Paulo Moura Oliveira

Abstract
Forest fires represent a significant and growing threat to natural ecosystems and human settlements, with their unpredictable behavior and capacity for rapid expansion over time, creating substantial challenges for effective prevention, control, and mitigation. This paper presents the development of a forest fire simulator designed to model and predict fire spread under varying environmental conditions. Such a simulator must consider how fire spreads in different locations and climate conditions, showing the final shape of the fire in a given period of time. Using the NetLogo agent-based modeling platform, a simulated forest environment was created in which trees function as autonomous agents interacting with one another and the environment. Identifying and understanding the risk factors that increase the likelihood of a fire occurring, as well as those that contribute to its spread and intensity, is essential for the development of an accurate forest fire simulator. Such a simulator can integrate the complex interactions among these variables to produce dynamic visualizations of fire progression, allowing users to evaluate different scenarios and make informed decisions for preventing, controlling and fighting forest fires. By incorporating key factors—such as vegetation density, temperature, humidity, topography, and wind direction—the system calculates the probability of fire propagation and generates visual representations of fire behavior over time. This tool allows users to forecast fire behavior and assess response strategies proactively, thereby improving the accuracy and efficiency of firefighting efforts. In addition, the simulator yields significant social benefits, especially for older adults residing in fire-prone areas, by supporting early warning systems, enabling prompt evacuations, and mitigating their susceptibility to fire-related risks through enhanced preparedness and coordinated response measures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
The paper presents an application of the new control paradigm, which is based on process moments, to a model of a DC motor. The basis of the new control paradigm is that it eliminates the process transfer function within the closed loop, as it estimates the final steady-state value of the process output and compares it with the reference signal. As a result, the closed loop response is much more stable and generally without overshoots. This property makes it suitable for application to motor-driven processes where overshoots is undesirable. It was shown that the control method provides very stable closed-loop responses even when the actual motor and the model parameters differ. It was also shown that the proposed method can be applied to constrained systems as the anti-windup protection is implicitly embedded in the control solution. © 2025 IEEE.

Abstract
The aging of the Portuguese population is a multifaceted challenge that requires a coordinated and comprehensive response from society. In this context, social service institutions play a fundamental role in providing aid and support to the elderly, ensuring that they can enjoy a dignified and fulfilling life even in the face of the challenges of aging. This research proposes a Balanced Multiple Traveling Salesman Problem based on the Ant Colony Optimization algorithm (ACO-BmTSP) to solve a distribution of meals problem in the municipality of Mogadouro, Portugal. The Multiple Traveling Salesman Problem (mTSP) is an NP-complete problem where m salesmen perform a shortest tour between different cities, visiting each only once. The primary purpose is to minimize the sum of all distance traveled by all salesmen keeping the tours balanced. This paper shows the results of computing obtained for three, four, and five agents with this new approach and their comparison with other approaches like the standard Particle Swarm Optimization and Ant Colony Optimization algorithms. As can be seen, the ACO-BmTSP, in addition to obtaining much more equitable paths, also achieves better results in lower total costs. In conclusion, some benchmark problems were used to evaluate the efficiency of ACO-BmTSP, and the results clearly indicate that this algorithm represents a strong alternative to be considered when the problem size involves fewer than one hundred locations.

Abstract
Information Systems (IS) projects are critical for organizational development, both in the private and public sectors. The relevance and complexity inherent in this type of project require management to be fully aware of the factors that influence success. This study contributes to the literature on public-sector IS project management by providing a comprehensive set of Success Factors (SFs) for different levels of the administration. The research method comprised a literature review, six case studies of central government, local government, and other types of administration, and a questionnaire-based survey of public sector IS experts. Forty-four SFs were identified, described, and organized in nine categories: organization and environment; strategy; project; scope; project manager and project team; stakeholders; vendors; clients and users; and monitoring and control. Our results add a new perspective to the theoretical body of knowledge on the SFs for IS projects in the public sector.

Abstract
Since the public unveiling of ChatGPT-3 in November 2022, its impact and consequences for society have been significant. This generative artificial intelligence has now become a disruptive technology. Education in general, and Engineering Education in particular, are feeling the effects of the widespread adoption of artificial intelligence tools by students. However, teachers and universities are still struggling with how to deal with these technologies. The current increase in digitalisation makes detecting unauthorised use of ChatGPT and similar tools a major challenge. This paper therefore explores several issues regarding the use of ChatGPT in the context of Engineering Education. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)