Team building activities in dance and discoveries from reflective essays

The purpose of this study was to determine if using team building activities within a university Latin dance course enhances cohesion. Students (N=30) completed the Group Environment Questionnaire (GEQ; Carron, Widmeyer, & Brawley, 1985), which measures group integration (individuals’ perceptions of the closeness, similarity, and bonding within the group as a whole) and individual attractions to the group in terms of both task and social cohesion. Students also completed an evaluation of the team building activities and wrote reflective essays about their experiences in the course. The course consisted of twenty 90-minute classes. In the third class students were provided an information sheet describing the research. In the fourth class the students completed a demographics questionnaire and the GEQ. The students completed the GEQ again during the ninth class. In classes 10 to 14 team building activities took up roughly the first third of each class. The students completed the GEQ again in classes 15 and 20. In class 16 the students completed the evaluation. The reflective essays were submitted two weeks after the last class. There were no significant differences across time in social cohesion. Group integration task, however, was significantly higher at times 3 and 4 compared to time 1. Students agreed that the team-building activities helped to bond class members, and felt it was valuable for these activities to be included in the unit in the future. The reflective essays indicated the students felt the team building activities improved social factors, and interpersonal, dance, and personal mental skills.

The measurement of broadband ultrasonic attenuation in cancellous bone-a review of the science and technology

The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone at the calcaneus was first described in 1984. The assessment of osteoporosis by BUA has recently been recognized by Universities UK, within its EurekaUK book, as being one of the “100 discoveries and developments in UK Universities that have changed the world” over the past 50 years, covering the whole academic spectrum from the arts and humanities to science and technology. Indeed, BUA technique has been clinically validated and is utilized worldwide, with at least seven commercial systems providing calcaneal BUA measurement. However, a fundamental understanding of the dependence of BUA upon the material and structural properties of cancellous bone is still lacking. This review aims to provide a science- and technology-orientated perspective on the application of BUA to the medical disease of osteoporosis.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Girl in the Shadows and resilience and coping strategies in contemporary young adult fiction

The novel manuscript Girl in the Shadows tells the story of two teenage girls whose friendship, safety and sanity are pushed to the limits when an unexplained phenomenon invades their lives. Sixteen-year-old Tash has everything a teenage girl could want: good looks, brains and freedom from her busy parents. But when she looks into her mirror, a stranger’s face stares back at her. Her best friend Mal believes it’s an evil spirit and enters the world of the supernatural to find answers. But spell books and ouija boards cannot fix a problem that comes from deep within the soul. It will take a journey to the edge of madness for Tash to face the truth inside her heart and see the evil that lurks in her home. And Mal’s love and courage to pull her back into life. The exegesis examines resilience and coping strategies in adolescence, in particular, the relationship of trauma to brain development in children and teenagers. It draws on recent discoveries in neuroscience and psychology to provide a framework to examine the role of coping strategies in building resilience. Within this broader context, it analyses two works of contemporary young adult fiction, Freaky Green Eyes by Joyce Carol Oates and Sonya Hartnett’s Surrender, their use of the split persona as a coping mechanism within young adult fiction and the potential of young adult literature as a tool to help build resilience in teen readers.