http://repositorio.ufc.br/handle/riufc/21997 Thu, 11 Jun 2026 18:10:11 GMT 2026-06-11T18:10:11Z http://repositorio.ufc.br/handle/riufc/84981 Título: Subdivisões de orientações do grafo bipartido completo K2,3 Autor(es): Serra, Philipe Medeiros Abstract: In this work, we explore the problem of finding a subdivision of a digraph F in a digraph D, with the goal of identifying polynomial-time and NP-complete instances of the problem. More specifically, we focus on the cases where F is an orientation of K2,3, in an attempt to gain a clearer understanding of a conjecture regarding the problem in planar graphs. We present all possible orientations of K2,3 and the cases where the problem can be solved in polynomial time, using flow techniques or the Directed Grid Theorem. The complexity of only one case remains open. Tipo: TCC Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/84981 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/80335 Título: Avaliação da capacidade computacional e representação de consciência de uma Conscious Turing Machine Autor(es): Fernandes, Guilherme Sales Abstract: With the rapid evolution of generative text models and their conversational abilities, many questions arise regarding the possibility of simulating consciousness in such systems. Addressing this issue requires tackling the classic philosophical challenge of understanding the nature of consciousness. This study explores this problem from the perspective of theoretical computer science, a field dedicated to investigating the foundations of computation and complexity. The Conscious Turing Machine (CTM), proposed by Manuel and Lenore Blum, was implemented in Python, and experiments were conducted using question-based tests to assess logical inference capabilities with the bAbI toy tasks dataset and textual inference capabilities with the RocStories dataset. The CTM’s performance was compared with that of individual language models, which collectively form the CTM processors. The results indicate that while the CTM provides advantages in interpretability and information organization, its performance is comparable to that of smaller models and comes with significantly higher computational costs. Furthermore, it presents theoretical divergences from classical theories of consciousness. We conclude that the CTM serves more as a computational metaphor for studying consciousness rather than as a practical approach to Artificial Intelligence. Additionally, we discuss implementation challenges and propose directions for future research. Tipo: TCC Wed, 01 Jan 2025 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/80335 2025-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/80322 Título: Mapeamento sistemático sobre técnicas de monitoramento de faltas baseadas em mineração de dados Autor(es): Rodrigues, Paulo Ricardo Fernandes Abstract: The increasing complexity and interconnection of modern software systems makes fault detection a significant challenge, as traditional testing techniques have proven insufficient, particularly in dynamic and large-scale systems. To address this issue, various real-time monitoring approaches based on data mining have been proposed. These approaches, through continuous system analysis and the use of anomaly detection techniques, are capable of identifying faults in software systems. This study presents a systematic mapping of the literature on these monitoring techniques, aiming to identify implementation challenges and provide a comprehensive overview of the current state of the research. The mapping was conducted using the Scopus database, and 20 studies were selected to help answer the research questions defined in this work. The analysis enabled the identification of not only the main detection techniques but also the types of monitored systems, fault categories, and evaluation metrics used in the proposed approaches. Among the main challenges identified are the difficulty in labeling data for training supervised models, the complexity of interpreting the generated models, and the need for computationally efficient monitoring. Tipo: TCC Wed, 01 Jan 2025 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/80322 2025-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/80320 Título: Uma avaliação de abordagens LDP aplicadas a conjuntos de dados longitudinais Autor(es): Marreiras Neto, Antônio Alves Abstract: Local differential privacy (LDP) was developed as a more strict version of differential privacy (DP), the state-of-the-art model of anonymity guarantee for databases. Due to the requirement of data anonymity before it is sent to the server, a challenge in guaranteeing LDP is the risk of excessive addition of noise to the data, which can be especially hard to avoid when applying LDP to longitudinal data, that requires successive queries over time, with each one having to guarantee LDP. In this paper, we aim to evaluate the performance of LDP protocols adapted for the protection of longitudinal data, when applied to the task of finding the k most frequent items, and their frequencies, among longitudinal data sets. To this end, we evaluate the performance of a wide range of LDP mechanisms when used in conjunction with the state-of-the-art SVIM approach, in the processing of four different datasets. After exhaustive experimentation, we compared the results found and indicated the most promising ones. Tipo: TCC Wed, 01 Jan 2025 00:00:00 GMT http://repositorio.ufc.br/handle/riufc/80320 2025-01-01T00:00:00Z