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Empowering Community-Based Heritage through Gaming : A Developer’s Perspective
(2026-06-01) Del Giudice, Nicola; Department of Computer Science
While the use of games to foster the preservation of cultural heritage seems to be an effective solution, we lack a discussion on how it can promote community-based heritage. This article introduces the topic from the point of view of software and game developers.
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Exploring actions, interactions and challenges in software modelling tasks : an empirical investigation with students
(2026-07) Chakraborty, Shalini; Troya, Javier; Burgueño, Lola; Liebel, Grischa; Department of Computer Science
Background: Software modelling is a creative yet challenging task. Modellers often find themselves lost in the process, from understanding the modelling problem to solving it with proper modelling strategies and modelling tools. Students learning modelling often get overwhelmed with the notations and tools. To teach students systematic modelling, we must investigate students’ practical modelling knowledge and the challenges they face while modelling. Aim: We aim to explore students’ modelling knowledge and modelling actions. Further, we want to investigate students’ challenges while solving a modelling task on specific modelling tools. Method: We conducted an empirical study by observing 16 pairs of students from two universities and countries solving modelling tasks for one hour. Results: We find distinct patterns of modelling of class and sequence diagrams based on individual modelling styles, the tools’ interface and modelling knowledge. We observed how modelling tools influence students’ modelling styles and how they can be used to foster students’ confidence and creativity. Based on these observations, we developed a set of guidelines aimed at enhancing modelling education and helping students acquire practical modelling skills. Conclusions: The guidance for modelling in education needs to be structured and systematic. Our findings reveal that different modelling styles exist, which should be properly studied. It is essential to nurture the creative aspect of a modeller, particularly while they are still students. Therefore, selecting the right tool is important, and students should understand how a tool can influence their modelling style.
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Electrochemical Production of Silicon Using an Oxygen-Evolving SnO2 Anode in Molten CaCl2-NaCl
(2025-12) Padamata, Sai Krishna; Haarberg, Geir Martin; Saevarsdottir, Gudrun; Department of Engineering
The electrochemical production of silicon from SiO2 in molten salts can reduce energy consumption and mitigate carbon emissions associated with the conventional carbothermic process. In this study, we compare the anodic behaviour of platinum, graphite, and tin oxide electrodes in molten CaCl2-NaCl-CaO-SiO2 at 850 °C using electrochemical methods including cyclic voltammetry, linear sweep voltammetry, and chronoamperometry. Pt exhibited low oxygen evolution overpotentials and no significant currents before OER, compared to SnO2. An eight-hour potentiostatic electrolysis with a SnO2 anode and a graphite cathode yielded a Si-Sn deposit, indicating partial dissolution of the SnO2 anode during the electrolysis process. These results highlight the kinetic trade-off of SnO2 relative to Pt, and the risk of Sn contamination with extended electrolysis times. While SnO2 is unsuitable for production of high-purity Si, it remains a promising anode candidate for Si-Sn alloy formation.
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Assessment of defectsin mountain roadway tunnel due to various natural and operational factors – Istiqlol (Republic of Tajikistan)
(2018) Teshaev, Umardzhon R.; Padamata, Sai Krishna; Vokhmin, Sergey A.; Trebush, Yuri P.; Khasanov, Nurali M.; Department of Engineering
The present article analyses the defects in a mountain roadway tunnel (Istiqlol) recorded between 2013 and 2017. The defect analysis of the mountain tunnel is vital as it deals with the safety of the passengers using the tunnel. The factors causing the deterioration of tunnel is discussed in this present work. Deterioration of the tunnel lining is due to continuous maintenance of the tunnel is the biggest threat to the durability of the tunnel. Infiltration of groundwater through seismic (deformation) seams, cracks through the tunnel lining have a special role in deteriorating the state of the tunnel construction, which leads to minor surface corrosion to major ones. The defects in the tunnel were noted personally in a regular basis between the years 2013 and 2017. Defects were categorized into 6 different types with respect to their nature. Probability plots were plotted with help of MINITAB software to analyse the probability at which a particular value of Technical condition severity occurs. The final observations states the main reason for the defects in the tunnel.
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A comparative analysis of unsupervised machine-learning methods in PSG-related phenotyping
(2025-06) Ghorvei, Mohammadreza; Karhu, Tuomas; Hietakoste, Salla; Ferreira-Santos, Daniela; Hrubos-Strøm, Harald; Islind, Anna Sigridur; Biedebach, Luka; Nikkonen, Sami; Leppänen, Timo; Rusanen, Matias; Department of Computer Science; Department of Engineering
Obstructive sleep apnea is a heterogeneous sleep disorder with varying phenotypes. Several studies have already performed cluster analyses to discover various obstructive sleep apnea phenotypic clusters. However, the selection of the clustering method might affect the outputs. Consequently, it is unclear whether similar obstructive sleep apnea clusters can be reproduced using different clustering methods. In this study, we applied four well-known clustering methods: Agglomerative Hierarchical Clustering; K-means; Fuzzy C-means; and Gaussian Mixture Model to a population of 865 suspected obstructive sleep apnea patients. By creating five clusters with each method, we examined the effect of clustering methods on forming obstructive sleep apnea clusters and the differences in their physiological characteristics. We utilized a visualization technique to indicate the cluster formations, Cohen's kappa statistics to find the similarity and agreement between clustering methods, and performance evaluation to compare the clustering performance. As a result, two out of five clusters were distinctly different with all four methods, while three other clusters exhibited overlapping features across all methods. In terms of agreement, Fuzzy C-means and K-means had the strongest (κ = 0.87), and Agglomerative hierarchical clustering and Gaussian Mixture Model had the weakest agreement (κ = 0.51) between each other. The K-means showed the best clustering performance, followed by the Fuzzy C-means in most evaluation criteria. Moreover, Fuzzy C-means showed the greatest potential in handling overlapping clusters compared with other methods. In conclusion, we revealed a direct impact of clustering method selection on the formation and physiological characteristics of obstructive sleep apnea clusters. In addition, we highlighted the capability of soft clustering methods, particularly Fuzzy C-means, in the application of obstructive sleep apnea phenotyping.

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