Published: 24.08.2022

Software Framework for Implementing User Interface Interaction in IOS Applications Based on Oculography

Nikita Stanislavovich Afanasev
198-245
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.

Developing Technological Cycle of Search System that Agregates Citations by Books

Roman Valerievich Mosolov
246-256
Abstract:

In this article, we have described the technological cycle to develop the search system by 14 philosophical books by L.A. Seklitova, and L.L. Strelnikova. The cycle contained 6 steps of work. The ideas from the article may be useful to project, and develop a software, aggregating citations from books series, monographs, scientific periodicals, or scientific articles. For example, this experience may be useful for creating customized links on secondary sources that needs at a stage of writing scientific articles and design of presentations in Pedagogy. The search system is the result of 1 year work by the article author, and the group of around 30 volunteers. The system is represented a service, integrating in the web application. The technological stack contains Jade, CSS, JS, Node.js, Express.js, ESLint, Jest.

Recommendation System for Selection of Players in Team Sports Built on the Basis of Machine Learning

Rinat Rustemovich Shigapov, Alexander Andreevich Ferenets
257-280
Abstract:

This article describes the development of a recommender system for selecting players based on machine learning. The system introduced the example of hockey with the possibility of expanding its use in various team sports. For each sport different roles and characteristics of the players were considered. The article analyzes information about hockey, football, basketball and volleyball. The characteristics of the players are structured and divided into general groups. For each parameter coefficients are displayed that show the impact on the result of the match. Various machine learning algorithms were used to build the model. The web interface of the application has been created.