The paper describes an active blended learning approach designed for engineering students with diverse educational backgrounds, forms and duration of training in the EuroTeQ transnational university alliance. The purpose of the present work is to suggest and justify new tools aimed at attracting and supporting the interest of university entrants in creativity, innovation and other advanced skills required under the novel Industry 5.0 initiative of the European Commission. At this, the emphasis is on the development of such qualities as adaptability and flexibility, cooperation and leadership, effective oral and written communication, self-regulation, new media literacy, and intercultural competence. The case study in teaching Robotics and Advanced Robotics at Tallinn University of Technology reveals some important advantages, as well as several problematic aspects of the method.

This study focuses on the impact of active learning on engineering students with diverse educational backgrounds, forms and duration of training, as well as the level of language proficiency. The purpose of the research is to determine to what extent it is effective and useful to implement the student-centered approach in order to gain the student’s engagement in active learning and achieve success in academic performance in the light of requirements posed by the fourth industrial revolution “Industry 4.0”. The case study in Robotics reveals some significant relations between long-term activities and creative brainstorming and their influence on the strong and weak trainees. Several troubling issues are analyzed in terms of enthusiasm shown by some students and disaffection expressed by other learners.

To verify the functionality of an intelligent open-loop fuzzy-logic-based antilock braking system control method for four on-board motor drive electric sport utility vehicle, a hardware-in-the-loop experiment is conducted in this article. The experimental facility includes a novel decoupled electrohydraulic brake test bed characterized by highly nonlinear dynamics and time-varying behavior. It reproduces real pressure dynamics of the brake circuit allowing for simulation of various tire-road adhesions conditions and brake blending scenarios. To cope with degradation of antilock braking system performance induced by unexpected changing environmental conditions, such as road surface, the developed fuzzy control features a very simple yet effective and robust road surface recognition tool with estimation of the peak braking demands. Thus, the fuzzy logic serves as a controller and road surface estimator simultaneously allowing for complex mathematical modeling and feedback control avoidance not sacrificing safety system's performance. The results indicate that the control method manages highly nonlinear and time-variant dynamics of the brake system and offers significant feasibility for optimal slip control at regenerative braking, ensuring fuzzy control's potentiality for real-time application.

Despite the numerous advantages of academic mobility, some of its participants face barriers to education and further success in life due to several issues associated with the social inclusion. This study examines the sources of students' failures and dissatisfaction with mobility, focusing on three questions: what are the reasons of travellers’ defeats, how they relate to engineering disciplines, and what steps should be taken to include foreigners in engineering courses? The outcomes obtained help increase the quality and diversity of education, as well as assist mobile students in guiding their own learning, improving curricula, enhancing communication, and strengthening collaboration with local staff. The proposed educational thesaurus can serve as an effective tool for adapting curricula to the actual students’ backgrounds.

In addition to vehicle control, drivers often perform secondary tasks that impede driving. Reduction of driver distraction is an important challenge for the safety of intelligent transportation systems. In this paper, a methodology for the detection and evaluation of driver distraction while performing secondary tasks is described and an appropriate hardware and a software environment is offered and studied. The system includes a model of normal driving, a subsystem for measuring the errors from the secondary tasks, and a module for total distraction evaluation. A new machine learning algorithm defines driver performance in lane keeping and speed maintenance on a specific road segment. To recognize the errors, a method is proposed, which compares normal driving parameters with ones obtained while conducting a secondary task. To evaluate distraction, an effective fuzzy logic algorithm is used. To verify the proposed approach, a case study with driver-in-the-loop experiments was carried out, in which participants performed the secondary task, namely chatting on a cell phone. The results presented in this research confirm its capability to detect and to precisely measure a level of abnormal driver performance.

The paper separates positive academic activities from deliberate fraud and offers an educational framework aimed to avoid academic dishonesty in engineering education, to remove factors that induce tricks, and to mitigate cheating incidents. The roots of misconduct are studied and their unintentional types are displayed. The measures and methods are demonstrated designed to prevent negative sides of plagiarism using motivation of students to learn engineering disciplines with competent involvement of copying, cloning, and other effective tools fostering education. Application of the designed approach in the courses supported by both the online and the traditional classroom modules show that students' self-motivation in learning has been greatly promoted, and their practical proficiency has been significantly improved. The insights from this paper could be used by educators and learners to determine when it is pedagogically more effective to involve copying and cloning in instruction; by educational course managers - to adapt their systems; and by assessment tools developers - to provide better learning outcomes.

Steep improvement of an in-vehicle info- and entertainment systems has a positive impact on vehicle control, comfort, safety, etc. Nevertheless, it also leads to a multitasking load increase on the in-vehicle information system due to fundamental problems of driver distraction. In this paper, a method for detection and evaluation of driver distraction induced by the driver's secondary activity is developed. The methodology is based on the machine learning and computation intelligence algorithms blend, which includes a driver model, a driver distraction detector, and a fuzzy logic evaluator. Several data fitting algorithms efficient for nonlinear regression are designed and are compared on the accuracy of the driver performance prediction. The method is verified by the driver-in-the-loop experiment with thirty participants on an advanced vehicle simulator. Driver's interaction with the commercial in-vehicle information system is exploited as a secondary distractive task.

Driver distraction is a fundamental problem for human safety, because the number of traffic accidents due to distracted driving does not decrease. In this paper, an enhancement of previously proposed driver distraction detection and evaluation methodology is introduced. The method is composed of computational intelligence algorithms: a driver performance prediction algorithm with nearest neighbor regression and an intelligent fuzzy logic evaluation algorithm. Thanks to the improvement, an additional variable for driver performance prediction and an additional performance-based indicator were introduced. To verify the novelty, the series of thirty driver-in-the-loop experiments has been delivered on an industrial vehicle simulator. At this, an interaction with a vehicle on-board computer was exploited as a distractive activity. Finally, the enhanced method is compared to the previously described one.

Considering highest demands continually imposed on equipment indispensable for safe transportation, this paper focuses on on-board controllers for blended (electro-hydraulic) antilock braking systems of road electric vehicles. Recommendations are issued regarding an influence of air friction and road inclination on torque allocation between electric and hydraulic brakes and accurate accounting of the hybrid energy storage. Following the study of three types of controllers-PID, tabular, and fuzzy logic-the latter one was offered as the most efficient solution for equally fast and safe braking with maximal energy recovery on different roads, from dry to icy, without locking and skidding even in critical situations. Several parts of the system were explored in case studies ensuring their validity and accuracy.

The paper focuses on the smart fluid adjustment of the centrifugal pumping station. The goal of the study is to provide the pressure management at minimal consumed energy. To solve the problem, the sensorless prediction method is proposed. The multi-motor variable speed drive has been designed and analyzed. A research is supported by experiments on the ABB Ebara CDX 120/12 pumping station fed by five ACQ810 variable speed induction motor drives with direct torque control. The offered multi-motor model is implemented based on ABB programmable logical controller AC500 PM 571 connected to the drives via the Profibus.

This paper concentrates on the methodology-oriented components of remote laboratory arrangement in the field of electrical drive. An active learning approach proposed to support online experimentation on the servo-drives, step drives, and induction motor drives helps the students to employ novel online tools and devices, to face real-world situations, and to interact with peers in circumstances that require problem solving skills through close collaboration. The e-assessment system designed focuses on the skill priority and engages the learners in development such individual and collaborative traits like interdisciplinary context, pragmatic outcomes, and professional preferences for getting the most out of their learning.

The paper explores Web technology, specifically social networking, which supports students' activity to enhance acquisition of Electrical Engineering disciplines. The results of the three-year study of the institutional learning management system, the thematic-oriented site, and the social network are presented. It was found that management of the learning content that combines various Internet services provides a suitable technology for students, being the social leverage to share and generate knowledge and experience.