In this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro

Objective:- Women's behavior during pregnancy which can affect the health of their infant , may be influenced by their attitude toward the pregnancy. The study was carried out to assess the pattern of health behaviors for pregnant women. Methodology: A descriptive study was carried out to select randomized (100) pregnant women attending Baghdad Teaching hospital. The data were collected through personal interview by using questionnaire form constructed for the purpose of the study. Results:- The result of the study revealed that the highest percentage of study sample were in age group (21-25) years, primary graduated and house wife . The results showed that the highest percentage( 64%) of them were primigravida, (72%) of them have (1-2)

Background: Although the new treatment methods developed in recent years are aiming to minimize the need for cooperation of the patients; however, the latter still important factor the treatment. The aim of the study was to evaluate the cooperation level of Class III maloc-clusion patients with orthodontic treatment. Materials and methods: This study followed a cross-sectional style; the targeted population was patients with Class III malocclusion who were treated with three different types of orthopaedic appliances. Four questionnaires were delivered to the patient, patient’s parents, and orthodontists. Statistical analyses of the study were performed with SPSS 20.0 software. Descriptive analyses were presented using fre-quency, percenta

This study aims to identify both the importance of using (LinkedIn) and its drawbacks for researchers and specialists in the field of information and knowledge technologies. The study relied mainly on the statistical method (analytical method) from the collection of data tools (questionnaire) that was distributed electronically (Google Forms) to the sample community of (55) instructors. The feedback received illustrates that (46) instructors among those who participated in the questionnaire subscribed to (LinkedIn) and the rest did not. Their data was analyzed statistically, and the general arithmetic mean and the hypothetical mean was extracted for them to achieve the objectives of the study and prove their hypotheses. The site positively

BACKGROUND: The degree of the development of coronary collaterals is long considered an alternate–that is, a collateral–source of blood supply to an area of the myocardium threatened with vascular ischemia or insufficiency. Hence, the coronary collaterals are beneficial but can also promote harmful (adverse) effects. For instance, the coronary steal effect during the myocardial hyperemia phase and that of restenosis following coronary angioplasty.

Objective: To find out the prevalence of anxiety and depression among Iraqi repatriated prisoners of Iran-Iraq war
(IRPOWs), and the relationship with some variables.
Methodology: A descriptive study was carried out from Oct. 18th, 2009 through Jan. 10th, 2010. A Snowball
sampling as a non-probability sampling technique was used to recruit 92 repatriates who had visited Ministry of
Human Rights. An instrument was constructed for this purpose. The constructed instrument consisted of six
demographic characteristics, and fourteen items to measure the level of anxiety and depression in prisoners of
war (POWs). Data were collected with using the constructed instrument and the process of the interview as means
for data col

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

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