1. Dataset of Uzbek verbs with formation and suffixesMaksud Sharipov, Jernej Vičič, 2025, other scientific articles Abstract: The main goal of this work is to create a dataset of Uzbek language verbs. This dataset stores information about which words verbs are derived from and with which affixes. The affixes are classified into distinct categories. With the help of this dataset, it is possible to determine from which parts of speech each Uzbek verb is derived and with which affixes. It also plays a key role in identifying verbs in Uzbek language texts and developing rule-based models for their analysis. Additionally, this dataset plays a key role in building various artificial intelligence models for the morphological and syntactic analysis of Uzbek language texts. Verbs play a crucial role in learning any language; therefore, students in schools and higher education institutions can also use this dataset during the learning process. The obtained dataset serves as a valuable resource for researchers and practitioners interested in Uzbek language processing tasks.
Keywords: verb phrase, Uzbek language, Uzbek web corpus, verb form, verb affixes
Published in RUP: 02.06.2025; Views: 111; Downloads: 8
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2. Occupancy estimation using indoor air quality data : opportunities and privacy implicationsDomen Vake, Niki Hrovatin, Jernej Vičič, Aleksandar Tošić, 2025, original scientific article Abstract: Indoor Air Quality (IAQ) has long been a significant concern due to its health-related risks and potential benefits. Readily available air quality sensors are now affordable and have been installed in many buildings with public buildings taking center stage. The dynamics of IAQ are commonly studied in relation to different materials used in construction, building design, room utility and effects on occupants. However, besides what the sensors were designed to measure, it is possible to infer other information. In this paper, we present a Machine Learning (ML) model that predicts the presence of people in the room with an accuracy as high as 93 % and the exact number of occupants with 2.17 MAE. We validate our proposed approach in the use-case of an elementary school in Slovenia. In collaboration with the elementary school in Ajdovščina, 8 air quality sensors were placed in classrooms and air quality parameters (VOC, CO, Temperature, and Humidity) were monitored for 6 months. During the monitoring period, school staff collected anonymous data about classroom occupancy. The indoor air quality data was paired with external weather data as well as occupancy to train the model. Moreover, we compare our approach with other commonly used ML approaches and provide results related to our use case. Finally, these results highlight the privacy concerns related to structural monitoring due to the established ability to infer potentially sensitive information.
Keywords: indoor air quality, occupancy estimation, machine learning, sensor networks, privacy, building monitoring
Published in RUP: 02.06.2025; Views: 149; Downloads: 7
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5. Upravljanje različnosti in poučevanje/učenje italijanskega jezika kot manjšinskega jezika : predlog učnega gradiva za soočanje z novimi izzivi kompleksnih družbMetka Malčič, 2024, doctoral dissertation Keywords: lingua italiana L2, italiano, Litorale sloveno, insegnamento/apprendimento dell'italiano, dimensioni della diversità, educazione alla diversità, nuove tecnologie, materiale didattico, piattaforma, tesi di dottorato
Published in RUP: 24.05.2024; Views: 1618; Downloads: 20
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