BlueFriends: measuring, analyzing and preventing social exclusion between elementary school students

Social exclusion is a relatively recent term, whose creation is attributed to René Lenoir(Lenoir, 1974). Its concept covers a remarkably wide range of social and economic problems, and can be triggered for various reasons: mentally and physically handicapped, abused children, delinquents, multi-problem households, asocial people, and other social “misfits” (Silver, 1995, pp. 63; Foucault, 1992). With an increasingly multi-cultural population, cultural and social inequalities rapidly ascend, bringing with them the need for educational restructuring. We are living in an evermore diverse world, and children need to be educated to be receptive to the different types of people around them, especially considering social and cultural aspects. It is with these goals that inclusive education has seen an increased trend in today’s academic environment, reminding us that even though children may be taught under the same roof, discriminatory practices might still happen. There are, however, a number of developed tools to assess the various dimensions of social networks. These are mostly based on questionnaires and interviews, which tend to be fastidious and don’t allow for longitudinal, large scale measurement. This thesis introduces BlueFriends, a Bluetooth-based measurement tool for social inclusion/exclusion on elementary school classes. The main goals behind the development of this tool were a) understanding how exclusion manifests in students’ behaviors, and b) motivating pro-social behaviors on children through the use of a persuasive technology. BlueFriends is a distributed application, comprised by an application running on several smartphones, a web-hosted database and a computer providing a visual representation of the data collected on a TV screen, attempting to influence children behaviors. The application makes use of the Bluetooth device present on each phone to continuously sample the RSSI (Received Signal Strength Indication) from other phones, storing the data locally on each phone. All of the stored data is collected, processed and then inserted into the database at the end of each day. At the beginning of each recess, children are reminded of how their behaviors affect others with the help of a visual display, which consists of interactions between dogs. This display illustrates every child’s best friends, as well as which colleagues they don’t interact with as much. Several tips encouraging social interaction and inclusiveness are displayed, inspiring children to change their behaviors towards the colleagues they spend less time with. This thesis documents the process of designing, deploying and analyzing the results of two field studies. On the first study, we assess how the current developed tools are inferior to our measuring tool by deploying a measurement only study, aimed at perceiving how much information can be obtained by the BlueFriends application and attempting to understand how exclusion manifests itself in the school environment. On the second study, we pile on the previous to try and motivate pro-social behaviors on students, with the use of visual cues and recommendations. Ultimately, we confirm that our measurement tool’s results were satisfying towards measuring and changing children’s behaviors, and conclude with our thoughts on possible future work, suggesting a number of possible extensions and improvements.

Compressão de imagem e vídeo com controlador ARM

Este trabalho foi desenvolvido num estágio na empresa ABS GmbH sucursal em Portugal, e teve como foco a compressão de imagem e vídeo com os padrões JPEG e H.264, respetivamente. Foi utilizada a plataforma LeopardBoard DM368, com um controlador ARM9. A análise do desempenho de compressão de ambos os padrões foi realizada através de programas em linguagem C, para execução no processador DM368. O programa para compressão de imagem recebe como parâmetros de entrada o nome e a resolução da imagem a comprimir, e comprime-a com 10 níveis de quantização diferentes. Os resultados mostram que é possível obter uma velocidade de compressão até 73 fps (frames per second) para a resolução 1280x720, e que imagens de boa qualidade podem ser obtidas com rácios de compressão até cerca de 22:1. No programa para compressão de vídeo, o codificador está configurado de acordo com as recomendações para as seguintes aplicações: videoconferência, videovigilância, armazenamento e broadcasting/streaming. As configurações em cada processo de codificação, o nome do ficheiro, o número de frames e a resolução do mesmo representam os parâmetros de entrada. Para a resolução 1280x720, foram obtidas velocidades de compressão até cerca de 68 fps, enquanto para a resolução 1920x1088 esse valor foi cerca de 30 fps. Foi ainda desenvolvida uma aplicação com capacidades para capturar imagens ou vídeos, aplicar processamento de imagem, compressão, armazenamento e transmissão para uma saída DVI (Digital Visual Interface). O processamento de imagem em software permite melhorar dinamicamente as imagens, e a taxa média de captura, compressão e armazenamento é cerca de 5 fps para a resolução 1280x720, adequando-se à captura de imagens individuais. Sem processamento em software, a taxa sobe para cerca de 23 fps para a resolução 1280x720, sendo cerca de 28 fps para a resolução 1280x1088, o que é favorável à captura de vídeo.