https://repositorio.ifgoiano.edu.br/handle/prefix/250 Tue, 21 Jul 2026 03:32:51 GMT 2026-07-21T03:32:51Z http://repositorio.ifgoiano.edu.br:80/retrieve/311/Cincia-da-Computao.png https://repositorio.ifgoiano.edu.br/handle/prefix/250 https://repositorio.ifgoiano.edu.br/handle/prefix/6788 Título: PROCESSO DE ADEQUAÇÃO DO SITE DO MERCADO LIVRE  À LEI GERAL DE PROTEÇÃO DE DADOS PESSOAIS (LGPD) Autor(es): Guimarães, Luiz Sérgio Costa Primeiro Orientador: França, Heyde Francielle do Carmo Abstract: The Brazilian General Data Protection Law (LGPD) established guidelines for the processing of personal data in Brazil, requiring organizations to adopt measures that ensure privacy, information security, and the protection of data subjects' rights. In this context, this study aimed to analyze the process of adapting Mercado Livre's website to the requirements of the LGPD, identifying the main practices implemented, the challenges encountered, and their impacts on legal compliance and user experience. The research is characterized as qualitative, exploratory, and descriptive, based on bibliographic and documentary research, a case study, and field research conducted with companies located in the region of Acreúna, Goiás, Brazil. The analysis addressed aspects such as privacy policies, cookie management, consent mechanisms, information security, data subjects' rights, and data governance. The results indicate that Mercado Livre demonstrates a high level of compliance with the principles established by the LGPD through accessible privacy policies, consent management mechanisms, and investments in information security. On the other hand, the field research revealed that local companies still face significant challenges, including limited knowledge of the legislation, financial constraints, lack of specific tools, and technical difficulties in implementing compliance measures. It is concluded that compliance with the LGPD is a continuous process that requires investments in technology, governance, organizational training, and awareness, contributing to the protection of personal data, strengthening users' trust, and promoting responsible digital governance. Editor: Instituto Federal Goiano Tipo: Trabalho de Conclusão de Curso Mon, 29 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6788 2026-06-29T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6784 Título: CLASSIFICAÇÃO DO NÍVEL DE MATURAÇÃO E CONTAGEM DE TOMATES COM REDES NEURAIS CONVOLUCIONAIS USANDO DADOS DE COLORIMETRIA Autor(es): Caetano, Guilherme Honório Primeiro Orientador: França, Heyde Francielle do Carmo Primeiro Membro da Banca: França, Heyde Francielle do Carmo Segundo Membro da Banca: Silva, Fábia Barbosa da Terceiro Membro da Banca: Costa, Adriano Ferraz da Abstract: Tomato maturity classification is an important task in precision agriculture and is traditionally performed manually and subjectively. This work presents an approach that combines colorimetric measurements in the CIELAB color space with YOLO models for automatic tomato detection, counting, and classification into green, intermediary, and red classes. A dataset containing 1,040 images and 8,748 annotated fruits was built, with maturity classes defined from measurements obtained from 150 samples and grouped using the K-means algorithm. YOLOv10, YOLO11, YOLO12, and YOLO26 models, in both Small and Medium variants, were evaluated, achieving precision values above 95%, recall above 94%, and mAP@0.5 up to 97.5%. YOLO26m achieved the best overall performance. The trained models were integrated into a web application developed using Streamlit for image and video processing. The results highlight the potential of combining colorimetry and deep learning techniques for automated tomato maturity monitoring. Editor: Instituto Federal Goiano Tipo: Trabalho de Conclusão de Curso Mon, 22 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6784 2026-06-22T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6770 Título: ESTUDO DE EXTRATORES DE CARACTERÍSTICAS PARA CLASSIFICAÇÃO DE SONS AMBIENTAIS Autor(es): Araújo, Matheus Joseph Marques Primeiro Orientador: Oliveira, Douglas Cedrim Primeiro Membro da Banca: Belo Filho, Márcio Antonio Ferreira Segundo Membro da Banca: Ribeiro, André da Cunha Abstract: The soundscape surrounding us goes far beyond spoken language or structured music; it is composed of a myriad of environmental sounds, ranging from a dog barking to machinery noise. Teaching computers to listen to and interpret these events—a capability known as acoustic perception—is fundamental for the advancement of modern technologies, such as intelligent security systems and autonomous vehicles. However, environmental audio is complex and unstructured, making feature extraction a critical challenge. This work presents a comparative study of feature extractors for environmental sound classification, aiming to analyze how these techniques map and separate audio events into distinct classes within the computational space. Using public datasets consolidated in the state-of-the-art, the class separation and distribution were visually evaluated, and the extracted attributes were used to train a Multilayer Perceptron (MLP) neural network. The results demonstrate the effectiveness of the proposed approach, achieving an accuracy of 77.50% on one of the tested datasets, highlighting the potential of spectro-temporal representations for the evolution of automated acoustic recognition. Editor: Instituto Federal Goiano Tipo: Trabalho de Conclusão de Curso Mon, 22 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6770 2026-06-22T00:00:00Z https://repositorio.ifgoiano.edu.br/handle/prefix/6762 Título: ANÁLISE DA TRAJETÓRIA COMPETITIVA NO IFGOIANO - CAMPUS RIO VERDE (2016--2025) Autor(es): Amorim, Matheus de Jesus Primeiro Orientador: Ribeiro, André da Cunha Primeiro Membro da Banca: Oliveira, Douglas Cedrim Segundo Membro da Banca: Ramos, Fábio Montanha Abstract: Competitive programming has been widely used as a complementary educational tool for Computer Science students, contributing to the development of problem-solving, logical reasoning, and teamwork skills. In this context, this study aimed to analyze the evolution of competitive programming at IF Goiano -- Rio Verde Campus between 2016 and 2025, seeking to understand how participation in programming competitions contributed to the consolidation of this culture within the institution. To achieve this goal, a descriptive and longitudinal documentary research approach was conducted based on institutional records and official results from the Brazilian Computer Society Programming Contest (SBC Programming Contest), the Brazilian Olympiad in Informatics (OBI), and the Abóbora Contest. The analysis revealed the growth and consolidation of competitive programming activities throughout the investigated period, highlighting increased student participation, the maintenance of competitive teams, and the development of local training and integration initiatives. Among these initiatives, the Abóbora Contest emerged as an important mechanism for preparing students for external competitions and ensuring the continuous renewal of participants. The results indicate that sustained participation in programming competitions, combined with institutional training initiatives, significantly contributed to strengthening the competitive programming culture at IF Goiano -- Rio Verde Campus. Editor: Instituto Federal Goiano Tipo: Trabalho de Conclusão de Curso Fri, 26 Jun 2026 00:00:00 GMT https://repositorio.ifgoiano.edu.br/handle/prefix/6762 2026-06-26T00:00:00Z