Intergenerational relationships refer to relationships between people in alternate generational groups. The increasing numbers of older people all over the world highlight the need for studies on psychological processes that enhance well-being through intergenerational relationships. People from different generations are co-dependent for care and support. Older people constitute a diverse group: some may experience a depletion of energy, physical, financial and emotional resources, while others have good health, financial security and stable social support networks. What all people, including older people, have in common, however, is a need for meaningful relationships. This makes it worthwhile to explore the experiences of relationships with younger people from the perspective of older people. This study is important because research indicates that the relationships between older people (60 years and older) and adolescents and young adults are strained. An initial study on intergenerational care experiences from the perspective of people aged 60 years and older and young people in the middle-adolescent developmental phase (at 16 years) revealed a lack of empathy from the older generation towards the younger generation. It was decided to focus in this study on intergenerational empathy specifically. Mutual empathetic understanding is suggested as a means to overcome challenges between members of generations that have to compete for limited resources, especially in low-resource areas such as the specific rural African community studied in Vaalharts, South Africa. It is suggested that empathy could increase intergenerational understanding between older and younger people dealing with their respective developmental challenges. The research was conducted in a community with high levels of poverty and limited physical and material resources. The study is qualitative in nature and used an interpretive descriptive research design. This design provided the basis to explore the perceptions of empathy by using theoretical constructs to derive at an understanding of experiences in the community and specifically those of the older generation. The 18 participants were all older than 60 and Setswana speaking but were also proficient in Afrikaans and English. Eight of the participants (1 man and 7 women) participated in study using the Mmogo-method®. This is a projective technique that uses visual presentations to gain a deeper insight into meaning that is developed between the participants. For the Mmogo-method®, participants (older people) were invited to make visual representations of how they experienced care in relation to young people in the middle adolescent developmental phase, at around 16 years. A further 10 participants (4 men and 6 woman), who were not part of the Mmogo-method® project, participated in semi-structured interviews. These interviews provided them the freedom to elaborate on their own unique experiences. Semi- structured interviews also provide a certain amount of structure for the interviewer to make sure that detailed information on empathy in arising relevant conversations are obtained. Data were analysed using an inductive approach as well as thematic analysis of experiences about intergenerational care: empathy (and specifically, a lack of empathy) emerged as a recurrent theme. The literature shows a connection between empathy and care, which accordingly served as the focus of this study. The data were further subjected to a directed form of content analysis (deductive category application) which was conducted after literature and theory on intergenerational empathy have been consulted. A visual analysis was conducted on the visual presentations that the participants built as part of the Mmogo- method®. Trustworthiness was ensured by using the principles proposed by Guba’s model of trustworthiness and that include: obtaining thick descriptions, ensuring credibility, member checking and ensuring confirmabillity. Ethical consent to conduct this study was given by the Human Research Ethics committee of the Faculty of Health Sciences in the North-West University (reference number NWU-00053-10-S1). A gatekeeper was used to gain access to the community studied and participants gave their informed consent. The lack of empathy from the perspective or the older people emerged from the way in which older people viewed the relationship with the young solely from their own perspective and from their inability to place themselves in the position of the younger persons. Older people were at first unable to visualize the young in their caring relationships; they expressed negative and judgemental attitudes towards them and perceived that the young people are rejecting the wisdom of their elders. Older people resorted to outsiders to assist in communicating with and disciplining the young. The lack of empathy on the part of the older people for the young can have dire effects on their vital intergenerational relationships. It is recommended that community-based interventions be developed to promote empathy between the two generations. / MA (Research Psychology), North-West University, Potchefstroom Campus, 2015

This study examined the dynamics, challenges and opportunities of developing innovation systems in low resource settings with a particular focus on Uganda. It applied perspectives of technoscience and concepts of innovation systems, triple helix as university-industry-government relationships, mode 2 knowledge production and situated knowledges in understanding the context, identifying key policy issues and suggesting ways to address them. A mixed methodology combining both quantitative and qualitative methods was used in the study. It involved review of key policy documents, key informant interviews, focus group discussions and meetings with scientists, business leaders in the target organizations and firms, community members as well as observations of production processes in firms. Findings underscore the need for greater interaction and learning among actors in the emerging innovation systems in Uganda and eastern Africa. An opportunity for this to happen may be the growing number of entrepreneurial initiatives at the university and some public research organizations in the country. These entrepreneurial initiatives are driven by scientists, who are enthusiastic about moving their research results and innovations to market. This makes it plausible, in low resource settings like in Uganda, to promote the university working closely with public research organizations and firms as a locus for research and innovation. However, enabling conditions, which foster interaction and learning among actors, should be put in place. First, there is need to formulate specific policies and strategies with clear goals and incentives to promote growth of particular innovation systems. Second, a clear national policy for financing research and innovation is needed, which involves on the one part core funding to universities and research organizations, and on the other, competitive grants for research and innovation. Third, business incubation services should be established and/or supported as places where entrepreneurial scientists and other persons develop and test their business ideas and models. Fourth, there is need for institutional reforms to make administrative processes less bureaucratic, more costeffective and efficient. These reforms are necessary for example in processes involving procurement and financial management, research project approvals (for ethics and safety), technology assessments, contracting and licensing and other registration services. The findings and conclusions from this study demonstrate that technoscientific perspectives and innovation systems approaches can be adapted and used as a framework for identifying and explaining conditions that promote or hamper innovation in low resource settings as well as policy options to address them.

A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine. / The rate of technology expansion is rapidly covering even the most remote parts of the globe and in the lowest resource settings. With globalization however, low and middle income areas are facing emerging health issues such as injuries and chronic medical conditions. With these illnesses, there are inevitable demands on emergency services. It has been thought that technology be utilized to augment emergency medical care in such settings where formal Emergency Medical Services. To aggregate and analyze the existing literature on the topic a systematic literature review was conducted. This study analyzed the existing literature on prehospital emergency care in settings in which no formal EMS services were utilized. Four databases were searched with inclusion and exclusion criteria, yielding 1782 results. The initial screening excluded all but 21 articles. Of the 21 articles in full review, 15 were included in the final review. Studies included in the final review were grouped into those reporting outcomes from five categories: Feasibility, Quality of Care, Response Time, Patient Outcomes, and Cost Effectiveness. Only one study was identified to be of high quality. There was a lack of studies with adequate statistical analysis to conduct statistical aggregation. Most studies however reported prehospital telemedicine in settings without EMS to be feasible, provide quality care, are be cost effective. However, the lack of statistical analysis makes it difficult to make conclusions. Also, several studies did show response time of a trained basic life support volunteer to be faster than EMS in many of the settings. But no positive health outcomes were observed in patients treated with projects utilizing technology in the prehospital setting. The prehospital emergency medicine setting is a young field of study that may have significant hurdles in application. The studies conducted have shown promise in the use of technology in prehospital settings without formal EMS services, but are not robust enough to make strong conclusions or recommendations that could be put into practice. Thus, more robust, statistically oriented research is imperative in the field so that we can fully explore the potential of technology in the prehospital setting, especially in low resource and rural settings without formal EMS services. With more robust studies, we can hope to integrate new technologies into practice and better serve the populations without adequate EMS coverage to provide more timely emergency care.

Children around the world need care outside their families for a variety of reasons including poverty, war and epidemics such as HIV/AIDS. The majority of these children live in developing countries where there are limited resources to care for them. As a result of concerns about the effects of institutional care on children, and following trends in the developed world, there is a movement in developing countries to replace large residential institutions with a system of adoption, foster care and small group homes. The aim of this study is to examine the experience of orphan, abandoned, and neglected or abused children who grew up in residential institutions in the Caribbean nation of Trinidad and Tobago, to learn the positives and negatives of residential care in order to contribute to developing a model of care suited for high need, low resource countries. Oral history methodology was used to collect the stories of 24 alumni (12 men and 12 women) from seven homes in Trinidad and Tobago. The homes were categorized as 1) state— partially funded by the state but managed by the Anglican and Catholic dioceses, 2) faith-based— run by religious communities, and 3) community homes run by individuals in the community. The findings of the study show that overall experiences were positive. For poor and working-class children, life in the home was better than their life would have been if they had remained with their families. However, discharge and transition from the homes were less favourable. Alumni from the state-funded homes experienced more difficulties than the faith-based and community homes as a result of poor planning and a lack of post-departure supports. Women suffered more hardships than men, often leading to sexual exploitation. The findings also show that being admitted with siblings and staying at the same home over the duration of care—as was the norm—correlated positively with educational outcomes for the majority of alumni. Some life-long relationships were maintained with volunteers and with friends made among peers at the homes. The study concludes that large group care is not necessarily harmful for children. It may be even beneficial and may be cost effective—a factor that is very important for low resource countries. An aftercare plan, with planning beginning at admission might ease the transition process and gender must be considered in discharge and transition policies. / October 2016

The aim of the thesis is to evaluate Czech text classification tasks in the low-resource settings. We introduce three datasets, two of which were publicly available and one was created partly by us. This dataset is based on contracts provided by the web platform Hlídač Státu. It has most of the data annotated automatically and only a small part manually. Its distinctive feature is that it contains long contracts in the Czech language. We achieve outstanding results with the proposed model on publicly available datasets, which confirms the sufficient performance of our model. In addition, we performed ex- perimental measurements of noisy data and of various amounts of data needed to train the model on these publicly available datasets. On the contracts dataset, we focused on selecting the right part of each contract and we studied with which part we can get the best result. We have found that for a dataset that contains some systematic errors due to automatic annotation, it is more advantageous to use a shorter but more relevant part of the contract for classification than to take a longer text from the contract and rely on BERT to learn correctly. 1

This thesis studies to automatically solve Arabic Math Word Problems (MWPs) by deep learning models. MWP is a text description of a mathematical problem, which should be solved by deriving a math equation and reach the answer. Due to their strong learning capacity, deep learning based models can learn from the given problem description and generate the correct math equation for solving the problem. Effective models have been developed for solving MWPs in English and Chinese. However, Arabic MWPs are rarely studied. To initiate the study in Arabic MWPs, this thesis contributes the first large-scale dataset for Arabic MWPs, which contain 6,000 samples. Each sample is composed of an Arabic MWP description and the corresponding equation to solve this MWP. Arabic MWP solvers are then built with deep learning models, and verified on this dataset for their effectiveness. In addition, a transfer learning model is built to let the high-resource Chinese MWP solver to promote the performance of the low-resource Arabic MWP solver. This work is the first to use deep learning methods to solve Arabic MWP and the first to use transfer learning to solve MWP across different languages. The solver enhanced by transfer learning has accuracy 74.15%, which is 3% higher than the baseline that does not use transfer learning. In addition, the accuracy is more than 7% higher than the baseline for templates with few samples representing them. Furthermore, The model can generate new sequences that were not seen before during the training with an accuracy of 27% (11% higher than the baseline).

The need for fully automatic translation at DigitalTolk, a Stockholm-based company providing translation services, leads to exploring Automatic Speech Recognition as a first step for Modern Standard Arabic (MSA). Facebook AI recently released a second version of its Wav2Vec models, dubbed Wav2Vec 2.0, which uses deep neural networks and provides several English pretrained models along with a multilingual model trained in 53 different languages, referred to as the Cross-Lingual Speech Representation (XLSR-53). The small English and the XLSR-53 pretrained models are tested, and the results stemming from them discussed, with the Arabic data from Mozilla Common Voice. In this research, the small model did not yield any results and may have needed more unlabelled data to train whereas the large model proved to be successful in predicting the audio recordings in Arabic and a Word Error Rate of 24.40% was achieved, an unprecedented result. The small model turned out to be not suitable for training especially on languages other than English and where the unlabelled data is not enough. On the other hand, the large model gave very promising results despite the low amount of data. The large model should be the model of choice for any future training that needs to be done on low resource languages such as Arabic.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19117号 / 情博第563号 / 新制||情||99(附属図書館) / 32068 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 石田 亨, 教授 吉川 正俊, 教授 河原 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24729号 / 情博第817号 / 新制||情||137(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 河原 達也, 教授 黒橋 禎夫, 教授 森 信介 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

The complexity for being at the forefront regarding information retrieval systems are constantly increasing. Recent technology of natural language processing called BERT has reached superhuman performance in high resource languages for reading comprehension tasks. However, several researchers has stated that multilingual model’s are not enough for low-resource languages, since they are lacking a thorough understanding of those languages. Recently, a Swedish pre-trained BERT model has been introduced which is trained on significantly more Swedish data than the multilingual models currently available. This study compares both multilingual and Swedish monolingual inherited BERT model’s for question answering utilizing both a English and a Swedish machine translated SQuADv2 data set during its fine-tuning process. The models are evaluated with SQuADv2 benchmark and within a implemented question answering system built upon the classical retriever-reader methodology. This study introduces a naive and more robust prediction method for the proposed question answering system as well finding a sweet spot for each individual model approach integrated into the system. The question answering system is evaluated and compared against another question answering library at the leading edge within the area, applying a custom crafted Swedish evaluation data set. The results show that the fine-tuned model based on the Swedish pre-trained model and the Swedish SQuADv2 data set were superior in all evaluation metrics except speed. The comparison between the different systems resulted in a higher evaluation score but a slower prediction time for this study’s system.