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The Causal Relationship between Forgiveness and Psychological Hardiness For University Students
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The research aimed to identify the causal relationship between forgiveness and psychological hardness for university students, by answering the following questions: Does forgiveness cause psychological hardiness? Does psychological hardiness cause forgiveness? Is the relationship between the two variables a reciprocal relationship? The research sample consisted of (300) male and female students from the universities of Baghdad and Al-Mustansiriya University. To extract the psychometric properties of the two scales: forgiveness and psychological hardiness, a sample of (50) male and female students employed to repeat the test, making the six connections between the two research variables. To determine the causal relationship, The Pearson correlation coefficient test was used. The results showed that the relationship is mutually beneficial between the two variables.

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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Mon Sep 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Experimental Performance of a Finned-tube Silica Gel Adsorption Chiller for Air-Conditioning Application
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This work presents the construction of a test apparatus for air-conditioning application that is flexible in changing a scaled down adsorbent bed modules. To improve the heat and mass transfer performance of the adsorbent bed, a finned-tube of the adsorbent bed heat exchanger was used. The results show that the specific cooling power (SCP) and the coefficient of performance (COP) are 163 W/kg and 0.16, respectively, when the cycle time is 40 min, the hot water temperature is 90oC, the cooling water temperature is 30oC and the evaporative water temperature is 11.4oC.

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
Wireless Optimization Algorithm for Multi-floor AP deployment using binary particle swarm optimization (BPSO)
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Abstract<p>Optimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol</p> ... Show More
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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
High Order Sliding Mode Observer-Based Output Feedback Controller Design For Electro-Hydraulic System
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A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Mathematical Model for BOD in Waste Water Discharges from Al Dora Refinery in Baghdad
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This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there
is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Tue Feb 01 2022
Journal Name
Macromolecular Symposia
Synthesis of 5‐Fluorouracil–Naproxen Conjugates as a Mutual Prodrug for Targeting Cancer Tissues
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Abstract<p>A new 5‐fluorouracil–naproxen conjugate is synthesized as a mutual prodrug for targeting cancer tissues. The structure of the target compound and their intermediate are characterized by their melting point, IR, <sup>1</sup>H NMR, <sup>13</sup>C NMR, and elemental microanalysis. The cytotoxic activity is preliminarily evaluated using nonsmall lung cancer CRL‐2049, human breast cancer CAL‐51, and one type of normal cell line; rat embryo fibroblast cell line. The synthesized compound shows a good cytotoxic effect at the cancer cell and no significant effect at rat embryo fibroblast cell line.</p>
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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Effect of Very Early Atorvastatin Initiation for Acute Myocardial Infarction on Creatine Kinase release
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Background : It has been suggested that pretreatment with a statin agent prior to
myocardial infarction limits myocardial
creatine kinase release, and thus may act to
limit myocardial infarct size in humans.
Objective : To examine the effect of very
early statin initiation for acute myocardial
infarction (AMI), to the extent of
myonecrosis as manifested by peak serum
creatine kinase levels.
Methods : Patients with AMI admitted to AlKindy teaching hospital cardiac care unit
from 1st February 2007 to 28th February
2008, who fulfilled the inclusion criteria
cited in the present study, were randomly
assigned into two study groups. The statin
group patients have received a single oral
dose of 40 mg

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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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