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Silvia Gašincová, Juraj Gašinec, Gabriel Weiss and Slavomír Labant

statistics, the approach based of influence functions. J.Willey&Sons, New York, 1986. [6] HAMPEL, F.: Contribution to the theory of robust estimation. PhD. Thesis, Univ. of California, 1968. [7] HOBST, E., HOBSTOVÁ, M.: Carl Friedrich Gauss - the founder of modern mathematics. Advances in Mathematics, Physics and Astronomy, Vol. 52 (2007), No. 4, 296-307, Nurnberg, 2007. [8] HUBER, P.J.: Robust statistics. Willey&Sons, New York, 1981. [9] HUBER, P.J.: Robust estimation of a location parameter. Ann Math Stat 35

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Vadim V. Romanuke

Abstract

Adjustment of an unknown parameter of the multistage expert procedure is considered. The lower and upper boundaries of the parameter are counted to be known. A key condition showing that experts’ estimations are satisfactory in the current procedure is an inequality, in which the value based on the estimations is not greater than the parameter. The algorithms of hard and soft adjusting are developed. If the inequality is true and its both terms are too close for a long sequence of expert procedures, the adjusting can be early stopped. The algorithms are reversible, implying inversion to the reverse inequality and sliding up off the lower boundary.

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Dalil Ichalal, Benoît Marx, José Ragot and Didier Maquin

References Akhenak, A., Chadli, M., Ragot, J. and Maquin, D. (2008). Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model, 16th Mediterranean Conference on Control and Automation, Ajaccio, France , pp. 286-291. Corless, M. and Tu, J. (1998). State and input estimation for a class of uncertain systems, Automatica   34 (6): 757-764. Darouach, M., Zasadzinski, M. and Xu, S. (1994). Full-order observers for linear systems with unknown

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Apáthy M. Sándor

time estimation , in 2012 23rd International Workshop on Database and Expert Systems Applications, Sept 2012, pp. 101–105. [8] F. V. R enatus , The Military Institutions of the Romans (De Re Militari), Book I: The Selection and Training of New Leviess, english translation by John Clarke ,, 3 ed., 1767. [9] A. K. S kidmore , A comparison of techniques for calculating gradient and aspect from a gridded digital elevation model , International Journal of Geographical Information Systems, 3 (1989), pp. 323–334. [10] E. R. S wanson , Geometric dilution

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Robert Duchnowski and Zbigniew Wiśniewski

, Manuscripta Geodaetica, Vol. 10, No 4, pp. 172-178. Duchnowski R., (2008): R-estimation and its application to the LS adjustment , Bollettino di Geodesia e Scienze Affini, Vol. 67, No 1, pp. 17-32. Duchnowski R., (2009): Geodetic Application of R-estimation - Levelling Network Examples , Technical Sciences, Vol. 12, pp. 135-144. Duchnowski R., (2010): Median-based estimates and their application in controlling reference mark stability , Journal of Surveying Engineering, Vol. 136, No 2, pp. 47

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H. Abouaïssa and H. Majid

References 1. Abouaissa, H., V. Iordanova. Algebraic Methods for Traffic Flow Densities Estimation. - a. Cybernetics and Information Technologies, Vol. 13, 2013, No 4, pp. 5-17. 2. Diop, S., M. Fliess. On Nonlinear Observability. - In: Proc. of 1st Europ. Control. Conf., a. Hermes, 1991, pp. 152-157. 3. Diop, S., M. Fliess. Nonlinear Observability, Identifiability and Persistent Trajectorie. - In: a. Proc. of 26th IEEE Conf. Decision Control, Brighton, 1991, pp. 714-719. 4. Fillip o v, A. F

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Ryszard Beniak

(11): 231-234 (2007). [4] Beniak R., A formalised variable structure method of modelling converter drives. Electrical Review 3: 83-87 (2009). [5] Beniak R., Comparison of Gradient and Gradientless Methods of the Dynamic Estimation of Static Scherbius Drive Parameters. Zeszyty Naukowe Elekryka No 788/91 SME'98, Łódź pp: 189-194 (1998). [6] Beniak R., The Estimation of the Brushless DC Motor Parameters by Use of Modified Jeeves & Hook Method , International Conference on Electrical Machines, ICEM'2002, on CD (25

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Theresa Rienmüller, Michael Hofbaur, Louise Travé-Massuyès and Mehdi Bayoudh

References Ackerson, G. and Fu, K. (1970). On state estimation in switching environments, IEEE Transactions on Automatic Control 15 (1): 10-17. Bayoudh, M., Travé-Massuyès, L. and Olive, X. (2008). Hybrid systems diagnosis by coupling continuous and discrete event techniques, Proceedings of the IFAC World Congress, Seoul, Korea , pp. 7265-7270. Benazera, E. and Travé-Massuyès, L. (2009). Set-theoretic estimation of hybrid system configurations, IEEE Transactions on Systems, Man and Cybernetics, Part

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Pawel Tomczak and Jakub Traczyk

Abstract

The anchoring heuristic refers to phenomena when an arbitrary number affects subsequent numerical estimations. Oppenheimer, LeBoeuf and Brewer (2008) showed that it is not necessary for the anchor to be a numerical value (i.e., the act of drawing lines of different length effectively shifts numerical estimations), yet current models describing the anchoring heuristic do not fully account for the mechanism of non-numerical anchoring. However, this effect shows similarity to the basic anchoring effect - obtained without the comparative question and based on the availability of the given number in working memory. In this study, we attempt to verify whether those two effect share the same psychological mechanism. In Experiment 1, we show that non-numerical anchoring based on magnitude priming cannot be obtained when the lines are just observed. The examined mechanism proves to be dependent on the act of drawing, displaying limitations similar to the basic anchoring effect, previously pointed out by Brewer and Chapman (2002). By using the same numerical anchors in different size formats, in Experiment 2 we showed that anchoring based on magnitude priming occurs even when the numerical values do not affect the estimations. The results are discussed in the light of a possible mechanism that underlies the investigated effect.

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H. Abouaïssa and V. Iordanova

Dimensional Systems. - In: Lecture Notes in Control Informat. Sci. T. Meurer, K. Graichen, E. D. Gilles, Eds. Vol. 322. 2005, 217-233. 7. Fliess, M. Analyse Non Standard du Bruit. - C. R. Acad. Sci. Paris, Ser. I, Vol. 342, 2006. 8. Fliess, M., C. Join, H. Sira-Ramíre z. Non-Linear Estimation is Easy. - International Journal of Modelling, Identification and Control, Vol. 3, 2008, No 5. 9. Gazi s, D. C., C. H. Knap p. On-Line Estimation of Traffic Densities from Times-Series of Flow and Speed Data. - Transportation Science