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Analysis of Models (NAGARCH & APGARCH) by Using Simulations
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Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting from the application of these models to the return series for the exchange rates of Iraqi dinar against US dollar (IQ/USD) for the period from (21/7/2011) until (21/07/2021) and then using these estimations in the process of generating data. The identifications were made using the (Ljung-Box and ARCH tests) with  (1000 replicates) and the result showed the presence of states (autocorrelation and heteroskedasticity) and this states increased with increasing the sample size and the best result of NAGARCH with Normal distribution and the best result of APGARCH with General error distribution. The Maximum Likelihood Estimation method used to estimate the parameters of the models and the best result with largest sample size (2000) , in the diagnostic checking phase the result showed the ability of the models (NAGARCH & APGARCH) to process the states of (autocorrelation and heteroskedasticity) and the best result with (APGARCH) model when the error distributed (General error distribution)

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Comparative Study of Image Denoising Using Wavelet Transforms and Optimal Threshold and Neighbouring Window
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NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among

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Publication Date
Sun Apr 07 2013
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of enrichment activities through using software program for second graders in Conversation article
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Today we are witnessing huge scientific and technical progress so we need more skills and methods of thinking that needs to be acquired by the teacher, as the importance of computers in education  there are  many teachers  suffering  of the difficulty in teaching for pupils . researchers tried to  find a good suitable way with the technological  interests for now which represent by  computer design software and the introduction of enrichment activities in the curriculum because it is one of a contemporary trends for the development of the Arabic language with various levels of education and knowing if this program has negative or positive impact.

So&nbsp

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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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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Estimate missing value by use analyses of covariance method for split block-design
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The research aims to estimate missing values using covariance analysis method Coons way to the variable response or dependent variable that represents the main character studied in a type of multi-factor designs experiments called split block-design (SBED) so as to increase the accuracy of the analysis results and the accuracy of statistical tests based on this type of designs. as it was noted in the theoretical aspect to the design of dissident sectors and statistical analysis have to analyze the variation in the experience of experiment )SBED) and the use of covariance way coons analysis according to two methods to estimate the missing value, either in the practical side of it has been implemented field experiment wheat crop in

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides
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 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between some well- Known methods to estimate the parameter of the proposed method of measurement and the reliability of the distribution function with two parameters Rally by simulation
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Abstract

            Rayleigh distribution is one of the important distributions used for analysis life time data, and has applications in reliability study and physical interpretations. This paper introduces four different methods to estimate the scale parameter, and also estimate reliability function; these methods are Maximum Likelihood, and Bayes and Modified Bayes, and Minimax estimator under squared error loss function, for the scale and reliability function of the generalized Rayleigh distribution are obtained. The comparison is done through simulation procedure, t

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
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The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Predicting Municipal Sewage Effluent Quality Index Using Mathematical Models In The Al-Rustamiya Sewage Treatment Plant
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Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and t

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Publication Date
Sat Jan 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Developing Bulk Arrival Queuing Models with Constant Batch Policy Under Uncertainty Data Using (0-1) Variables
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This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of The College Of Languages (jcl)
English Personal Pronouns as a Manipulation Strategy in Political Discourse: A Critical Discourse Analysis
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Manipulation is a discursive concept which plays a key role in political discourse by which politicians can impose some impact on their recipients through using linguistic features, most prominent of which are personal pronouns (Van Dijk, 1995). The aim of this study is to investigate how politicians utilize the personal pronouns, namely; We and I and their possessive forms as a tool of manipulating the audience's mind based on Van Dijk's  "ideological square" which shows positive-self representation and negative-other representation (Van Dijk,1998:p.69). To this end, American President Donald Trump's 2020 State of the Union speech was chosen to be the data of analysis. Only (8)

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