V. A. Parkhomenko, X. A. Naidenova, T. A. Martirova, A. V. Schukin
{"title":"Experimental Study of Cognitive Function of Generating Elliptical Sentences in Planimetric Tasks","authors":"V. A. Parkhomenko, X. A. Naidenova, T. A. Martirova, A. V. Schukin","doi":"10.3103/S0005105525700190","DOIUrl":"10.3103/S0005105525700190","url":null,"abstract":"<p>The paper is devoted to the study of the cognitive function associated with the generation of elliptical sentences in the Russian language. The study is conducted by testing this cognitive ability using a computer system specially developed by the authors for this purpose. Testing of this cognitive ability is proposed and implemented for the first time. The system is an extension of Moodle and is openly hosted in the github repository. Elliptical constructions are limited to verbal and nominal ellipses, which are theoretically possible to be completely reconstructed based on the context of the sentence. The study is conducted with the participation of SPbPU students as respondents. The texts of planimetric tasks are chosen as the subject area. As a result of the analysis of testing data, the following results are obtained: the influence of the respondent’s knowledge of the subject area (planimetry) on the test results is established; a tendency towards self-study of respondents was discovered, which is manifested in a reduction in time and an increase in scores as they pass tests; it is shown that respondents are poorly motivated if they do not see feedback on the answer to the completed task. The paper discusses the problems of further development of the testing system and its use in adapting questionnaires (tasks) to assess the knowledge of SPbPU students in the field of automation of bug detection in programs, as well as for diagnosing the functional state of operator specialists and express diagnosis of dementia. It also seems promising to use the system to improve the processes of syntactic parsing of elliptic sentences and automate the restoration of ellipses in the subject area of planimetry.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3 supplement","pages":"S123 - S130"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676218","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}
Ch. B. Minnegalieva, I. I. Kashapov, O. D. Morozova
{"title":"Automated Grading of Students’ Short Answers Using Language Models","authors":"Ch. B. Minnegalieva, I. I. Kashapov, O. D. Morozova","doi":"10.3103/S0005105525700177","DOIUrl":"10.3103/S0005105525700177","url":null,"abstract":"<p>Methods of assessing student answers using language models are currently being studied by various specialists. The results of automated assessment depend on the subject area and characteristics of the academic discipline. This paper analyzes students’ answers received during a Computer Graphics and Design course. It is proposed to determine the cosine similarity of document vectors obtained using language models and refine the estimates by checking keywords. The results obtained can be used for preliminary assessment of students’ answers and form the basis for further research.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3 supplement","pages":"S109 - S114"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676500","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":"Subjective Notes on Search Engines","authors":"Y. E. Polak","doi":"10.3103/S0005105525700086","DOIUrl":"10.3103/S0005105525700086","url":null,"abstract":"<p>This work commemorates the 25th anniversary of the establishment of the main search engines for our country, Yandex and Google, which happened one after another. This article attempts to describe some events from the history of the development of internet navigation tools from the point of view of a witness (and partly a participant).</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 1 supplement","pages":"S27 - S42"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676531","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":"Application of Synthetic Data to the Problem of Anomaly Detection in the Field of Information Security","authors":"A. I. Gurianov","doi":"10.3103/S0005105525700128","DOIUrl":"10.3103/S0005105525700128","url":null,"abstract":"<div><p>Synthetic data are highly relevant for machine learning. Modern algorithms to generate synthetic data make it possible to generate data that are very similar in their statistical properties to the original data. Synthetic data is used in practice in a wide range of tasks, including those related to data augmentation. The author of the article proposes a method of data augmentation combining the approaches of increasing the sample size using synthetic data and synthetic anomaly generation. This method has been used to address the information security problem of anomaly detection in server logs to detect attacks. The model trained for the task presents high results. This demonstrates the effectiveness of the use of synthetic data to increase sample size and generate anomalies, as well as the ability to use these approaches together with high efficiency.</p></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 2 supplement","pages":"S68 - S72"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676536","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":"Design and Development of a Training Blockchain Simulator","authors":"O. M. Mekhovnikov, A. S. Toschev","doi":"10.3103/S0005105525700165","DOIUrl":"10.3103/S0005105525700165","url":null,"abstract":"<p>This article presents an educational blockchain simulator that is intended to train students and beginning blockchain developers. This simulator was created to provide users with an intuitive and accessible tool for learning the basic concepts and mechanisms of blockchain functioning. The article discusses the main aspects of the design and architecture of the simulator and provides a demonstration of the application. In addition, the possibilities for further development of the simulator and its potential as a teaching tool for research in the field of blockchain technologies are discussed. The resulting simulator contributes to the field of education and science, helping increase the level of competence of specialists and the development of innovative solutions in blockchain.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3 supplement","pages":"S102 - S108"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676499","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":"Analyzing Machine Learning Models Based on Explainable Artificial Intelligence Methods in Educational Analytics","authors":"D. A. Minullin, F. M. Gafarov","doi":"10.3103/S0005105525700189","DOIUrl":"10.3103/S0005105525700189","url":null,"abstract":"<p>The problem of predicting early dropout of students of Russian universities is urgent and requires the development of new innovative approaches to address it. To do so, it is possible to develop predictive systems based on the use of student data that are available in the information systems of universities. This paper investigates machine learning models for the prediction of early student dropout, trained on the basis of student characteristics and performance data. The main scientific novelty of this work lies in the use of explainable artificial intelligence (AI) methods to interpret and explain the performance of the trained machine learning models. Explainable AI methods allow us to understand which of the input features (student characteristics) have the greatest influence on the results of the machine learning models and can also help understand why models make certain decisions. The findings expand the understanding of the influence of various factors on early dropout of students.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3 supplement","pages":"S115 - S122"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676217","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 Replenishment of Metadata of Digital Publications Using the Semantic Services of the Internet","authors":"P. O. Gafurova","doi":"10.3103/S0005105525700116","DOIUrl":"10.3103/S0005105525700116","url":null,"abstract":"<p>This article describes approaches to replenishing the metadata of documents in electronic collections of a digital mathematical library. An open resource of the semantic network is used as a replenishment. For this purpose, software tools have been developed to search for the necessary data and include them in a metadata set. A separate block of metadata in a scientific article is formed from the affiliation of the authors presented in the document. Typically, ownership in a document does not contain sufficient data to generate a set of metadata. A method has been developed for providing author affiliation metadata, providing an open research organization registry (ROR), as well as means for making connections between ROR and other semantic chains. This method was applied to the collections of articles of the journal <i>Elektronnye Biblioteki</i> (Digital Libraries) for 2021–2022. The article describes a method for connecting the Lobachevsky digital mathematical library-DML to new electronic collections and describes a method for transforming metadata into a digital format that would be available for downloading.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 2 supplement","pages":"S59 - S67"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676538","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":"Stochastic Analysis of Ocean–Atmosphere Heat Fluxes in the North Atlantic","authors":"N. P. Tuchkova, K. P. Belyaev, G. M. Mikhaylov","doi":"10.3103/S0005105525700104","DOIUrl":"10.3103/S0005105525700104","url":null,"abstract":"<p>Observational data on the North Atlantic obtained over the 40 years of the NAAD project were analyzed. The total heat flux from the ocean to the atmosphere (and from the atmosphere to the ocean) was considered as a sum of latent and sensible heat. The coefficients of the stochastic differential equation representing the stochastic process were statistically determined from the original data set. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation that is generated by the constructed diffusion process was proven when Kolmogorov’s conditions were met. Numerical calculations were conducted on the Lomonosov-2 supercomputer at the Lomonosov Moscow State University.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 1 supplement","pages":"S51 - S57"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676532","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":"List of the Higher Attestation Commission: User Interface in the RSJ Database and Elibrary.Ru","authors":"T. A. Polilova","doi":"10.3103/S0005105525700074","DOIUrl":"10.3103/S0005105525700074","url":null,"abstract":"<p>The list of peer-reviewed scientific journals of the Higher Attestation Commission is gradually becoming a complex information system that is based on the normative documents of the Higher Attestation Commission, bibliometric data eLibrary.ru, and decisions of the expert councils of the Higher Attestation Commission and working groups engaged in the analysis, ranking and categorization of the journals of the list. The database of Russian Scientific Journals (RSJ) created by RIEPL may come to serve the requests of different categories of users in relation to the topic of dissertation defense. So far, the RSJ has implemented the interface of a representative of the journal’s editorial board and the interface of a member of the expert council of the Higher Attestation Commission. It is desirable to include in the RSJ an open interface that is addressed to the degree applicant to verify compliance with the requirements of the Higher Attestation Commission for publications in journals from the List. With the established mutual exchange of data between RSJ and eLibrary.ru, the applicant’s interface with the designated functionality can be organized in the eLibrary.ru user environment.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 1 supplement","pages":"S17 - S26"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676257","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":"Virtual Exhibition as a Means of Integrating into a Unified Digital Space of Scientific Knowledge the Information Systems in the Field of Science and Culture","authors":"I. N. Sobolevskaya, A. N. Sotnikov","doi":"10.3103/S0005105525700098","DOIUrl":"10.3103/S0005105525700098","url":null,"abstract":"<p>The study examines the principle of creating virtual exhibitions as a means of integration into the Common Digital Space of Scientific Knowledge the information systems in the field of science and culture with the aim of promoting science, ensuring access to information in various scientific fields and drawing attention to current issues and achievements in the scientific sphere. The main methods of creating virtual exhibitions are formulated, including content selection and segmentation into main sections. In addition, a classification of virtual exhibitions into autonomous, remote, and combined is proposed. Special attention is paid to the methodology of creating virtual exhibition at the Moscow Center of the Russian Academy of Sciences. Using the example of an interdepartmental combined virtual exhibition, a detailed description of the “Madame Penicillin” exhibition dedicated to the creator of penicillin, Z.V. Ermol’eva, is provided.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 1 supplement","pages":"S43 - S50"},"PeriodicalIF":0.5,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143676534","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}