China
Africa
Explore chapters and articles related to this topic
I
Published in Carl W. Hall, Laws and Models, 2018
HENRY, William, 1774-1836, English chemist LANGMUIR, Irving, 1881-1957, American chemist TELLER, Edward, twentieth century (b. 1908), Hungarian American physicist Sources: Chemical Engineering 102(11):92-102, Nov. 1995; Menzel, D. H. 1960. See also BRUNNER-EMMETT-TELLER; FREUNDLICH; HARKINS-JURA; HENRY; LANGMUIR ITERATED LOGARITHM, LAW OF THE There are quite a few generalizations with regard to the expression and application of this law, many of which are quite complicated, and it is a modification of the strong law of large numbers. The law of integrated logarithms for the square of independent variables has served well as a starting point for the applicability to sequences of dependent random variables. The law deals with the sums of independent and ideally distributed random variables, xi, with i = 1, 2, 3, ... with: Ex1 = and var x1 = E(x1 – )2 = 2 where E = expected value = variance Keywords: distributed, independent, random, variables Sources: Hazewinkel, M. 1987; Kotz, S. and Johnson, N. L. 1983. See also KOMOGOROV; LARGE NUMBER; STRONG LAWS
Identification and Entity Authentication
Published in Alfred J. Menezes, Paul C. van Oorschot, Scott A. Vanstone, Handbook of Applied Cryptography, 2018
Alfred J. Menezes, Paul C. van Oorschot, Scott A. Vanstone
10.34 Remark (asymptotic concepts vs. practical protocols) The asymptotic conditions for soundness specified in Note 10.33 have little meaning in practice, e.g., because big-O notation is not applicable once fixed values are assigned to parameters. Indeed, zero-knowledge is a theoretical concept; while complexity-theoretic definitions offer guidance in selecting practical security parameters, their significance diminishes when parameters are fixed. Regarding Note 10.33, if t =1 is viewed as the instantiation of a non-constant parameter (e.g., the iterated logarithm of n), then t = 1 will suffice for all practical purposes; consider n = 1024, t = [lg4n] =1.
Stochastic Processes
Published in Athanasios Christou Micheas, Theory of Stochastic Objects, 2018
Laws of iterated logarithm Brownian motion satisfies lim supt→∞|Bt|/2tln(lnt)=1a.s.,
Instantiation of the multi-viewpoints ontology from a resource
Published in International Journal of Computers and Applications, 2022
Ouahiba Djama, Zizette Boufaida
So, the average consumption of the verification time of the semantic constraints to align the resource elements with the ontology elements allows calculating how complex those three examples are. We notice that all the examples show an iterated logarithm complexity, according to the formula: Log* (n). This is because the proposed approach represents an iterated algorithm.