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Effectiveness of an Educational Program on Nurses' Knowledge Toward Early Prediction of Acquired Weakness in The Intensive Care Unit.
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Abstract:

Objectives: The present study aims to evaluate effectiveness of educational program the nurses' knowledge towards early prediction of acquired weakness in the intensive care unit.

Methodology: A pre-experimental study design (comparison of two groups), which was achieved through the pre and post-test method for the study sample through the application of an educational program in the intensive care unit of Al-Zahra Teaching Hospital in Kut city, Wasit Governorate. The study was conducted for the period from 28th April 2022 to 15th August 2022 by selecting a purposive (non-probability) sample for this study. The study sample size was (52) nurses, divided into two groups, each one containing (26) nurse as a control group and a study group. The study group was shown the educational program while the control group was not exposed to the educational program.

Results: The results of the study show a clear positive effect on the nurses' knowledge toward the early predictive acquired weakness in the intensive care unit. The study indicated that their high significant differences between the control group and study group, between the pre and post for the study group after presenting them with the educational program.

Recommendations: The study recommended to design and construct an educational program for the nursing staff, whereby through the program emphasizing the directed and familiarize with how to deal with acquired weakness in intensive care unit and who reduce complications that result from long stay in ICU.

Keys of words: effectiveness educational programs, nurses' knowledge, acquired weakness, intensive care unit


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Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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Publication Date
Fri Jan 01 2016
Journal Name
Procedia Economics And Finance
Impact of Information Technology Infrastructure on Innovation Performance: An Empirical Study on Private Universities In Iraq
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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of International Studies
Emergence and developing united Arab of Emirates nuclear program
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United Arab of Emirates made efforts in developing workforce in the field of nuclear energy that it had a chance to attract specialized of this field that it reflect growth in every field of life through which it take special procedures to face casas as fokoshima .the state had started to apply the UAE peaceful nuclear program by opening (Baraka)station in 2010 as to be the first in the Arab world to aim to enhance and diversification energy sources of electricity there in addition to enhance the state’s efforts to achieve economic refreshing and environmental protect.

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Doctrinal responses On the fabrications of succor Tamimism
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Doctrinal responses
On the fabrications of succor
Tamimi

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Publication Date
Mon Dec 16 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of information technology on tax evasion
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The research aims at shedding light on the impact of information technology in reducing tax evasion in the General Authority for Taxation. In order to achieve this, the research relied on the analysis of its variables as a main tool for collecting data and information. The results showed that there is a positive and positive effect of information technology on tax evasion. The impact of information technology on increasing tax revenues and reducing the phenomenon of tax evasion In the performance of the research sample, the research sought to highlight the importance of tax information technology through its data and information to the tax administration for the purpose of completing the process Taxpayers for persons subject to income ta

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
The effect of context on some Quranic methods
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Each book has a specific style in which its author walks on it from its beginning to its end, and the Holy Qur’an is a book that compiled many methods that were indicative of its miracle, and that it is one unit even though it has been astrologer for twenty-three years.
There is no doubt that knowledge of the Qur’anic methods is one of the pillars of the approach that deals with any of the Qur’an, and the multiplicity of Qur’anic methods is a fact that has many causes. It has been expressed by the Qur’anic discharge and the conjugation of verses to bring them to different methods, and on multiple forms such as nominal, actual, singular Qur’an, presentation, delay, deletion, mention, abbreviation and redundancy. The Qur'ani

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Mon Aug 18 2025
Journal Name
Soil And Sediment Contamination: An International Journal
Remediation Prediction of Contaminated Soil with Crude Oil Using the Optimized Remediation Method for the Iraqi Environment
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Large quantities of petroleum-contaminated soil are generated with increased global energy consumption and crude oil production. This theoretical study evaluates the treatment of 1 ton of petroleum-contaminated soil using seven methods: incineration, physical washing, chemical washing, thermal pyrolysis, Fenton-oxidation-pyrolysis, the biological treatment, and asphaltenes. Data were based on experimental results from the Nahran Bin Omar oil lake in Basra Governorate, Iraq, (2019–2021). The methods were compared by waste generation, treatment cost, and duration. Results indicate that using petroleum-contaminated soil as a raw material for asphalt manufacturing is most beneficial since it is sold as a raw material. Incineration is faster a

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
The Contribution of Behavioral Disorders to Predicting Bullying Patterns in a Sample of Adolescents with Autism Spectrum Disorder: College of Education and Arts - Northern Border University - Kingdom of Saudi Arabia.
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The present study aims to identify the role of behavioral disorders (anxiety disorder, behavior disorder "behavior", confrontation and challenge disorder, aggressive behavior) in predicting bullying patterns (verbal, physical, electronic, school) in a sample of adolescents with autism spectrum disorder. For this purpose, the researcher developed scales to measure the behavioral disorders and the bullying patterns among adolescents with autism spectrum disorder. The researcher adopted the descriptive survey approach. The study sample consists of (80) adolescents with autism spectrum disorder with ages range from (15-19 years) and (45-53 years old) in association with israr association for people with special needs in the northern borders

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

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