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FP7 Partner offer profile

Chuvash State University - SSH.2012.3.2-1 Families in transitions

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Date of filling in 14.08.2011
Organization name Chuvash State University
Organization adress Chuvash State University, Moskovsky prosp., 15, City of Cheboksary, 428015, Russia
Department/Unit Faculty of Applied Mathematics, Physics and Information Technology/ Department of Thermo Physics, Nanotechnology and Intelligence Method for Data Analysis
Contact person Prof. Victor S. Abrukov, Dr. Sci., professor, chair of Department of Thermo Physics, Nanotechnology and Intelligence Method for Data Analysis
Phone +7-9196636683
Fax +7-8352-452403
E-Mail abrukov@yandex.ru
Web-site http://www.chuvsu.ru
http://www.chuvsu.ru/2008/proekt.html
http://www.chuvsu.ru/2008/proekt_eng.html
Organization type
  • Consultancy
  • Research
  • Education
Special Programme
Cooperation
Theme
Socio-economic sciences and humanities (SSH)
Call identifier
FP7-SSH-2012-1
Topic number SSH.2012.3.2-1 Families in transitions
Call Deadline 02.02.2012
Short description of the organization (max 12 lines): Chuvash State University was founded in 1967. The University cosist of 21 faculties three branches. Main activities: public education, scientific and applied research and innovation.
Department of Applied Mathematics, Physics and Information Technology was established in 1968. The Faculty has eight departments. Department of Thermal Physics was founded in October 1967. The department trains specialists in the field of physics of nanostructures and nanotechnology, physics, combustion and explosion, artificial intelligence and data mining (Data Mining, Artificial Neural Networks). During the period 2007-2011 it has been received several grants from the Russian Foundation for Basic Research (RFBR) and the Ministry of Education and Science of the Russian Federation on topics related to the use of Data Mining, in particular, in the 2007 - 2009's it had the grant RFBR 07-06-00277 "Development of models of social phenomena using the methods of Data Mining"
Expertise offered Goal: Development of qualitative and quantitative (computational) models of family relations using data mining techniques.
Suggested methods and approaches to solving problems:
With the help of our site http://www.chuvsu.ru/2008/proekt.html (short version in English: http://www.chuvsu.ru/2008/proekt_eng.html) we have been collected a unique database. Currently the database contains about 400 "deep" interview-questionnaires concerning to various type of real families (divorced, “happy”, “unhappy”), and about 500 "deep" interview-questionnaires of those who wish to create a family. The database is constantly updated. Simulation of family relations will be conducted by means of Data Mining (method of "decision tree" method of artificial neural networks, a method of self-organizing Kohonen maps). To carry out the project we will use the analytical platform «Deductor» - production of BasegroupLab, Ryazan (http://www.basegroup.ru) that contains all tools of Data Mining as well as all necessary data preprocessing methods (purification, filtration, partial treatment, factor and correlation analysis). In the first year we plan to organize joint project website (in English and Russian) and new data collection. In general, the website has to be the online resource providing communications space of the project, collecting data, the interoperability of all interested parties in the project. From the outset of the project we plan to conduct a joint analysis and modeling of all pre-existing questionnaire-interview. We also plan to conduct a joint analysis and modeling of all new incoming data, adjusting the structure of the questionnaire-interview in accordance with the results of simulation and verification. By the end of the first year of the project it is planned to develop a new methodology for social science research in the field of family relationships and establish the new qualitative and quantitative (computational) models of family relationships. A very important component of the project is to work to find databases on Family Relations of the European community. For the second year of the project it will be devoted to the construction of working models, which can be used in real-world social science research in the field of family relations, and their verification. It is planned to create the ready to use computer analysis modules for issuing forecasts and decisions in the field of family relationships for different cases. They will be the multi-factor computer models that will able approximate the effect of a combination of internal and external factors on the duration of the marriage, satisfaction with marriage, etc. By the end of the second year it is planned to prepare a monograph "Application of intelligent methods of data analysis - Data Mining in the study of social phenomena", that will describe in detail the methodology and application technology of Data Mining in the analysis and modeling of social phenomena on the example of family relations. The project involves the establishment of cooperation with scientific groups and organizations involved in the study of social processes in order to gather sociological data. It is planned an involvement in the validation of models developed the state, public and private institutions, the implementation of computer-designed modules.
The global purpose of the work is to make the advansed steps for a development of new methodological base and technologies of DM application at build-up of new models of social phenomena on an example of the analysis of the family relations. Other possible objects of research are: Love as a goal function of social development as well as Terrorism, Education systems, and HR modeling.
Our team has a large experience in the field of Data Mining usage. Earlier we have been used DM for development of calculating models for solution of inverse and direct problems of optics by means of incomplete data in particular by means of “one-point measurement”, for determination of temperature profiles in burning wave of propellants by means of measurement of burning rate, for a prediction of wave form on a free surface of fluid (a task of tsunami), for a creation of models of automatic control system of boiler unit during transient processes, for a creation of models of deflagration-to-detonation transition under various experiment conditions, for a creation of models of prediction of regularities of energetic materials under various pressures and characteristics of composition, for creation models of optical and electrical properties of new nano materials.
Expertise offered
Our goal: Development of qualitative and quantitative (computational) models of family relations using data mining techniques.
Suggested methods and approaches to solving problems:
With the help of our site http://www.chuvsu.ru/2008/proekt.html (short version in English: http://www.chuvsu.ru/2008/proekt_eng.html) we have been collected a unique database. Currently the database contains about 400 "deep" interview-questionnaires concerning to various type of real families (divorced, “happy”, “unhappy”), and about 500 "deep" interview-questionnaires of those who wish to create a family. The database is constantly updated. We can model the family relations by means of Data Mining (method of "decision tree" method of artificial neural networks, a method of self-organizing Kohonen maps). To carry out the project we will use the analytical platform «Deductor» - production of BasegroupLab, Ryazan (www.basegroup.ru) that contains all tools of Data Mining as well as all necessary data preprocessing methods (purification, filtration, partial treatment, factor and correlation analysis). We are ready to take part in join work deals with an organization of joint project website (in English and Russian) and new data collection. We can create the ready to use computer analysis modules for issuing forecasts and decisions in the field of family relationships for different cases. They will be the multi-factor computer models that will able approximate the effect of a combination of internal and external factors on the duration of the marriage, satisfaction with marriage, etc.
Our team has a large experience in the field of Data Mining usage. Earlier we have been used DM for development of calculating models for solution of inverse and direct problems of optics by means of incomplete data in particular by means of “one-point measurement”, for determination of temperature profiles in burning wave of propellants by means of measurement of burning rate, for a prediction of wave form on a free surface of fluid (a task of tsunami), for a creation of models of automatic control system of boiler unit during transient processes, for a creation of models of deflagration-to-detonation transition under various experiment conditions, for a creation of models of prediction of regularities of energetic materials under various pressures and characteristics of composition, for creation models of optical and electrical properties of new nano materials.
Scientific keywords Social phenomena Family relations Duration of marriage Data Mining Artificial neural networks
Publications on the topic (other references)
  • Abrukov VS, Nikolayev YG, Makarov D., Sergeev AA, Karlovic E. Development of models of social phenomena by means of "Data Mining". In the book.: A sociological diagnosis of culture Russian society of the second half of XIX - beginning of XXI century.: All-Russian Conference "The third reading on the history of Russian sociology" (June 20-21, 2008, St. Petersburg) / Edited by V. Kozlovskogoyu St. Petersburg.: Intersotsis, 2008, pp. 49-55. ISBN: 978-5-94348-051-5.
  • VS Abrukov, YG Nikolaev, DN Makarov, AA Sergeev, EV Karlovic. Application of Data Mining to study the incompletely specified systems / Journal Chuvash University, № 2, 2008, pp. 233-241.
  • VS Abrukov, YG Nikolaev, LS Abrukova, DA Troeshestova, AA Sergeev, DN Makarov. Development of models of certain incomplete systems using self-organizing Kohonen maps / Journal Chuvash University, № 2, 2008, pp. 241-246.
  • V.S. Abrukov, Ja.G. Nikolaeva, D.N. Makarov, A.A. Sergeev, E.V. Karlovich. Development of Computing Models of Social Phenomena on Example of Family Relations by Means of Data Mining. Publishing date: August 15, 2008; Source: SciTecLibrary.ru: http://www.sciteclibrary.ru/texsts/eng/stat/st2404eng.pdf
  • Abrukov VS, Troeshestova DA, Chernov AS, Pavlov RA, Smirnov EV, Malinin GI, Volkov ME Application of Artificial Neural Networks for Solution of Scientific and Applied Problems for Combustion of Energetic Materials. In Book "Advancements in Energetic Materials and Chemical Propulsion / Ed. By Kenneth K. Kuo and Juan Dios Rivera, Begell House, Inc. Of Redding, USA, Connecticut, 2007.-816 pp., pp. 268-283.
  • V. G. Schetinin, V. S. Abrukov and A. I. Brazhnikov. A method for synthesizing neural-network models under incomplete data. / / Optoelectronics, Instrumentation and Data Processing. Allerton Press, Inc., 2007, Volume 43, Number 5/October 2007, pp. 433-440.
  • Abrukov V.S., Malinin G.I., Volkov M.E. Makarov D.N., Ivanov P.V. Application of artificial neural networks for creation of "black box" models of energetic materials combustion. In Book "Advancements in Energetic Materials and Chemical Propulsion / Ed. By Kenneth K. Kuo and Keiichi Hori, Begell House, Inc. Of Redding, USA, Connecticut, 2008.-1136 pp., pp. 377-386.
  • VS Abrukov, YG Nikolaev. Quantitative and qualitative methods: join and run! SOCIS (Social Research), Moscow, 2010, N 1, pp. 142-145.
  • Victor S. Abrukov, E. V. Karlovich, V. N. Afanasyev, Yu. V. Semenov, & S. V. Abrukov. Sreation of propellant combustion models by means of data mining tools / / International Journal of Energetic Materials and Chemical Propulsion. - 2010 (2011 issued). - № 9 (5). - PP. 1-12.
Description of previous and present experience in International Cooperation Two science contracts with the Office of Naval Research (USA) in 1996 and 1999. Grant of National University of Singapore (NUS) Eastern Europe Research Scientists & Students Exchange & Collaboration Program (2007). NATO Advanced Study Institutes: Canada, 2001; Italy, 2001; Turkey, 2002; Portugal, 2003, Turkey, 2009.
Previous participation in EU’s Framework Programme projects