The researchers predict a future, where people’s interaction with things is decreased and things become more autonomous, requiring less control from people, aiming to make life easier. However, the question is if we really are ready to let go of the control over such systems in order to have easier life. This is what this research through design project is aiming to find out through a research question How the different user interaction modalities with IoT devices at home influence the sense of control for users? and sub-question How the sense of control over IoT devices would influence how people trust them? With the help of prototype, questionnaire and online sessions, two lists of guidelines were created, consisting of points to consider while designing for such systems from control and trust perspective.The angle was narrowed down to a morning routine and interaction with the alarm clock connected to a coffeemaker.

Made available in DSpace on 2016-04-26T18:14:46Z (GMT). No. of bitstreams: 1 Gilmar Pereira da Silva.pdf: 3720753 bytes, checksum: 965b4fd78fbb8eaac6f442d2f1e30e27 (MD5) Previous issue date: 2014-12-09 / By means of a sincronic and diacronic approach, the present study attempts to analize humor as an interpretation of reality attentive to its finite character, by way of humoristic images, and more specifically, in those images circumscribed by the space of the web. For this, the investigation was centered in a bibliographic revision and in the analysis of the humoristic blog Kibe Loco. Taking as principal theoretical references Søren Aabye Kierkagaard and Walter Benjamin, the notion of humor was studied as a way of signifying reality that which would favor an existencial leap, according to the first author and as a dialectical image as a historical category that would provoke a waking up according to the second in order to observe the function of humoristic images in digital medias. In this way, it was sought to comprehend the extent to which dialectical images would contribute to the referred leap and waking up , qualitative changes in the relation of the individual with herself and with society as a whole, always making the comparison with the diverse humoristic production of the blog. The first chapter is centered on humor; the second on the image, above all humoristic images; the third chapter combines the theories of the first two with the hypertextual writing of digital platforms / Por meio de uma abordagem sincrônica e diacrônica, o presente trabalho busca analisar o humor como modo de significação da realidade, bem como as imagens humorísticas e, mais especificamente, as circunscritas ao espaço web. Para tanto, a pesquisa centrou-se em revisão bibliográfica e na análise do blog humorístico Kibe Loco. Tomando como referenciais teóricos principais Søren Aabye Kierkegaard e Walter Benjamin, partiu-se da noção de humor como modo de leitura da realidade atenta aos seus aspectos de finitude que favoreceria um salto existencial , conforme o primeiro e de imagem dialética como categoria histórica que suscitaria o despertar , conforme o segundo para observar o funcionamento das imagens humorísticas em mídias digitais. Desse modo, buscou-se compreender em que medida as imagens humorísticas poderiam ser compreendidas como imagens dialéticas e, por tanto, contribuiriam aos referidos salto e despertar , mudanças qualitativas na relação do indivíduo consigo e com a sociedade, sempre cotejando com a diversificada produção humorística do blog. O primeiro capítulo centra-se no humor; o segundo na imagem, sobretudo as humorísticas; o terceiro conjuga as teorias dos dois primeiros com a escrita hipertextual das plataformas digitais

Отчет содержит 80 страниц, 35 рисунков, 3 таблицы, 25 источников, 3 приложения. Объект исследования – модель машинного обучения, используемая в сфере научных исследований и мониторинга сна человека. Цель работы – создание модели машинного обучения, способной на основе данных акселерометра с достаточной степенью точности определять состояние сна: пробуждение или засыпание. Методы проведения работы: исследование научных работ, сбор и подготовка данных, разработка, обучение и тестирование моделей машинного обучения. Результаты работы и их новизна: обученная модель машинного обучения, способная определять одно из двух состояний сна: пробуждение или засыпание и оказать влияние на практику мониторинга сна в домашних условиях. Область применения полученных результатов: исследования в медицинских учреждениях. Рекомендации по внедрению: наличие программного и аппаратного обеспечения для запуска обученной модели машинного обучения, устройства сбора данных – акселерометра, специалистов для дальнейшего поддержания работоспособности модели машинного обучения. Значимость работы: разработанная модель машинного обучения поможет исследователям быстрее и качественнее анализировать данные с акселерометра, глубже понять закономерности и функции сна человека. Прогнозные предположения о развитии объекта исследования: совершенствование алгоритмов машинного обучения разработанного инструмента, использование устройств с более точными датчиками и с расширенным набором дополнительных датчиков, обучение модели на данных, размеченных более качественно. / The report contains 80 pages, 35 figures, 3 tables, 25 sources, 3 appendices. The object of research is a machine learning model used in the field of scientific research and human sleep monitoring. The aim of the work is to create a machine learning model capable of determining the state of sleep with a sufficient degree of accuracy based on accelerometer data: waking up or falling asleep. Methods of work: research of scientific papers, data collection and preparation, development, training and testing of machine learning models. The results of the work and their novelty: a trained machine learning model capable of determining one of two sleep states: waking up or falling asleep and influencing the practice of sleep monitoring at home. The scope of the results obtained: research in medical institutions. Implementation recommendations: availability of software and hardware to run a trained machine learning model, an accelerometer data acquisition device, and specialists to further maintain the machine learning model. The significance of the work: the developed machine learning model will help researchers analyze data from the accelerometer faster and better, and better understand the patterns and functions of human sleep. Predictive assumptions about the development of the research object: improving the machine learning algorithms of the developed tool, using devices with more accurate sensors and with an expanded set of additional sensors, training the model on data marked up more efficiently.