Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-07T12:51:30Z No. of bitstreams: 1 gustavohenriquedarochareis.pdf: 1407647 bytes, checksum: b94399b5bafb2e6cb8e48443f285a7c4 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-09T10:33:11Z (GMT) No. of bitstreams: 1 gustavohenriquedarochareis.pdf: 1407647 bytes, checksum: b94399b5bafb2e6cb8e48443f285a7c4 (MD5) / Made available in DSpace on 2015-12-09T10:33:11Z (GMT). No. of bitstreams: 1 gustavohenriquedarochareis.pdf: 1407647 bytes, checksum: b94399b5bafb2e6cb8e48443f285a7c4 (MD5) Previous issue date: 2015-08-06 / O uso de dispositivos m oveis v^em aumentando signi cativamente nos ultimos anos. Outra tend^encia e a consolida c~ao no uso Tecnologias Digitais da Informa c~ao e Comunica c~ao para ns educacionais. Estes cen arios juntos possibilitam novas formas de comunica c~ao entre professores e alunos, como, por exemplo, a recomenda c~ao de conte udos educacionais e colabora c~ao utilizando dispositivos m oveis. Este trabalho mostra uma arquitetura, chamada CALearning, que re une as principais caracter sticas para um sistema de aprendizado m ovel, como promover a colabora c~ao (recomenda c~ao e avalia c~ao de conte udos) entre os alunos e fazer a recomenda c~ao de conte udos de acordo com o estilo de aprendizagem e prefer^encias do usu ario. A arquitetura tamb em faz uso de informa c~oes de contexto para recomendar conte udos adaptados de acordo com as caracter sticas de acesso a Internet (taxa de transmiss~ao) e deslocamento do aluno durante sua intera c~ao com o aplicativo. Como prova de conceito foi desenvolvido tr^es sistemas chamados CALearningDroid, CALearningWeb e CALearningWS, baseado na arquitetura proposta / The use of mobile devices have increased signi cantly in recent years. Another trend is the consolidation in using Digital Technologies of Information and Communication for educational purposes. These scenarios together enable new forms of communication between teachers and students, for example, the recommendation of educational content and collaboration using mobile devices. This work shows an architecture called CALearning, which brings together the main features for a mobile learning system as promote collaboration (recommendation and content evaluation) among students and to do the content recommendation according to the learning style and user's preferences. The architecture also does use of context information to recommend content tailored according to the Internet access features (transmission rate) and displacement of the learner during their interaction with the application. As proof of concept, was developed three systems called CALearningDroid, CALearningWeb and CALearningWS, based in the proposed architecture.

A oferta de produtos,informação e serviços a partir de perfis de usuários tem tornado os sistemas de recomendação cada vez mais presentes na Web, aumentando a facilidade de escolha e de permanência dos usuários nestes sistemas. Entretanto, existem otimizações a serem feitas principalmente com relação à modelagem do perfil do usuário. Geralmente, suas preferências são modeladas de modo superficial, devido à escassez das informações coletadas,como notas ou comentários, ou devido a informações indutivas que estão suscetíveis a erros. Esta dissertação propõe uma ferramenta de recomendação baseado em interações multimodais, capaz de combinar informações de usuários processadas individualmente por algoritmos de recomendação tradicionais. Nesta ferramenta desenvolveram-se quatro técnicas de combinação afim fornecer aos sistemas de recomendação, subsídios para melhoria na qualidade das predições em diversos domínios. / Providing products, information and services from user profiles has made the recommendation systems to be increasingly present, increasing the ease of selection and retention of users in Webservices. However, there are optimizations to be made in these systems mainly with respect to modeling the user profile. Generally, the preferences are modeled superficially, due to the scarcity of information collected, as notes or comments, or because of inductive information that is susceptible to errors. This work proposes are commendation tool based on multimodal interactions that combines users\' interactions, wich are processed individually by traditional recommendation algorithms. In this tool developed four combination of techniques in order to provide recommendation systems subsidies to improve the quality of predictions.

No período gestacional a mulher está mais suscetível às recomendações dos profissionais de saúde que a acompanha durante todo o pré-natal, sendo um momento propicio para orientá-las a adotarem um estilo de vida ativo. Entretanto, devido à alta prevalência de inatividade física na gestação, deve-se analisar a lacuna que existe entre a recomendação e a prática de atividade física no lazer/exercício físico realizado pelas mulheres neste período. Dessa maneira, o objetivo do presente estudo é verificar a associação entre a prática regular de atividades físicas no lazer e/ou exercícios físicos na gestação e orientações recebidas durante o atendimento de pré-natal. Trata-se de um estudo transversal com 290 puérperas (captadas no pós-parto imediato) de dois hospitais de Santo André, sendo um da rede pública e outro da rede privada de atendimento de pré-natal. Adicionalmente, participaram 45 profissionais de saúde captados em clínicas, hospitais, consultórios e postos de saúde. Utilizou-se um questionário para obter informações referentes à prática de atividade física no lazer/exercício físico e ao aconselhamento realizado pelo profissional de saúde. Para avaliar associação e concordância foi realizado o teste de qui-quadrado, a análise de regressão logística binomial e análise de Kappa, considerando-se o nível de significância inferior a 5%. As usuárias do serviço privado possuíam maior idade, renda e escolaridade (p<0,001). Todavia, as puérperas do serviço público apresentavam maior nível de atividade física (p<0,001) e consequentemente maior gasto energético (p<0,001). Mas, 56,8% do gasto energético eram influenciados pela atividade física doméstica (p=0,011). Houve maior frequência de recomendação para a prática de atividade física no lazer/exercício físico para as mulheres do serviço privado. A prática de atividade física pré-gestacional e a presença de recomendação do profissional de saúde estavam associados ao nível de atividade física no lazer, aumentando a chance da mulher atingir a recomendação (150 minutos de atividade física semanal). A maioria das mulheres citou a falta de tempo e de interesse como principais barreiras a adoção de um estilo de vida ativo. Em relação aos profissionais, observou-se que há associação entre a recomendação de atividade física no lazer e a formação do profissional. A prática da caminhada e a hidroginástica foram as atividades mais recomendadas. Em relação ao volume semanal e a intensidade da atividade física, 35,4% dos profissionais recomendavam pelo menos 150 minutos e 66,7% recomendavam a intensidade leve. Não houve concordância entre as informações percebidas pelas mulheres durante o pré-natal com as recomendações proferidas pelos profissionais de saúde, demonstrando a importância de desenvolver estratégias para suprir esta lacuna na comunicação entre a usuária e o profissional. Ainda assim, observa-se que a adequação de conteúdo e forma das recomendações realizadas durante as consultas de pré-natal podem auxiliar no quadro do estilo de vida ativo da mulher. Sugere-se a realização de novos estudos com intervenções com os profissionais de saúde para que se possa formar uma equipe multidisciplinar e oferecer a saúde materno-fetal uma melhor qualidade de vida / During pregnancy women are more susceptible to the recommendations of health professionals who accompanies throughout the prenatal, being a propitious moment to target them to take an active lifestyle. However, due to the high prevalence of physical inactivity during pregnancy, you should analyze the gap between the recommendation and the practice of physical activity in leisure / exercise performed by women in this period. Thus, the objective of this study is to assess the association between regular physical activity in leisure and / or physical exercise during pregnancy and guidance received during prenatal care. It is a cross-sectional study of 290 women (captured in the immediate postpartum) of two hospitals in Santo André, one of public and other private health care providers of prenatal care. In addition, 45 health professionals raised in clinics, hospitals, clinics and health posts attended. We used a questionnaire to obtain information regarding the practice of leisure physical activity / exercise and counseling performed by a healthcare professional. The association agreement and the chi-square test and analysis of binomial logistic regression and analysis of agreement Kappa, considering the level of less than 5% significance was conducted. The private service users had higher age, income and education (p <0.001). However, the mothers of the public service had a higher level of physical activity (p <0.001) and consequently higher energy expenditure (p <0.001). But 56.8% of energy expenditure were influenced by domestic physical activity (p = 0.011). There was a higher frequency of recommendation for physical activity in leisure / exercise for women in the private service. The practice of pre-pregnancy physical activity and the presence of the recommendation of the health professional was associated with level of physical activity during leisure time, increasing the chance of women reach the recommended (150 minutes of physical activity per week). Most women cited lack of time and interest as the main barriers to adoption of an active lifestyle. Regarding professional, it was observed that there is an association between the recommendation of physical activity during leisure time and professional training. The practice of walking and aerobics were recommended activities. Regarding the weekly volume and intensity of physical activity, 35.4% of the professionals recommend at least 150 minutes and 66.7% recommended light intensity. There was no agreement between the information perceived by women during the prenatal to the recommendations given by health professionals, demonstrating the importance of developing strategies to fill this gap in communication between the user and the professional. Still, it is observed that the suitability of content and form of the recommendations made during prenatal consultations can assist within the active lifestyle of women. It is suggested to conduct further studies with interventions with health professionals so that they can form a multidisciplinary team and provide maternal-fetal a better quality of life

Dada a grande quantidade de conteúdo criado por usuários na Web, uma proposta para ajudar na busca e organização é a criação de sistemas de anotações (tagging systems), normalmente na forma de palavras-chave, extraídas do próprio conteúdo ou sugeridas por visitantes. Esse trabalho aplica um algoritmo de mineração de dados em um banco de dados RDF, contendo instâncias que podem fazer referências à rede Linked Data do DBpedia, para recomendação de tags utilizando as medidas de similaridade taxonômica, relacional e literal de descrições RDF. O banco de dados utilizado é o Arquigrafia, um sistema de banco de dados na Web cujo objetivo é catalogar imagens de projetos arquitetônicos, e que permite que visitantes adicionem tags às imagens. Foram realizados experimentos para a avaliação da qualidade das recomendações de tags realizadas considerando diferentes modelos do Arquigrafia incluindo o modelo estendido do Arquigrafia que faz referências ao DBpedia. Os resultados mostram que a qualidade da recomendação de determinadas tags pode melhorar quando consideramos diferentes modelos (com referências à rede Linked Data do DBpedia) na fase de aprendizado. / Given the huge content created by users in the Web, a way to help in search and organization is the creation of tagging systems, usually in a keyword form (extracted from the Web content or suggested by users). This work applies a data mining algorithm in a RDF database, which contain instances that can reference the DBpedia Linked Data repository, to recommend tags using the taxonomic, relational and literal similarities from RDF descriptions. The database used is the Arquigrafia, a database system available in the Web which goal is to catalog architecture projects, and it allows a user to add tags to images. Experiments were performed to evaluate the quality of the tag recommendations made considering differents models of Arquigrafia\'s database, including an extended model which has references to DBpedia. The results shown that the quality of the recommendations of some tags can be improved when we consider different models (with references to DBpedia Linked Data repository) in the learning phase.

Coleções digitais de mídias, tanto pessoais como online, crescem rapidamente. Para que grandes quantidades de músicas sejam acessíveis à usuários, serviços populares como iTunes, Last.fm e Pandora oferecem recomendações. Essa abordagem livra usuários de lembrarem de músicas, e permite a descoberta de canções novas ou esquecidas. Mas recomendações apresentam problemas com usuários, como credibilidade e falta de controle. A motivação deste trabalho é melhorar a experiência de usuários com recomendações de música através do uso de explicações. Ao usar um sistema de recomendação, a satisfação e aprovação de usuários não depende só da eficácia do algoritmo, mas também de explicações. Pesquisas mostram que estas podem beneficiar sistemas de recomendação, aumentando a credibilidade e satisfação de usuários, ao oferecer mais transparência e formas de correção. O objetivo deste trabalho é projetar e desenvolver uma nova forma de visualização de tags, e testar sua viabilidade para explicar e filtrar recomendações de músicas. Mais precisamente, investigamos se esta visualização pode favorecer as metas de inspeção (scrutability), eficiência, eficácia e satisfação. A partir da pesquisa em necessidades de usuários para recomendações e música, a visualização Tag Strings foi projetada e desenvolvida. Tag Strings inclui tanto a interface da visualização, quanto o processo de coleta e cálculo de relevância de tags e músicas. Para a avaliação da visualização Tag Strings, dois tipos de experimentos foram construídos: a comparação entre uma lista de recomendações com Tag Strings, e a comparação entre o design de referência (baseado nos serviços Last.fm e Pandora) e Tag Strings. A construção desses dois experimentos permitiu a avaliação de Tag Strings como uma forma de explicação para recomendações de música. Os resultados dos experimentos evidenciam que a nova forma de visualização Tag Strings favorece as metas de inspeção (scrutability), eficiência, eficácia e satisfação, melhorando a usabilidade e experiência de usuários com recomendações de música. / Digital media collections, both personal and online, grow rapidly. To make large music collections available to users, popular services such as iTunes, Last.fm and Pandora offer recommendations. This approach frees users from searching for music, and allows for the discovery of new or forgotten items. But recommendations present issues such as user trust and lack of control. The motivation for this project is to improve user experience with music recommendations through explanations. While using a recommendation system, user acceptance and satisfaction depends not only on the algorithm effectiveness, but also on explanations. Research shows that recommendations benefit from explanations, increasing user trust and satisfaction by offering more transparency and scrutability. The goal of this project is to design and develop a new form of tag visualization, and test its feasibility to explain and filter music recommendations. We specifically investigate if the visualization can support the aims of scrutability, efficiency, effectiveness and satisfaction. Based on the user research and needs for music recommendation, the visualization Tag Strings was designed and developed. Tag Strings includes both the visualization interface and the process of collecting and calculation of tag and track relevancy. To evaluate the visualization Tag String, we designed two types of experiments: comparing Tag Strings with a recommendation list, and comparing Tag Strings with a design reference (based on the services Last.fm and Pandora). The design of these two experiments allowed the evaluation of Tag Strings as a form of explanation to music recommendation. The experiment results highlight that the new visualization Tag Strings favors the aims of scrutability, efficiency, effectiveness and satisfaction, improving the user experience with music recommendations.

abstract: Availability of affordable image and video capturing devices as well as rapid development of social networking and content sharing websites has led to the creation of new type of content, Social Media. Any system serving the end user’s query search request should not only take the relevant images into consideration but they also need to be divergent for a well-rounded description of a query. As a result, the automated optimization of image retrieval results that are also divergent becomes exceedingly important. The main focus of this thesis is to use visual description of a landmark by choosing the most diverse pictures that best describe all the details of the queried location from community-contributed datasets. For this, an end-to-end framework has been built, to retrieve relevant results that are also diverse. Different retrieval re-ranking and diversification strategies are evaluated to find a balance between relevance and diversification. Clustering techniques are employed to improve divergence. A unique fusion approach has been adopted to overcome the dilemma of selecting an appropriate clustering technique and the corresponding parameters, given a set of data to be investigated. Extensive experiments have been conducted on the Flickr Div150Cred dataset that has 30 different landmark locations. The results obtained are promising when evaluated on metrics for relevance and diversification. / Dissertation/Thesis / Masters Thesis Computer Science 2020

Since the popularisation of media streaming, a number of video streaming services are continually buying new video content to mine the potential profit. As such, newly added content has to be handled appropriately to be recommended to suitable users. In this dissertation, the new item cold-start problem is addressed by exploring the potential of various deep learning features to provide video recommendations. The deep learning features investigated include features that capture the visual-appearance, as well as audio and motion information from video content. Different fusion methods are also explored to evaluate how well these feature modalities can be combined to fully exploit the complementary information captured by them. Experiments on a real-world video dataset for movie recommendations show that deep learning features outperform hand crafted features. In particular, it is found that recommendations generated with deep learning audio features and action-centric deep learning features are superior to Mel-frequency cepstral coefficients (MFCC) and state-of-the-art improved dense trajectory (iDT) features. It was also found that the combination of various deep learning features with textual metadata and hand-crafted features provide significant improvement in recommendations, as compared to combining only deep learning and hand-crafted features. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2021. / The MultiChoice Research Chair of Machine Learning at the University of Pretoria / UP Postgraduate Masters Research bursary / Electrical, Electronic and Computer Engineering / MEng (Computer Engineering) / Unrestricted

The main goal of this diploma thesis is the risk analysis of transport company JAPO-Transport, s r o. with the usage of appropriate methods of economic and strategic analysis. This thesis is divided into five parts. The first one contains introduction of the company, the second part contains the analyses of current status. The third part sets the goals and shows the problems next the fourth part contains theoretical basics. In the fifth part there is a risk analysis and given recommendations for adequate risk measures.

This paper describes personalization of web applications and options of usage for scientific web portals. Theoretical part introduces main personalization principles and methods. Practical part of this paper focuses on resulting application. The application provides personalized services based on created user profile such as personalized search, content recommendation and conference planner.

Deficiency in the nurse's communication when transferring information can lead to serious consequences for the patient. It is often in transition between different teams or nursing units that deficiencies arise in the transfer of information, but the results of deficiencies can also arise throughout the care chain. The aim of this study was to elucidate the way in which SBAR facilitates nurse communication when transferring a patient within the health care system. This literature study was based on analysis of quantitative research. Seven quantitative articles were analysed using five step model by Friberg. The results of this study showed that SBAR helps the nurse to focus, prepare and structure the documentation and contributes to safer patient assessments. The use of SBAR leads to efficient reporting that promotes collaboration with other professions by making the message clear and structured. The conclusion was that by using SBAR as a communication tool for the nurse, patient safety increases.