{"title":"Calculation of Rod Elements with Cracks Based on a Combination of Rod Theory and Elasticity Theory","authors":"M. N. Serazutdinov","doi":"10.3103/S0005105526700226","DOIUrl":"10.3103/S0005105526700226","url":null,"abstract":"<p>Mathematical models are presented for calculating the stress-strain state of rods with cracks under tension-compression and bending deformations. The work uses a combination of the relations of elasticity theory and rod theory. The main provisions of the proposed modeling method are based on dividing the rod into fragments and finding, for each of the selected fragments, deformations and stresses based on rod theory or elasticity theory. Calculation algorithms are described, which are relatively simple to implement. In order to confirm the reliability and accuracy of calculations based on the proposed models, results from solving problems are presented.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 1","pages":"S125 - S132"},"PeriodicalIF":0.5,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148193797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Web-Systems on Graph-Theoretic Models and Methods in Programming","authors":"V. N. Kasyanov, E. V. Kasyanova","doi":"10.3103/S0005105526700123","DOIUrl":"10.3103/S0005105526700123","url":null,"abstract":"<p>Graph theory is increasingly urning from an academic discipline into a tool, mastery of which is becoming decisive for the successful use of computers in many applied areas. Despite the existence of extensive specialized literature on solving problems on graphs, the widespread use of the obtained mathematical results in programming practice is difficult due to the lack of a systematic description of them oriented towards programmers. Therefore, a significant class of practical problems, essentially reduced to a simple choice of a suitable solution method and to the construction of specific formulations of abstract algorithms, for many programmers still remains a field for intellectual activity in the rediscovery of known methods. The paper is devoted to the digital wiki dictionary WikiGRAPP on graph theory and its applications in computer science and programming and the digital wiki encyclopedia WEGA of graph-theoretical algorithms for solving computer science and programming problems, being developed at the Ershov Institute of Informatics Systems SB RAS.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 1","pages":"S37 - S47"},"PeriodicalIF":0.5,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148193845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multitimeframe Drummond Patches and JEPA Pretraining for Short-Term Retail OHLC Series Forecasting","authors":"A. S. Sizov, Y. A. Khalin, A. A. Belykh","doi":"10.3103/S0005105526700238","DOIUrl":"10.3103/S0005105526700238","url":null,"abstract":"<p>We propose a method for constructing scale-invariant representations of retail revenue time series based on three-bar Drummond geometry (DG) computed over three adjacent periods, extended with a multitimeframe context (day, partial calendar week, and a rolling 7-day window). Self-supervised pretraining on these “patches” is performed using a joint-embedding predictive architecture (JEPA) with spatiotemporal masking, followed by fine-tuning with output heads that quantify predictive uncertainty for next-day and next-week forecasts. The work analyzes the properties of affine invariance of the features and the identifiability of the weekly phase; empirical improvement over strong baseline models on real-world data is demonstrated.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 1","pages":"S133 - S138"},"PeriodicalIF":0.5,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148193849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic Addition of SEO Metadata to News Articles Using Qwen-Coder","authors":"H. Salem, A. S. Toshchev","doi":"10.3103/S0005105526700202","DOIUrl":"10.3103/S0005105526700202","url":null,"abstract":"<p>A previously developed pipeline for enriching news articles with structured data is summarized, and an updated configuration is presented in which GPT-3–OpenAI’s third-generation natural language processing model is replaced with Qwen-Coder. As previously, the updated enrichment pipeline uses a dataset of 400 pages selected from Google News, a free news aggregator provided by Google, remains compatible with the Google Rich Results Test (Google’s tool for validating eligible structured results), and demonstrates that GPT-3-comparable output quality can be achieved on a low-power desktop PC. We describe how this substitution reduces dependence on paid GPT services and report an evaluation comparing the similarity of outputs produced by Qwen-Coder against the GPT-based baseline. The results also show the better performance of the new algorithm compared with the GPT version. The proposed tools lower the barrier to adopting semantic markup practices and thereby broaden their application in digital journalism. Overall, the findings support Qwen-Coder as a cost-effective alternative to large proprietary models for metadata enrichment tasks.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 1","pages":"S111 - S116"},"PeriodicalIF":0.5,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148193806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. P. Antonov, S. A. Afonin, A. C. Kozitsyn, V. M. Staroverov
{"title":"Method for Automatic Classification of Full-Text Descriptions of Cores Using Dictionaries","authors":"A. P. Antonov, S. A. Afonin, A. C. Kozitsyn, V. M. Staroverov","doi":"10.3103/S0005105526700081","DOIUrl":"10.3103/S0005105526700081","url":null,"abstract":"<p>The use of automatic text processing methods, including full-text description classification methods, helps significantly reduce labor costs of experimental data processing. This paper discusses the use of the automatic text classification method in processing and classifying elements of cores and determining lithofacies. Lithofacies are coeval geological bodies (deposits) that differ in composition or structure from adjacent layers. When assessing oil and gas field potential, it is necessary to construct maps and diagrams of lithofacies distribution. This requires classifying a large number of full-text descriptions of core sections pre-pared by specialists. The algorithm proposed here makes it possible, based on the specified rules and dictionaries, to conduct classification taking into account the order and significance of keywords in sentences. The advantages of this approach are the ability to distinguish between similar lithofacies, the ability to use archival data, ease of configuration for new classes, adaptation to Russian-language core descriptions, and the ability to be used locally without the need to send core descriptions to third-party applications.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 1","pages":"S1 - S6"},"PeriodicalIF":0.5,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148193770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Analysis of Syntactic Relations in Science Terms","authors":"A. A. Mastikhina, E. D. Shalyutina","doi":"10.3103/S000510552670007X","DOIUrl":"10.3103/S000510552670007X","url":null,"abstract":"<p>The paper examines the formalization of the process of extracting multicomponent terms from Russian-language scientific and technical texts. A predicative approach is used to extract terms, while a grammatical approach is currently more well-developed. We propose a predicate algebra and a system of axioms that make it possible to determine, using axiom statements, whether a sequence of words in a sentence constitutes a multicomponent term. Based on this, an algorithm for automatic term extraction has been developed. The algorithm checks the text for repetitions of a certain sequence of nouns and adjectives and participles, then uses the endings of the identified words and possible prepositions. The algorithm must determine whether each such sequence of words constitutes a term. Examples of the algorithm’s operation are analyzed, including those where terms are extracted, but, due to homonymy, the grammatical properties of individual words are ambiguously determined. Importantly, the algorithm does not use preliminary syntactic parsing of the sentence and is also specific to the Russian language and subject area. It is believed that this approach can be adapted to other contexts, such as a different subject area or a different language, by varying the axiom system. A combination with the syntactic analysis is also possible.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"110 - 117"},"PeriodicalIF":0.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148061027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. V. Kan, Alexander A. Khoroshilov, I. A. Chechulin, A. V. Rykalin, Aleksey A. Khoroshilov, D. E. Rozhkov
{"title":"Automation of the Development of a Set of Declarative Tools for a System of Semantic Analysis of Industry-Specific Scientific and Technical Documents","authors":"A. V. Kan, Alexander A. Khoroshilov, I. A. Chechulin, A. V. Rykalin, Aleksey A. Khoroshilov, D. E. Rozhkov","doi":"10.3103/S0005105526700251","DOIUrl":"10.3103/S0005105526700251","url":null,"abstract":"<p>The paper considers methods and technologies of automated development of declarative tools for the system of semantic analysis of scientific and technical documents by analyzing the lexical and conceptual-terminological composition of scientific and technical texts in the VINITI RAS databases. Using methods of phraseological conceptual text analysis (PCTA), statistical analysis of the lexical and conceptual-terminological composition of scientific and technical texts across a wide range of subject-areas, and the principle of linguistic analogy, statistical data on the frequency composition of industry-specific text corpora have been compiled. These data became the basis for the automated development of a set of declarative tools for morphological, conceptual, and semantic-syntactic analysis of polythematic texts. Based on statistical data from frequency dictionaries of word forms and standard word forms, the composition and scope of dictionaries that ensure maximum coverage of industry-specific text corpora have been identified. The algorithms for creating a set of industry-specific dictionaries are developed using the authors’ own tools which enable their construction with minimal effort. Based on research findings, industry-specific declarative tools have been developed for the morphological, conceptual, and semantic-syntactic analysis of polythematic texts. The results of the research and dictionary development will be used to automate key technological tasks at VINITI RAS, such as document classification, coordinate indexing, abstracting, and semantic search, as well as for future-oriented tasks involving the creation of industry-specific ontologies and knowledge bases.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"118 - 131"},"PeriodicalIF":0.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148060974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. A. Kobylkina, V. V. Marochkina, A. V. Glazkova, O. V. Zakharova
{"title":"Implementation of a Trendcarbon Web Service for Automated Monitoring of Scientific Publications on Carbon Research","authors":"A. A. Kobylkina, V. V. Marochkina, A. V. Glazkova, O. V. Zakharova","doi":"10.3103/S0005105526700263","DOIUrl":"10.3103/S0005105526700263","url":null,"abstract":"<p>The paper describes the TrendCarbon web service for the automated analysis and monitoring of scientific publications in the field of carbon research. It compares topic modeling methods (LDA, BERTopic) and evaluates the effectiveness of large language models (LLaMA 3, Mistral, YandexGPT-5 Lite, T-Lite) for the generation of interpretable topic labels. The service is implemented using a client–server architecture based on Elasticsearch, FastAPI, and React. Experimental evaluation on a corpus of Russian-language publications confirmed the effectiveness of TrendCarbon in identifying research trends and in supporting information analysis.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"132 - 140"},"PeriodicalIF":0.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148060975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of an Information System for Business Process Management in a Service Company Based on the SPA Approach","authors":"A. K. Kashima, M. I. Kolosov","doi":"10.3103/S0005105526700056","DOIUrl":"10.3103/S0005105526700056","url":null,"abstract":"<p>The paper addresses the problem of digitalization of operational activities of small and medium-sized service companies engaged in field technical maintenance. Existing CRM/ERP solutions were analyzed and the limitations of their application for dispatching field service operations were identified. The design and implementation of a specialized information system based on React and Flask are described. Interaction between the client and server components is organized through a REST API with data exchange in JSON format. SQLite was used at the prototyping stage, while PostgreSQL was selected for deployment. Data access is implemented using the SQLAlchemy ORM. The paper presents the role-based access model, key security modules, and the results of pilot operation. The developed system demonstrates improved efficiency in processing service requests and enhances operational transparency for service companies.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"75 - 87"},"PeriodicalIF":0.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148061064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling Optimization of Integration of Systems for Acquiring Scientific and Technical Documentation Archives within the CIS (Application for Databases and Corpora)","authors":"I. N. Sukhoruchkina","doi":"10.3103/S0005105526700287","DOIUrl":"10.3103/S0005105526700287","url":null,"abstract":"<p>This paper presents the application of modeling toolkits for optimizing the integration of national scientific and technical documentation archiving systems, assessing the value of document corpora, applying cognitive semantic classification, and defining the subject matter of scientific and technical documents within the CIS and for the Federal Abstract Database of the All-Russian Institute for Scientific and Technical Information of the Russian Academy of Sciences (VINITI Database of the RAS). Models are analyzed for improving the information support of integrating national scientific and technical documentation archiving systems and technology transfer based on interstate exchange and the international scientific and technical information network of the CIS countries within multilateral interstate CIS agreements and the Strategy for Scientific and Technological Development of the CIS for 2026—2035 in order to standardize and digitalize archival acquisition using artificial intelligence, preserve scientific and technological heritage, and provide access to R&D project archives.</p><p>scientific and technical documentation, archive acquisition, modeling of archive acquisition optimization, document value assessment, cognitive semantic classification of documents, definition of document subject matter, CIS, VINITI RAS, Federal Abstract Database of VINITI RAS, Strategy for Scientific and Technological Development of the CIS for 2026–2035, archive digitalization, archive standardization, technology transfer, use of artificial intelligence</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"100 - 109"},"PeriodicalIF":0.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148061026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}