http://repositorio.ufc.br/handle/riufc/19757 2026-04-11T14:36:12Z http://repositorio.ufc.br/handle/riufc/85471 Título: Uma validação das leis de Lehman: uma investigação quantitativa no desenvolvimento de software moderno Autor(es): Sousa, Augusto Braz de Abstract: This study investigates the applicability and relevance of Lehman’s Laws in the current context of software development, using a quantitative approach to analyze three modern systems: Dropwizard, K-9 Mail, and LanguageTool. Through the Goal Question Metric (GQM) framework, the research empirically validates Lehman’s Laws, which describe fundamental principles of software evolution, such as continuous change, increasing complexity, and conservation of organizational stability. The study is divided into two main stages. The first stage involves analyzing the evolution metrics of the three selected software systems, verifying their compliance with Lehman’s Laws. The second stage utilizes the lessons learned to develop practical guidelines that can be applied to software development and maintenance. The results confirm that Lehman’s Laws are applicable and relevant to modern software systems, providing a theoretical foundation for guiding development and maintenance practices. The analyzed metrics demonstrate growth and complexity patterns that corroborate Lehman’s proposed laws. Additionally, the study offers a summary of the lessons learned and practical guidelines for developers and maintenance teams, aiming to improve adaptability, reduce complexity, and ensure the continuous quality of systems. These guidelines are based on empirical evidence collected and offer recommendations for the efficient evolution of software. The main contributions of this work include the empirical validation of Lehman’s Laws, the application of the GQM framework as a methodological basis, and the creation of practical guidelines based on the lessons learned. Tipo: Dissertação 2024-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85469 Título: Desacoplamento de controle longitudinal e lateral em veículos autônomos usando controle preditivo baseado em modelo: validação usando o simulador CARLA Autor(es): Rodrigues, João Pedro da Silva Abstract: This dissertation presents the comparison and validation of two trajectory control strategies for autonomous vehicles within a hierarchical planning and control architecture. In the first approach, referred to as coupled control, a Model Predictive Controller (MPC) simultaneously performs both lateral and longitudinal control actions, while in the second approach, referred to as decoupled control, the predictive controller is responsible for lateral control and a proportional– integral (PI) controller governs the vehicle’s longitudinal dynamics. In both cases, the predictive control is based on the dynamic bicycle model. The lateral controller ensures that the vehicle follows the desired trajectory, while the longitudinal controller maintains the vehicle at a predefined constant speed by generating acceleration based on the longitudinal reference velocity. The reference trajectories and velocity are generated by a trajectory planner that employs a receding-horizon control strategy based on mixed-integer quadratic programming. Validation is carried out through co-simulation in MATLAB and CARLA environments, where the controllers are implemented in MATLAB and the vehicle model is simulated in CARLA, an open-source high-fidelity simulator for autonomous driving research. The simulation experiments consider two distinct scenarios. In the first scenario, the maneuver of a vehicle traveling along a one-way road in the presence of a static obstacle is evaluated. In the second scenario, the maneuver is evaluated in the presence of a dynamic obstacle moving at a constant longitudinal speed. The results show that the coupled strategy achieves better lateral trajectory tracking, especially at higher speeds, with a root mean square error (RMSE) of 0.084 m compared to 0.089 m for the decoupled method. However, it is less accurate in longitudinal speed control, with an RMSE of 1.32 m compared to 1.21 m. The computational performance analysis indicates that both approaches meet real-time requirements and are computationally feasible, with the decoupled method exhibiting a slightly lower solution time (2.6 ms versus 2.7 ms). Tipo: Dissertação 2025-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85468 Título: Redes neurais profundas para classificar imagens de radiografias odontológica panorâmica na perspectiva de grupos etários: um estudo exploratório Autor(es): Oliveira, Michele Faria de Abstract: Estimating chronological age is an essential process in forensic dentistry, as it allows inferring an individual’s age group based on biometric characteristics, particularly those observable in dental radiographs. Although traditional methods, such as those proposed by Nolla and Demirjian, are widely adopted, they often require expert interpretation and may present limitations regarding accuracy and scalability. Deep neural networks have emerged as a promising alternative in this context, offering a non-invasive, automated, and low-cost approach. This dissertation comprises three main parts. The first presents a systematic literature review aimed at identifying the state of the art in using deep learning for age estimation based on panoramic dental radiographs. Following a rigorous selection process, 17 primary studies were included and analyzed. Key f indings indicate that the ResNet and AlexNet architectures stand out among the evaluated approaches, particularly for younger age groups (3 to 14 years), and that accuracy and recall are the most frequently used performance metrics. The second stage involved the construction of a dataset composed of 1,545 panoramic radiographic images obtained through partnerships with dental clinics. All images were anonymized and standardized, and a mask was applied to highlight the anatomical region of interest. This dataset aims to facilitate replication and future expansion in similar studies. Finally, the third part of this work consisted of an exploratory study using seven convolutional neural network architectures (AlexNet, VGG16, ResNet50, DenseNet, MobileNetV2, EfficientNet-B3, and InceptionV3), aiming to evaluate their effectiveness in estimating age based on the constructed dataset. The results support previous findings from the literature and demonstrate the potential of deep learning approaches in real-world forensic scenarios. This research contributes valuable insights for developing intelligent solutions in forensic dentistry, supporting researchers, tool developers, and healthcare professionals. Tipo: Dissertação 2025-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/85433 Título: Desenvolvimento e aplicação de fonte de corrente Howland para avaliação da eletrólise pulsada da água Autor(es): Frota, Francisco Wilson Oliveira da Abstract: Pulsed water electrolysis has emerged as a promising strategy to mitigate limitations inherent to conventional electrolysis, particularly those associated with activation and ohmic overpotentials, mass transport phenomena, and the dynamic behavior of the electrical double layer. However, experimental investigation of pulsed regimes requires current sources capable of delivering precise, stable, and reproducible waveforms under dynamic variations of the electrolytic cell impedance. In this context, this dissertation presents the development, implementation, and application of a Howland Current Source (HCS) specifically designed for pulsed electrolysis studies. The Howland topology was selected due to its high output impedance, linearity, and ability to supply modulated currents with minimal load dependence, which are essential features for accurate pulse control. The developed system was employed both for electrical characterization of the electrolytic cell, through transient analysis of the electrical double layer, and for comparative evaluation between continuous and pulsed electrolysis. Experimentally, pulsed electrolysis achieved a maximum relative energy efficiency gain of 9.72%, reaching efficiencies up to 31.1% when operated at frequencies between 40 and 50 kHz and duty cycles ranging from 20% to 50%, under a current density of approximately 0.5 A/cm². Under these conditions, a reduction of up to 700 mV in the average cell voltage was observed, indicating partial mitigation of electrochemical overpotentials. The Howland current source exhibited a maximum mean squared error of 0.053 relative to an ideal waveform, demonstrating stable and reproducible dynamic performance even at high frequencies. These results highlight the HCS as a low-cost, high-fidelity experimental tool for advanced investigations of pulsed water electrolysis and green hydrogen production. Tipo: Dissertação 2025-01-01T00:00:00Z