Abstract:

Usage of gaze tracking technologies for the purpose of user interface interaction in iOS applications is significantly hampered by the absence of a unified approach to their integration. Current solutions are either strictly limited to their own use-case or made solely for research purposes and thus inapplicable to real-world problems. The focus of this article is the development of a software framework that performs gaze tracking using native technologies and suggests a unified approach to the development of gaze-driven iOS applications.

Abstract:

By the radiosounding of the ionosphere with short-wave signals, can be obtained information about the processes in the ionospheric plasma, about its structure and state; these data are also extremely important for radio engineering systems operating in the short-wave range. To date, a large amount of experimental data has been accumulated for various geo- and heliophysical, spatial and temporal conditions. The interest in large amounts of ionospheric radiosonde data is also motivated by the possibility of constructing statistical models using machine learning theory methods. The paper presents some Internet resources with ionospheric radiosonde data, shows the prospects for their application, and also identifies some problems, such as insufficient documentation of some data formats and the presentation of ionograms only in the form of raster images, most of which are also scanned from photographic films.

Abstract:

The paper considers a method for classifying unmanned aerial vehicles (UAVs) and birds based on radar measurements in various object movement scenarios. The relevance of the problem is explained by the complexity of UAV detection due to its small overall dimensions, high agility, and similar geometry to a bird. To solve the problem, a classification method based on the analysis of micro-Doppler signatures, which reflect the dynamics of object motion, is applied. The scenarios are modelled in the Engee environment, where models of radar system, UAV and birds are developed.

Abstract:

The experience of game studios shows that classical methodologies of software development are poorly implemented in video game development because of the interactive component of this area, related to the correct creation of feedback between the game and the user. In addition, video game development involves a large number of developers from different areas, whose activities must be coordinated in the project.

Despite these differences, video games, like any other developed software, need a development team organization process. In this article we reviewed traditional software development methodologies, as well as modifications specializing specifically in video game development. The most popular methodologies were compared and the quality of their implementation in video game development studios was determined.

Abstract:

The idea of using the available large arrays of ionogram processing results from vertical radiosonde of the ionosphere as training datasets for building predictive models using machine learning methods is put forward. The most common formats for saving the results of ionogram processing are considered, as well as some Internet resources with archives of freely available files of these formats. These datasets are used by us to build predictive models, including time series of critical frequencies of ionospheric layers. It is also possible to use some datasets of ionogram processing results to train models designed for automatic ionogram processing.

Abstract: Implementation of augmented reality session synchronization algorithm in mobile iOS applications. Algorithm allows to create augmented reality sessions with several participants for their joint interaction with the same virtual objects.

Abstract:

An approach for designing Microlearning Applications is presented. The dependency of reliability of knowledge evaluation from visual representation of testing questions. And architecture of system and working principle of developed instrument for designing adaptive tests and testing scenarios is shown.

Abstract:

The paper proposes software mechanisms aimed at enhancing video production processes for the authors of artistic video materials. We propose a mechanism for creating animated three-dimensional shooting plans (storyboards) using augmented reality to position and animate the movement of actors. In order to overcome the limitations of the iOS operating system related to access to sensors, we developed a mechanism for separately capturing audio and video streams from device sensors for recording and their subsequent synchronization by timestamps for saving to device memory. Computer vision technologies are used to ensure compliance with the rules of compositional construction and image quality analysis. The paper also presents mechanisms for working with the script, including text processing algorithms for displaying subtitles on the screen, and speech recognition algorithms for comparing speech recognition of actors with the text of the script.

Abstract: Currently, the need for distributed ML training solutions in the world is increasing. However, existing tools, in particular TensorFlow Federated, are at the very beginning of their development, difficult to implement, and currently suitable exclusively for simulation on servers. For mobile devices, reliable approaches for this purpose do not exist. This article has designed and presented an approach to such distributed training of the ML-model on mobile devices, implemented on existing technologies. It is based on the concept of model personalization. In this approach, this concept is improved as a consequence of mitigating the identified drawbacks. The implementation process is structured so that at all stages of working with the ML-model use only one Swift programming language (Swift for TensorFlow and Core ML 3 are used), making this approach even more convenient and reliable due to the common code base.

Abstract:

The advantages of simulation training in clinical skills training are shown. Examples of simulators for building an optimal development process are reviewed. A way of transferring invasive surgery practices to the virtual operating room is presented.

As a logical development of functionality, approaches are presented that will be able to emulate all the practices that take place during real operations, including multiplayer mode, variability in surgery scenarios, achieving mastery of manual techniques, and the need to introduce incidents that initiate psychological burnout of future surgeons and a conscious choice of specialization.

Abstract:

The article discusses various solutions that exist in the field of remote control of robotic devices equipped with manipulators. New approaches are presented for organizing joint telecontrol of multiple manipulators using various user inputs. The following usage scenarios are considered: the architecture of a system with many manipulators and user control interfaces, including such promising areas as deep machine learning and neural interfaces.

Abstract: The article discusses the recursive ratios implementation in solving mathematical problems using instrumental software resources. It is emphasized that programs development for solving such problems contributes to a deeper understanding of the recursion process essence.

Abstract: Mass identification of a list of radio sources with the sky surveys of different ranges of the electromagnetic spectrum has undoubted interest to astronomers. Identification of the radio sources is not a straightforward procedure because of the different angular resolution, sensitivity limit, coordinate precision  of the radio catalogues, as well as due to the morphological structure of radio sources themselves.

Abstract:

The problem of high and increasing cost of video game development is considered, and to solve it is proposed to apply procedural content generation, which will reduce development costs.

The work is a part of a large-scale research on automatic prototyping of video games and is devoted to the processing of game scenarios, i.e. natural language texts. It is proposed to extract the necessary entities from the scripts and pass them to further steps of the algorithm, which will generate game resources based on the textual descriptions.

There are several publications devoted to game text processing, in which several different structures for storing the extracted information are proposed. In this paper we propose a universal format that is suitable for processing the text of any video game and allows to create a corpus of texts for use in further research and automatic generation of game prototypes.

Abstract: Today the Virtual Observatory tools provide easy access to astronomical data and improve the efficiency of researches. Based on the existing web technologies the astronomical community is developing on realization greater data semantic connectivity. This will put the virtual observatory services to a new level of exchange of not only data but also knowledge. However, there is no development of tools for actualization information collected from web resource, and a means of organizing heterogeneous data prepared by the user for scientific analysis, which could improve further work. We consider the approach to organization of diverse information for a studying object, based on the development of the existing formats of astronomical data and tools to support semantic data connectivity.

Abstract:

The study addresses the problem of integrating cognitive and mathematical modeling in research on the development directions of the fuel and energy complex, taking into account energy security requirements. The relevance of the work is due to the fact that in the existing two-level research methodology, the transition from the results of qualitative analysis using cognitive modeling to the parameters of the mathematical model is largely performed manually, which reduces the reproducibility of numerical experiments and limits the efficiency of accumulated knowledge usage. The aim of the work is to develop a software component that ensures the combined use of cognitive and mathematical models within an Energy Knowledge Ecosystem. A software component is proposed, implemented as part of the INTEC‑SAW suite, which provides the transformation of changes in the cognitive model into the parameters of the economic-mathematical model, as well as the reverse interpretation of calculation results. Technology for conducting numerical experiments has been developed, including the construction of semantic (ontological and cognitive) models, formation of computational scenarios, execution of optimization calculations, and presentation of results, distinguished by the automation of the joint use of ontological, cognitive, and economic-mathematical models. To account for uncertainty, a numerical method of stochastic parameter adjustment based on cognitive weights is proposed. The effectiveness of the approach is demonstrated through a numerical experiment investigating the impact of CO₂ emission constraints on the energy balances of the Siberian Federal District. The practical significance of the work lies in increasing the validity and reproducibility of research on the development of the fuel and energy complex through the coordinated use of qualitative and quantitative analysis tools.

Abstract: The article describes the experience of usage of new mobile map platform «CarryMap» in preparation for the detailed geostructural mapping and geochemical study of the Olon-Obod gold ore cluster (Southern Mongolia). The authors accumulated all types of geological information into a single ArcGIS project. The project contains raster maps, vector maps, and digital geological information. We converted this project in CMF2 and placed on mobile iOS & Android devices.

Abstract:

The article deals with the problems of organizing programming practice for schoolchildren aged 13–17, as well as the problems of their motivation. A methodology and a software platform are proposed that provide such students with a workshop on algorithmization and programming by implementing algorithms written in various programming languages on this competition platform.

Abstract:

The article presents an approach to the development of an intelligent multimodal monitoring service for the surveillance area using large neural network models. The proposed solution is capable of analyzing heterogeneous data – video streams, environmental sensor signals (temperature, humidity, etc.), and event logs – to obtain a complete picture of what is happening. The main tools used are large language and visual models (for example, LLaMA, MiniCPM‑V, etc.) deployed locally using the Ollama platform, which provides autonomous and secure information processing without the need to transfer data to the cloud. A prototype system has been developed that works offline and is capable of detecting critical situations, abnormal deviations from the norm and contextually significant events in the observed area. The method of forming test scenarios and conducting a qualitative assessment of the model's performance using the metrics F1-measure, Precision, Recall on a set of various situations is described. The experimental results confirm the applicability of multimodal models for monitoring tasks: the prototype successfully recognizes complex patterns of behavior and demonstrates the potential of large models in building adaptive and scalable surveillance systems.

Abstract:

The paper presents the implementation of a visual script editor that allows you to design a series of experiments for virtual educational laboratories. The connection of the above approach with the possibility of explicit control over students' involvement and methods of its evaluation is described.