Most of the big companies and especially the intillictual ones become a ware of an important fact, and That is, The intillictual capital in new global economy, is a new source for Them & This Valuable source exceed in importance. The other company's sources.

The Traditional disclouser systemes are unable to supply the decisions makers with the Fundimental information require to handel the on going operations which are based on Knowledge and intangible source. But the measuring of this source and the disclose for it in the financial Statements will lead to gain features Statements which will benefit all the parties and lead to make the value of the company great.

And as a resul

Rapid, reproducible and accurate method has been developed for the assay for of mebendazol (MBZ) residual assay. The method is based on alkaline hydrolysis of MBZ with sodium hydroxide then oxidation with N-bromosuccinimide (NBS) followed by coupling with 4-Bromoaniline (4-BA) to yield a highly colored product absorbed at maximum 434 nm. Regression analysis of linearity range was found (0.6-2.8) µg.ml^-1.  The optimum conditions that affect the oxidation were studied. The developed method was found to be precise with mean value of relative standard deviation (1.153- 1.303) and accurate with relative error (-0.5940-1.7821) .The calculated molar absorptivity and sandal sensitivity values of (29825 L.mol^-1.cm

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

The principal components analysis is used in analyzing many economic and social phenomena; and one of them is related to a large group in our society who are the university instructors. This phenomenon is the delay occurred in getting university instructor to his next scientific title. And as the determination of the principal components number inside the principal components depends on using many methods, we have compared between three of these methods that are: (BARTLETT, SCREE DIAGRAM, JOLLIFFE).

     We concluded that JOLLIFFE method was the best one in analyzing the studying phenomenon data among these three methods, we found the most distinguishing factors effecting on t

Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta

DBN Rashid, 2012 - Cited by 2

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a