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Numeral Recognition Using Statistical Methods Comparison Study

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Ordinary Methods (LS,IV) and Robust Methods (2SWLS,LTS,RA) to estimate the Parameters of ARX(1,1,1) Model for Electric Loads

 

Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Optimization of Lovastatin Production from A Local Isolate of Aspergillus terreus A50 in Solid State Fermentation by Classical and Statistical Methods

Lovastatin is one of the most important compounds that is produced from some filamentous fungi, being employed in the reduction of hypocholesterolemia. The results of screening, after the collection of seventy-three local fungal isolates from different areas, demonstrated that the local isolate Aspergillus terreus A50 was the best isolate for lovastatin production, with a concentration of 12.66 µg/ml, through the submerged fermentation. Lovastatin produced from A. terreus A50 showed antimicrobial activities against a Candida albicans isolate. Solid state fermentation (SSF) was the best system to produce the highest yield of lovastatin by A. terreus A50 as compared to the submerged fermentation (SmF)

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Statistical Approximation Operators

   In this paper we obtain some statistical approximation results for a general class of maxproduct operators including the paused linear positive operators.

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparative Statistical Analysis

In this paper, a statistical analysis compared the pattern of distribution of spending on various goods and services and to identify the main factors that control the rates of spending between the survey of social and economic status of families in Iraq for the year (2007) and the survey of Iraq knowledge net work (IKN) for the year (2011), which were carried out by the Central Bureau  of Statistics through the use of factor analysis and cluster analysis, using the ready statistical software package ready (SPSS) to gain access to the results.

 

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Comparison of Three DNA Extraction Methods for Detection Echinococcus granulosus Isolated from Sheep and Cows

Background: Hydatosis caused by Echinococcus granulosus dog tap worm is zoonotic infection and economic importance and to public health constitutes a major threat in certain regions of the Middle East. There is an establishment of preventive and control strategy for characterization of E.granulosus in all endemic area which is essential in all molecular studies, to check the DNA of the parasite.
Objective: Our study aimed to obtain the best from three extractions DNA methods from hydatid cyst protoscolecses isolated from sheep in Al-shawlla abattoir in Baghdad.
Subjects and Methods: Three methods were used to extract DNA samples (boiling, crushing and commercial) DNA samples were performed with electrophoreses on 1.3% agarose. Rega

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)

In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of classical method and optimization methods for estimating parameters in nonlinear ordinary differential equation

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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Maximum Likelihood and Bayesian Methods For Estimating The Gamma Regression With Practical Application

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Comparison of Single and Group Bored Piles Settlement Based on Field Test and Theoretical Methods

 Bored piles settlement behavior under vertical loaded is the main factor that affects the design requirements of single or group of piles in soft soils. The estimation of bored pile settlement is a complicated problem because it depends upon many factors which may include ground conditions, validation of bored pile design method through testing and validation of theoretical or numerical prediction of the settlement value. In this study, a prototype single and bored pile group model of arrangement (1*1, 1*2 and 2*2) for total length to diameter ratios (L/D) is 13.33 and clear spacing three times of diameter, subjected to vertical axial loads. The bored piles model used for the test was 2000

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Car Logo Image Extraction and Recognition using K-Medoids, Daubechies Wavelets, and DCT Transforms

     Recognizing cars is a highly difficult task due to the wide variety in the appearance of cars from the same car manufacturer. Therefore, the car logo is the most prominent indicator of the car manufacturer. The captured logo image suffers from several problems, such as a complex background, differences in size and shape, the appearance of noise, and lighting circumstances. To solve these problems, this paper presents an effective technique for extracting and recognizing a logo that identifies a car. Our proposed method includes four stages: First, we apply the k-medoids clustering method to extract the logo and remove the background and noise. Secondly, the logo image is converted to grayscale and also converted to a binary imag

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