In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of  specific time points (m)،since the frequent measurements within the subjects are almost connected an

This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

The current research discusses the jurisprudence of the argumentative meaning in the Qur’an, and it is one of the general methods of responses in the Qur’an, as well as the argumentative approach to the recitations of the readers and directing their meanings. I have chosen a model for three verses from Surat Al-An’am, in which there are seven frequent recitations and seven odd ones, on a topic related to theology and faith; It forms the centerpiece of the argument verses in Surat Al-An'am; It contains the jurisprudence of dealing with infidels and dissenters, turning away and forbidding insulting what they claim besides God in the event of corruption, and God Almighty’s decree and wisdom in the occurrence of unbeli

Praise be to God, prayer, and peace be upon the Messenger of Allah and his God and his companions. The field of the judiciary to prove or invalidate some cases in the field of proof of descent and attachment to the plaintiff or exile, and other legal and judicial issues, especially in this era where the spread of previously unknown evidence, such as DNA, which was discovered in 1953, and the genetic fingerprint discovered 1984, blood analysis and a Saliva, sweat, poetry, etc. in the field of forensic evidence, in forensic medicine or medical expertise, it can be used to identify the killer, or verify his identity, using all the evidence in the scene, such as a point of blood or sweat, and the like So, as well as to prove the lineage is u

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

Language ecology is the interactions between the environment and language. Such a discipline, ‘language ecology’ or ‘ecolinguistics has been founded by Einar Haugen’. Accordingly,  the study aims at qualitatively reviewing the theoretical and conceptual issues surrounding the subject of language ecology  by tracing the roots of language ecology. It further highlights the fundamental inconsistencies between how the concept of ecology is perceived in sociology and biology, and is applied to language, particularly, transposing the main central concepts of bio-ecology, such as relationship/interaction, environment, and organism to human language and theory of ecological-linguistic. The theory wavers among placing the focus

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6^th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f