http://repositorio.ufc.br/handle/riufc/379 2026-05-13T10:07:50Z http://repositorio.ufc.br/handle/riufc/86239 Título: Guia de teste de interoperabilidade para aplicações de Internet das Coisas Autor(es): Branco, Karina da Silva Castelo Abstract: Technology has significantly transformed human interactions with everyday objects, expanding the way they communicate. This broad connectivity with the Internet gave rise to the “Internet of Things (IoT)”, which expanded the boundaries of the Internet to encompass these objects, called smart, which, when interconnected, can collect and share information to provide services effectively. However, the intense data traffic and the diversity of interaction methods of these objects bring several challenges related to interoperability. Interaction methods refer to the different ways in which IoT devices communicate and share data, which can vary widely according to the protocols and standards used. In turn, interoperability refers to the ability of different systems to communicate effectively, ensuring data integrity. In this context, interoperability tests assess the ability of systems and devices to cooperate efficiently. Among the challenges of interoperability testing, the following stand out: architectural complexity, communication between devices, device heterogeneity, and ensuring effective connectivity between them. This master’s dissertation aims to develop an interoperability testing guide for IoT applications based on the methodology proposed by Carvalho et al., (2022). The construction of the guide is based on a literature review, data extraction and analysis, structuring of the guide, and observations of real IoT environments. The guide covers 12 topics, including feature definition and correlation, interoperability testing challenges, environment configuration, subfeatures, contextualization, test cases, measurements, impact of subfeatures, cost-benefit, tool suggestions, and usage examples. The evaluation of the guide consisted of three stages: (1) a structural evaluation using the Technology Acceptance Model (TAM); (2) a controlled experiment applying the guide to test a real IoT application; and (3) an evaluation of the guide with experts. The evaluation showed that the guide provides a comprehensive and practical framework for conducting interoperability testing, assisting experts in identifying problems and improving the integration between IoT systems and devices. Tipo: Dissertação 2024-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85917 Título: On bipolar argumentation frameworks and their equivalence with logic programming and SETAF Autor(es): Cordeiro, Renan de Castro Silva Abstract: Logic programming and abstract argumentation are closely connected paradigms suitable for representing incomplete, contradictory, and/or uncertain information. In Normal Logic Programs (NLPs), each claim is represented by an atom, which is considered true iff it can be derived by a set of logical rules. In Abstract Argumentation Frameworks (AAFs), claims are encoded as arguments and evaluated solely based on an attack relation, which determines how arguments (negatively) interact with each other. Different interactions give rise to distinct argumentation variants, such as Bipolar Argumentation Frameworks (BAFs) and Frameworks with Sets of Attacking Arguments (SETAFs), that additionally allow expressing the notions of support and collective attacks, respectively. For each variant, a evaluation criteria, called semantics, is needed to specify precisely which claims should be regarded as accepted, rejected, or neither (undecided). In this work, we study BAFs by both a semantic and a structural perspective. We propose new semantics for BAFs, called β-semantics, and employ them to find semantic-preserving translations between BAFs, SETAF, and NLPs. Moreover, our proposed translations preserve the structure of these formalisms when restricted to redundancy-free classes of them. The resulting translations are made accessible in the following website: https://web.archive.org/web/20260327154048/https://renpet-hhh.github.io/argnlp/static/. Tipo: Dissertação 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85302 Título: Jogo normal de dominação em grafos: estratégias vencedoras e complexidade computacional Autor(es): Matias, João Marcos Brito Abstract: Impartial Combinatorial Game Theory is a branch of mathematics that studies mathematical models of conflict and cooperation among individuals by modeling them as games that must satisfy certain criteria: two players alternating turns, a finite set of moves, perfect information, no randomness, and both players having the same set of possible moves in any position of the game. Around 1930, independently, Sprague and Grundy developed a theory stating that we can assign a non-negative integer value (nimber) to any position of an impartial combinatorial game and, with this, determine which of the two players will be the winner from the analyzed position. In parallel, we say that a set of vertices D dominates a graph G if every vertex of G is either in D or is adjacent to some vertex in D. With this, we can consider the DOMINATION GAME on graphs, an impartial combinatorial game in which two players alternately choose a vertex that has not yet been chosen and that must dominate at least one vertex that has not yet been dominated. The game ends when there are no more playable vertices, that is, when the chosen set of vertices forms a dominating set of the graph. This game has three versions: normal (the last player to move wins), misère (the last player to move loses), and optimization. In the optimization version, a player wins if they manage to finish the game in a number of turns less than or equal to a positive value k, and the opponent wins otherwise. In the literature there are many results for the optimization version of this game, but nothing has been found about the normal and misère versions. Therefore, in this work we present results for these versions. We use the Sprague-Grundy Theory to solve the NORMAL DOMINATION GAME on paths and cycles. In addition, we present a proof of the PSPACE-completeness of the DOMINATION GAME in its normal and misère versions. Tipo: Dissertação 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85300 Título: Análise de desempenho da quantização em soluções de aprendizado dividido federado Autor(es): Sales, Claro Henrique Silva Abstract: This paper addresses Split Federated Learning (SFL), a technique that enables artificial neural network models to be trained across multiple entities without directly sharing their data, thereby preserving data privacy. By partitioning the model between the client and the server, SFL also helps to reduce the computational load on the client side. However, despite its advantages, using this solution remains challenging in computationally constrained environments, such as mobile devices and IoT devices, especially on the client side. This work analyzes the performance of quantization, a technique that reduces the numerical precision of neural network parameters and activations to lower computational costs for clients during inference in SFL solutions. To this end, an empirical study was conducted in a cloud environment using the VGG11, ResNet18, and MobileNetV2 models over IID and non-IID variations of the CIFAR-10 dataset. The Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) schemes are compared with the full-precision model. The results demonstrate that the gains and losses from quantization are directly linked to the architecture, the choice of the cut layer, and the data distribution. Quantizing the client model accelerated the client’s forward pass by 4.3 on average. The reduction in memory consumption ranged from 26% to 56%, while the decrease in network consumption remained at 75% for all cases. The accuracy loss is also linked to the architecture: while the VGG11 and ResNet18 models maintained an accuracy loss of less than 2%, PTQ on the MobileNetV2 architecture led to losses of up to 22.7%, underscoring the need for QAT. Tipo: Dissertação 2025-01-01T00:00:00Z