2,577 research outputs found

    Separation of variables in the generalized 4th Appelrot class

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    We consider the analogue of the 4th Appelrot class of motions of the Kowalevski top for the case of two constant force fields. The trajectories of this family fill the four-dimensional surface O^4 in the six-dimensional phase space. The constants of three first integrals in involution restricted to this surface fill one of the sheets of the bifurcation diagram in R^3. We point out the pair of partial integrals to obtain the explicit parametric equations of this sheet. The induced system on O^4 is shown to be Hamiltonian with two degrees of freedom having the thin set of points where the induced symplectic structure degenerates. The region of existence of motions in terms of the integral constants is found. We provide the separation of variables on O^4 and the algebraic formulae for the initial phase variables.Comment: LaTex, 16 pages, 1 figur

    Application of Simplified Models to Qualitative Geotechnical Analysis

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    The paper describes an approach for qualifying soil-structure systems behavior, using simple numeric models – β€œgeotoys”, reflecting the main features of the systems behavior and enabling numeric simulation of various case histories. Three case histories of major karstic sinkholes are analyzed to show that man-made structures above a karstic cavity prevent formation sinkhole. When plastic zones reach the structure periphery, the soil-structure system becomes unstable. Prior settlements could be negligible to serve as precursors. Another soil-footing-superstructure (SFSS) model is a 2D geotoy - an exact mathematical solution, used for multiple simulations (about 10,000) of SFSS sensitivity i.e., response to input parameters variations. The sensitivity was rated for each input-output pair [1]. The most interesting findings are the following: 1) SFSS stress state is very sensitive to soil strength parameters c and Ο†, which are responsible for formation of soil disruption zones (β€˜plastic zone’) under footing edges. 2) If a structure rests on a homogeneous soil base then it is practically insensitive to soil base compressibility i.e., soil modulus E variations. 3) 3D FEM analysis confirmed that 2D simulations can be used for qualitative SFSS analysis. 4) Geotoys can be used for case histories analysis, risk assessment, training practical intuition, education purposes and international exchange and cooperation

    Updating DL-Lite ontologies through first-order queries

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    In this paper we study instance-level update in DL-LiteA, the description logic underlying the OWL 2 QL standard. In particular we focus on formula-based approaches to ABox insertion and deletion. We show that DL-LiteA, which is well-known for enjoying first-order rewritability of query answering, enjoys a first-order rewritability property also for updates. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a nonrecursive datalog program. Such a program is readily translatable into a first-order query over the ABox considered as a database, and hence into SQL. By exploiting this result, we implement an update component for DLLiteA-based systems and perform some experiments showing that the approach works in practice.Peer ReviewedPostprint (author's final draft

    Seismic Behavior of Nailed Soil Massifs

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    Soil nailing technology can be successfully applied to strengthen natural soil massifs in seismic regions, provided adequate analysis is available. Conventionally, the design of soil nailing is performed iteratively: firstly parameters of nailing and their distribution are assigned, the safety factor of the nailed massif is calculated, if its value is less than 1 then nailing parameters are reassigned, etc. Such β€œtrial and error” approach is laborious and especially so, because different types of ULSs shall be analyzed. The method, discussed in the paper, is based on assumption that the effect of nailing in soil with internal cohesion c=c(x,y) could be simulated by equivalent internal cohesion Ξ”c=Ξ”c(x,y) (deficit) of unreinforced massif. Formulae for calculating nailing parameters are determined on the basis of deficit distribution. A MathCad code has been developed, examples are given. The method can be easily applied to assess seismic stability of nailed soil massifs

    ΠŸΡ€ΡΠΌΠΎΠ΅ Π½Π΅Ρ‡Π΅Ρ‚ΠΊΠΎΠ΅ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΠ΅ Β«Ρ†Π΅ΠΏΠΎΡ‡Π΅ΠΊΒ» финансовых рисков ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ

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    The object of the research is the diagnosis and evaluation of financial risks in order to create an effective risk management policy. The subject of the research is the methodology of direct fuzzy evaluation of financial risk β€œchains” of an organisation. The relevance of the problem is due, on the one hand, to the dynamic and chaotic macro-environment and the business environment of organisations, on the other hand, to the drawback of the analytical and expert methods used to assess financial risks. The former, moreover, imply statistical data processing and operate with quantitative measures. For the latter, the difficulty is the impossibility of their application in a short time interval. From the perspective of operational risk management, financial risks deserve special attention since the effective operation of the entire organisation depends on them. The purpose of the research is to form a methodology for direct fuzzy evaluation of financial risk β€œchains” of an organisation. The authors apply the methods of mathematical forecasting, fuzzy modelling, calculation of financial and economic indicators, and expert risk assessment. The proposed methodology consists of 12 stages, beginning with the analysis of business processes and the identification of financial risks of the organisation. The main stage is the construction of a fuzzy evaluation model and the calculation of indicators: the probability of occurrence and realization of risks and risky situations of the financial risk β€œchains”, and the degree of confidence of the calculations conducted. The final stage of the methodology is an analysis of the results obtained to adjust the selected development strategy of the organisation, and the choice of methods for managing identified financial risks bearing the most significant financial and economic losses. The authors conclude the developed methodology allows to accurately assess the threat of a certain risk β€œchain” and losses from the implementation of specific risk situations for any organisation in the conditions of dynamic changes in internal and external elements of the business environment. The advantage of the methodology should be considered in the comparability of the accuracy of the evaluation and the low cost of modelling.ΠžΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠΌ исслСдования выступаСт диагностика ΠΈ ΠΎΡ†Π΅Π½ΠΊΠ° финансовых рисков с Ρ†Π΅Π»ΡŒΡŽ создания эффСктивного риск-ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½Ρ‚Π°. ΠŸΡ€Π΅Π΄ΠΌΠ΅Ρ‚ΠΎΠΌ исслСдования являСтся ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ° Π½Π΅Ρ‡Π΅Ρ‚ΠΊΠΎΠ³ΠΎ прямого оцСнивания Β«Ρ†Π΅ΠΏΠΎΡ‡Π΅ΠΊΒ» финансовых рисков ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ. ΠΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠ°Ρ‚ΠΈΠΊΠΈ обусловлСна, с ΠΎΠ΄Π½ΠΎΠΉ стороны, Π΄ΠΈΠ½Π°ΠΌΠΈΡ‡Π½ΠΎΠΉ ΠΈ Ρ…Π°ΠΎΡ‚ΠΈΡ‡Π½ΠΎΠΉ ΠΊΠ°ΠΊ макросрСдой, Ρ‚Π°ΠΊ ΠΈ бизнСс-срСдой ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ, с Π΄Ρ€ΡƒΠ³ΠΎΠΉ β€” нСдостатками примСняСмых аналитичСских ΠΈ экспСртных ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² ΠΎΡ†Π΅Π½ΠΊΠΈ финансовых рисков. ΠŸΠ΅Ρ€Π²Ρ‹Π΅ ΠΏΡ€ΠΈ этом ΠΏΠΎΠ΄Ρ€Π°Π·ΡƒΠΌΠ΅Π²Π°ΡŽΡ‚ ΡΡ‚Π°Ρ‚ΠΈΡΡ‚ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΡƒ Π΄Π°Π½Π½Ρ‹Ρ… ΠΈ ΠΎΠΏΠ΅Ρ€ΠΈΡ€ΡƒΡŽΡ‚ количСствСнными ΠΌΠ΅Ρ‚Ρ€ΠΈΠΊΠ°ΠΌΠΈ. Для Π²Ρ‚ΠΎΡ€Ρ‹Ρ… Ρ‚Ρ€ΡƒΠ΄Π½ΠΎΡΡ‚ΡŒ Π·Π°ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ΡΡ Π² нСвозмоТности ΠΈΡ… примСнСния Π½Π° ΠΊΠΎΡ€ΠΎΡ‚ΠΊΠΎΠΌ Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠΌ ΠΈΠ½Ρ‚Π΅Ρ€Π²Π°Π»Π΅. Π‘ ΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ риск-ΠΌΠ΅Π½Π΅Π΄ΠΆΠΌΠ΅Π½Ρ‚Π° Π·Π°ΡΠ»ΡƒΠΆΠΈΠ²Π°ΡŽΡ‚ особого внимания финансовыС риски, ΠΏΠΎΡΠΊΠΎΠ»ΡŒΠΊΡƒ ΠΎΡ‚ Π½ΠΈΡ… зависит эффСктивноС Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ всСй ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ. ЦСль исслСдования Π·Π°ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ΡΡ Π² Ρ„ΠΎΡ€ΠΌΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ Π½Π΅Ρ‡Π΅Ρ‚ΠΊΠΎΠ³ΠΎ прямого оцСнивания Β«Ρ†Π΅ΠΏΠΎΡ‡Π΅ΠΊΒ» финансовых рисков ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ. Π˜ΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ матСматичСского прогнозирования, Π½Π΅Ρ‡Π΅Ρ‚ΠΊΠΎΠ³ΠΎ модСлирования, расчСта финансово-экономичСских ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ, экспСртной ΠΎΡ†Π΅Π½ΠΊΠΈ рисков. ΠŸΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌΠ°Ρ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ° состоит ΠΈΠ· 12 этапов, начинаСтся с Π°Π½Π°Π»ΠΈΠ·Π° бизнСс-процСссов ΠΈ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ финансовых рисков ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ. ΠžΡΠ½ΠΎΠ²Π½Ρ‹ΠΌ Π΅Π΅ этапом являСтся построСниС Π½Π΅Ρ‡Π΅Ρ‚ΠΊΠΎΠΉ ΠΎΡ†Π΅Π½ΠΎΡ‡Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ расчСт ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ: Π²Π΅Ρ€ΠΎΡΡ‚Π½ΠΎΡΡ‚ΡŒ возникновСния ΠΈ Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ рисков ΠΈ рисковых ситуаций Β«Ρ†Π΅ΠΏΠΎΡ‡ΠΊΠΈΒ» финансовых рисков, ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ увСрСнности ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠΌΡ‹Ρ… расчСтов. ΠšΠΎΠ½Π΅Ρ‡Π½Ρ‹ΠΉ этап ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ являСт собой Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Ρ… Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² с Ρ†Π΅Π»ΡŒΡŽ ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²ΠΊΠΈ Π²Ρ‹Π±Ρ€Π°Π½Π½ΠΎΠΉ стратСгии развития ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ, Π²Ρ‹Π±ΠΎΡ€Π° ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² управлСния выявлСнными финансовыми рисками, нСсущими Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ сущСствСнныС финансово-экономичСскиС ΠΏΠΎΡ‚Π΅Ρ€ΠΈ. Π‘Π΄Π΅Π»Π°Π½ Π²Ρ‹Π²ΠΎΠ΄ ΠΎ Ρ‚ΠΎΠΌ, Ρ‡Ρ‚ΠΎ разработанная ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ° позволяСт с высокой Ρ‚ΠΎΡ‡Π½ΠΎΡΡ‚ΡŒΡŽ ΠΎΡ†Π΅Π½ΠΈΡ‚ΡŒ ΡƒΠ³Ρ€ΠΎΠ·Ρƒ возникновСния ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Π½ΠΎΠΉ Β«Ρ†Π΅ΠΏΠΎΡ‡ΠΊΠΈΒ» рисков ΠΈ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ ΠΎΡ‚ Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½Ρ‹Ρ… рисковых ситуаций для любой ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ Π² условиях Π΄ΠΈΠ½Π°ΠΌΠΈΡ‡Π½Ρ‹Ρ… ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π²Π½ΡƒΡ‚Ρ€Π΅Π½Π½ΠΈΡ… ΠΈ Π²Π½Π΅ΡˆΠ½ΠΈΡ… элСмСнтов бизнСс-срСды. Π•Π΅ прСимущСством слСдуСт ΡΡ‡ΠΈΡ‚Π°Ρ‚ΡŒ ΡΠΎΠΏΠΎΡΡ‚Π°Π²ΠΈΠΌΠΎΡΡ‚ΡŒ точности ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠΉ ΠΎΡ†Π΅Π½ΠΊΠΈ ΠΈ Π½Π΅Π±ΠΎΠ»ΡŒΡˆΠΈΡ… Π·Π°Ρ‚Ρ€Π°Ρ‚ Π½Π° ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅
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