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On Inference of Finite Mixture of Rayleigh Distribution by Gibbs Sampler and Metropolis-Hastings
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Inferential methods of statistical distributions have reached a high level of interest in recent years. However, in real life, data can follow more than one distribution, and then mixture models must be fitted to such data. One of which is a finite mixture of Rayleigh distribution that is widely used in modelling lifetime data in many fields, such as medicine, agriculture and engineering. In this paper, we proposed a new Bayesian frameworks by assuming conjugate priors for the square of the component parameters. We used this prior distribution in the classical Bayesian, Metropolis-hasting (MH) and Gibbs sampler methods. The performance of these techniques were assessed by conducting data which was generated from two and three-component mixture of the Rayleigh distribution according to several scenarios and comparing the results of the scenarios by calculating the mean of classification successful rate (MCSR) and the mean of mean square error(MMSE). The results showed that Gibbs sampler algorithm yields a better computation results than the others in terms of MMSE and MCSR.

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Sustainable Urban Distribution of Educational Institutions and Population Density in Baghdad City Using Remote Sensing Techniques
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Abstract<p>Urban planning include the creation of strategies as well as the management of metro regions, municipalities, and cities. In this study, the importance of applications of remote sensing and GIS in urban planning will be studied. The distribution of educational destitution cases in cities will be considered. A study area (Baghdad city) will be adopted, and the spatial analysis of the distribution will be according to population densities. In this study, the focus was on the importance of the sustainable distribution of urban educational institutions and the spatial appropriateness of this distribution according to the study areas and the available information. Distribution maps were pr</p> ... Show More
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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Spatial Distribution of Soil Quality and Health Index for the Umm Al-Naaj Marsh in Maysan
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The Umm Al-Naaj Marsh was chosen in Maysan province, and it is one of the sections of Mar Al-Hawza, which is one of the most prominent Iraqi marshes in the south. The marshes are located between latitudes 30 35 and 32 45 latitudes and longitudes 13 46 and 48 00. The area of the study area is 76479.432142 hectares to evaluate soil quality and health index and their spatial distribution based on measuring physical, chemical, biological and fertility traits and calculating the total quality index for those characteristics. Using an auger drilling machine, we collected 50 randomly selected surface samples, evenly distributed across the study region, from Al-Aq 0.0–0.30 m, noting their precise locations along the way. Soil health and quality w

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Publication Date
Fri Sep 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Radon-Distribution Measurements With CR-39, LR-115 And CN-85 DeteCtors
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The  aim  of this  work  is to determine radon and  its decay  product concentratiQns  indoor   and  outdoor   in  different   areas   in  north   and middle  are·a of Iraq by using nuclear  trak detectors  , CR-39  , CN- 85 andLR-115.                        -

For   CR-39    detectors   ,   the   highest    radon    concentration  was

(64.07Bq/m3)indoor and  (52.4  Bq/m3)

outdoor &n

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On a New Kind of Collection of Subsets Noted by δ–field and Some Concepts Defined on δ–field
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     The objective of this paper is, first, study a new collection of sets such as field and we discuss the properties of this collection. Second, introduce a new concepts related to the field such as measure on field, outer measure on field and we obtain some important results deals with these concepts. Third, introduce the concept of null-additive on field as a generalization of the concept of measure on field. Furthermore, we establish new concept related to - field noted by weakly null-additive on field as a generalizations of the concepts of measure on and null-additive. Finally, we introduce the restriction of a set function  on field and many of its properties and characterizations are given.

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Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Effect of SiC particles and water absorption on thermal conductivity of epoxy reinforcement by (bi-directional) glass fiber
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In this study the thermal conductivity of the epoxy composites were characterized as function of volume fraction, particle size of fillers and the time of immersion(30,60,90)days in water .Composites plates were prepared by incorporating (bi-directional) (0º-90º) glass fiber and silicon carbide (SiC) particles of (0.1,0.5,1)mm as particle size at (10%,20%,30%,40%) percent volume in epoxy matrix.
The composites shows slightly increase of the thermal conductivity with increasing volume fraction, particle size and increase with increasing the days of immersion in water. The maximum thermal conductivity (0.51W/m.K) was obtained before the immersion in water at 90 days for epoxy reinforcement by bi-directional glass fiber and SiC particl

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Comparison Between the Bayes Estimator and the Maximum Likelihood Estimator of the Reliability Function for Negative Exponential Distribution
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     In this paper, the maximum likelihood estimator and the Bayes estimator of the reliability function for negative exponential distribution has been derived, then a Monte –Carlo simulation technique was employed to compare the performance of such estimators. The integral mean square error (IMSE) was used as a criterion for this comparison. The simulation results displayed that the Bayes estimator performed better than the maximum likelihood estimator for different samples sizes.

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Finite Element Modeling of One-Way Recycled Aggregate Concrete Slabs Strengthened using Near-Surface Mounted CFRPs under Repeated Loading
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This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Wed May 10 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate The Mean of Normal Distribution Via Preliminary Test Shrinkage Technique
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 This paper is concerned with preliminary test single stage shrinkage estimators for the mean (q) of normal distribution with known variance s2 when a prior estimate (q0) of the actule value (q) is available, using specifying shrinkage weight factor y( ) as well as pre-test region (R).         Expressions for the Bias, Mean Squared Error [MSE( )] and Relative Efficiency [R.Eff.( )] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants including in these expressions. Comparisons between suggested estimators with respect to usual estimators in the sense of Relative Efficiency are given. Furthermore, comparisons with the earlier existi

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