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Assessment of Clinical Learning and Training Environment for Maternal and Child Health Nursing Students
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Objective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged between (19-23) years
and 56% were male student, 66.9% were third year nursing students, and 59.4% were morning study. The study
revealed that there were high mean score response among study sample except item (11) the response was (No)
in which as (The learning environment in the hospital with a homogeneous environment college) at student's
attitude's regarding clinical learning environment. And the study revealed that there were high mean score
response among study sample at the clinical training.
Recommendations: The study recommended to need to conduct other the researches to evaluate the actual
clinical learning environment for nurse's skills and practices performance in the hospital. And to determine factors
influence student's during clinical learning environment and clinical training

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Potential use of Dry Metallic Copper and Colloidal silver solution to reduce survival of Pseudomonas aeruginosa isolates from healthcare environment
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The objective of this study was to evaluate the activity of dry metallic copper and colloidal silver solution to reduce the viability of P.aeruginosa isolates compared with stainless steel as a control. Three clinical isolates of P.aeruginosa (108, 110 and 111 ) which were multi antibiotics resistant tested by inoculating 107 CFU/ml on to coupons( 1cm x 1cm) of copper and stainless steel and incubated at room temperature for various time periods ranging from 30minutes up to 180 minutes .Bacterial viability was determined by plate viable count CFU/ml. The results on copper coupons shows complete killing of isolates after 120 min in contrast to stainless steel, viable organisms were detected after 180 min, indicating a significant P value

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Hybrid CNN-SMOTE-BGMM Deep Learning Framework for Network Intrusion Detection using Unbalanced Dataset
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This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Psychological health disorders in kindergarten
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The goal of modern education is to achieve healthy growth of the individual and
society Since childhood is one of the most serious developmental stages in the human
identity, which is not limited to the threat to it stage the foundations of personal sound is
placed where the dimensions of the various components and based on the foregoing targets
Current Search: "Measuring the level of psychological health kindergartens"
And it included a sample search on the kindergarten children in the province of
Baghdad and achieve the objectives of research have been prepared in scale mental health and
concluded the researcher through the search results that kindergarten children suffering from
disorders in mental health, the

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Publication Date
Sat Feb 27 2021
Journal Name
Journal Of Engineering
Assessment of Electromagnetic Pollution in Some Hospitals and Schools in Al-Najaf City
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The tremendous benefits of using cellular phones, which began to increase and unprecedented spread worldwide last decade, were accompanied by harmful effects on the environment due to the increase in electromagnetic radiation (EMR) which be emitted from mobile phone towers. This effect on humans, animals, and plants, which is considered a form of environmental pollution, was sensed by developed countries and Environmental protection organizations. These countries have established restrictions and enacted laws to reduce their negative impact on living beings. The field survey included six major hospitals and 38 schools were distributed over the central neighbourhoods in Al-Najaf city. The results showed that power density (PD) measurement

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Publication Date
Thu May 31 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Seroprevalence of Toxoplasmosis Antibodies among Diabetes Mellitus Patients and Assessment some Biochemical Markers
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         Toxoplasma gondii is an protozoan intracellular coccidian protozoan parasite. Latent toxoplasmosis threat to immunocompetent individuals. Diabetic patients are more susceptible to infect with toxoplasmosis due to their low level of immunity response. The purpose of this research is to define the association between toxoplasmosis and diabetes mellitus and detection serum levels of chemokines (monocyte chemoattractant protien-1 and transforming growth factor-β) in diabetic patients infected with toxoplasmosis. Serum samples were collected from 120 diabetic patients and 50 healthy individuals as a control group  from the Imamein Kadhimein Medical City in Baghdad. In order&nbs

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Publication Date
Fri Jan 31 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of serum and salivary ceruloplasmin level in patients with oral lichen planus
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Background: Oxidative stress is a deleterious process that can be an important mediator of damage to cell structures and consequently various disease states. Exposure to free radicals from a variety of sources has led organisms to produce a series of defense mechanisms. The antioxidant ceruloplasmin is a copper-containing ferroxidase that can oxidize ferrous iron (Fe2+) to its nontoxic ferric (Fe3+) form. Ferrous iron (Fe2+) is extremely damaging because of its ability to generate toxic free radicals. Oral lichen planus (OLP) is a chronic inflammatory oral mucosal disease of unknown etiology. Previous studies reported that reactive oxygen species may be involved in the pathogenesis of lichen planus. The aim of this study was to estimate the

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Publication Date
Mon Jan 03 2022
Journal Name
Iraqi Journal Of Science
Accuracy Assessment of 3D Model Based on Laser Scan and Photogrammetry Data: Introduction
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    A three-dimensional (3D) model extraction represents the best way to reflect the reality in all details. This explains the trends and tendency of many scientific disciplines towards making measurements, calculations and monitoring in various fields using such model. Although there are many ways to produce the 3D model like as images, integration techniques, and laser scanning, however, the quality of their products is not the same in terms of accuracy and detail. This article aims to assess the 3D point clouds model accuracy results from close range images and laser scan data based on Agi soft photoscan and cloud compare software to determine the compatibility of both datasets for several applications. College of Scien

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