Deer forests, game shooting and landed estates in the South West of Ireland, 1840 - 1970

This thesis is concentrated on the historical aspects of the elitist field sports of deer stalking and game shooting, as practiced by four Irish landed ascendancy families in the south west of Ireland. Four great estates were selected for study. Two of these were, by Irish standards, very large: the Kenmare estate of over 136,000 acres in the ownership of the Roman Catholic Earls of Kenmare, and the Herbert estate of over 44,000 acres in the ownership of the Protestant Herbert family. The other two were, in relative terms, small: the Grehan estate of c.7,500 acres in the ownership of the Roman Catholic Grehan family, and the Godfrey estate of c.5,000 acres, in the ownership of the Protestant Barons Godfrey. This mixture of contrasting estate size, owner's religions, nobleman, minor aristocrat and untitled gentry should, it is argued, yield a diversity of the field sports and lifestyles of their owners, and go some way to assess the contributions, good or bad, they have bequeathed to modern Ireland. Equally, it should help in assessing what importance, if any, applied to hunting. In this context, hunting is here used in its broadest meaning, and includes deer stalking and game shooting, as well as hunting with dogs and hounds on foot and horseback. Where a specific type of hunting is involved, it is so described; for example, fox hunting, stag hunting, hare hunting. Similarly, the term game is sometimes used in sporting literature to encompass all species of quarry killed, and can include deer, ground game (hares and rabbits), waterfowl, and various species of game birds. Where it refers to specific species, these are so described; for example grouse, pheasants, woodcork, wild duck, etc. Since two of these estates - the Kenmare and Herbert - each created a deer forest, unique in mid-19th century Ireland, they form the core study estates; the two smaller estates serve as comparative studies. And, equally unique, as these two larger estates held the only remnant population of native Irish red deer, the survival of that herd itself forms a concomitant core area of analysis. The numerary descriptions applied to these animals in popular literature are critically reassessed against prime source historical evidence, as are the so-called deer forest 'clearances'. The core period, 1840 to 1970, is selected as the seminal period, spanning 130 years, from the creation of the deer forests to when a fundamental change in policy and administration was introduced by the state. Comparison is made with similar estates elsewhere, in Britain and especially in Scotland. Their influence on the Irish methods and style of hunting is historically examined.

Automatic detection of learner-style for adaptive eLearning

The advent of modern wireless technologies has seen a shift in focus towards the design and development of educational systems for deployment through mobile devices. The use of mobile phones, tablets and Personal Digital Assistants (PDAs) is steadily growing across the educational sector as a whole. Mobile learning (mLearning) systems developed for deployment on such devices hold great significance for the future of education. However, mLearning systems must be built around the particular learner’s needs based on both their motivation to learn and subsequent learning outcomes. This thesis investigates how biometric technologies, in particular accelerometer and eye-tracking technologies, could effectively be employed within the development of mobile learning systems to facilitate the needs of individual learners. The creation of personalised learning environments must enable the achievement of improved learning outcomes for users, particularly at an individual level. Therefore consideration is given to individual learning-style differences within the electronic learning (eLearning) space. The overall area of eLearning is considered and areas such as biometric technology and educational psychology are explored for the development of personalised educational systems. This thesis explains the basis of the author’s hypotheses and presents the results of several studies carried out throughout the PhD research period. These results show that both accelerometer and eye-tracking technologies can be employed as an Human Computer Interaction (HCI) method in the detection of student learning-styles to facilitate the provision of automatically adapted eLearning spaces. Finally the author provides recommendations for developers in the creation of adaptive mobile learning systems through the employment of biometric technology as a user interaction tool within mLearning applications. Further research paths are identified and a roadmap for future of research in this area is defined.

SDC: Scalable description coding for adaptive streaming media

Video compression techniques enable adaptive media streaming over heterogeneous links to end-devices. Scalable Video Coding (SVC) and Multiple Description Coding (MDC) represent well-known techniques for video compression with distinct characteristics in terms of bandwidth efficiency and resiliency to packet loss. In this paper, we present Scalable Description Coding (SDC), a technique to compromise the tradeoff between bandwidth efficiency and error resiliency without sacrificing user-perceived quality. Additionally, we propose a scheme that combines network coding and SDC to further improve the error resiliency. SDC yields upwards of 25% bandwidth savings over MDC. Additionally, our scheme features higher quality for longer durations even at high packet loss rates.

ALD: adaptive layer distribution for scalable video

Recent years have witnessed a rapid growth in the demand for streaming video over the Internet and mobile networks, exposes challenges in coping with heterogeneous devices and varying network throughput. Adaptive schemes, such as scalable video coding, are an attractive solution but fare badly in the presence of packet losses. Techniques that use description-based streaming models, such as multiple description coding (MDC), are more suitable for lossy networks, and can mitigate the effects of packet loss by increasing the error resilience of the encoded stream, but with an increased transmission byte cost. In this paper, we present our adaptive scalable streaming technique adaptive layer distribution (ALD). ALD is a novel scalable media delivery technique that optimises the tradeoff between streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data are spread amongst all packets, thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the resiliency of the scalable video. The Subjective testing results illustrate that our techniques and models were able to provide levels of consistent high-quality viewing, with lower transmission cost, relative to MDC, irrespective of clip type. This highlights the benefits of selective packetisation in addition to intuitive encoding and transmission.

ALD: adaptive layer distribution for scalable video

Bandwidth constriction and datagram loss are prominent issues that affect the perceived quality of streaming video over lossy networks, such as wireless. The use of layered video coding seems attractive as a means to alleviate these issues, but its adoption has been held back in large part by the inherent priority assigned to the critical lower layers and the consequences for quality that result from their loss. The proposed use of forward error correction (FEC) as a solution only further burdens the bandwidth availability and can negate the perceived benefits of increased stream quality. In this paper, we propose Adaptive Layer Distribution (ALD) as a novel scalable media delivery technique that optimises the tradeoff between the streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data is spread amongst all datagrams thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the scalable video, while providing increased resilience to the highest quality layers. Our experimental results show that ALD improves the perceived quality and also reduces the bandwidth demand by up to 36% in comparison to the well-known Multiple Description Coding (MDC) technique.