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Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both solar power automation subsystem and transformer simultaneously or consumption unit; otherwise it works with fully or lesser efficiency. Statistically independent failures and repairs are considered. Using the elementary probabilities phenomenon incorporated with differential equations is employed to examine the system reliability, for repairable and non-repairable system, and to analyze its cost function. The accuracy and consistency of the system can be improved by feed forward- back propagation neural network (FFBPNN) approach. Its gradient descent learning mechanism can update the neural weights and hence the results up to the desired accuracy in each iteration, and aside the problem of vanishing gradient in other neural networks, that increasing the efficiency of the system in real time. MATLAB code for FFBP algorithm is built to improve the values of reliability and cost function by minimizing the error up to 0.0001 precision. Numerical illustrations are considered with their data tables and graphs, to demonstrate and analyze the results in the form of reliability and cost function, which may be helpful for system analyzers.

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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Thu Feb 01 2024
Journal Name
Structures
Accelerating reliability analysis of deteriorated simply supported concrete beam with a newly developed approach: MCS, FORM and ANN
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Reliability analysis methods are used to evaluate the safety of reinforced concrete structures by evaluating the limit state function 𝑔(𝑋𝑖). For implicit limit state function and nonlinear analysis , an advanced reliability analysis methods are needed. Monte Carlo simulation (MCS) can be used in this case however, as the number of input variables increases, the time required for MCS also increases, making it a time consuming method especially for complex problems with implicit performance functions. In such cases, MCS-based FORM (First Order Reliability Method) and Artificial Neural Network-based FORM (ANN FORM) have been proposed as alternatives. However, it is important to note that both MCS-FORM and ANN-FORM can also be time-con

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Publication Date
Wed Oct 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Design of Self-Assessment Scale to Accreditation Standards
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The process of self-assessment plays a key role in achieving quality educational institutions (college, department or program academic particular), because the assessment process provides reviews of the effectiveness of the criteria used in the enterprise, especially in the field of teaching and learning, and is result self-assessment providing self-assessment report. The self- assessment can be performed at different levels (college, academic department, Master, Ph.D. program, or courses). The importance of the research focused on to provide a measure of self-assessment helps profile officials in the implementation of the assessment process are clear and precise and fast, and to provide them to measure the availability requireme

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Publication Date
Sat Nov 03 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nursing College Students' Health Protective Behaviors
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Objective: to assess the Nursing College students' health-protective behaviors (HPBs) and their
association with some sociodemograghic characteristics.
Methodology: A sample of 100 Students (males and females) was selected through a systematic
random sample that were at the third and fourth year of Nursing College in Baghdad University for the
period of April 1st through April 30th 2007. Data were collected through the use of a self-report
instrument that used for Americans as HPBs assessment that contains 23 items. Reliability and validity
of the tool were determined through a pilot study. A descriptive statistical approach (frequencies and
percentages) and inferential statistical approach (chi-square) were used for

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Publication Date
Wed Feb 01 2017
Journal Name
Heliyon
Environmental assessment of Al-Hammar Marsh, Southern Iraq
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Publication Date
Thu Nov 01 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Factors That Contribute to Bladder Cancer
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Abstract Objective: The study aimed to assess the factors contributes of patient with bladder cancer and to find out the relationship between the factors of bladder cancer with certain variable. Methodology: A descriptive study to assessment of factors that contribute to bladder cancer that was carried out Al-Karama teaching hospital, Al-Kendy teaching hospital, Specialty Surgery teaching hospital and Al-Yarmok teaching hospital for the period of November 2003 to August 2004. A purposive (non-probability) sample of (100) patients with bladder cancer. An assessment from was constructed for the purpose of the st

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Competitive Study Using UV and Ozone with H2O2 in Treatment of Oily Wastewater
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          In this study, ultraviolet (UV), ozone techniques with hydrogen peroxide oxidant were used to treat the wastewater which is produced from South Baghdad Power Station using lab-scale system. From UV-H2O2 experiments, it was shown that the optimum exposure time was 80 min. At this time, the highest removal percentages of oil, COD, and TOC were 84.69 %, 56.33 % and 50 % respectively. Effect of pH on the contaminants removing was studied in the range of (2-12). The best oil, COD, and TOC removal percentages (69.38 %, 70 % and 52 %) using H2O2/UV were at pH=12. H2O2/ozone experiments exhibited better performance compared to

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Publication Date
Wed Jan 13 2016
Journal Name
University Of Baghdad
Employ Mathematical Model and Neural Networks for Determining Rate Environmental Contamination
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Publication Date
Tue Jan 01 2019
Journal Name
مجلة كلية التربية للبنات
استخدام نظام مكتبي لادارة مكتبة كلية القانون
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Water Treatment Using Zinc Nanoparticles and Apricot Plant Extracts from Organic and Inorganic Pollution
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The apricot plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the apricot plant using ethanol, which was then analysed using GC-MS, Fourier transform infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using an alcoholic extract. FTIR, UV-Vis, SEM, EDX, and TEM are used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with apricot extract and powder were employed to clean polluted water. Firstly, 2 g of zinc nanoparticles were used with 20 ml of polluted water, and the results were Tetra 44% and Levo 32%; after

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