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jeasiq-2423
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squares method (FGLS) and the mean group method (MG) were used, and then the efficiency of the extracted estimators was compared in the case of mixed random parameters and the method that gives us the efficient estimator was chosen. Real data was applied that included the per capita consumption of electric energy (Y) for five countries, which represents the number of cross-sections (N = 5) over nine years (T = 9), so the number of observations is (n = 45) observations, and the explanatory variables are the consumer price index (X1) and the per capita GDP (X2). To evaluate the performance of the estimators of the (FGLS) method and the (MG) method on the general model, the mean absolute percentage error (MAPE) scale was used to compare the efficiency of the estimators. The results showed that the mean group estimation (MG) method is the best method for parameter estimation than the (FGLS) method. Also, the (MG) appeared to be the best and best method for estimating sub-parameters for each cross-section (country).

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Improving an Ovulation Rate in Women with Polycystic Ovary Syndrome by Using Silymarin
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Polycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the  levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day)  .The second group received

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Publication Date
Sun Jun 06 2021
Journal Name
Materials
Strengthening of Continuous Reinforced Concrete Deep Beams with Large Openings Using CFRP Strips
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To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Face Recognition Using Stationary wavelet transform and Neural Network with Support Vector Machine
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Face recognition is a type of biometric software application that can identify a specific
individual in a digital image by analyzing and comparing patterns. It is the process of
identifying an individual using their facial features and expressions.
In this paper we proposed a face recognition system using Stationary Wavelet Transform
(SWT) with Neural Network, the SWT are applied into five levels for feature facial
extraction with probabilistic Neural Network (PNN) , the system produced good results
and then we improved the system by using two manner in Neural Network (PNN) and
Support Vector Machine(SVM) so we find that the system performance is more better
after using SVM where the result shows the performance o

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Embedding a Digitized Watermark Upon Colored Image Using Wavelet Transform with Comparative Technique
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A special methodology for adding a watermark for colored (RGB) image is formed and adding the wavelet transform as a tool during this paper. The watermark is added into two components. The primary one is by taking the key that contain associate eight range from (0...7) every range in it determines the actual bit position in specific component of canopy image. If that bit is analogous to the bit in watermark, (0) are hold on within the Least Significant Bit (LSB) of the watermarked image; otherwise (1) are hold on. The other is that it will add multiple secret keys victimization shift and rotate operations. The watermark is embedded redundantly over all extracted blocks in image to extend image protection. This embedding is completed with

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Physics: Conference Series
A New Iterative Methods For a Family of Asymptotically Severe Mappings
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Abstract<p>The aim of this paper is to introduce the concepts of asymptotically p-contractive and asymptotically severe accretive mappings. Also, we give an iterative methods (two step-three step) for finite family of asymptotically p-contractive and asymptotically severe accretive mappings to solve types of equations.</p>
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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Physics: Conference Series
Iterative Methods for Approximation of Fixed Points Via Like Contraction Mappings
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Abstract<p>The aim of this paper, is to study different iteration algorithms types two steps called, modified SP, Ishikawa, Picard-S iteration and M-iteration, which is faster than of others by using like contraction mappings. On the other hand, the M-iteration is better than of modified SP, Ishikawa and Picard-S iterations. Also, we support our analytic proof with a numerical example.</p>
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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Ag-SiO2 nanoparticales prepared by Sol-Gel methods for antibacterial effect
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Sol-gel method was use to prepare Ag-SiO2 nanoparticles. Crystal structure of the nanocomposite was investigated by means of X-ray diffraction patterns while the color intensity was evaluated by spectrophotometry. The morphology analysis using atomic force microscopy showed that the average grain sizes were in range (68.96-75.81 nm) for all samples. The characterization of Ag-SiO2 nanoparticles were investigated by using Scanning Electron Microscopy (SEM). Ag-SiO2 NPs are highly stable and have significant effect on both Gram positive and negative bacteria. Antibacterial properties of the nanocomposite were tested with the use of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacteria. The results have shown antibacteri

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Publication Date
Mon Jan 04 2021
Journal Name
Iium Engineering Journal
RELIABLE ITERATIVE METHODS FOR SOLVING 1D, 2D AND 3D FISHER’S EQUATION
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In the present paper, three reliable iterative methods are given and implemented to solve the 1D, 2D and 3D Fisher’s equation. Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM) and Banach contraction method (BCM) are applied to get the exact and numerical solutions for Fisher's equations. The reliable iterative methods are characterized by many advantages, such as being free of derivatives, overcoming the difficulty arising when calculating the Adomian polynomial boundaries to deal with nonlinear terms in the Adomian decomposition method (ADM), does not request to calculate Lagrange multiplier as in the Variational iteration method (VIM) and there is no need to create a homotopy like in the Homotopy perturbation method (H

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Publication Date
Mon Oct 28 2019
Journal Name
Iraqi Journal Of Science
Re-Evaluation Solution Methods for Kepler's Equation of an Elliptical Orbit
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An evaluation was achieved by designing a matlab program to solve Kepler’s equation of an elliptical orbit for methods (Newton-Raphson, Danby, Halley and Mikkola). This involves calculating the Eccentric anomaly (E) from mean anomaly (M=0°-360°) for each step and for different values of eccentricities (e=0.1, 0.3, 0.5, 0.7 and 0.9). The results of E were demonstrated that Newton’s- Raphson Danby’s, Halley’s can be used for e between (0-1). Mikkola’s method can be used for e between (0-0.6).The term  that added to Danby’s method to obtain the solution of Kepler’s equation is not influence too much on the value of E. The most appropriate initial Gauss value was also determined to

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