information technology

Model for Evaluating the Quality of Interface Prototyping

This article is devoted to the development and substantiation of a comprehensive model for evaluating the quality of interface prototyping in software systems. The relevance of the study is determined by the increasing complexity of modern interfaces and the need to make well-founded design decisions prior to the software implementation stage. The paper addresses the problem of formalizing the evaluation of prototype quality while accounting for the multidimensional nature of evaluation criteria and the significant proportion of subjective qualitative characteristics.

Data-Driven Detection of Wheel Imbalance Using Accelerometer Signals and Fuzzy Logic

This paper presents an experimental study of imbalance detection in a rotating bicycle wheel using vibration measurements from a tri-axial accelerometer. A laboratory test bench, in which a bicycle wheel equipped with an in-wheel motor has been mounted on a stand and instrumented with an accelerometer for real-time vibration monitoring, has been developed. Experiments have been conducted under balanced conditions and under controlled imbalance introduced by adding external mass to the wheel rim. Acceleration signals have been collected and analyzed in time and frequency domains.

Performance Evaluation of ESP-NOW for Low-Latency Indoor IoT Systems

This paper presents an experimental study of communication latency in ESP-NOW wireless networks under different indoor conditions. A testbed consisting of three ESP32 devices (one master and two slave nodes) has been developed to evaluate one-way transmission delays without the use of a Wi-Fi access point. The slave nodes generate periodic sensor traffic and transmit data simultaneously, creating controlled network load conditions. A software-based time synchronization mechanism based on a message-exchange protocol has been implemented to estimate one-way latency.

Information Technology for Toxicity Detection in Text

This paper addresses the challenge of automating toxic content detection within the Ukrainian segment of the Internet, a critical task given the scarcity of specialized linguistic resources for this language. The study focuses on developing and evaluating an information technology framework capable of effectively classifying toxic messages using foundational machine learning algorithms. For the experimental phase, a dataset comprising 4,600 records was compiled by aggregating data from YouTube and Google Play with existing open-source datasets.

Virtual Museum and the Phenomenon of Digital Heritage: Challenges of the 21st Century

The paper presents an analysis of the use of digital technology in the museum industry, the introduction of the term “museum computing” by museum specialists and the emergence of a new phenomenon – the phenomenon of a virtual museum, as a museum that uses up-to-date information and communication technology for the presentation of museum collections. It has been stated that a virtual museum can be interpreted as “an integrated cognitive system, i.e.

EXPERIMENTAL RESEARCH ON APPROACHES TO GENERATING TEST SELECTORS USING GNN IN THE PROCESS OF AUTOMATED TESTING OF WEB APPLICATIONS

The article discusses the problem of instability of test selectors in the process of automated testing of web applications. It raises the issue of selectors’ adaptability to changes in the DOM structure, which is critically important in the development of modern dynamic web interfaces. A comparative analysis of three approaches to selector generation is conducted: manual (via Chrome DevTools), semi-automated (using DevTools), and automated using graph neural networks (GNN).

Information Technology for Text Classification Tasks Using Large Language Models

The article addresses the problem of text classification in the context of growing information flows and the need for automated content analysis. A universal information technology is proposed, combining classical machine learning methods with the potential of Large Language Models for processing news, scientific, literary, journalistic and legal texts. Using the BBC News corpus (2225 texts), k-means clustering with TF-IDF demonstrated clear thematic grouping.

Machine Learning Methods for Classification of Electrocardiographic Signals Based on Rhythmic and Morphological Features

The article presents an experimental study of the effectiveness of machine learning methods for classifying electrocardiographic signals by rhythmic and morphological features using information tech- nology based on the mathematical apparatus of cyclic random processes. The problem of automated detection of atrial arrhythmias is considered, particularly atrial fibrillation and atrial flutter, which are characterized by complex changes in both ECG wave morphology and cardiac cycle time intervals.

Development of the Information Society: Legal Implications and Challenges for Public Administration

The article considers the phenomenon of information society and its impact on the development of the public administration system. The author analyzes the role of information and communication technologies (ICT) in the transformation of social relations and legal regulation, and identifies the key challenges arising from digitalization. Particular attention is paid to the issues of information and digital human rights that arise in the context of ICT integration into all spheres of public life.

The Impact оf Artificial Intelligence оn Human Rights and General Recommendations for Sustainable Implementation

The relevance of the topic is due to the development of artificial intelligence (AI), one of the most important technological trends of our time, which has a significant impact on human rights and various aspects of human life. AI is developing extremely fast. This creates new challenges for human rights that need to be addressed immediately. It is important to understand how technology can change our society and what measures should be taken to protect human rights.