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.

Investigation of lantibiotic regulation, immunity and synergy

Due to the increasing incidence of antibiotic resistant strains, the use of novel antimicrobials, such as bacteriocins, has become an ever more likely prospect. Lacticin 3147 (of which there are two components, Ltnα and Ltnβ) and nisin belong to the subgroup of bacteriocins called the lantibiotics, which has attracted much attention in recent years. The lantibiotics are antimicrobial peptides that contain unusual amino acids resulting from a series of enzyme-mediated post translational modifications. Given that there have been relatively few examples of lantibiotic-specific resistance; these antimicrobials appear to represent valid alternatives to classical antibiotics. However, the fact that lantibiotics are naturally only produced in small amounts often hinders their commercialisation. In order to overcome this bottleneck, several approaches can be employed. For example, we can create a situation that reduces the quantity of a lantibiotic required to inhibit a target by combining it with other antimicrobials. Here, following an initial screen involving lacticin 3147 and several classical antibiotics, it was observed between lacticin 3147 and the commercial antibiotics polymyxin B/E function synergistically. This reduced the amounts of the individual antimicrobials required for kill and broadened the spectrum of inhibition of both agents. Upon combination with polymyxins, lacticin 3147, which has been associated with Gram positive targets only, actively targeted Gram negative species such as Escherichia coli and Cronobacter sp. An alternative means of addressing problems associated with lantibiotic yield is to better understand how production is regulated, and ultimately use this information to enhance peptide levels. With this in mind the regulation of lacticin 3147 production from the promoter Pbac was investigated using a green fluorescent protein (GFP) expression reporter system. This revealed that elements within both of the divergent operons of the lacticin 3147 gene cluster are involved in Pbac regulation. That is, LtnR, already established as a negative regulator of itself and the lacticin 3147 associated immunity genes, also acts as an activator of Pbac transcription. In contrast, an enhanced level of expression is observed in the absence of the lacticin 3147 structural genes, ltnA1 and ltnA2, indicating that these genes/gene products are involved in Pbac repression. In fact, through complementation of the ltnA2 gene, it was revealed that this regulation is more likely to be dependent on the presence of the gene transcript rather that the corresponding prepropeptide or modified Ltnβ. It may be that if lacticin 3147 production is successfully enhanced, the ability of the producing cell to protect itself may become an issue. To prepare for such a possibility a bioengineered derivative of the lacticin 3147 immunity protein LtnI (LtnI I81V) which provides enhanced protection was discovered through an in depth investigation involving the site and saturation mutagenesis of this protein. In addition, the creation of truncated forms of LtnI allowed the identification of important and essential regions of this immunity protein. Finally, as mentioned, self-immunity is essential to prevent self-killing. However the discovery of nisin U immunity and regulatory gene homologues (spiFEGRR’K) within the pathogenic strain S. infantarius subsp. infantarius is a cause for concern as it represents an example of immune mimicry, a form of lantibiotic-specific resistance. The ability of spiFEG to confer protection was apparent when they successfully provided protection to nisin A, F, Z, Q and U when expressed heterologously in the nisin sensitive L. lactis HP host. As a consequence of the studies presented in this thesis, it is likely that strategies will emerge that will facilitate the production of greater levels of lacticin 3147 production and lead to enhanced immunity in lactococcal backgrounds. Alternatively the need for enhanced production could be avoided through the use of antimicrobial combinations. In addition, providing awareness of the threats of the emergence of resistance through immune mimicry can allow researchers to develop strategies to prevent this phenomenon from leading to the dissemination of lantibiotic resistance.

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.