• The subject of this research is the study of the formal alienation of contemporary English sculpture, by comparing the most important sculptors of the new contemporary generation. This research problem is to look for the important factors in the formation of the contemporary sculptural structure of the exotic, and what is the mechanism of formation and output of these forms. The research seeks to explore (Alienation in contemporary sculpture between the works of Anthony Caro and Tony Cragg) in a comparative study. The importance of the research is to identify the concept of alien forms in contemporary British sculpture, especially in the cases of Anthony Caro and Tony Cragg that this research is considered a know

This  research  involves  studying  the  influence  of  increasing  the

number of Gaussian points and the style of their distribution, on a circular exit pupil, on the numerical calculations accuracy of the point spread function for an ideal optical system and another system having focus error of (0.25 A. and 0.5 A. )

It was shown that the accuracy of the results depends on the type of

distributing points on the exit pupil. Also, the accuracy increases with the increase of the number of points (N) and the increase of aberrations which requires on increas (N).

Docetaxel is an effective treatment approved for many types of cancers, but its effectiveness in clinical practice can be compromised by significant occurrence of adverse drug reactions. The aim of the current study was to measure the distribution of adverse drug reactions of docetaxel reported in Iraq and to assess the causality, severity, seriousness, preventability, expectedness and outcome of these adverse reactions. A retrospective study conducted on individual case safety reports from the Iraqi Pharmacovigilance Center / Ministry of Health. The study included 118 individual case safety report containing 236 adverse drug reactions.
Most of the adverse drug reactions were related to skin and subcutaneous tissue disorders(26.7%), f

       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

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

BACKGROUND: Enteric fever caused by Salmonella Typhi is an endemic disease in Iraq. Variations in presentations make it a diagnostic challenge. If untreated or treated inappropriately then it is a serious disease with potentially life-threatening complications. The recent emergence of drug resistant strains of S. Typhi is a rising public health problem and a clinical concern to the physician. AIM: The objectives of the study were to assess and describe the patterns of antimicrobial resistance, clinical characteristics, epidemiological distribution, and complications of typhoid fever. PATIENTS AND METHODS: Fifty cases of typhoid fever (culture proven) were collected during the period from February 2019 to November 2019 in the me

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.