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Comparison of Robust Circular S and Circular Least Squares Estimators for Circular Regression Model using Simulation
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In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the methods of the robust circular S method in the case that the data does not contain outlier values because it was recorded the lowest mean criterion, mean squares error (Median MSE), the least median standard error (Median SE) and the largest value of the criterion of the mean cosines of the circular residuals A(K) for all proposed sample sizes (n=20, 50, 100). In the case of the contaminant in the vertical data, it was found that the circular least squares method is not preferred at all contaminant rates and for all sample sizes, and the higher the percentage of contamination in the vertical data, the greater the preference of the validity of estimation methods, where the mean criterion of median squares of error (Median MSE) and criterion of median standard error (Median SE) decrease and the value of the mean criterion of the mean cosines of the circular residuals A(K) increases for all proposed sample sizes. In the case of the contaminant at high lifting points, the circular least squares method is not preferred by a large percentage at all levels of contaminant and for all sample sizes, and the higher the percentage of the contaminant at the lifting points, the greater the preference of the validity estimation methods, so that the mean criterion of mean squares of error (Median MSE) and criterion of median standard error (Median SE) decrease, and the value of the mean criterion increases for the mean cosines of the circular residuals A(K) and for all sample sizes.

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Publication Date
Sat Nov 05 2022
Journal Name
Sensors
Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
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Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using si

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Natural Sciences
Determination of the Electron Density Variation for Ionosphere Layer Over Iraqi Zone Using IRI Model
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KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1

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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Study of nuclear structure for carbon isotopes using local scale transformation technique in shell model
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This work is devoted to study the properties of the ground states such as the root-mean square ( ) proton, charge, neutron and matter radii, nuclear density distributions and elastic electron scattering charge form factors for Carbon Isotopes (9C, 12C, 13C, 15C, 16C, 17C, 19C and 22C). The calculations are based on two approaches; the first is by applying the transformed harmonic-oscillator (THO) wavefunctions in local scale transformation (LST) to all nuclear subshells for only 9C, 12C, 13C and 22C. In the second approach, the 9C, 15C, 16C, 17C and 19C isotopes are studied by dividing the whole nuclear system into two parts; the first is the compact core part and the second is the halo part. The core and halo parts are studied using the

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Publication Date
Sat Jul 31 2021
Journal Name
Brain Sciences
Robust EEG Based Biomarkers to Detect Alzheimer’s Disease
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Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Teaching Using Adey- Shire Model and its Effect in Achievement and Critical Thinking for first intermediate students in Mathematics
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The aim of this research is to measure the effect of Adey- Shire model in the achievement and critical thinking of first intermediate female students in mathematics. The researcher adopted the experimental method with a post-test, the research of sample consists of (60) female students, divided into two groups with (30) students in the experimental group, that studied with Adey- Shire model, and (30) students in the control group who studied in the usual way. The two groups are equivalent in many variables. The researcher makes two tests of multiple choices, the first one is an achievement test consists (30) items and another test was for a critical thinking test with (25) items. The statistical analysis make to both tests is made with s

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Publication Date
Mon Feb 11 2019
Journal Name
Journal Of Pharmaceutical Sciences And Research
Design of experiments model for optimization of spectrophotometric determination of phenylephrine hydrochloride in pure and pharmaceutical formulations using p-bromanil
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A simple, fast, inexpensive and sensitive method has been proposed to screen and optimize experimental factors that effecting the determination of phenylephrine hydrochloride (PHE.HCl) in pure and pharmaceutical formulations. The method is based on the development of brown-colored charge transfer (CT) complex with p-Bromanil (p-Br) in an alkaline medium (pH=9) with 1.07 min after heating at 80 °C. ‘Design of Experiments’ (DOE) employing ‘Central Composite Face Centered Design’ (CCF) and ‘Response Surface Methodology’ (RSM) were applied as an improvement to traditional ‘One Variable at Time’ (OVAT) approach to evaluate the effects of variations in selected factors (volume of 5×10-3 M p-Br, heating time, and temperature) on

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Publication Date
Mon Sep 01 2008
Journal Name
Al-khwarizmi Engineering Journal
Design and Simulation of GaussianFSK Transmitter in UHF Band Using Direct Modulation of ΣΔ Modulator Fractional-N Synthesizer
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This research involves design and simulation of GaussianFSK transmitter in UHF band using direct modulation of ΣΔ  fractional-N synthesizer with the following specifications:

Frequency range (869.9– 900.4) MHz, data rate 150kbps, channel spacing (500 kHz), Switching time 1 µs, & phase noise @10 kHz = -85dBc.

New circuit techniques have been sought to allow increased integration of radio transmitters and receivers, along with new radio architectures that take advantage of such techniques. Characteristics such as low power operation, small size, and low cost have become the dominant design criteria by which these systems are judged.

A direct modulation by ΣΔ  fractional-N synthesizer is proposed

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of monetary policy variables inflation in Algeria: standard study using self regression time gaps
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                In the past years, the Algerian Economy has witnessed various monetary developments characterized by different monetary and banking reforms aimed by monetary authorities to achieve monetary stability and driving overall growth. It should be noted that there is evidence to initiate fundamental changes on the basis of which new monetary, financing and banking policy mechanisms must be formulated in Algeria by enhancing the pursuit of reforming the monetary system, in order to improve monetary and economic indicators.

                The study a

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the Population Mean in Stratified Random Sampling Using Combined Regression with the Presence of Outliers
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In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

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