Abstract
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Abstract
The main objective of this work was to develop a tuning method for PID controllers suitable for use in an industrial environment. Therefore, a computationally simple tuning method is presented based on a simple experiment on the process without requiring any input from the user. Essentially, the method matches the closed-loop response to the response obtained in the steady-state change experiment. The proposed method requires no prior knowledge of the process and, in its basic form, only the measurement of the change in the steady state of the process in the manually or automatically performed experiment is needed, which is not limited to step-like process input signals. The user does not need to provide any prior information about the process or any information about the closed-loop behavior. Although the control loop dynamics is not defined by the user, it is still known in advance because it is implicitly defined by the process open-loop response. Therefore, no exaggerated control signal swings are expected when the reference signal changes, which is an advantage in many industrial plants. The presented method was designed to be computationally undemanding and can be easily implemented on less powerful hardware, such as lower-end PLC controllers. The work has shown that the proposed model-free method is relatively insensitive to process output noise. Another advantage of the proposed tuning method is that it automatically handles the tuning of highly delayed processes, since the method discards the initial process response. The simplicity and efficiency of the tuning method is demonstrated on several process models and on a laboratory thermal system. The method was also compared to a tuning method based on a similar closed-loop criterion. In addition, all necessary Matlab/Octave files for the calculation of the controller parameters are provided online.

Abstract
The 10th edition of the Technological Ecosystems for Enhancing Multiculturality (TEEM 2022) brings together researchers and postgraduate students interested in combining different aspects of the technology applied to knowledge society development, with particular attention to educational and learning issues. This volume includes contributions related to communication, educational assessment, sustainable development, educational innovation, mechatronics, and learning analytics. Besides, the doctoral consortium papers close the proceedings book from a transversal perspective. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Abstract
The article focuses on the consumption of goods used by consumers of different generations from 3 different countries: Albania, Polish and Portugal. The aim of the analysis was to identify respondents"indications concerning: (1) knowledge of the definition of the circular economy, (2) declared by respondents places of purchase of used products and (3) type of purchased products used by respondents. The analysis was conducted among 495 respondents from Albania, Polish and Portugal representing three generations (X, Y, Z). Correspondence analysis was used for statistical data analysis. Statistically significant differences in knowledge of the definition of the circular economy were shown between respondents from Albania, Polish and Portugal. It was also found that respondents"preferences regarding the place of purchase of second-hand goods are differentiated (at a statistically significant level) by nationality and year of birth (generation). The obtained results open the possibility of further research aimed at identifying different behaviors among these groups of consumers. The presented work, both in the cognitive and application part, can be a source of knowledge and popularization of research, as well as a source of inspiration for in-depth reflection and scientific discussion. The analyses presented in the publication may complement the existing research in the field of circular economy. Extending the survey to other EU countries can help define a strategy for policymakers, manufacturers and retailers to make greater use of circular economy solutions, while maintaining the viability of their operations. © 2023 Altin Kulli et al., published by Sciendo.

Abstract
Public lighting is crucial for maintaining the safety and well-being of communities. Current inspection methods involve examining the luminaires during the day, but this approach has drawbacks, including energy consumption, delay in detecting issues, and high costs and time investment. Utilising deep learning based automatic detection is an advanced method that can be used for identifying and locating issues in this field. This study aims to use deep learning to automatically detect burnt-out street lights, using Seville (Spain) as a case study. The study uses high-resolution night time imagery from the JL1-3B satellite to create a dataset called NLight, which is then divided into three subsets: NL1, NL2, and NT. The NL1 and NL2 datasets are used to train and evaluate YOLOv5 and YOLOv7 segmentation models for instance segmentation of streets. And then, distance outliers were detected to find the lights off. Finally, the NT dataset is used to evaluate the effectiveness of the proposed methodology. The study finds that YOLOv5 achieved a mask mAP of 57.7%, and the proposed methodology had a precision of 30.8% and a recall of 28.3%. The main goal of this work is accomplished, but there is still space for future work to improve the methodology.

Abstract
Teaching and learning are processes that must accompany the digital transition, which is one of the biggest challenges we currently face, along with the green transition. The digital transition in education is a process with several challenges that must count on the involvement and collaboration of all stakeholders, contributing to the schools of the future. For this, technology plays a decisive role, and must be integrated into classes as a relevant tool to develop and implement different types of experiments, motivating the students towards STEM areas. In this context, a project financed by IFAC made it possible to use pocket laboratories in different high schools, encouraging teachers to prepare activities supported by this equipment, stimulating students to be interested in engineering topics. This article presents the approach followed in one high school and discusses the results obtained, highlighting the usefulness and opportunity of using pocket labs, and low-cost equipment in general, in school activities, which can promote the STEM areas and, in particular, the engineering courses.