DSpace Coleção:https://repositorio.ufms.br/handle/123456789/562026-04-18T12:36:05Z2026-04-18T12:36:05ZControle de Semáforos para Veículos de Emergênciahttps://repositorio.ufms.br/handle/123456789/142152026-01-19T12:42:14Z2025-01-01T00:00:00ZTítulo: Controle de Semáforos para Veículos de Emergência
Abstract: The high volume of vehicles in large metropolitan areas creates challenges for first responders, such as firefighters and paramedics, as it delays emergency vehicles due to traffic congestion. A standard way to reduce congestion is traffic light preemption on emergency vehicle (EV) routes. In this context, we propose an innovative traffic-light control system for emergency vehicles using smart city middleware that centralizes information and manages traffic lights along the whole EV route. Our primary contribution is the design and evaluation of an efficient preemption algorithm to reduce EV delays during emergencies. The algorithm utilizes a Timed Petri Net to coordinate concurrent events, thereby avoiding simultaneous actions at traffic lights along the EV’s route. Complementarily, the time required for vehicle queue dissipation is calculated based on the shockwave principle, allowing for an accurate estimation of road clearance. Extensive simulations in both real and synthetic scenarios demonstrate that our solution reduces EV delays and outperforms three competing algorithms.
Tipo: Tese2025-01-01T00:00:00ZIdentificação Automática de Áreas de Cana-de-Açúcar e Árvores Isoladas Utilizando Segmentação Semânticahttps://repositorio.ufms.br/handle/123456789/133582025-11-28T09:33:51Z2025-01-01T00:00:00ZTítulo: Identificação Automática de Áreas de Cana-de-Açúcar e Árvores Isoladas Utilizando Segmentação Semântica
Abstract: Manual orthophoto segmentation has limitations such as high costs, low scalability, and susceptibility to errors. Semantic segmentation is a crucial task for agricultural monitoring but faces challenges like class imbalance.The main objective of this work is to investigate semantic segmentation methodologies for the automatic identification of sugarcane areas and the mapping of isolated trees in orthophotos.One of the most significant contributions was the comparative evaluation of state-of-the-art models, such as SegFormer and InternImage, against more traditional and widely used convolutional architectures, like U-Net and DeepLabV3+. This analysis provided a comprehensive overview of the performance of different approaches in agricultural image segmentation.Furthermore, the study delved into the impact of class imbalance, a significant technical challenge in agricultural domains. To mitigate this issue, pre-processing strategies were proposed and investigated, including Crop-Focused sampling and Boundary-Zone sampling.The research also included an analysis of the effect of patch size on segmentation performance, addressing the trade-off between capturing global context and preserving local details. This demonstrated the viability of automating essential mappings, such as identifying planting areas and isolated trees, which shows direct gains in productive efficiency and a reduction in operational costs.These contributions, collectively, validate the capability of semantic segmentation solutions for automated monitoring, offering a path toward the implementation of more efficient and sustainable agricultural practices.
Tipo: Dissertação2025-01-01T00:00:00ZTowards Improving the LGBTQIAPN+ Developer Experience (DevX) in the Software Engineering Industryhttps://repositorio.ufms.br/handle/123456789/132322025-11-24T14:27:24Z2025-01-01T00:00:00ZTítulo: Towards Improving the LGBTQIAPN+ Developer Experience (DevX) in the Software Engineering Industry
Abstract: Recent research highlights the growing study of hidden populations in software en-
gineering and the dynamics that affect the productivity and experience (Developer
Experience) of these groups. Therefore, identifying factors that affect the DX of
LGBTQIAPN+ professionals becomes essential to charting paths that aim to mit-
igate challenges and provide solutions that integrate, facilitate, and direct sustain-
able software engineering environments for this developer population. This research
sought to understand the state of the art regarding the experience of LGBTQIAPN+
developers, capturing elements of classical and formal literature and gray literature.
Furthermore, two primary studies were conducted: a survey targeted at LGBTQI-
APN+ professionals and a subsequent combination of survey and video interviews.
This methodological design allows for the collection of evidence that supports the
construction of a DX model for LGBTQIAPN+ professionals based on the practical
experience of these professionals, in order to guide the agile technology industry in
the reception, integration, and retention of these engaged professionals. Thus, the
findings of this research include the following: Less structured environments, with
immature teams and few processes, in small companies in general, are prone to
episodes of prejudice and integration difficulties. On the other hand, environments
with structured processes and more developed teams, such as those in large com-
panies, provide a differentiated experience, but not exempt from episodes of bias
or gender prejudice. Among the guidelines presented in the model proposed in this
research are: listening to professionals, welcoming them in the face of episodes of
prejudice, and respecting gender identities and pronouns. Furthermore, agile cere-
monies can respect the processes and challenges these professionals face, fostering
the development of an environment of collaboration and engagement.
Tipo: Dissertação2025-01-01T00:00:00ZAvanços no cálculo da distância Double Cut and Join com regiões intergênicas para genomas reaishttps://repositorio.ufms.br/handle/123456789/130912025-11-16T03:04:50Z2025-01-01T00:00:00ZTítulo: Avanços no cálculo da distância Double Cut and Join com regiões intergênicas para genomas reais
Abstract: The double cut and join (DCJ) distance problem has been extensively studied in recent years, leading to the development of multiple algorithms for its different variations. However, limited attention has been given to the DCJ distance problem in the context of genomes containing duplicated genes and intergenic regions. The genome sizes and the inequalities of the intergenic sizes play an important role in the running times of algorithms; yet these factors are often overlooked in existing studies. In this work, we establish a formal definition for the DCJ distance problem considering intergenic regions and duplicated genes, and propose different strategies to find a heuristic solution for it by using existing exact and approximation algorithms. The methods we propose improve upon existing approaches in both quality and efficiency, particularly overcoming severe limitations of the current methods regarding the number of genes and intergenic size inequalities.
Tipo: Dissertação2025-01-01T00:00:00Z