http://hdl.handle.net/11422/56 Fri, 17 Jul 2026 01:41:25 GMT 2026-07-17T01:41:25Z http://hdl.handle.net/11422/29383 Title: Modelagem e visualização de TriQuad Author(s)/Inventor(s): Gomes, Thiago Elias Advisor: Toledo, Rodrigo Penteado Ribeiro de Abstract: This work presents a new model of algebraic curves TriQuad. In this new formulation, a cubic algebraic curve is generated by spatially interpolating three quadratic forms, each one associated to a vertex of a triangle. TriQuad is thus a specialization of a group of implicit curves generated by interpolation of other ones. In order to eciently visualize those curves, the image domain is triangulated, and the proposed algorithm uses shaders to achieve real time performance. Regarding the modeling of those curves, a restricted least squares method is proposed to t a TriQuad to a given set of points. In order to qualify the approximation, an error metric is described and used for evaluating the results. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação Wed, 05 Feb 2014 00:00:00 GMT http://hdl.handle.net/11422/29383 2014-02-05T00:00:00Z http://hdl.handle.net/11422/29382 Title: Uma arquitetura de sensoriamento social para suporte à comunicação não planejada no contexto de violência urbana no projeto CidadeSocial Author(s)/Inventor(s): Silva, Eliel Roger da Advisor: Sampaio, Jonice de Oliveira Abstract: Violence in large urban centers poses significant challenges for both citizens and institutions, requiring public administrators to manage official information dissemination while residents seek ways to access critical data beyond their immediate social networks. The widespread use of social media has enabled individuals to act as human sensors, reporting urban violence through mobile devices. This study proposes and evaluates the feasibility of a software architecture to support unplanned communications and automatically detect/classify violence-related messages by severity level, adopting a Design Science Research methodology that includes: (1) problem context analysis and literature review on automated violence detection, (2) conception of a social sensing-based architecture, and (3) experimental validation through human sensor emulation, machine learning model development for violence classification, and architecture testing with multiple messages. Results demonstrate the viability of social sensing for enabling communication among unconnected individuals and confirm the effectiveness of human-as-sensor approaches for violence detection, offering practical solutions for urban safety challenges. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação Mon, 26 May 2025 00:00:00 GMT http://hdl.handle.net/11422/29382 2025-05-26T00:00:00Z http://hdl.handle.net/11422/29290 Title: REALM: um framework computacional para mapear os impactos da ciência através de análise de redes sociais, bibliometria e altmetria Author(s)/Inventor(s): Maia, Luís Fernando Monsores Passos Advisor: Sampaio, Jonice de Oliveira Abstract: Nowadays, a lot of universities and research institutes are concerned with measuring the productivity and progress of their research in its current state of the art. Furthermore, there is growing concern about understanding public opinion regarding their scientific discoveries, that is, how citizens interpret the efficiency of scientists and their efforts to find solutions. This scenario demands mechanisms to identify the reputation of experts in specific fields of science or topics of interest, such as the Zika virus. To address this problem, in this work we have developed a computational framework based on alternative metrics. The framework allows the extraction of three groups of metrics, productivity (bibliometrics), academic impact (social network analysis - centrality metrics) and social impact (altmetrics), and correlates these metrics, enabling the identification of the main scientists or research groups in specific fields of science. We have also developed a web system, based on the framework, to automate the procedures of mining, processing, merging, visualizing and analyzing data from various sources. The system provides mechanisms to assist in management of researchers' reputations and to perform comparisons between different scenarios or fields of science. The framework was applied to the Zika scenario, where the most important names in studies related to the disease were identified and their reputation was evaluated by experts from Oswaldo Cruz Foundation (Fiocruz), Zika Social Sciences Network and the international consortium ZIKAlliance. The main goal was to confirm whether the names identified by the framework match, in fact, to scientists of high academic and social prestige, recognized by the Zika virus research community. The evaluations’ results clearly show that the analyses carried out by the system are consistent and successfully highlight the leading scientists in the field, their main contributions and their societal impacts. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação Fri, 31 May 2019 00:00:00 GMT http://hdl.handle.net/11422/29290 2019-05-31T00:00:00Z http://hdl.handle.net/11422/29190 Title: SUFe: uma arquitetura de referência para sistemas de apoio à decisão em agricultura urbana inteligente Author(s)/Inventor(s): Jorge, Emanuele Nunes de Lima Figueiredo Advisor: Farias, Claudio Miceli de Abstract: Currently, family farming accounts for most of Brazilian food production. However, small and medium farmers face technological challenges that limit the efficiency and sustainability of their agricultural practices. Moreover, the tacit knowledge accumulated by these farmers is often underutilized due to the lack of systems capable of capturing and processing this information. In the face of increasing challenges related to food security and climate change, the integration of advanced technologies, such as the Internet of Things (IoT) and Knowledge Representation, becomes essential. This work proposes SUFe (System for Smart Urban Farming Environments) as a reference architecture for decision support systems in smart urban agriculture. The architecture integrates low-cost IoT sensors, knowledge representation models, and a rule-based inference engine to formalize farmers’ tacit knowledge and transform it into operational decisions. To validate its applicability, an instance of the architecture was implemented in a real-world setting focused on banana production (Musa spp., Prata cultivar) in Mangaratiba, RJ. The system incorporates wireless communication and solar energy to correlate environmental variables with local agricultural knowledge.Results demonstrated SUFe’s potential as a reference model to support decision-making, reduce waste, and enhance production efficiency. Publisher: Universidade Federal do Rio de Janeiro Type: Tese Thu, 28 Aug 2025 00:00:00 GMT http://hdl.handle.net/11422/29190 2025-08-28T00:00:00Z