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Subsurface Investigation Using Electrical Resistivity Imaging for Proposed Industrial Site near Erbil-Kirkuk Borders, Northern Iraq
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The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel profiles in a specific direction. The positions of Electrical Resistivity Imaging profiles in the project area have been determined according to a preliminary subject plan from the civil engineers for factory foundation constructions and proposed locations of heavy machines. The inversion results of profiles showed that areas of blocks A, B, C, and D consist mainly of clastic rocks and sediments, e.g., claystone, siltstone and sandstone. The Electrical Resistivity Imaging inversion sections of blocks A, B, C, and D do not show any indication of cavitation or weak zones of sizes more than 2.0 meters, and no signs of gypsum bodies are found in these areas in general. Gypsum bodies are probably detected at block E, the southern part of the study area. The researchers recommended to keep these rocks in block E away from the continuous running water to avoid cavitation. Furthermore, the construction of heavy machines should keep away from this part of the study area to avoid to some extent, subsoil failure and subsidence in the future. Middle and Northern parts are more consistent to the constructions and factory foundations.

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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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

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Publication Date
Thu Dec 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The design of a proposed model for the application of the insurance policy for medical errors
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The aim of this study is to design a proposed model for a document to insure the mistakes of the medical profession in estimating the compensation for medical errors. The medical profession is an honest profession aimed primarily at serving human and human beings. In this case, the doctor may be subject to error and error , And the research has adopted the descriptive approach and the research reached several conclusions, the most prominent of which is no one to bear the responsibility of medical error, although the responsibility shared and the doctor contributes to them, doctors do not deal with patients according to their educational level and cultural and there are some doctors do not inform patients The absence of a document to insu

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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Asphaltene Precipitation Investigation Using a Screening Techniques for Crude Oil Sample from the Nahr-Umr Formation/Halfaya Oil Field
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Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Knowledge of Breastfeeding: A descriptive study among mothers in Kirkuk Governorate
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Aims: The present study aims at assessing mothers’ knowledge of breastfeeding in Kirkuk governorate,
besides determining the relationship between mothers’ knowledge and some of their demographic
attributes.
Methodolgy: A descriptive study was used the assessment approach and applied on mothers in Kirkuk
governorate from January 15th 2011 to July 25th
, 2011. Non-probability sampling a convenience sample of
(72) mothers, attending pediatric general hospital in Kirkuk governorate for following up the health status
of their children, was selected for the purpose of the study. A questionnaire was developed for the
purpose of the study. It was comprised of two parts; the first part includes the mothers' demographic

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Hypertension among Cardiac Diseases Inpatients at Kirkuk City Hospitals
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Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Prevalence of obesity among adolescents at secondary schools in Kirkuk city
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Objective: to identify the secondary school adolescent's obesity, and to find out the relationship between
adolescents obesity characteristics and their family history.
Methodology: A cross-sectional study was carried out among 537 adolescents (270 boys and 267 girls) aged 12-15
years selected by means of a multistage stratified random sampling technique.
Results: the prevalence of obesity among adolescents was 22.3%. (55.8%) of the obese adolescents were male,
(42.5%) their age is (13) years old, and (79.2%) of them coming from middle level of socio economic status score.
There are a significant relationship between obese adolescents and their family history of obesity which indicated
that obese father, and obese br

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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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Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika
Proposed different relay selection schemes for improving the performance of cooperative wireless networks
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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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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Publication Date
Fri Jan 01 2021
Journal Name
Advances In Intelligent Systems And Computing
Γ-n-Derivations on Semigroup Ideals on Prime Γ-Near-Rings
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