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Estimating the Rate of Occurrence of Extreme value process Using Classical and Intelligent Methods with Application: nonhomogeneous Poisson process with intelligent
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     In this paper, the propose is to use the xtreme value distribution as the rate of occurrence of the non-homogenous Poisson process, in order to improve the rate of occurrence of the non-homogenous process, which has been called the Extreme value Process. To estimate the parameters of this process, it is proposed to use the Maximum Likelihood method, Method of Moment and a smart method represented by the Artificial Bee Colony:(ABC) algorithm to reach an estimator for this process which represents the best data representation. The results of the three methods are compared through a simulation of the model, and it is concluded that the estimator of (ABC) is better than the estimator of the maximum likelihood method and method of moment in estimating the time rate of occurrence of the proposed Extreme value process. The research also includes a realistic application that deals with the operating periods of two successive stops for the raw materials factory from the General Company for Northern Cement / Badush Cement Factories (new) during the period from 1/4/2018 to 31/1/2019, in order to reach the time rate of factory stops.

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Wed Jun 01 2022
Journal Name
Res Militaris
Building the proposed Fama and French Six-Factor Model FF6M-DLE by adding the indebtedness factor and its reflection on the fair value of common stock
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The research aims to determine the required rate of return according to the Fama and French five-factor model, after strengthening it by adding the indebtedness factor to build the Fama and French six-factor model FF6M-DLE. The effect of the indebtedness factor on the company's profitability and the real value of the ordinary shares calculated according to the (equivalent ascertainment) model and its suitability with the company's situation, and an analysis of the fluctuation between the market value and the real value of the ordinary stocks.

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Publication Date
Mon May 15 2023
Journal Name
Iraqi Journal Of Science
Using Linear Local Dependence Measure to Study the factors that are Leading to the Growth of Preferring the Application in Private Universities of Iraq
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In this paper a measure of linear local dependence has been used between two
random variables and a study is conducted for the properties of this measure where
two examples of bivariate probability distributions has been considered, which are
bivariate Gumbel distribution and bivariate Beta-Stacy distribution, and applied on
data collected by using a questionnaire conducted to study the reasons for the
increase of application in private collages in Iraq. Five elements has been considered
as random variables and the dependence has been measured between every two
elements to estimate how correlated these elements are and their effect on the
application in private collages of Iraq generally and Baghdad specifically.<

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Publication Date
Mon May 16 2016
Journal Name
Far East Journal Of Mathematical Sciences (fjms)
MINIMIZING WAITING TIMES USING MULTIPLE FUZZY QUEUEING MODEL WITH SUPPLY PRIORITIES
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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
VoIP Speech Encryption System Using Stream Cipher with Chaotic Key Generator
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Recently, with the development multimedia technologies and wireless telecommunication, Voice over Internet Protocol, becomes widely used in communication between connecting people, VoIP allows people that are connected to the local network or the Internet to make voice calls using digital connection instead of based on the analog traditional telephone network. The technologies of Internet doesn’t give any security mechanism and there is no way to guarntee that the voice streams will be transmitted over Internet or network have not been intercepted in between. In this paper, VoIP is developed using stream cipher algorithm and the chaotic cryptography for key generator. It is based on the chaotic maps for generating a one-time rando

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Publication Date
Wed Mar 16 2022
Journal Name
2022 Muthanna International Conference On Engineering Science And Technology (micest)
A hybrid feature selection technique using chi-square with genetic algorithm
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Nuclear level density with proton resonance using Gaussian orthogonal ensemble theory
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The Gaussian orthogonal ensemble (GOE) version of the random matrix theory (RMT) has been used to study the level density following up the proton interaction with 44Ca, 48Ti and 56Fe.

A promising analysis method has been implemented based on the available data of the resonance spacing, where widths are associated with Porter Thomas distribution. The calculated level density for the compound nuclei 45Sc,49Vand 57Co shows a parity and spin dependence, where for Sc a discrepancy in level density distinguished from this analysis probably due to the spin  misassignment .The present results show an acceptable agreement with the combinatorial method of level density.

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