In this research, the effect of changing the flood level of Al-Shuwaija marsh was studied using the geographic information systems, specifically the QGIS program, and the STRM digital elevation model with a spatial analysis accuracy of 28 meters, was used to study the marsh. The hydraulic factors that characterize the marsh and affecting on the flooding such as the ranks of the water channels feeding the marsh and the degree of slope and flat areas in it are studied. The area of immersion water, the mean depth, and the accumulated water volume are calculated for each immersion level, thereby, this study finds the safe immersion level for this marsh was determined.

The typical test for diagnosis of severe acute respiratory syndrome coronavirus 2 is a reverse transcription-polymerase chain reaction (RT-PCR) technique, but the chest CT scan might play a complementary role at the first detection of Coronavirus Disease 2019 (COVID-19) pneumonia. Objectives: To determine the sensitivity of CT scan on patients with COVID-19 in Al-Najaf, Iraq, and to compare the accuracy of CT scan with that of RT-PCR technique. Material and Method: This is a prospective study. The patients suspicious of having COVID-19 infection and respiratory symptoms were registered. All patients were diagnosed by RT-PCR and chest CT. Diagnostic performance of CT was intended using RT-PCR as the reference sta

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

This study explored the feasibility of removing nickel (Ni) and Pb (II) from water solutions using the adsorption technique by cellulose recovered from office paper waste. Metal removal is required to reduce the direct or indirect exposure of industrial waste to the environment, due to its potential for harm to human health and ecosystems. The release criterion is maintained to keep the efficient wastewater treatment of the metals of concern, which are toxic to both humans and other organisms. The cellulose was first prepared from office paper waste. The removal values can be rationalized as follows: Lead removal efficiencies of were obtained upto %95.0632, while the removals of nickel were obtained as 54.3866%. The adsorption proce

Abstract This research deals with the Al-Tossy contribution Islamic government and explain the directions of early shiaa political thoughts and knowing the opinions of Al-Shakh Al- Tossy in the Islamic Government

A water resources management for earthen canal/stream is introduced through creating a combination procedure between a field study and the scientific analytical concepts that distinguish the hydraulic problems on this type of stream with using the facilities that are available in HECRAS software; aiming to point the solutions of these problems. Al Mahawil stream is an earthen canal which is subjected to periodic changes in cross sections due to scour, deposition, and incorrect periodic dredging processes due to growth of the Ceratophyllum plants and weeds on the bed and banks of the stream; which affect the characteristics of the flow. This research aims to present a strategy of water resources management through a field study that conducte

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a