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An Efficient Shrinkage Estimator for the Parameters of Simple Linear Regression Model
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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
Sat Jan 31 2015
Journal Name
International Journal Of Research In Applied, Natural And Social Sciences
The Influence of Premenopausal Simple Hysterectomy on Bone Mass Density
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Publication Date
Wed Dec 30 2015
Journal Name
Mathematical Theory And Modeling
On the stability of an SIS epidemic model involving treatment
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The objective of this paper is to study the stability of SIS epidemic model involving treatment. Two types of such eco-epidemiological models are introduced and analyzed. Boundedness of the system is established. The local and global dynamical behaviors are performed. The conditions of persistence of the models are derived.

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Proposing Robust IRWs Technique to Estimate Segmented Regression Model for the Bed load Transport of Tigris River with Change Point of Water Discharge Amount at Baghdad City
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Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

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Publication Date
Mon Oct 01 2012
Journal Name
Iraqi Journal Of Physics
Double probe for measuring the plasma parameters
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In this work the diode planer magnetron sputtering device was
designed and fabricated. This device consists of two aluminum discs
(8cm) diameter and (5mm) thick. The distance between the two
electrodes is 2cm, 3cm, 4cm and 5cm.
Design and construction a double probe of tungsten wire with
(0.1mm) diameter and (1.2mm) length has been done to investigate
electron temperature, electron and ion density under different
distances between cathode and anode. The probes were situated in
the center of plasma between anode and cathode.
The results of this work show that, when the distance between
cathode and anode increased, the electron temperature decreased.
Also, the electron density increases with the increasing

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Bat Algorithm Based an Adaptive PID Controller Design for Buck Converter Model
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The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
A An Authentication and Access Control Model for Healthcare based Cloud Services
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Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s

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Publication Date
Mon Sep 30 2024
Journal Name
Joiv : International Journal On Informatics Visualization
Evaluation of the Performance of Kernel Non-parametric Regression and Ordinary Least Squares Regression
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Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson

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