https://repositorio.ufpb.br/jspui/handle/123456789/2404 Tue, 07 Apr 2026 08:07:26 GMT 2026-04-07T08:07:26Z https://repositorio.ufpb.br/jspui/handle/123456789/36175 Título: avaliação e seleção de fundos de investimentos multimercado no Brasil utilizando Análise Envoltória de Dados Autor(es): Andrade, Késsia Gomes Orientador: Rotella Junior, Paulo Abstract: This study proposes the application of Data Envelopment Analysis (DEA) for evaluation and selection of investment funds classified as Multimarket in Brazil as an alternative to traditional performance evaluation methods. The main objective was to identify and select the most efficient funds considering risk, return, cost, and performance consistency criteria. The model used was DEA-BCC output-oriented with computational implementation via Python. The input variables were return volatility over two and five years and the management fee, while the output variables were average annual returns over two and five years and the percentage of months with positive returns over five years. 602 funds were analyzed after a filtering process using Economatica, and the results demonstrated that only 34 funds (5.6% of the sample) reached the efficiency frontier. When compared to the sample, funds considered efficient showed superior average annual returns, greater consistency, lower costs, and lower volatility. The study concludes that DEA is a valuable tool for analysis and selection of Multimarket funds in Brazil and that efficiency is achieved through simultaneous optimization across multiple performance dimensions Editor: Universidade Federal da Paraíba Tipo: TCC Mon, 06 Oct 2025 00:00:00 GMT https://repositorio.ufpb.br/jspui/handle/123456789/36175 2025-10-06T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/36172 Título: Análise de som para detectar desbalanceamento em um sistema de hélice usando redes neurais convolucionais / Alexandre Sampaio de Figueiredo Autor(es): Figueiredo, Alexandre Sampaio de Orientador: Rodrigues, Marcelo Cavalcanti Abstract: Early fault diagnosis is traditionally performed using vibration analysis, acoustics, and visual inspection techniques; however, these methods have limitations when applied on a large scale or in environments with high noise levels. In this scenario, advances in artificial intelligence, particularly Convolutional Neural Networks CNNs, have enabled new approaches for the automatic detection of anomalies in signals of audio and images. This work presents the application of CNNs to the processing of audio to identify faults in rotating machinery. The experiment consisted of collecting data under two conditions: normal state and with imbalance in one of the propeller blades. The audio signals were processed and transformed into spectrographic representations, allowing them to be used in CNNs for automatic classification. The applied methodology aims to contribute to the advancement of predictive maintenance in machines by offering an artificial intelligence-based approach for diagnosing mechanical faults. Results indicate high model accuracy (100% accuracy, 100% f1- score, 100% precision, 100% recall), demonstrating the viability of the proposal. Editor: Universidade Federal da Paraíba Tipo: TCC Wed, 24 Sep 2025 00:00:00 GMT https://repositorio.ufpb.br/jspui/handle/123456789/36172 2025-09-24T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/36144 Título: Análise Numérica e Experimental da Aerodinâmica de uma Motocicleta de Competição em Escala Reduzida Utilizando OpenFOAM e um Túnel de Vento / Autor(es): Frederico, Nathan Pereira Orientador: Santos, Paulo Henrique Dias dos Abstract: This work presents a numerical and experimental analysis of the aerodynamics of a scaleddown competition motorcycle prototype. The numerical investigation was conducted using the open-source software OpenFOAM with the SST k–ω turbulence model. In parallel, a low-cost wind tunnel was designed and instrumented for experimental validation, featuring an acrylic test section, a 1800 W suction blower, and a data acquisition system based on an Arduino Uno with a load cell and HX711 module for direct drag force measurement. A mesh independence study was carried out, comparing three refinement levels based on the aerodynamic drag coefficient (CD) number of elements, and computational time. The numerical results for the drag coefficient CD = 0.59169 and drag force FD = 2.04 gf were compared with experimental data CD = 0.62014 and FD = 2.14 ± 0.20 gf, showing differences of 4.67% for the drag force and 4.59% for the drag coefficient. This close agreement validates the adopted numerical methodology and demonstrates the feasibility of the low-cost experimental apparatus. The study confirms that the combination of computational simulation and accessible experimental validation is a powerful and replicable tool for aerodynamic development in academic environments and for competition teams with limited resources, such as those in MotoStudent. Editor: Universidade Federal da Paraíba Tipo: TCC Tue, 16 Sep 2025 00:00:00 GMT https://repositorio.ufpb.br/jspui/handle/123456789/36144 2025-09-16T00:00:00Z https://repositorio.ufpb.br/jspui/handle/123456789/36143 Título: Desenvolvimento de procedimentos operacionais das atividades críticas da manutenção mecânica da unidade CSN Alhandra Autor(es): Alves, Giulia Peregrino Orientador: Albuquerque, Siderley Fernandes Abstract: nao consta abstrac Editor: Universidade Federal da Paraíba Tipo: TCC Wed, 27 Aug 2025 00:00:00 GMT https://repositorio.ufpb.br/jspui/handle/123456789/36143 2025-08-27T00:00:00Z