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Investigating the Color Distribution of Young and Old Galaxies Using Observations from SDSS
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     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and all subsamples are bimodal. This indicates that the color distribution is an ideal tool to differentiate between young and old galaxies. The young and blue star-forming galaxies are represented by one of the two peaks, while the old and red non-star-forming galaxies are represented by the other peaks of the color distribution.

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Publication Date
Thu Feb 02 2012
Journal Name
Education College Journal/al-mustansiriyah University
On Significance Testimator in Pareto Distribution Via Shrinkage Technique
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In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Design Sampling Plan when Life Time Follows Logistic Distribution
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Design sampling plan was and still one of most importance subjects because it give lowest cost  comparing with others, time live statistical distribution should be known to give best estimators for  parameters of sampling plan and get best sampling plan.

Research dell with design sampling plan when live time distribution follow Logistic distribution with () as location and shape parameters, using these information can help us getting (number of groups, sample size) associated with reject or accept the Lot

Experimental results for simulated data shows the least number of groups and sample size needs to reject or accept the Lot with certain probability of

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Salt Distribution in a Soil Irrigated by Subsurface Emitter
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The best design of subsurface trickle irrigation systems requires knowledge of water and salt distribution patterns around the emitters that match the root extraction and minimize water losses. The transient distribution of water and salt in a two-dimensional homogeneous Iraqi soil domain under subsurface trickle irrigation with different settings of an emitter is investigated numerically using 2D-HYDRUS software. Three types of Iraqi soil were selected. The effect of altering different values of water application rate and initial soil water content was investigated in the developed model. The coefficient of correlation (R2) and the root-mean-square error (RMSE) was used to validate the predicted numerical res

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Discussing Fuzzy Reliability Estimators of Function of Mixed Probability Distribution By Simulation
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This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Phenolic Compounds from Aqueous Solution by Using Agricultural Waste (Al-Khriet)
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Adsorption techniques are widely used to remove organics pollutants from waste water particularly, when using low cost adsorbent available in Iraq. Al-Khriet powder which was found in legs of Typha Domingensis is used as bio sorbent for removing phenolic compounds from aqueous solution. The influence of adsorbent dosage and contact time on removal percentage and adsorb ate amount of phenol and 4- nitro phenol onto Al-Khriet were studied. The highest adsorption capacity was for 4-nitrophenol 91.5% than for phenol 82% with 50 mg/L concentration, 0.5 gm. dosage of adsorbent and pH 6 under a batch condition. The experimental data were tested using different isotherm models. The results show that Freundlich model resulted in the best fit also

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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Removal of Lead (II) from Aqueous Solution Using Chitosan Impregnated Granular Activated Carbon
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The use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions  pb.2+   from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption  pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f

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Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Oxidation desulfurization of model oil using carbon composite derived from peach stone waste
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     In this study, oxidative desulfurization of dibenzothiophene (DBT) with H2O2 as an oxidant was studied, whereas the catalyst used was zirconium oxide supported on Activated carbon (AC). Zirconium oxide (ZrO2) was impregnated over prepared activated carbon (AC) and characterized by various techniques such as XRD, FTIR, BET, SEM, and EDX. This composite was used as a heterogeneous catalyst for oxidation desulfurization of simulated oil. The results of this study showed that ZrO2/AC composite exhibited significant catalytic activity and stability, effectively lowering sulfur content under mild conditions. Factors such as reaction temperature (30, 40, 50, 60°C), time (5, 10, 15,20,30,60, 80 100 min), catalyst dose (0.3, 0.5,

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Removal of Cadmium from Simulated Wastewaters Using a Fixed Bed Bio-electrochemical Reactor
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In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficie

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