Volume 14, Nº 3 (2024)

The problem of achieving completeness and unity of objective, subjective, and virtual reality is considered in relation to the applied tasks of designing interactive user interfaces. Within the framework of constructing an immersive environment using modern information technologies, the problem of forming an ontology of perception is investigated. The key role of a sign in information interaction is highlighted, taking into account the individual characteristics of its perception by users of virtual reality. In an immersive environment, virtual signs can be embodied both as observable objects with varying degrees of realism and directly in the form of signs, both graphic and text, that have a specific location in space. The proposed approach allows for setting an algorithm for visual impact on a person by dynamically forming a sequence of signs. The formed sequences create a queue of visual stimuli that adjust the tempo-rhythm of the user's interaction with the computer system. The signs observed by the user can be classified as iconic signs corresponding to conventional symbols or pictograms, index signs acting as pointers to other objects and marking space for orientation purposes, and symbolic signs signaling or warning about changes in an object, event, or phenomenon. The article considers test examples of user behavior in a virtual reality environment. The proposed approach is implemented in a software system for psychological diagnostics and rehabilitation. A special feature of the system is the control of patient involvement based on the analysis of the dynamics of head movements, facial movements, and gaze trajectory using artificial neural networks. In case of distraction or loss of interest, the computer system adapts the user interface by adding visual stimuli according to specified pragmatic rules. The application of the obtained results has enabled the adaptation of the user interface and created the possibility for a personalized approach to the provision of medical services.

Cognitive challenges in mastering graphic disciplines are attributed to the introduction of computer technologies. Graphics departments are reorienting the educational process towards teaching modern methods of computer 3D modeling. Opinions have been expressed about the secondary nature or even the rejection of drawings. This article proposes viewing drawings as a type of text. As a justification for the "linguistic turn", the unique role of natural language as a means of updating and disseminating knowledge is noted. The similarity of the main properties of drawings with those of texts is traced. These properties include the discreteness of text elements, conventionality, parametric style of describing objects, conceptuality, hierarchical structuring, and contextuality of perception. It is argued that the determining factor for the feasibility of drawings is not the geometric accuracy of images, but linguistic accuracy, which allows one to "understand" the drawing and establish a connection between the contents of the drawing and the technologies of producing an object or its computer model. The exceptional role of drawings as the language of technology is substantiated, and the possibility of replacing drawings with 3D modeling is rejected. The view of project documentation as an integral part of a single pyramid of knowledge is established. The role of the concept of computable knowledge in the effective use of knowledge is emphasized. A list of questions that can be included in the content of teaching the "language of technology" is provided.

To automate the workflow of a pharmacy, an information system based on a pharmaceutical ontology is proposed. The entities in the developed ontology include drugs, symptoms, and diseases. Instructions for medicines, drugs and their analogues are used as sources to describe relationships between entities. The main properties of each drug are described by its characteristics: name, expiration date, pharmacological group, storage location, dispensing form, manufacturer, price, etc. Key features of the designed information system include the ability to search for medicines and drugs available in the pharmacy and included in the ontology by symptom or disease, and restricting the sale of medicines that have contraindications for the buyer. The functioning of most modules of the information system is carried out using an ontology inference engine. For each specific process, an automatic check of the consistency of restrictions in the ontology is performed, taking into account the specifics of storage, dispensing, and sale of pharmaceuticals. A distinctive feature of the developed information system is its capability to perform semantic searches on pharmaceutical ontology objects.

The article describes the TurkLang model of the linguistic knowledge graph for Turkic languages, which underpins software products for processing these languages. The model’s core elements are morphemes, the smallest meaningful units of language. It captures the properties of morphemes across morphonological, morphological, syntactic, and semantic levels. This model is particularly well-suited to the structural and functional characteristics of Turkic languages, which are agglutinative, offering a comprehensive and pragmatically oriented description of their capabilities and textual manifestations. The model's properties are applied in semantic text processing software, including the "Turkic Morpheme" linguistic portal and the updated Tatar language electronic corpus "Tugan Tel." The unified TurkLang model ensures full compatibility across software products for Turkic languages and standardizes the concepts and terms used in linguistic research. This is important for Turkic languages, as many existing models are based on languages with different structures (like English or Russian) and fail to fully address the communicative, cognitive, and lexical-grammatical features of Turkic languages.

The research focuses on developing cluster analysis methods, specifically clustering methods with partial teacher involvement, where background knowledge from the subject area is used when assigning objects to classes. The traditional approach to this problem involves modifying existing clustering methods, most of which are local search methods. The article proposes a systematic approach to searching for optimal partitions within the constraint programming paradigm. The originality of this research lies in solving the clustering problem as a constraint satisfaction problem, utilizing specialized table constraints, known as D-type smart tables, to model basic and additional conditions. Table constraint reduction rules are employed to organize logical inference procedures on D-type smart tables. The advantages of this approach are discussed, demonstrating how analyzing one of the optimal solutions can help identify objects on the boundary of clusters and those belonging to the same cluster for any optimal partition.

In the process of human-machine collaboration, recurring problems often arise, prompting the use of collaboration patterns that offer ready-made solution schemes for similar recurring issues. The aim of the research is to develop models that facilitate the organization of human-machine collaboration while supporting decision-making based on collaboration patterns. The paper employs methods of conceptual, ontological, and scenario modeling. Based on the descriptions of collaboration patterns found in various problem areas, conceptual models were constructed representing five types of patterns: organizational patterns, cognitive patterns, information interaction patterns, process patterns, and joint engineering patterns. An ontological model of a collaboration pattern and an ontology of human-machine collaboration patterns were developed, integrating various types of such patterns. The developed models represent a new result that unifies existing approaches to the description of collaboration patterns. A scenario variant is proposed, demonstrating the possibility of using the developed ontology to support decision-making. The developed models for organizing human-machine teams and their activities can enhance the quality of decisions by using solution patterns for similar problems and ensuring effective cooperation between humans and machines.