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«INFORMATICS AND APPLICATIONS»
Scientific journal
Volume 7, Issue 4, 2013

Content | Abstract | About  Authors

References

STUDY OF THE DYNAMICS OF MULTIDIMENSIONAL STOCHASTIC SYSTEMS BASED ON ENTROPY MODELING.

  • A. N. Tyrsin   Science and Engineering Center «Reliability and Resource of Large Systems and Machines», Ural Branch, Russian Academy of Sciences, Yekaterinburg 620049, Russian Federation, at2001@yandex.ru
  • O. V. Vorfolomeeva  Chelyabinsk State University, Chelyabinsk 454001, Russian Federation, ya.olga.work@yandex.ru

References

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A LIMIT THEOREM FOR GEOMETRIC SUMS OF INDEPENDENT NONIDENTICALLY DISTRIBUTED RANDOM VARIABLES AND ITS APPLICATION TO THE PREDICTION OF THE PROBABILITIES OF CATASTROPHES IN NONHOMOGENEOUS FLOWS OF EXTREMAL EVENTS.

  • M. E. Grigor’eva  Parexel International, Moscow 121609, Russian Federation, maria2grigoryeva@yandex.ru
  • V. Yu. Korolev  Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, victoryukorolev@yandex.ru
  • I. A. Sokolov   Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, isokolov@ipiran.ru

References

  1. Korolev, V. Yu., and I.A. Sokolov. 2005. Nekotorye voprosy analiza katastroficheskikh riskov, svyazannyh s neodnorodnymi potokami ekstremal’nykh sobytiy [Some problems of the analysis of catastrophic risks related to nonhomogeneous flows of extremal events]. Sistemy i sredstva informatiki. Special’nyj vypusk “Matematicheskie metody v informacionnyh tehnologijah” [Systems andMeans of Informatics. Special Issue “Mathematical Methods and Models of Informatics”]. Moscow: IPI RAN. 109–125.
  2. Korolev, V. Yu., I.A. Sokolov, A. S. Gordeev, M.E. Grigor’eva, S. V. Popov, and N.A. Chebonenko. 2006. Nekotorye metody analiza vremennykh kharakteristik katastrof v neodnorodnykh potokakh ekstremal’nykh sobytiy [Some methods for the analysis of temporal characteristics of catastrophes in nonhomogeneous flows of extremal events]. Sistemy i sredstva informatiki. Special’nyy vypusk “Matematicheskie metody v informatsionnykh tehnologijakh” [Systems and Means of Informatics. Special Issue “Mathematical methods in information technologies”]. Moscow: IPI RAN. 5–23.
  3. Korolev, V. Yu., I.A. Sokolov, A. S. Gordeev, M. E. Grigor’eva, S. V. Popov, and N.A. Chebonenko. 2007. Nekotorye metody prognozirovaniya vremennykh kharakteristik riskov, svyazannykh s katastroficheskimi sobytiyami [Some methods for the prediction of the temporal characteristics of risks related to catastrophic events]. Aktuariy [Actuary] 1:34–40.
  4. Korolev, V. Yu., and I.A. Sokolov. 2008. Matematicheskie modeli neodnorodnykh potokov ekstremal’nykh sobytiy [Mathematical models of nonhomogeneous flows of extremal events]. Moscow: TORUS PRESS. 200 p.
  5. Korolev, V. Yu., and S. Ya. Shorgin. 2011. Matematicheskie metody analiza stokhasticheskoy struktury informatsionnykh potokov [Mathematical methods for the analysis of the stochastic structure of information flows]. Moscow: IPI RAN. 130 p.
  6. Korolev, V. Yu., A. V. Chertok, A. Yu. Korchagin, and A.K. Gorshenin. 2013. Veroyatnostno-statisticheskoe modelirovanie informatsionnykh potokov v slozhnykh finansovykh sistemakh na osnove vysokochastotnykh dannykh [Probability and statistical modeling of information flows in complex financial systems based on highfrequency data]. Inform. Appl. 7(1):12–21.
  7. Kalashnikov, V. 1997. Geometric sums: Bounds for rare events with applications. Dordrecht–Boston–London: Kluwer Academic Publs. 288 p.
  8. Korolev, V. Yu., V. E. Bening, and S. Ya. Shorgin. 2011. Matematicheskie osnovy teorii riska [Mathematical foundations of risk theory]. 2nd ed. Moscow: Fizmatlit. 620 p.
  9. Korolev, V. Yu. 1994. Convergence of random sequences with the independent random indices. I. Theory Probab. Appl. 39(2):282–97.
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THE DISTRIBUTION OF THE RETURN TIME FROM THE SET OF OVERLOAD STATES TO THE SET OF NORMAL LOAD STATES IN A SYSTEM   M|M|1|<L,H>|<H,R>    WITH HYSTERETIC LOAD CONTROL .

  • Yu. V. Gaidamaka   Peoples’ Friendship University of Russia, Moscow 117198, Russian Federation, ygaidamaka@sci.pfu.edu.ru
  • A. V. Pechinkin  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, apechinkin@ipiran.ru
  • R. V. Razumchik   Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, rrazumchik@ieee.org
  • A. K. Samuylov  Peoples’ Friendship University of Russia, Moscow 117198, Russian Federation, asam1988@gmail.com
  • K. E. Samouylov  Peoples’ Friendship University of Russia, Moscow 117198, Russian Federation, ksam@sci.pfu.edu.ru
  • I. A. Sokolov  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, isokolov@ipiran.ru
  • E. S. Sopin  Peoples’ Friendship University of Russia, Moscow 117198, Russian Federation, sopin2eduard@yandex.ru
  • S. Ya. Shorgin  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, sshorgin@ipiran.ru

References

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ABOUT ONE TASK OF OVERLOAD CONTROL.

  • M. G. Konovalov   Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, mkonovalov@ipiran.ru

References

  1. Konovalov, M.G. 2010. Oplanirovanii potokov v sistemakh vychislitel’nykh resursov [On task flow planning in computional resource systems]. Inform. Appl. 4(2):3–12.
  2. Konovalov, M. 2010. Multiagent model for jobs flows planning and pricing in distributed computing systems. 2010 Congress (International) on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). ICUMTT, ICUMT-CS and Associated Workshops Proceedings. CDROM. IEEE, Catalog Number CFP1063G-CDR. ISBN 978-1-4244-7286-4. Report 1569339397.
  3. Konovalov, M.G., Yu. E.Malashenko, and I. A. Nazarova.  2011. Job control in heterogeneous computing systems. J. Comput. Syst. Sc. Int. 50(2):220–37.
  4. Konovalov, M.G. 2012. Optimizatsiya raboty vychislitel’nogo kompleksa s pomoshch’yu imitatsionnoy modeli i adaptivnykh algoritmov [Computer system optimization using simulation model and adaptive algorithms]. Inform. Appl. 6(1):37–48.
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FUNCTIONS OPTIMIZATION OF LAB - CONTRAST GRADED TRANSFORMATION.

  • O. P. Arkhipov   Oryol Branch, Institute of Informatics Problems, Russian Academy of Sciences, Oryol 302025, Russian Federation, arkhipov12@yandex.ru
  • Z. P. Zykova  Oryol Branch, Institute of Informatics Problems, Russian Academy of Sciences, Oryol 302025, Russian Federation, zykzoya@yandex.ru

References

  1. Arkhipov, O. P., and Z. P. Zykova. 2008. Dopechatnoe testirovanie individual’nogo zritel’nogo vospriyatiya [Preprinting test of individual visual perception]. Herald of Computer and Information Technologies 12:2–8.
  2. Arkhipov, O.P., and Z. P.Zykova. 2010. Integraciya geterogennoy informatsii o tsvetnykh pikselyakh i ikh tsvetovospriyatii [Integration of heterogeneous information about color pixels and their color perception]. Inform. Appl. 4(4):14–25.
  3. Arkhipov, O. P., and Z.P. Zykova. 2010. Funktsional’noe opisanie individual’nogo tsvetovospriyatiya [Characteristics of color perceptual space]. Informatsionnye sistemy i tekhnologii [Information Systems andTechnologies] 5:5–12.
  4. Arkhipov, O. P., and Z.P. Zykova. 2010. RGB kharakterizatsija prostranstva tsvetovospriyatiya [RGBcharacterization of color perception space]. Systems and Means of Informatics 20(1):73–90.
  5. Arkhipov, O. P., and Z.P. Zykova. 2011. Mnogokriterial’nyy vybor testovogo mnozhestva pri issledovanii tsvetovospriyatiya [Multicriterion choice of test set when studying the color perception]. Informatsionnye tekhnologii [Information Technologies] 2:67–73.
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  7. Arkhipov, O. P., and Z.P. Zykova. 2012. Personifitsirovannoe preobrazovanie predstavleniy tsvetnykh izobrazheniy na monitore PEVM [Personified transformation of color images presentations on a PC monitor]. Systems and Means of Informatics 22(1):22–37.
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  9. Arkhipov, O. P., and Z.P. Zykova. 2013. Korrektsiya detalizatsii predstavleniy RGB-izobrazheniy na periferiynykh ustroystvakh PEVM [Correcting of detail presentations of RGB-images on peripherals of PC]. Informatsionnye Tekhnologii [Information Technologies] 2:56–60.
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METHOD OF BIBLIOGRAPHIC INFORMATION EXTRACTION FROM FULL-TEXT DESCRIPTIONS OF INVENTIONS.

  • I. M. Zatsman   Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, iz_ipi@a170.ipi.ac.ru
  • V. A. Havanskov  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, havanskov@a170.ipi.ac.ru
  • S.K. Shubnikov  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, sergeysh50@yandex.ru

References

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  10. Minin, V.A., I.M. Zatsman, M.G. Kruzhkov, and T. P. Norekjan. 2013. Metodologicheskie osnovy sozdaniya informatsionnykh sistem dlya vychisleniya indikatorov tematicheskikh vzaimosvyazey nauki i tekhnologiy [Methodological basis for the creation of information systems for the calculation of indicators of thematic linkages between science and technology]. Inform. Appl. 7(1):70– 81.
  11. Minin, V.A., I.M. Zatsman, V.A. Havanskov, and S.K. Shubnikov. 2013. Arkhitekturnye resheniya dlya sistem vychisleniya indikatorov tematicheskikh vzaimosvyazey nauki i tekhnologiy [Information system conceptual decisions for assessment of linkages between science and technologies]. Systems and Means of Informatics 23(2):260–83.
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ON CONVERGENCE OF THE DISTRIBUTIONS OF RANDOM SUMS TO SKEW EXPONENTIAL POWER LAWS.

  • M. E. Grigor’eva  Parexel International,Moscow 121609, Russian Federation, maria-grigoryeva@yandex.ru
  • V. Yu. Korolev  Faculty of Computational Mathematics and Cybernetics, M.V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, victoryukorolev@yandex.ru

References

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INVERSION OF SPHERICAL RADON TRANSFORM IN THE CLASS OF DISCRETE RANDOM FUNCTIONS.

  • O. V. Shestakov   Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, oshestakov@cs.msu.su
  • M. G. Kuznetsova  Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, m.g.kuznetsova@gmail.com
  • I. A. Sadovoy   Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, isadovoy@gmail.com

References

  1. Louis, A.K., and E.T. Quinto. 2000. Local tomographic methods in Sonar. Surveys on solution methods for inverse problems. Vienna: Springer. 147–54.
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THE INFORMATION-ANALYTICAL COMPUTER SYSTEM “MEGALITH” IN OPTIMIZATION OF THE DIAGNOSIS AND TREATMENT OF UROLITHIASIS.

  • M. P. Krivenko  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, mkrivenko@ipiran.ru
  • S. A. Golovanov  Research Institute of Urology, Moscow 105425, Russian Federation, sergeygol124@mail.ru
  • P. A. Savchenko  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, psavchenko@ipiran.ru
  • A. V. Sivkov  Research Institute of Urology, Moscow 105425, Russian Federation, uroinfo@yandex.ru
  • A. P. Suchkov  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, asuchkov@ipiran.ru

References

  1. Ramello, A., C. Vitale, and D. Marangella. 2000. Epidemiology of nephrolithiasis. J.Nephrol. 13(Suppl. 3):45– 50.
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  3. Pearle, M. S., E.A. Calhoun, and G.C. Curhan. 2005. Urologic diseases inAmerica project:Urolithiasis. J.Urology 173:848–57.
  4. Lieske, J.C., L. S. Pena de la Vega, J.M. Slezak, E. J. Bergstralh; C.L. Leibson, K. L. Ho, and M.T. Gettman. 2006. Renal stone epidemiology in Rochester,Minnesota: An update. Kidney Int. 69(4):760– 68.
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  6. Yasui, T, M. Iguchi, S. Suzuki, and K. Kohri. 2008. Prevalence and epidemiological characteristics of urolithiasis in Japan: National trends between 1965 and 2005. Urology 71(2):209–13.
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  11. Routh, J.C., D.A. Graham, and C. P. Nelson. 2100. Epidemiological trends in pediatric urolithiasis at United States freestanding pediatric hospitals. J. Urology 184(3):1100–4.
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ANALYSIS OF DATA HOMOGENEITY OF THE CHEMICAL COMPOSITIONS OF STONES IN CASE OF UROLITHIASIS.

  • M. P. Krivenko  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, mkrivenko@ipiran.ru
  • S. A. Golovanov  Research Institute of Urology, Moscow 105425, Russian Federation, sergeygol124@mail.ru
  • A. V. Sivkov  Research Institute of Urology, Moscow 105425, Russian Federation, uroinfo@yandex.ru

References

  1. Ramello, A., C. Vitale, and D. Marangella. 2000. Epidemiology of nephrolithiasis. J. Nephrol. 13(3):45–50.
  2. Pak, C.Y., M. I. Resnick, and G.M. Preminger. 1997. Ethnic and geographic diversity of stone disease. Urology 50(4):504–7.
  3. Takasaki, E. 1986. Chronologocal variation in the chemical composition of upper urinary tract calculi. J. Urology 136(1):5–9.
  4. Trinchieri, A., F. Coppi, E. Montanari, A. Del Nero, G. Zanetti, and E. Pisani. 2000. Increase in the prevalence of symptomatic upper urinary tract stones during the last ten years. Eur. Urol. 37:23–25.
  5. Arias Funez, F., E. Garcia Cuerpo, F. Lovaco Castellanos, A. Escudero Barrilero, S. Avila Padilla, and J. Villar Palasi. 2000. Epidemiologia de la litiasis urinaria en nuestraUnidad. Evolucion en el tiempo y factores predictivos. [Epidemiology of urinary lithiasis in our unit. Clinical course in time and predictive factors]. Arch. Esp. Urol. 53(4):343–47.
  6. Tiktinskij, O. L., and V. P. Aleksandrov. 2000. Mochekamennaya bolezn’ [Urolithiasis]. St. Petersburg, Russia: Piter. 379 p.
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  15. Baringhaus, L., andC.Franz. 2004.On a newmultivariate two-sample test. J. Multivariate Anal. 88:190–206.

PREDICTION AND CLASSIFICATION METHOD FOR CENSORED DATA.

  • T. V. Zakharova   Department of Mathematical Statistics, Faculty ofComputational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, lsa@cs.msu.ru
  • E. M. Abramova  Department of Mathematical Statistics, Faculty ofComputational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow 119991, Russian Federation, houselake@gmail.com

References

  1. Afifi, A.A., and S. P Azen. 1979. Statistical analysis. A computer oriented approach. 2nd ed. New York–San Francisco– London: A Subsidiary of Harcourt Brace Jovanovich Publs.
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  3. Rebrova, O. Ju. 2002. Statisticheskiy analiz meditsinskikh dannykh. Primenenie paketa prikladnykh programm STATISTICA [Statistical analysis of medical data. Application software package STATISTICA]. Moscow: Media Sfera. 312 p.
  4. Halafjan, A.A. 2008. Sovremennye statisticheskie metody meditsinskikh issledovaniy [Advanced statistical methods for medical research].Moscow: Editorial URSS. 320 p.
  5. Zakharova, T.V., and M. V.Zoloeva. 2007. Prognozirovanie sostoyaniya patsientov [The patients’ conditions forecast]. Obozrenie prikladnoi i promyshlennoy matematiki [Review of Applied Industrial Mathematics] 14:298–99.
  6. Dranitsyna, M.A., and T. V. Zakharova. 2009. Klassifikatsiya sostoyaniy patsientov s tsel’yu prognozirovaniya rezul’tatov lecheniya [Classification of patients’ conditions to forecast the outcomes of the treatment]. Obozrenie prikladnoy i promyshlennoymatematiki [Review of Applied Industrial Mathematics] 16:840–41.
  7. Dranitsyna, M.A., and T. V. Zakharova. 2013. Diskriminantnyy analiz dlya klassifikatsii i prognozirovaniya rezul’tatov lecheniya [Discriminant analysis for classification and forecasting outcomes of the treatment]. Systems and Means of Informatics 23(2):89–95.

CONCEPTUAL DECLARATIVE PROBLEM SPECIFICATION AND SOLVING IN DATA INTENSIVE DOMAINS.

  • L. Kalinichenko  Institute of Informatics Problems, Russian Academy of Sciences,Moscow 119333, Russian Federation, leonidandk@gmail.com
  • S. Stupnikov  Institute of Informatics Problems, Russian Academy of Sciences,Moscow 119333, Russian Federation, ssa@ipi.ac.ru
  • A. Vovchenko  Institute of Informatics Problems, Russian Academy of Sciences,Moscow 119333, Russian Federation, itsnein@gmail.com
  • D. Kovalev  Institute of Informatics Problems, Russian Academy of Sciences,Moscow 119333, Russian Federation, dm.kovalev@gmail.com

References

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PROBABILISTIC METHODS FOR SELF - CORRECTING HARDWARE DESIGN.

  • S. Dolev  Department of Computer Science, Ben-Gurion University, Beer-Sheva 84105, Israel, dolev@cs.bgu.ac.il
  • S. Frenkel  Institute of Informatics Problems, Russian Academy of Sciences, Moscow 119333, Russian Federation, Moscow Institute of Radio, Electronics, and Automation  «MIREA», Moscow 119454, Russian Federation, fsergei@mail.ru
  • D.E. Tamir  Department of Computer Science, Texas State University, San-Marcos, TX 78666, USA, dt19@txstate.edu

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