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Bayes Analysis for the Scale Parameter of Gompertz Distribution
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In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distribution, with different samples sizes. The estimates have been compared in terms of their mean-squared error (MSE).

The results of this paper show that bayes estimators of the scale parameter  of the Gompertz distribution, under the exponential loss function (proposed) are superior to the bayes estimators  under  the squared error loss function , based on erlang-chi-square double prior with  for  all samples sizes  and for all the true values of , in terms of their mean-squared error (MSE)

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
"Compared some of the semi-parametric methods in analysis of single index model "
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As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment
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Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
new Estimator of the parameter of negative exponential
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the main of this paper is to give a comprehensive presentation of estimating methods namely maximum likelihood bayes and proposed methods for the parameter

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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Wave Propagation in Detection of Aorta Dieses Using Lumps Analysis
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In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Bayes estimators of a multivariate generalized hyperbolic partial regression model
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the structure of salaries of public sector workers for strategic planning purposes An analytical study in the general body of groundwater
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The research discusses the problem of salaries in the public sector in terms of the process of analyzing its structure and the possibility of benefiting from the information provided by the analysis process for the strategic planning process, and the General Authority for Groundwater has been adopted and one of the formations of the Ministry of Water Resources, which is centrally funded, to represent the salary structure of its employees (1117) employees be a field of research, as the salary structure in it was analyzed for the period between (2014-2019) using the quantitative approach to analysis and by relying on a number of statistical tools in the analysis process, including mathematical circles, upper limits, lower limits, p

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
The Gumbel- Pareto Distribution: Theory and Applications
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In this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The Analysis of Regional Development in Abu Ghraib Municipality within the Available Sources
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The judgment enjoys many potential sources. If we look at these sources with analytical view that enable us to identify the potentials of strength in them which is the existence of features that distinct each place from the other one, which can be considered opportunities that provide the designer and the planner the possibility to design and planning which is based on subs taken from the reality of the available data of the location.
At this point outstands the role of development sources as one of the processes of re-configuring the place which appear as a result of a reality that requires setting new goals for the society and to achieve these goals it takes observations dealing with the place policies that should be taken, so this

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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