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The T1DCoach mobile application is designed to educate patients—children with type 1 diabetes (T1D) and their caregivers and diabetes educators. The idea behind the mobile application is that its users perform actions that the patient needs to perform in real life. These include measuring blood glucose levels, operating the insulin pump, meal calculation, bolus administration, etc. These in-application activities are performed on the patient's digital twin. To increase user engagement, gamification elements have been implemented in the application. An important element of the T1DCoach mobile application is its interface, which should be adapted to very different groups of users: children, their caregivers and educators. In addition to presenting the T1DCoach application, the paper presents the stage examining the quality of the interface using three research groups: children, their caregivers and educators. The research was conducted using the scenario method, using eye-tracking, recording activities and thinking aloud. After the application testing sessions, surveys were carried out using the System Usability Scale method and focus group interviews were conducted. The research results are presented in the article along with the most important recommendations for improving the application interface. [ABSTRACT FROM AUTHOR]

This paper describes a method and technology for processing natural language texts and extracting data from the text that correspond to the semantics of an ontological model. The proposed method is distinguished by the use of a Large Language Model algorithm for text analysis. The extracted data are stored in an intermediate format, after which individuals and properties that reflect the specified semantics are programmatically created in the ontology. The proposed technology is implemented using the example of an ontological model that describes the geographical configuration and administrative–territorial division of Kazakhstan. The proposed method and technology can be applied in any subject areas for which ontological models have been developed. The results of the study can significantly improve the efficiency of using knowledge bases based on semantic networks by converting texts in natural languages into semantically linked data. [ABSTRACT FROM AUTHOR]

At present, the following IT technologies are mainly used to obtain data on historical heritage cultural objects [[1]]: (a) Photogrammetry; (b) Scanning using structured light; (c) Laser scanning. Elements of cultural heritage preservation and popularization are defined in the Convention Concerning the Protection of the World Cultural and Natural Heritage, which came into force in 1975 and obliges United Nations Educational, Scientific and Cultural Organization (UNESCO) member states to protect cultural and natural heritage [[1]]. Techniques for documenting the appearance of cultural heritage objects are currently being rapidly developed thanks to information technology (IT). [Extracted from the article]

Air quality is of great importance for human health and life expectancy. It becomes crucial to monitor atmospheric dust in the air of cities. In connection with the development of mobile networks and low-cost sensory agents, it has become possible to create inexpensive environmental monitoring systems. The paper presents results of studies on the system monitoring dust concentration in city air. The system consists of moving IoT agents placed on vehicles (taxies, busses, private cars) and measure the dust concentration. Agents, using a wireless connection, are sending the data to the recording server. The server application collects the data and visualises them on the map in a certain colour, depending on the dust concentration in the air and the values acceptable by standards. The system architecture, the algorithm of measurements and the agent-server data exchange protocol were presented in the article, as well as the example of data visualisation.