C.56.> Perceptions on web supported workplace learning of electronic engineering students: A nonparametric statistical assessment

Summarization: Workplace learning (WPL) of tertiary education students provides an important link by connecting real life working environments with Higher Educational Institutions (HEIs). As it concerns the case of engineering students, various scientific, technical and soft skills should be acquired during their WPL period, in order to achieve an effective overall engineering education. The focus of this paper is on the perceptions of all parties involved (students, workplace supervisor, academic supervisor) with the WPL at the Department of Electronic Engineering-Technological Educational Institute of Crete (DoEE/TEIoC). In particular, based on quantitative data collected at the end of the WPL period of DoEE/TEIoC students, a nonparametric statistical analysis is carried out. The data were extracted from questionnaires (sample size=91) completed by each student and their corresponding workplace and academic supervisors. Our aim is to compare the perception of the aforementioned three respondent groups in terms of students’ competences and other WPL-related issues. Evaluation results of our research can provide an insight towards the achievement of an effective WPL for DoEE/TEIoC students.Παρουσιάστηκε στο: 8th International Conference “New Horizons in Industry, Business and Education

Telecommunication circuits design and development using FPGA technology

Summarization: The wide application of FPGA chips becomes a trend in telecommunications and wireless communications era. FPGAs have been deployed in numerous fields of electronics engineering. Thus, the adoption of FPGAs in telecommunications curriculum it is necessity. This paper emphasizes on a collaborative approach to teach undergraduate state of the art telecommunications and wireless communications in the Broadband Communications & ElectroMagnetic Applications (BCEMA) Laboratory of the Department of Electronic Engineering (DoEE) of the Technological Educational Institute of Crete (TEIoC).Παρουσιάστηκε στο: 8th International Conference “New Horizons in Industry, Business and Educatio

Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge

Sewage sludge hydrochars (SSHs), which are produced by hydrothermal carbonization (HTC), offer a high calorific value to be applied as a biofuel. However, HTC is a complex processand the properties of the resulting product depend heavily on the process conditions and feedstock composition. In this work, we have applied artificial neural networks (ANNs) to contribute to the production of tailored SSHs for a specific application and with optimum properties. We collected data from the published literature covering the years 2014–2021, which was then fed into different ANN models where the input data (HTC temperature, process time, and the elemental content of hydrochars) were used to predict output parameters (higher heating value, (HHV) and solid yield (%)). The proposed ANN models were successful in accurately predicting both HHV and contents of C and H. While the model NN1 (based on C, H, O content) exhibited HHV predicting performance with R2 = 0.974, another model, NN2, was also able to predict HHV with R2 = 0.936 using only C and H as input. Moreover, the inverse model of NN3 (based on H, O content, and HHV) could predict C content with an R2 of 0.939