure that the video indexes are valid at all time without manual checking, and schema-less modeling to allow several passes of instantiation in which additional elements can be declared. To demonstrate the performance of the events detection, a large dataset of sport videos with a total of around 15 hours including soccer, basketball and Australian football is used.

Using decision-tree to automatically construct learned-heuristics for events classification in sports video

Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.

Workplace strategies and facilities management

This book provides comprehensive coverage of issues that facility managers in the property industry need to understand and apply in the pursuit of value for money over the life span of built facilities. The authors introduce the fast-growing discipline of facility management, examine the core competencies that facility managers should possess and study different contemporary drivers of change. The book emphasises the need to consider facilities management issues at the pre-design stage of the construction process, rather than only when the building is completed, in order to maximise value for money.