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Evaluate Factors Influencing Depression in Baghdad: Using Deck-Depression Inventory
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Objective: This study goal was to screen participants from different settings in Baghdad for depression using Beck Depression Inventory (BDI) scale and identify factors influencing the levels of depression. Methods: This cross-sectional study included a convenience sample of 313 people from four settings (teaching hospital, college of medicine, college of pharmacy, and high school) in Baghdad, Iraq. The participants were screened using paper survey relying on the BDI scale during spring 2018. Using multiple linear regression analysis, we measured the association between depression scores and six participant factors. Results: The overall prevalence of depression in our sample was 57.2%. Female participants had higher BDI scores (depression symptoms) than male participants.  Among those with depression, the majority (73.7%) had mild or moderate degree of depression. In terms of the cut-off scores, 42.8 % scored in the normal range, 20.4 % in the mild range, 7.0 % in the borderline range, 14.7 % in the moderate range, 10.5 % in the severe range and 4.5 % in the very severe range depression. Approximately 63% of the participants had sort of suicidal thoughts. The regression analysis showed significant (P-value < 0.05) association between having higher scores of depression symptoms and the presence of chronic disease(s), recent family loss, young age and female gender. Conclusions: In our findings, depression was quite prevalent among people in Iraq.  The study demonstrates the importance of broad screening and social/psychiatric counseling of young population. Iraqi healthcare professionals should structure specific actions for patients with chronic diseases to minimize their depression symptoms.   Article Type: Orignal Research

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Publication Date
Wed Jul 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Fast and robust approach for data security in communication channel using pascal matrix
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This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

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Publication Date
Mon Oct 01 2018
Journal Name
2018 International Conference On Advanced Science And Engineering (icoase)
Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
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Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
The effect of using XCAST based routing protocol in wireless ad hoc networks
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Publication Date
Wed Mar 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
ESTIMATION OF MASS TRANSFER COEFFICIENTS IN A PACKED DISTILLATION COLUMN USING BATCH MODE
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This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.

KOV = 3.3 * 10-10

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between robust methods in canonical correlation by using empirical influence function
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       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Mechanical Science And Technology
Damage detection in glass/epoxy composite structure using 8–12 GHz X-band
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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Sat Sep 01 2018
Journal Name
2018 15th European Radar Conference (eurad)
Delamination Detection in Glass-Fibre Reinforced Polymer (GFRP) Using Microwave Time Domain Reflectometry
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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Using dickey _ fuller expanded test for testing variables of investment function in Iraq
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         To ascertain the stability or instability of time series, three versions of the model proposed by Dickie-Voller were used in this paper. The aim of this study is to explain the extent of the impact of some economic variables such as the supply of money, gross domestic product, national income, after reaching the stability of these variables. The results show that the variable money supply, the GDP variable, and the exchange rate variable were all stable at the level of the first difference in the time series. This means that the series is an integrated first-class series. Hence, the gross fixed capital formation variable, the variable national income, and the variable interest rate

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