INFORMATION ABOUT PROJECT,
SUPPORTED BY RUSSIAN SCIENCE FOUNDATION

The information is prepared on the basis of data from the information-analytical system RSF, informative part is represented in the author's edition. All rights belong to the authors, the use or reprinting of materials is permitted only with the prior consent of the authors.

 

COMMON PART


Project Number22-11-20024

Project titleDevelopment of fundamental foundations for information and analytical support of the tasks of integrated development of urban areas using ontological engineering methods

Project LeadParygin Danila

AffiliationFederal state budget educational of office highly professional education "Volgograd State Technical University",

Implementation period 2022 - 2024 

Research area 01 - MATHEMATICS, INFORMATICS, AND SYSTEM SCIENCES, 01-512 - Information technologies of intellectual support for decision-making

Keywordsdata-driven management, geospatial data, urban data mining, urbanized area, urban area infrastructure, urban architectural and ecological environment, ontological model, urban environment quality indicators, area management support, data-oriented analysis, scenario modeling, area infrastructure integrity


 

PROJECT CONTENT


Annotation
The task of managing the development of urban areas is multifaceted and includes: developing strategies, identifying problems, agreeing on goals, developing criteria for assessing the effectiveness of management, forecasting and assessing the risks of decisions made. The need to quickly respond to a changing situation and take into account a large number of factors requires the involvement of technologies and methods based on modern approaches to processing and analyzing information. There is more and more scope for analyzing and using data to support urban development management, as the amount of data generated at different levels of city systems increases. On the other hand, modern approaches to the formalization of knowledge make it possible to automate the process of analyzing information, identifying patterns to justify decisions on the transformation of urban areas. In this regard, the scientific problem being solved is associated with the creation of a new methodological approach to support decision-making in the problems of the development of urban areas on the basis of mathematical models built using urban data based on ontological engineering methods. The development of a new approach will allow taking into account various aspects of the functioning of the city as a complex system, when formalizing the processes under study and when choosing methods for supporting decision-making, which are supposed to be machine learning, multi-criteria optimization, etc. The direction related to the modernization of Russian cities based on modern intelligent technologies is currently being implemented within the framework of the National Program "Digital Economy of the Russian Federation" and the National Project "Housing and Urban Environment" (in accordance with the order of the Government of the Russian Federation of March 23, 2019 No. 510-р federal project "Formation of a comfortable urban environment" by the end of 2024 provides for a reduction in the number of cities with an unfavorable environment by half); Decree of the President of the Russian Federation of July 21, 2020 No. 474 “On the national development goals of the Russian Federation for the period up to 2030”; Strategies for the spatial development of the Russian Federation for the period up to 2025 (approved by the order of the Government of the Russian Federation dated 13.02.2019 No. 207-r). In the process of implementing the project "Strategy for the socio-economic development of the Volgograd region until 2030", a change in approaches to the design of a comfortable urban environment is envisaged, which will certainly require new tools for analyzing options for the development of urban areas and interdisciplinary research, for the implementation of which it is necessary to create a unified approach to information processing, the integration of knowledge in the field of management of the development of the city territory and the introduction of new procedures for the preparation, making and analysis of decisions.

Expected results
The following specific scientific and scientific-practical results are planned according to the results of the project: 1. An ontological model for representing knowledge of the problem area (architectural and ecological environment of the city), as well as the corresponding algorithms for reasoning on the knowledge represented by this model has been developed. 2. A technology has been created for applying models based on the analysis of urban data to support the tasks of managing the quality of the urban environment. 3. A complex of data-oriented methods and algorithms has been developed for the analysis of indicators of the quality of the urban environment, taking into account the characteristics of the territory. 4. A decision support system has been developed for managing the quality of the urban environment based on ontological and scenario modeling. Thus, as a result of the project implementation, an integrated approach will be developed to solving the problems of urban areas development based on the analysis of data on the structure of the territory, environmental conditions, and properties of the urban environment. This approach will make it possible to more reasonably assess the criteria for the quality of the urban environment and provide an opportunity to choose the most effective management decisions. The scientific significance of the project is characterized by the results that will be achieved during its implementation: (a) methods of knowledge formalization and inference algorithms for architectural and ecological analysis of the urban environment based on the ontological approach have been developed; (b) machine learning algorithms have been developed for predictive modeling of processes that affect the quality of the urban environment, including for the selection of optimal parameters in various options for transforming urban spaces, taking into account the characteristics of the territory.


 

REPORTS


Annotation of the results obtained in 2022
The following scientific results were obtained during the first stage of research on the project: 1. The task of classifying urban objects, taking into account the provision of living conditions in various natural and climatic conditions, was solved on the basis of a study of the components of urban infrastructure and an analysis of factors affecting the quality of the urban environment. The systematization of information about the structural features of the urban environment was carried out on the basis of the study of objects that ensure the realization of the needs of human life activity. Twelve basic components were identified, on the basis of which a set of properties was determined that characterizes compliance with the standards of a comfortable and safe urban environment. 2. The classification of the basic components of the urban infrastructure, objects of the urbanized territory and elements of the urban planning system was carried out, in accordance with the general principles of their creation and operation, as well as taking into account certain variable natural and ecological-climatic factors of the environment. A three-stage approach to assessing the state of objects in the urban environment based on the analysis of spatial data is proposed. The developed approach was tested on two cases: (i) inspection for visual contamination of the vertical surfaces of the territory's objects; (ii) controlling the filling of garbage containers and waste collection areas. 3. The systematization of information about the features of urban spaces was carried out, which made it possible to form indicators characterizing the influence of environmental and climatic factors on the ability of the urban environment to provide the necessary level of safety for the health and comfort of residents. It is proposed to use open data with geospatial reference to assess the quality of the urban environment. Individual indicators can be evaluated both for a local area of the territory and for the entire city. Presentation of evaluation results is implemented on the basis of spatial data visualization methods. Atmospheric air quality; the state of the geological and aquatic environment; noise impact; the quality of the visual environment; bioclimatic conditions are considered as analyzed indicators. 4. The problems accompanying the process of managing objects of urbanized territories are analyzed. Issues related to obtaining information for their accounting and analysis of the state are considered. Additional criteria are proposed for selecting options for the development of the territory, taking into account the feasibility of transforming the project, taking into account the existing development. It is shown that the efficiency of urban area management depends on the correct choice of the strategy for involving objects in economic activity, restoring their functional significance and ensuring environmental safety. The method based on fuzzy sets is proposed to be used to select effective solutions for the use of the territory, as the most optimal in conditions of high uncertainty and complexity of the processes under consideration. 5. The conducted studies made it possible to assess the potential of various sources of information about the state of the human life activity environment, including various infrastructural factors and the activities of the people themselves. It is proposed to use social response as a basis for one of the aspects of urban development monitoring. An approach to generating a news feed using heterogeneous sources of information was implemented to conduct field experiments during the study. An approach has been developed for creating synthetic news messages that characterize the state of the urban environment and the events taking place in it, based on parsing real news, changing geographic data in real news, generating texts using the GPT-3 neural network, generating texts based on the template library and generating game news based on information from a mobile application for accounting the state of urban environment objects. 6. The analysis of the problems of using ontological models in the design of architectural objects, buildings and structures is carried out. The urban planning norms and standards that determine the procedure for the construction of urban infrastructure facilities, as well as the features of the complex structure of the organization of such documentation, containing nesting, contradictions, mutual references, etc., are analyzed. The basic principles of creating ontologies, key elements, query options are described on the example of the problem of modeling objects of the architectural and ecological environment of a city. The classes of urban planning objects are defined. The criteria for the quality of the urban environment are formulated. An ontological knowledge base has been developed to support decision-making in architectural design, containing the classes of urban objects “park”, “shopping center”, “school”, “buildings”, etc. The ontology is filled with information. The program “Protégé”, which has a free license, was chosen as the means of implementation. Neurocybernetic and informational approaches to the construction of decision support systems in industry-specific tasks based on the developed ontology are studied. 7. Primary studies of the issues of organizing the sustainable development of the urban environment through the implementation of projects for the integrated area development (IAD) were carried out. A comparison of the tasks of the IAD and sustainable development was carried out, on the basis of which an approach was proposed for the implementation of a decision support system to achieve the desired development indicators, taking into account the assessment of the quality of a given territory for the consumer as a key assessed indicator. A methodology has been developed for assessing the consumer attractiveness of a territory for calculating the proposed indicator. Methods for collecting, filtering and processing information about the objects of the territory, presented in open sources, have been developed. Algorithms for assessing the infrastructural provision of real estate objects and calculating assessments of their attractiveness have been developed. Estimates of attractiveness were carried out for various variants of IAD for an urban district (using the example of Volgograd). 8. More than twenty scientific papers have been prepared in the process of project research of the first stage. 12 of which have been published in leading peer-reviewed journals and peer-reviewed collections of international conferences, including two publications indexed by Web of Science and Scopus at the time of submission of the report of the current period. 20 reports were made at all-Russian and international scientific conferences in Russia and abroad, including five plenary ones.

 

Publications

1. Dubov I.A., Rashevskiy N.M., Yanin K.D., Galyanina P.Yu. Подходы к сбору информации для формирования модели знаний визуальной экологии Инженерно-строительный вестник Прикаспия, № 2 (40), С. 115–120 (year - 2022) https://doi.org/10.52684/2312-3702-2022-40-2-98-103

2. Ereshchenko T.V., Rashevskiy N.M., Khoroshun D.A., Ryapalov D.N., Kuramshin R.F. Анализ и моделирование транспортных потоков на перекрестке для управления качеством городской среды Инженерный вестник Дона, № 8 (92), С. 99–107 (year - 2022)

3. Finogeev A., Deev M., Parygin D., Finogeev A. Intelligent SDN Architecture With Fuzzy Neural Network and Blockchain for Monitoring Critical Events Applied Artificial Intelligence, Vol. 36, No. 1, Art. no. 2145634 (year - 2022) https://doi.org/10.1080/08839514.2022.2145634

4. Ignatyev A.V., Kulikov M.A., Tsapiev D.N., Tirin V.V. Методика автоматической классификации дорог с использованием нейронной сети Mask R-CNN Инженерный вестник Дона, № 5 (89), С. 274–283 (year - 2022)

5. Parygin D., Sadovnikova N., Gamidullaeva L., Finogeev A., Rashevskiy N. Tools and Technologies for Sustainable Territorial Development in the Context of a Quadruple Innovation Helix Sustainability, Vol. 14 (15), Art. no. 9086 (year - 2022) https://doi.org/10.3390/su14159086

6. Rashevskiy N.M., Rudenko I.Ya., Sokolov D.A., Feklistov V.A., Yakunin O.A. Разработка системы поддержки принятия решений на основе рассуждения по прецедентам по оценке безопасности участка транспортной системы города Инженерный вестник Дона, № 7 (91), С. 133–140 (year - 2022)

7. Savina O.V., Sadovnikova N.P., Mashakaryan A.S., Katerinina S.Yu., Gurtyakov A.S. К вопросу о совершенствовании процесса управления имущественным комплексом территории муниципального образования Инженерный вестник Дона, № 4 (88), С. 87–104 (year - 2022)

8. Shuklin A.A., Parygin D.S., Finogeev A.A., Zelenskiy I.S., Anokhin A.O. Генерация синтетических новостей для продуцирования социального отклика на городские события Социология города, № 1-2, С. 81–92 (year - 2022) https://doi.org/10.35211/19943520_2022_1-2_81

9. Sinitsyn I.S., Sulitsky M.V., Parygin D.S., Dzhagaev V.A., Seryakova V.N. Использование нейронных сетей для определения дорожной обстановки Системный анализ в науке и образовании, № 2, С. 17–22 (year - 2022)

10. Sukhomlinov N.M., Finogeev A.G., Smirnova T.V., Ivashchenko V.D., Parygin D.S. Применение микроконтроллерных систем в исследованиях (на примере машины Атвуда) Прикаспийский журнал: управление и высокие технологии, № 3 (59), С. 112–121 (year - 2022) https://doi.org/10.54398/20741707_2022_3_112

11. Burov S., Parygin D., Finogeev A., Ather D., Rashevskiy N. Rule-Based Pedestrian Simulation Proceedings of the Advancement in Electronics & Communication Engineering 2022, Art. no. 4160252, P. 1–7 (year - 2022) https://doi.org/10.2139/ssrn.4160252

12. Ignatyev A.V., Kulikov M.A., Tsapiev D.N., Tirin V.V., Ather D. Using neural networks for the classification of city roads based on satellite images and in the photographs of roads Proceedings of the Advancement in Electronics & Communication Engineering 2022, Art. no. 4157527, P. 342–247 (year - 2022) https://doi.org/10.2139/ssrn.4157527

13. - Калькулятор низкоаллергенного ландшафта -, 2022619660 (year - )

14. - ЦТУАС на 100+ TechnoBuild Пресс-центр ИАиС ВолгГТУ, Новости, 26.10.2022 (year - )

15. - Процесс. Волгоград. How old is this house Карты возраста домов, 2022 (year - )


Annotation of the results obtained in 2023
The following scientific results were obtained during the second stage of the project research: 1. Research has been carried out related to improving approaches to assessing the state of urban infrastructure using methods for recognizing objects in the processes under study on frames of a video stream captured by city video surveillance cameras and Earth remote sensing equipment in high resolution. An information model is proposed for structuring information about recognized objects. The possibility of categorizing quantitative assessments for various tasks of analyzing the balance of urban systems is considered. 2. Issues of formalizing knowledge for assessing the visual environment of a city, assessing the climate-ecological state and sound landscape are considered for the first time. An ontology was chosen as a formal model for representing knowledge, ensuring the integration of heterogeneous information and the ability to automate its processing. Models for the distribution of pollutants in urban areas and models for the formation of a favorable sensory landscape have been developed. Such models can be used to obtain additional information for the formation of rules in intelligent decision support systems for transforming the urban environment. 3. An approach to forecasting the needs of city residents and justifying the requirements for urban infrastructure is proposed. Software based on methods of spatial data analysis for solving problems of urban area management and urban planning, including analysis of the city territory occupied by objects of different categories, has been implemented. The implementation of the proposed approach was tested using the example of calculating the areas occupied by industrial facilities. 4. Existing approaches to generative design in the field of urban planning, which will allow iterative analysis and consideration of many factors such as topography, climatic conditions, people flows, transport networks and other parameters to develop the best urban planning solutions for a specific area of the territory were studied. Issues of using ontological engineering to create formal descriptions and knowledge representation models about urban planning that combine information about the physical environment, infrastructure, public places, transport networks, etc. are considered. The prospects for combining generative design and ontological engineering in urban planning for the automatic generation and evaluation of various urban planning options taking into account given parameters and goals are analyzed. 5. An approach has been developed that allows to create information and graphic models of an existing infrastructure facility at the operational stage, applicable for assessing the operational characteristics of the facility and analyzing possible improvements to buildings and structures, as well as the surrounding area, evacuation modeling and other promising scientific and practical problems. A method for developing a digital twin of a construction site and a section of an urban area is proposed, requirements for its implementation are formulated, and methods of using the developed models are described (including process simulation algorithms and tasks to be solved). 6. An approach to constructing “control panels” for presenting city development data has been implemented. The approach includes the preparation of statistical data and spatial information about the structure and state of the urban environment through pre-processing and integration of source data (including spatially referenced data). A list of indicators and formats for their visualization have been defined to support the analysis of the current situation with the development of an urbanized area for decision makers. The Dashboard service http://CityDashboard.ru/ has been developed and posted on the Internet, reflecting a set of source and model data on the development of the city of Volgograd. 7. The results of the second stage of project research, obtained during the reporting period, were published in 31 scientific papers in leading peer-reviewed journals and peer-reviewed collections of international conferences, including 11 articles in publications indexed by Web of Science and/or Scopus. 27 reports were made at all-Russian and international scientific conferences in Russia and abroad, five of which were invited, including two plenary reports at international conferences in India. In-person participation was taken in seven scientific and practical events, including in Yekaterinburg, Nizhny Novgorod and Tambov. Three detailed interviews with comments on the topics of project work and the procedure for grant support from the Russian Science Foundation were prepared for regional television channels of the Volgograd region, as part of information programs for the popularization of science in Russia.

 

Publications

1. Anokhin A.O., Parygin D.S., Sadovnikova N.P., Finogeev A.A., Gurtyakov A.S. Моделирование поведения интеллектуальных агентов на основе методов машинного обучения в моделях конкуренции Программные продукты и системы, Т. 36, № 1, С. 46–59 (year - 2023) https://doi.org/10.15827/0236-235X.141.046-059

2. Burov S.S., Parygin D.S., Rashevskiy N.M. Разработка правил моделирования перемещения пешеходов Информационное общество: образование, наука, культура и технологии будущего, Выпуск 6, С. 187–196 (year - 2023) https://doi.org/10.17586/2587-8557-2022-6-187-196

3. Davtian A.G., Shabalina O.A., Sadovnikova N.P., Berestneva O.G. Трансформация бизнес-моделей в контексте технологий Индустрии 4.0 Математические методы в технологиях и технике, № 5, С. 107–110 (year - 2023) https://doi.org/10.52348/2712-8873_MMTT_2023_5_107

4. Emelyanenko S.A., Parygin D.S., Anokhin A.O., Zelenskiy I.S., Yartsev V.S. Исследование одного аспекта городской экологии (на примере экологического следа новогодней ели) Социология города, № 3, С. 83–100 (year - 2023) https://doi.org/10.35211/19943520_2022_3_83

5. Gorlov D.A., Rashevsky N.M., Dyatlov K.A., Zalinyan A.K., Shcherbakov A.G. Применение онтологической модели представления знаний в проектировании архитектурных объектов Природные и техногенные риски. Безопасность сооружений, № 6 (61), С. 22–25 (year - 2023) https://doi.org/10.55341/PTRBS.2022.61.6.001

6. Ignatyev A.V., Cibulina D.Yu., Kulikov M.А., Parygin D.S. QGIS как инструмент разработки интерактивных карт городских общеобразовательных учреждений Социология города, № 2, С. 94–104 (year - 2023) https://doi.org/10.35211/19943520_2023_2_94

7. Ignatyev A.V., Tirin V.V., Tsapiev D.N., Saushkin D.A. Применение нейронных сетей для определения основных характеристик автотранспортных потоков в городе Социология города, № 4, С. 70–80 (year - 2023) https://doi.org/10.35211/19943520_2022_4_70

8. Parygin D.S. Поддержка принятия решений на основе данных с пространственной привязкой в задачах управления развитием урбанизированных территорий Математические методы в технологиях и технике, № 10, С. 109–116 (year - 2023) https://doi.org/10.52348/2712-8873_MMTT_2023_10_109

9. Rashevskiy N., Sadovnikova N., Ereshchenko T., Parygin D., Ignatyev A. Atmospheric Ecology Modeling for the Sustainable Development of the Urban Environment Energies, Vol. 16(4), Art. no. 1766 (year - 2023) https://doi.org/10.3390/en16041766

10. Rashevskiy N.M., Parygin D.S., Kulikov M.А., Sadovnikova N.P., Ignatyev A.V. Проблема учета эколого-климатических факторов для уточнения методики расчета показателей качества городской среды Социология города, № 4, С. 44–57 (year - 2023) https://doi.org/10.35211/19943520_2022_4_44

11. Rashevskiy N.M., Parygin D.S., Nazarov K.R., Sinicyn I.S., Feklistov V.A. Интеллектуальный анализ звукового ландшафта городской территории Социология города, № 1, С. 125–139 (year - 2023) https://doi.org/10.35211/19943520_2023_1_125

12. Sadovnikova N., Savina O., Parygin D., Churakov A., Shuklin A. Application of Scenario Forecasting Methods and Fuzzy Multi-Criteria Modeling in Substantiation of Urban Area Development Strategies Information, Vol. 14(4), Art. no. 241 (year - 2023) https://doi.org/10.3390/info14040241

13. Savina O.V., Parygin D.S., Finogeev A.A., Chikin A.D., Shcherbakov A.G. Поддержка принятия решений по повышению энергоэффективности объектов городской инфраструктуры Социология города, № 4, С. 58–69 (year - 2023) https://doi.org/10.35211/19943520_2022_4_58

14. Shcherbakov A.G., Parygin D.S., Saushkin D.A., Shiganov R.Ya., Gorlov D.A. Создание цифрового двойника образовательного кампуса на этапе эксплуатации: перспективы применения Природные и техногенные риски. Безопасность сооружений, № 6 (61), С. 30–34 (year - 2023) https://doi.org/10.55341/PTRBS.2022.61.6.003

15. Shuklin A.A., Sadovnikova N.P., Gurtyakov A.S. Подход к генерации новостной ленты о событиях в городе Информационное общество: образование, наука, культура и технологии будущего, Выпуск 6, С. 219–227 (year - 2023) https://doi.org/10.17586/2587-8557-2022-6-219-227

16. Smirnov M.A., Chikin A.D., Yasenetsky A.V., Parygin D.S., Nazarov K.R. Мониторинг качества воздуха для построения экологически чистых маршрутов Инженерный вестник Дона, № 1 (97), С. 585–593 (year - 2023)

17. Sulitskiy M.V., Zelenskiy I.S., Sadovnikova N.P., Finogeev A.G., Katerinina S.Yu. Разработка интеллектуальной системы распознавания объектов для решения задач ситуационного управления в городе Современные наукоемкие технологии, № 7, С. 104–109 (year - 2023) https://doi.org/10.17513/snt.39702

18. Zelenskiy I., Parygin D., Savina O., Finogeev A., Gurtyakov A. Effective Implementation of Integrated Area Development Based on Consumer Attractiveness Assessment Sustainability, Vol. 14(23), Art. no. 16239 (year - 2023) https://doi.org/10.3390/su142316239

19. Zelenskiy I.S., Parygin D.S., Savina O.V. Оценка привлекательности недвижимости при комплексном развитии участка территории Информационное общество: образование, наука, культура и технологии будущего, Выпуск 6, С. 197–206 (year - 2023) https://doi.org/10.17586/2587-8557-2022-6-197-206

20. Anokhin A., Ereshchenko T., Parygin D., Khoroshun D., Kalyagina P. Applying Machine Learning and Agent Behavior Trees to Model Social Competition Lecture Notes in Networks and Systems, Vol. 784, P. 256–265 (year - 2023) https://doi.org/10.1007/978-3-031-44146-2_26

21. Ather D., Rashevskiy N., Parygin D., Gurtyakov A., Katerinina S. Intelligent Assessment of the Visual Ecology of the Urban Environment Proceedings of the 2nd International Conference on Technological Advancements in Computational Sciences, P. 361–366 (year - 2023) https://doi.org/10.1109/ICTACS56270.2022.9988692

22. Danilov I., Shuklin A., Zelenskiy I., Gurtyakov A., Kulikov M. Spatial Data Analysis for Decision Support in Urban Infrastructure Development Planning Communications in Computer and Information Science, Vol. 1909, P. 568–578 (year - 2023) https://doi.org/10.1007/978-3-031-44615-3_40

23. Danilova L.O., Gurtyakov A.S., Khoroshun D.A. Автоматизация обработки данных аэрофотосъемки при построении цифровой модели рельефа Актуальные проблемы компьютерного моделирования конструкций и сооружений, С. 285–287 (year - 2023)

24. Davtian A., Shabalina O., Sadovnikova N., Parygin D., Berestneva O. Business Model Innovation: Considering Organization as a Form of Reflection of Society Communications in Computer and Information Science, Vol. 1909, P. 206–219 (year - 2023) https://doi.org/10.1007/978-3-031-44615-3_14

25. Galyanina P., Sadovnikova N., Smirnova T., Zalinyan A., Baranova E. Ontological Model of Knowledge Representation for Assessing the City Visual Environment Quality Lecture Notes in Networks and Systems, Vol. 783, P. 130–139 (year - 2023) https://doi.org/10.1007/978-3-031-44097-7_13

26. Ignatyev A., Kulikov M., Parygin D. Assessing City Green Spaces by Voluntary Geographic Information Proceedings of the 1st International Conference on Methods, Models, Technologies for Sustainable Development, P. 103–108 (year - 2023) https://doi.org/10.5220/0011555500003524

27. Khayrov A., Shabalina O., Sadovnikova N., Kataev A., Petrova T. Computer-Aided Development of Adaptive Learning Games Lecture Notes in Networks and Systems, Vol. 784, P. 354–362 (year - 2023) https://doi.org/10.1007/978-3-031-44146-2_37

28. Parygin D.S., Yasenetsky A.V., Feklistov V.A. Разработка цифровых моделей участков городского пространства с использованием современных игровых движков Актуальные проблемы компьютерного моделирования конструкций и сооружений, С. 321–323 (year - 2023)

29. Rashevskiy N., Parygin D., Nazarov K., Sinitsyn I., Feklistov V. Intelligent Assessment of the Acoustic Ecology of the Urban Environment Lecture Notes in Networks and Systems, Vol. 784, P. 91–100 (year - 2023) https://doi.org/10.1007/978-3-031-44146-2_9

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