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alkej-164
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

150 sets of data were generated in different days by the reference heat exchanger model to training the network. Regression between desired target and prediction ANN output for training , validation, testing and all samples show reasonably values are equal to one (R=1) . 50 sets of data were generated to test the network and compare between desired and predicated exit temperature (water temp. and air temp.) show a good agreement ( ).

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Numerical and experimental investigation on the performance of the capillary tube using R-134a and R-600a
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In this paper, isobutane (R-600a) is used as a suitable substitute for (R-134a) when changing the length of capillary tube. And the experimental data on capillary tube are obtained under different conditions such as (subcooling and ambient temperatures) on domestic refrigerator (9ft3 size), this data shows that (R-600a) a suitable substitute for (R134a) .The test presented a model for a steady state, two-phase flow in capillary tube for vapour compression system .The numerical model depends on conservation equations (mass, energy and momentum) as wall as the equation of state for refrigerant. The solution methodology was implemented by using finite difference techniques. The system results indicate that it is possible to change the refri

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Comparing Weibull Stress – Strength Reliability Bayesian Estimators for Singly Type II Censored Data under Different loss Functions
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     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
BUILD AN EFFICIENT INVESTMENT PORTFOLIO USING THE WILLIAM RATIO (EMPIRICAL STUDY) IN IRAQ STOCK EXCHANGE: BUILD AN EFFICIENT INVESTMENT PORTFOLIO USING THE WILLIAM RATIO (EMPIRICAL STUDY) IN IRAQ STOCK EXCHANGE
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ABSTRACT

            This study aimed to choose top stocks through technical analysis tools specially the indicator called (ratio of William index), and test the ability of technical analysis tools in building a portfolio of shares efficient in comparison with the market portfolio. These one technical tools were used for building one portfolios in 21 companies on specific preview conditions and choose 10 companies for the period from (March 2015) to (June 2017). Applied results of the research showed that Portfolio yield for companies selected according to the ratio of William index indicator (0.0406) that

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
The Numerical Technique Based on Shifted Jacobi-Gauss-Lobatto Polynomials for Solving Two Dimensional Multi-Space Fractional Bioheat Equations
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This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

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Publication Date
Thu Dec 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Implementation of Total Productive Maintenance (TPM) for industrial establishments and their impact on operational strategy: applied research in a sample of industrial companies
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The aim of the research is to measure the relationship and effect of the application of total production maintenance TPM in the operational strategy, as it is considered one of the most important strategies for the process of restoring production losses because of inefficient equipment. Competitive edge in the global market by upgrading the operational strategies of OS in the application of TPM in those institutions that apply both H-OS-oriented and P-OS-oriented strategies where the strategy has been identified as a critical success factor. The aim of this study is to attempt to consider the application of comprehensive productive maintenance in industrial establishments

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using Multivariate GARCH Models CCC (Constant Conditional Correlation) and DCC(Dynamic Conditional Correlation) To Forecast Iraqi Dinar Exchange Rate in Dollar
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Abstract

Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three  financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera  , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Comparison of Properties of Various Heat Storage Fluids used with Evacuated Tube of Solar Water Heater
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The aim of this work was to capture solar radiation and convert it into solar thermal energy by using a storage material and the heat transfer fluid like oil and water and comparison between them, we used the evacuated tube as a receiver for solar radiation, The results showed that the oil better than water as storage material and the heat transfer fluid and the effective thermal conductivity material and good for power level, rates and durations of charge and discharge cycles.

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