For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2^nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

The paper is concerned with posterior analysis of five exponentiated (Weibull, Exponential, Inverted Weibull, Pareto, Gumbel) distrebutions. The expressions for Bayes estimators of the shape parameters have been derived under four different prior distributions assuming four different loss functions. The posterior predictive distributions have been obtained, and the comparison between estimators made by using the mean squared errors through generated different sample sizes by using simulation technique. In general, the performance of estimators under Chi-square prior using squared error loss function is the best.

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

The development of better tools for diagnosis and more accurate prognosis of cancer includes the search for biomarkers; molecules whose presence, absence or change in quantity or structure is associated with a particular tumour or prognosis/therapeutic outcome. While biomarkers need not be functionally relevant, if cell survival, then they could also provide new targets for therapeutic drugs. In recent years attention has been applied to a group of proteins known as cancer testis antigens (CT antigens) [1]. These proteins are products of genes whose expression was normally confined to the testis, yet they are expressed in tumour cells. CT genes are bound to serve a wide array of roles in the testes, which have many highly differentiated cel

In this paper, we give new results and proofs that include the notion of norm attainment set of bounded linear operators on a smooth Banach spaces and using these results to characterize a bounded linear operators on smooth Banach spaces that preserve of approximate - -orthogonality. Noting that this work takes brief sidetrack in terms of approximate - -orthogonality relations characterizations of a smooth Banach spaces. 

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Background: An important factor influencing duration of breastfeeding is mother’s employment status. The nutritional, immunological, psychological and economic benefits of breastfeeding are well documented. Both UNICEF and the World Health Organization recommend mothers should breastfeed exclusively for at least 6 months.
Objectives: To determine how the employment and the employment variables (type of work, time of return to work and hours of work) influence the breast feeding practices.
Methods: A cross- sectional study was carried out on a sample of 200 employed mothers who had their last child been completed at least tow years. Data were collected using a questionnaire form. It was carried out during the period from 1st of Ap

      The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of

The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <