This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

In this paper we will explain ,how use Bayesian procedure in analysis multiple linear regression model with missing data in variables X's  as the new method suggest , and explain some of missing  Patterns under missing mechanism , missing complete at random MCAR and compare Bayesian estimator with complete case estimator by use  simulation procedure .           

تقدير النموذج اللوجستي باستخدام اوزان بيز المتسلسل

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

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

The problem of the damage caused by terrorist acts has raised many difficulties in many countries, including Iraq, which requires the existence of a law that sets out sufficient rules for compensating the victims of terrorist acts, in order to compensate them for the harm they have not suffered. It may be difficult or impossible for them to identify causing damage, and therefore unable to obtain compensation by applying the traditional rules of liability that require proof of fault and identify the culprit. The security funds come as an appropriate alternative that pays compensation in such cases for victims to reparation for the damage they suffered. Therefore, this problem remains one of the most problems that Iraq suffers from it, which

Background: To evaluate the effect of antierosive agents (10% Nano-Hydroxyapatite (NHA), 10% Casein Phophopeptide-Amorphous Calcium Phosphate (CPP-ACP), and combination of 10% NHA and 10% CPP-ACP) on loss of minerals from enamel surface of permanent teeth treated with antierosive agents when exposed to an acidic beverage and investigate the morphological changes of treated enamel surface after demineralization with cola based beverage under Scanning Electron Microscope (SEM). Materials and Methods: Sixty maxillary first premolars were randomly divided into four groups, 15 teeth for each group. Group I treated with 10% NHA, Group II treated with 10% CPP-ACP, Group III treated with 10% NHA and 10% CPP-ACP, and Group IV did not treat with any

Diabetic nephropathy (DN) is the foremost cause of end-stage renal disease. Early detection of DN can spare diabetic patients of severe complications. This study aimed to evaluate the diagnostic value of red cell distribution width (RDW) and neutrophil-lymphocyte ratio (NLR) in the detection of DN in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included a total of 130 patients with T2DM, already diagnosed with T2DM. The albumin creatinine ratio (ACR) in urine samples was calculated for each patient, according to which patients were divided into two groups: with evidence of DN when ACR ? 30 mg/g, and those with no evidence of DN when ACR < 30 mg/g. According to multivariate analysis, each of disease duration (OR