Pub Date : 2024-03-07DOI: 10.3103/s0147688223060060
V. L. Khatskevich
Abstract—
On the basis of the fuzzy medians of fuzzy number systems, a class of averaging operators is introduced and studied for the implementation of the problem of the aggregation of fuzzy information. The established properties of symmetry, idempotence, continuity, and monotonicity of averaging operators are a modification of the characteristic properties of scalar aggregation functions for the fuzzy case. Additionally, the properties of additivity and homogeneity, as an extreme property, are established. This determines the adequacy of the use of fuzzy medians in the tasks of aggregating fuzzy information.
{"title":"Fuzzy Medians as Aggregators of Fuzzy Information","authors":"V. L. Khatskevich","doi":"10.3103/s0147688223060060","DOIUrl":"https://doi.org/10.3103/s0147688223060060","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract—</h3><p>On the basis of the fuzzy medians of fuzzy number systems, a class of averaging operators is introduced and studied for the implementation of the problem of the aggregation of fuzzy information. The established properties of symmetry, idempotence, continuity, and monotonicity of averaging operators are a modification of the characteristic properties of scalar aggregation functions for the fuzzy case. Additionally, the properties of additivity and homogeneity, as an extreme property, are established. This determines the adequacy of the use of fuzzy medians in the tasks of aggregating fuzzy information.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"47 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140055034","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}
Pub Date : 2024-03-07DOI: 10.3103/s0147688223060047
V. G. Chernov
Abstract
A method of solution of antagonistic games in violation of a common knowledge principle is described, wherein players have incomplete knowledge of possible solutions and appropriate outcomes for the opposite side. As a formal model of for a game situation, it is proposed to use a fuzzy-multiple representation of estimates of the possibilities of using players’ strategies and the corresponding consequences. The solution for this problem is based on the transformation of the fuzzy estimates of the results of possible solutions for each situation in the form of an equivalent fuzzy set that has a triangular membership function. The developed method does not impose restrictions on the affiliation functions of the initial fuzzy data. In addition to the selection of the best solution, an estimation of the result and the degree of feasibility is obtained.
{"title":"Decision-Making in a Conflict Situation with Fuzzy Types of Participants","authors":"V. G. Chernov","doi":"10.3103/s0147688223060047","DOIUrl":"https://doi.org/10.3103/s0147688223060047","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>A method of solution of antagonistic games in violation of a common knowledge principle is described, wherein players have incomplete knowledge of possible solutions and appropriate outcomes for the opposite side. As a formal model of for a game situation, it is proposed to use a fuzzy-multiple representation of estimates of the possibilities of using players’ strategies and the corresponding consequences. The solution for this problem is based on the transformation of the fuzzy estimates of the results of possible solutions for each situation in the form of an equivalent fuzzy set that has a triangular membership function. The developed method does not impose restrictions on the affiliation functions of the initial fuzzy data. In addition to the selection of the best solution, an estimation of the result and the degree of feasibility is obtained.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"38 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882925","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}
Pub Date : 2024-03-07DOI: 10.3103/s0147688223060151
A. V. Smirnov, A. V. Ponomarev, N. G. Shilov, T. V. Levashova
Abstract
The development of artificial intelligence technologies and the growing complexity of decision-making when managing complex dynamic systems necessitate the joint work of humans and artificial intelligence, including as part of teams of heterogeneous participants (for example, experts and agents operating with artificial intelligence). The paper discusses the requirements for collaborative human-machine decision support systems and the problems that can arise during their creation. The methods of neuro-symbolic artificial intelligence can help resolve some of these problems. An analysis of modern results in the field of ontology-oriented neuro-symbolic artificial intelligence is carried out, primarily intended to explain neural network models using ontologies and symbolic knowledge to improve the efficiency of neural network models. A conceptual model of a collaborative human-machine decision support system based on ontology-oriented neuro-symbolic intelligence is proposed.
{"title":"Collaborative Decision Support Systems Based on Neuro-Symbolic Artificial Intelligence: Problems and Generalized Conceptual Model","authors":"A. V. Smirnov, A. V. Ponomarev, N. G. Shilov, T. V. Levashova","doi":"10.3103/s0147688223060151","DOIUrl":"https://doi.org/10.3103/s0147688223060151","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The development of artificial intelligence technologies and the growing complexity of decision-making when managing complex dynamic systems necessitate the joint work of humans and artificial intelligence, including as part of teams of heterogeneous participants (for example, experts and agents operating with artificial intelligence). The paper discusses the requirements for collaborative human-machine decision support systems and the problems that can arise during their creation. The methods of neuro-symbolic artificial intelligence can help resolve some of these problems. An analysis of modern results in the field of ontology-oriented neuro-symbolic artificial intelligence is carried out, primarily intended to explain neural network models using ontologies and symbolic knowledge to improve the efficiency of neural network models. A conceptual model of a collaborative human-machine decision support system based on ontology-oriented neuro-symbolic intelligence is proposed.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"42 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140889760","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}
Pub Date : 2024-03-07DOI: 10.3103/s0147688223060059
V. I. Gorodetsky
Abstract—
This article outlines the boundaries of data science in relation to artificial intelligence. It also describes the multidimensional bilateral relationships between data science and other related sciences and provides a brief introduction to the methodology of data science and its key research directions. Finally, the article also discusses some challenging problems that data science is expected to address.
{"title":"Data Science: Key Directions, Problems, and Perspectives","authors":"V. I. Gorodetsky","doi":"10.3103/s0147688223060059","DOIUrl":"https://doi.org/10.3103/s0147688223060059","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract—</h3><p>This article outlines the boundaries of data science in relation to artificial intelligence. It also describes the multidimensional bilateral relationships between data science and other related sciences and provides a brief introduction to the methodology of data science and its key research directions. Finally, the article also discusses some challenging problems that data science is expected to address.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"2012 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882928","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}
Pub Date : 2024-03-05DOI: 10.3103/s0147688223040159
V. A. Mutev
Abstract
In the analysis of scientific and pedagogical approaches to news literacy, two fundamentally different areas of research have been identified: practice-oriented and comprehensive. The origins, essence, subject field, and crucial concepts of library and information approach to news literacy are elaborated. The institutionalization patterns of news literacy within the framework of library and information activities have been identified and discussed. The experience of designing an educational discipline on the analysis of news is characterized, and original analytical technology for deconstructing news messages is presented.
{"title":"News Literacy in the System of Library and Information Knowledge","authors":"V. A. Mutev","doi":"10.3103/s0147688223040159","DOIUrl":"https://doi.org/10.3103/s0147688223040159","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In the analysis of scientific and pedagogical approaches to news literacy, two fundamentally different areas of research have been identified: practice-oriented and comprehensive. The origins, essence, subject field, and crucial concepts of library and information approach to news literacy are elaborated. The institutionalization patterns of news literacy within the framework of library and information activities have been identified and discussed. The experience of designing an educational discipline on the analysis of news is characterized, and original analytical technology for deconstructing news messages is presented.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"51-52 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036165","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}
Pub Date : 2024-03-05DOI: 10.3103/s0147688223050088
O. A. Ivaschuk, V. A. Berezhnoy, Y. N. Maslakov, V. I. Fedorov
Abstract
In this article, the authors present the results of the development and study of methods for creating 3D models of plants grown in vitro, which provides the ability to accurately record the morphometric indicators of the growth of the individual parts and organs of plants, as well as of plants as a whole, cultivated on different nutrient media. The presented methods and algorithms together solve the problems arising in the process of studying plants in a test tube, such as those related to the complexity of the plant structure, the occurrence of distortions at the borders of the test tube, fogging of the test tube, and the influence of the human factor. A bank of 792 3D models has been created for plants of six species, allowing simulation experiments to be conducted to identify cause-and-effect relationships, forecasting and gaining new knowledge. The developed methods have been checked for adequacy, and an example of use for a specific plant is presented. The presented methods and algorithms can be the basis for the implementation of the process of digital phenotyping of plants.
{"title":"Creation and Study of 3D Models for Digital Plant Phenotyping","authors":"O. A. Ivaschuk, V. A. Berezhnoy, Y. N. Maslakov, V. I. Fedorov","doi":"10.3103/s0147688223050088","DOIUrl":"https://doi.org/10.3103/s0147688223050088","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In this article, the authors present the results of the development and study of methods for creating 3D models of plants grown in vitro, which provides the ability to accurately record the morphometric indicators of the growth of the individual parts and organs of plants, as well as of plants as a whole, cultivated on different nutrient media. The presented methods and algorithms together solve the problems arising in the process of studying plants in a test tube, such as those related to the complexity of the plant structure, the occurrence of distortions at the borders of the test tube, fogging of the test tube, and the influence of the human factor. A bank of 792 3D models has been created for plants of six species, allowing simulation experiments to be conducted to identify cause-and-effect relationships, forecasting and gaining new knowledge. The developed methods have been checked for adequacy, and an example of use for a specific plant is presented. The presented methods and algorithms can be the basis for the implementation of the process of digital phenotyping of plants.</p>","PeriodicalId":43962,"journal":{"name":"Scientific and Technical Information Processing","volume":"24 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882855","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}