Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the

this research aims at a number of objectives including Developing the tax examination process and raise its efficiency without relying on comprehensive examination method using some statistical methods in the tax examination and Discussing the most important concepts related to the statistical methods used in the tax examination and showing its importance and how they are applied. the research represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side Some statistical methods applied to the sample of the final accounts for the contracting company (limited) and the pharmaceutical industry (

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

0

This study was attempted to determine optimum conditions, for Glutathione s-Transferase enzyme, in sera of three groups diabetic patients type1 depending on duration of disease without complications compared with control group. The aim of this study was to find optimum conditions were determined such as (pH, Substrate Concentration, Temperature, Incubation time, Enzyme concentration, and effect of(0.15M)(0.25M) of mono divalent compounds). And to find the kinetics parameters in the three groups of diabetic patients when compared with control. It was found optimum pH(8.5,4.5,2.5,6.5).Temperatures(20cº,40cº,50cº,30cº). Incubation times (7min, 4min, 4min, 5min) substrate concentrations (12µl, 10µl, 5µl, 10µl) enzyme concentra

In Iraqi patients with acromegaly the present investigation included 40 control group and 70 patients with acromegaly divided 35 patients with Diabetic while another 35 patients without Diabetic, with ages between (29-72) years for the identification of GST activity polymorphisms by present and absent GSTM1, GSTT1, and PCR-RFLP, enzymatic digestions were carried out using BsmAI (Biolabs. England, UK) for GSTP1b and AciI (Biolabs, England, UK) for GSTP1c.the association GSTActivity with GST genotype were investigated in a cohort of Iraq acromegaly patients comparing with the healthy control group. The results show a non-significant change in GSTP1b gene in both groups, while show high significantly in GSTP1c in diabetic and non-diabetic acro

In this paper, Touchard polynomials (TPs) are presented for solving Linear Volterra integral equations of the second kind (LVIEs-2k) and the first kind (LVIEs-1k) besides, the singular kernel type of this equation. Illustrative examples show the efficiency of the presented method, and the approximate numerical (AN) solutions are compared with one another method in some examples. All calculations and graphs are performed by program MATLAB2018b.

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a