6 resultados para Context data

em Repositório Institucional da Universidade de Aveiro - Portugal


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Orientações curriculares portuguesas para o 1.º Ciclo do Ensino Básico [CEB] preconizam o desenvolvimento de capacidades transversais como a resolução de problemas [RP] e a comunicação (em) matemática [CM], o estabelecimento de conexões Matemática–Ciências Físicas e Naturais [CFN] e a articulação de contextos de educação formal [EF] e de educação não formal [ENF]. Em Portugal, professores manifestam querer utilizar recursos didáticos com estes atributos. Contudo, tais recursos escasseiam, assim como investigação que se situa na confluência destas dimensões. Por conseguinte, na presente investigação, foram desenvolvidos recursos didáticos centrados na promoção de conexões Matemática-Ciências Físicas e Naturais e na articulação de contextos de EF e de ENF. Assim, a presente investigação tem por finalidade desenvolver (conceber, produzir, implementar e avaliar) recursos didáticos de exploração matemática de módulos interativos de ciências, articulando contextos de EF e ENF que, nomeadamente, apelem e possam desenvolver capacidades básicas ligadas à RP e à CM de alunos do 1.º CEB. Decorrente desta finalidade, definiram-se as seguintes questões de investigação: 1. Quais as repercussões dos recursos didáticos desenvolvidos na capacidade de RP de alunos do 4.º ano do 1.º CEB?; 2. Quais as repercussões dos recursos didáticos desenvolvidos na capacidade de CM de alunos do 4.º ano do 1.º CEB?. Além disso, procurou-se auscultar a opinião de alunos e professora sobre a exploração dos recursos didáticos desenvolvidos, principalmente, ao nível de conexões Matemática–CFN e articulação de contextos de EF e ENF de Ciências. Para tanto, foi realizado um estudo de caso com uma professora e seus alunos do 4.º ano do 1.º CEB, em sala de aula e num espaço de ENF de Ciências. A recolha de dados envolveu diversas técnicas e vários instrumentos. A técnica de análise documental incidiu nas produções dos alunos registadas em Guiões do Aluno e em Tarefas-Teste. No âmbito da técnica de inquirição foram administrados questionários a todos os alunos da turma – o Questionário Inicial e o Questionário Final – e entrevistas semiestruturadas à professora – a Entrevista Inicial à Professora e a Entrevista Final à Professora – e aos três alunos caso – Entrevista ao aluno caso. No que respeita à técnica de observação foi implementado o instrumento Notas de campo, onde foram efetuados registos de natureza descritiva e reflexiva. Os dados recolhidos foram objeto de análise de conteúdo e de análise estatística. Resultados da investigação apontam para que a exploração dos recursos didáticos desenvolvidos possa ter promovido o desenvolvimento de capacidades matemáticas de RP e, sobretudo, de CM dos alunos. Parecem ainda indicar que, genericamente, os alunos e a professora possam ter considerado que os recursos didáticos promoveram conexões Matemática– CFN e a articulação entre espaços de EF e ENF de Ciências.

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Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

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Information Visualization is gradually emerging to assist the representation and comprehension of large datasets about Higher Education Institutions, making the data more easily understood. The importance of gaining insights and knowledge regarding higher education institutions is little disputed. Within this knowledge, the emerging and urging area in need of a systematic understanding is the use of communication technologies, area that is having a transformative impact on educational practices worldwide. This study focused on the need to visually represent a dataset about how Portuguese Public Higher Education Institutions are using Communication Technologies as a support to teaching and learning processes. Project TRACER identified this need, regarding the Portuguese public higher education context, and carried out a national data collection. This study was developed within project TRACER, and worked with the dataset collected in order to conceptualize an information visualization tool U-TRACER®. The main goals of this study related to: conceptualization of the information visualization tool U-TRACER®, to represent the data collected by project TRACER; understand higher education decision makers perception of usefulness regarding the tool. The goals allowed us to contextualize the phenomenon of information visualization tools regarding higher education data, realizing the existing trends. The research undertaken was of qualitative nature, and followed the method of case study with four moments of data collection.The first moment regarded the conceptualization of the U-TRACER®, with two focus group sessions with Higher Education professionals, with the aim of defining the interaction features the U-TRACER® should offer. The second data collection moment involved the proposal of the graphical displays that would represent the dataset, which reading effectiveness was tested by end-users. The third moment involved the development of a usability test to the UTRACER ® performed by higher education professionals and which resulted in the proposal of improvements to the final prototype of the tool. The fourth moment of data collection involved conducting exploratory, semi-structured interviews, to the institutional decision makers regarding their perceived usefulness of the U-TRACER®. We consider that the results of this study contribute towards two moments of reflection. The challenges of involving end-users in the conceptualization of an information visualization tool; the relevance of effective visual displays for an effective communication of the data and information. The second relates to the reflection about how the higher education decision makers, stakeholders of the U-TRACER® tool, perceive usefulness of the tool, both for communicating their institutions data and for benchmarking exercises, as well as a support for decision processes. Also to reflect on the main concerns about opening up data about higher education institutions in a global market.

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The study of forest re activity, in its several aspects, is essencial to understand the phenomenon and to prevent environmental public catastrophes. In this context the analysis of monthly number of res along several years is one aspect to have into account in order to better comprehend this tematic. The goal of this work is to analyze the monthly number of forest res in the neighboring districts of Aveiro and Coimbra, Portugal, through dynamic factor models for bivariate count series. We use a bayesian approach, through MCMC methods, to estimate the model parameters as well as to estimate the common latent factor to both series.

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Personal information is increasingly gathered and used for providing services tailored to user preferences, but the datasets used to provide such functionality can represent serious privacy threats if not appropriately protected. Work in privacy-preserving data publishing targeted privacy guarantees that protect against record re-identification, by making records indistinguishable, or sensitive attribute value disclosure, by introducing diversity or noise in the sensitive values. However, most approaches fail in the high-dimensional case, and the ones that don’t introduce a utility cost incompatible with tailored recommendation scenarios. This paper aims at a sensible trade-off between privacy and the benefits of tailored recommendations, in the context of privacy-preserving data publishing. We empirically demonstrate that significant privacy improvements can be achieved at a utility cost compatible with tailored recommendation scenarios, using a simple partition-based sanitization method.

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In recent years the technological world has grown by incorporating billions of small sensing devices, collecting and sharing real-world information. As the number of such devices grows, it becomes increasingly difficult to manage all these new information sources. There is no uniform way to share, process and understand context information. In previous publications we discussed efficient ways to organize context information that is independent of structure and representation. However, our previous solution suffers from semantic sensitivity. In this paper we review semantic methods that can be used to minimize this issue, and propose an unsupervised semantic similarity solution that combines distributional profiles with public web services. Our solution was evaluated against Miller-Charles dataset, achieving a correlation of 0.6.