In this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes  n=40,60,100,variances used σ²=0.5,1,1.5 the results  for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the

A harvested prey-predator model with infectious disease in preyis investigated. It is assumed that the predator feeds on the infected prey only according to Holling type-II functional response. The existence, uniqueness and boundedness of the solution of the model are investigated. The local stability analysis of the harvested prey-predator model is carried out. The necessary and sufficient conditions for the persistence of the model are also obtained. Finally, the global dynamics of this model is investigated analytically as well as numerically. It is observed that, the model have different types of dynamical behaviors including chaos.

The research aims to measure the extent of the impact of Earnings quality in the continuity of the company for a sample of private commercial banks listed on the Iraq Stock Exchange. The research sample included (15) of the listed commercial banks that continue to issue their financial statements for the period from (2009-2018).The research relied on three main models of measurement and on four steps. The first step is to measure the Persistence (Earnings Quality) by Depending the sustainability model. While the second step included measuring the Predictability of accounting profits by deriving the square root of the disparity of the estimation error from the first model Persistence (Earnings Quality), and the third step included

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

Objectives: This study aims to assess and compare the micro-shear bond strength (μSBS) of a novel resin-modified glass-ionomer luting cement functionalized with a methacrylate co-monomer containing a phosphoric acid group, 30 wt% 2-(methacryloxy) ethyl phosphate (2-MEP), with different substrates (dentin, enamel, zirconia, and base metal alloy). This assessment is conducted in comparison with conventional resin-modified glass ionomer cement and self-adhesive resin cement. Materials and methods: In this in vitro study, ninety-six specimens were prepared and categorized into four groups: enamel (A), dentin (B), zirconia (C), and base metal alloys (D). Enamel (E) and dentin (D) specimens were obtained from 30 human maxillary first premolars e

Congenital absence of anterior cruciate ligament is highly uncommon occurrence. It has since been documented as a standalone anatomical entity or, more frequently, in conjunction with other congenital anomalies. Surgical treatment for this patient population has only been reported in very few cases. In this article, we share our experience in managing a case of unilateral congenital deficiency of anterior cruciate ligament (ACL) in a 13 years old female patient by physeal sparing arthroscopic ACL reconstruction, using All-inside technique.

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class