The protection and security of vulnerable populations in complex emergencies using the Dadaab refugee camps in the north eastern province of Kenya as a case study

The past two decades has seen a dramatic upheaval in the international world order: the end of the Cold War, the 9/11 attacks and the subsequent 'War on Terror', increased Jihadist activities, the accelerated pace of globalization, climate change and the 2008 global financial crisis have contributed to fear, uncertainty, poverty, conflict, massive displacements of populations of asylum seekers and refugees globally and a proliferation of Protracted Refugee Situations (PRS), defined as situations in which refugees have been in exile 'for 5 years or more after their initial displacement, without immediate prospects for implementation of durable solutions. In the past two decades there has been a huge proliferation of these with more than 7.2 million refugees now trapped in these PRS, with a further 16 million internally displaced persons (IDPs) trapped in camps within their own countries. The Dadaab refugee complex in Kenya, which of as March 2012, holds over 463,000 refugees, is the most significant and extreme example in recent times of a PRS. It was established in 1991 following the collapse of the Somali Government of Dictator Siad Barre, and the disintegration of Somalia into the chaos that still exists today. PRS such as Dadaab raise particular issues about humanitarianism in terms of aid, protection, security, human rights and the actions (or inaction) of the various stakeholders on an international, national and local level. This thesis investigates these issues by the use of a case study methodology on Dadaab as a PRS, framed in the context of humanitarianism and in particular the issues that arise in terms of how the international community, the UN system and individual states provide assistance and protection to vulnerable populations. Although the refugee camps have been in existence (as of 2012) for over 20 years, there has never been such a detailed study of Dadaab (or any other PRS) undertaken to date and would be of interest to academics in the areas of international relations, refugee/migration studies and global Governance as well as practitioners in both humanitarian response and development

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.

The impact of saving and credit cooperatives on food security in the West Amhara Region of Ethiopia

In rural Ethiopia, among other things, lack of adequate financial service is considered as the basic problem to alleviate rural poverty and to solve the problem of food insecurity. Commercial banks are restricted to urban centres. Providing rural financial service through RUSACCO to the poor has been proposed as a tool for economic development and for achieving food security. Evidence from research in this regard has been so far scanty, especially in rural Ethiopia. The aims of this study are to analyze the determinants of membership, to identify socioeconomic and demographic factors that influence members’ participation in RUSACCOs and to quantify the impact of RUSACCOs on member households’ food security. The study was conducted in two purposely selected woredas in the Amhara region one from food insecure (Lay Gayint woreda) and the other from food secure (Dejen woreda). Six RUSACCOs were selected randomly from these two woredas. Both qualitative and quantitative data were collected. Key informant interviews, focus group discussions and survey techniques were used to collect primary data. Collected data was then analyzed using mixed methods depending on the nature of data. For quantitative data analysis appropriate statistical models were used. The study result reveals that the number of members in each RUSACCO is very small. However, the majority of non-member respondents are willing to join RUSACCO. Lack of information about the benefits of RUSACCO membership is the main problem why many rural poor do not join RUSACCOs. Members participate in different aspects of the cooperatives, starting from attending general assembly up to board membership. They also participate actively in saving and borrowing activities of RUSACCO. The majority of the respondents believe the RUSACCO is a vital instrument in combating food insecurity. The empirical findings indicate that gender, marital status, occupation, educational level, participation in local leadership and participation in other income generation means determine the decision of rural poor to join a RUSACCO or not. The amount of saving is determined by household head occupation, farming experience and income level. While age of household head, primary occupation, farming experience, date of membership, annual total consumption expenditure, amount of saving and participation in other income generation activities influence members’ amount of borrowing by RUSACCO members. Finally, the study confirms that RUSACCO participation improves household food security. RUSACCO membership has made positive impact on household total consumption expenditure and food expenditure.

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.