Abstract
Scientific advances in recent decades have provided universal access to a variety of new digital technologies. These technologies are used by the vast majority of today's university students. Therefore, the incorporation of innovative methods and technologies is a must in order to actively engage students in the learning process. In this paper, a selection of techniques that can be considered 'outside of the box' are examined in the context of the application of teaching/learning methods in control engineering and industrial automation education. © 2022 IEEE.

Abstract
The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.

Abstract
The Multiple Traveling Salesman Problem (mTSP) is an interesting combinatorial optimization problem due to its numerous real-life applications. It is a problem where m salesmen visit a set of n cities so that each city is visited once. The primary purpose is to minimize the total distance traveled by all salesmen. This paper presents a hybrid approach called GABC-LS that combines an evolutionary algorithm with the swarm intelligence optimization ideas and a local search method. The proposed approach was tested on three instances and produced some better results than the best-known solutions reported in the literature.

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