Thesis (M. Sc.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 39-45).

published_or_final_version / Sports Science / Master / Master of Science in Sports Science

No description available.

Programmers want to write modular programs to increase maintainability and create abstractions, but modularity hampers optimizations, especially when modules are compiled separately or written in different languages. In languages with syntactic extension capabilities, each module in a program can be written in a separate language, and the module system must ensure that the modules interoperate correctly. In Racket, the module system ensures this by separating module code into phases for runtime and compile-time and allowing phased imports and exports inside modules. We present an algorithm, called demodularization, that combines all executable code from a phased modular program into a single module that can then be optimized as a whole program. The demodularized programs have the same behavior as their modular counterparts but are easier to optimize. We show that programs maintain their meaning through an operational semantics of the demodularization process and verify that performance increases by comparing modular Racket programs to the equivalent demodularized and optimized programs. We use the existing Racket optimizer to optimize the demodularized programs by decompiling them into an intermediate form that the optimizer uses. We also demonstrate a dead code elimination optimization that dramatically reduces the file size of demodularized Racket programs.

Sound is used as a medium for communication by taxa as varied as insects, fish, amphibians, birds and mammals. In some birds like the suboscines, song is genetically encoded, whereas in parrots, hummingbirds and oscines, it is learnt. The diversity and plasticity of birdsong continues to generate interest amongst ornithologists, and many questions remain unresolved. For instance, why do some species sing hundreds of different songs while others use simple, stereotyped ones for the same purposes? Why do some birds learn not only their own species’ song, but also the songs of heterospecifics? There are several anecdotal reports of such vocal mimicry in wild birds, where a species imitates the song or call of heterospecifics in its natural habitat, but much has yet to be learnt about this intriguing phenomenon. There has been a recent surge of interest and research into avian vocal mimicry. Despite having several species of birds that are known to produce mimicry, there is a dearth of research on this field in India. The Greater Racket-tailed drongo’s loud song and ability to mimic other species of birds with great accuracy has drawn the attention of many birdwatchers, but other than a few phonetic descriptions, no study has focussed on their song. Therefore, this thesis focuses on the structure, contexts and functions of vocal mimicry in this species. In order to understand the functions of vocal mimicry in any species, we require certain fundamental data, which are often overlooked in many studies of bird song. Since this is the first study focusing on the racket-tailed drongo in India, I began with collecting natural history data on the ecology and breeding biology of the species. Then, I attempted to arrive at an objective and quantitative definition and classification of the racket-tailed drongo’s vocal repertoire, especially its mimicry. It is also essential to have information on the contexts in which this mimicry is used. Using a combination of focal animal sampling and sound recordings, I documented the contexts in which the racket-tailed drongo imitates other species in the wild. I also examined the diversity of the species that were mimicked across these contexts. Building on the data from these observations, I used playback experiments to test hypotheses for the functions of mimicry in multiple contexts. Results from these show that greater racket-tailed drongos use mimicry in a flexible manner according to the intended audience. Drongos use two different sets of mimicked calls with distinct syntax directed at conspecifics and heterospecifics respectively, the former in territorial song and the latter to attract members of mixed-species flocks. These results also imply that mimicry may be driven by both sexual and natural selection within the same species, and have implications for the definition of avian vocal mimicry, which remains highly debated.

No description available.

No description available.

No description available.

Full-body three-dimensional kinematic characteristics were determined for the badminton jump smash and the tennis serve in order to investigate contributions to pace and variability. Kinematic (400 Hz) data were collected for a group of badminton and tennis players, using an 18 camera Vicon Motion Analysis System. Each participant performed 24 jump smashes or tennis serves. The best trials - maximal velocity with minimal marker loss - were analysed for each participant using a 18 segment rigid body model customised for each participant using subject-specific segmental properties. Parameters were calculated describing elements of the badminton jump smash and tennis serve technique as well as variability. The effect of these technique parameters on: speed were addressed using stepwise linear regression and on variability using one-way ANOVA. The results suggest that the fastest badminton players had a smaller elbow extension angle at the end of retraction, a larger wrist extension angle at shuttle contact, and a larger time between preparation and shuttle contact; that accounted for 84% of variation in shuttle speed. The results also showed that variability in the badminton smash was caused by differences in body placement, shuttle location on the racket at impact and movement timings. In the tennis serve, linear regressions showed that there were no variables significant to speed when players hit to the right and left centre court lines. When players hit in the advantage court trunk rotation at the racket lowest point key instant could explain 35.2% of the variation in speed, and when hitting towards the deuce court timing from the end of retraction to ball contact explained 33.6% of ball speed. The results show that there are differences in technique between the badminton jump smash and the tennis serves especially in the first half of the sporting actions.

The DataFrame is a powerful table-like data structure used frequently in Data Science, the in-demand and innovative field focused on the extraction of valuable insights from data. Typically, datasets are not perfect upon collection and need to be prepared so that the resulting dataset is useful for statistical analysis. A DataFrame API supports optimized methods such as, selecting, aggregating and filtering rows, columns, and cells as well as renaming row and column labels. It also supports methods for normalizing data, merging data, adding new columns and labelling missing data among numerous other features. An API to work with tabular data would be useful in any general purpose language, so DataFrames have been incorporated into libraries like Pandas for Python and provided as native libraries in the languages R and Scala. Due to their wide-ranging use it is not uncommon to find implementations in many other languages like Java and Julia \cite{BigData}. In this work, we introduce RacketFrames, a Racket V8.0+ DataFrame implementation. We show the benefits an implementation can have on existing and future Racket projects. To quantify the performance of major DataFrame operations, we measure speed against Python Pandas and compare functional and object oriented paradigms. We hope to continue the trend for further Data Science tool development for Racket and other programming languages.