In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.

This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq

Background: The aim of this national oral health survey was to determine the prevalence of malocclusions due to some anomalies in the dentition among the 13 years old Kurdish students in sulaimani intermediate school. Materials and methods: The total sample was 950 (455 males and 495 females) which assessed by diagnostic set and special instrument. The clinical examination was mainly based on the definitions of Björk et al. Some variables were recorded as present or absent sometimes denoting the tooth or the teeth involved in malocclusion and their distribution according to the whole sample. Results: The results showed that 1)The most common extracted tooth was the mandibular first molar (2.9%). 2) At this age group the most common partial

     Fifty patients(24 female and 26 male)with pressure ulcersassociated with different diseasesand attending AL-yarmouk Teaching Hospital in Baghdad were selected in this study. The duration of sample collection was from March  to December 2018. All blood samples collected from patients were submitted to a blood culturing technique to examine bacteremia. The results showed that12 blood bacterial isolates were obtained. The isolated bacteria were subjected to Vitek-2, which is an accurate identification technique. The results of the blood culturing technique revealed that 33.3% were Gram negative bacteria, while 66.6% were Gram positive. Diagnosis by Vitek-2 showed that 33.3%  wereStaphylococcus spp. , 33.3% were Enterococcus

This study was initiated to examine the tomato-infecting viruses belonging to the Tobamovirus and Potexvirus genera in Iraq. Field observations and surveys were carried out for three successive cropping seasons (2020/21 to 2022/23) in selected tomato production areas. The purpose was to identify the main viruses associated with tomato epidemics and assess the impact of different tomato cultivars on disease occurrence. A total of 700 tomato leaf samples were collected from seven governorates (Baghdad, Diyala, Babylon, Najaf, Kerbala, Nasiriya, and Basrah) and tested using pathogen-specific immunostrip kits. The survey showed a presence of Tomato brown rugose fruit virus (ToBRFV), Tobacco mosaic virus (TMV), Pepper mild mottle virus (

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

The objective of this article is to delve into the intricate dynamics of marriage relationships, exploring the impact of emotions such as fear, love, financial considerations and likability. In our investigation, we adopt a perspective that acknowledges the nonlinear nature of interactions among individuals. Diverging from certain prior studies, we propose that the fear element within the context of marriage is not a singular, isolated factor but rather a manifestation resulting from the amalgamation of numerous social issues. This, in turn, contributes to the emergence of strained and unsuccessful relationships. Unlike conventional approaches, we extensively examine the conditions essential for the existence of all socially signifi

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