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Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique
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Abstract<p>Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essentially based on the repetitive construction projects’ composition of identical production units. This study develops a mathematical model to forecast repetitive construction projects using the Support Vector Machine (SVM) technique. The software (WEKA 3.9.1©2016) has been used in the process of developing the mathematical model. The number of factors affecting the planning and scheduling of the repetitive projects has been identified through a questionnaire that analyzed its results using SPSS V22 software. Three accuracy measurements, correlation coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), were used to check the mathematical model and to compare the actual values with predicted values. The results showed that the SVM technique was more precise than those calculated by the conventional methods and was found the best generalization with R 97 %, MAE 3.6 %, and RMSE 7 %.</p>
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Publication Date
Wed Jun 10 2020
Journal Name
Annals Of Tropical Medicine & Public Health
EFFECT OF EUCALYPTUS AND MYRTUS EXTRACTS IDENTIFICATION BY GAS CHROMATOGRAPHY-MASS SPECTROMETRY ON SOME SPECIES OF CANDIDA AS A MODEL OF MEDICAL PLANTS
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The study showed that all extracts (aqueous, ethanolic and acetonic) of the leaves of Eucalyptus and Myrtus plants had a inhibitory effect on the growth of all types of yeasts studied, acetone extract recorded the highest inhibition of yeastat 100ppm concentration,The inhibition was 35mm, 34mm, 24mm and 20mm for Candida parapsilosis, Candida glabrata, Candida tropicalis and Candida albicans respectively, The experiments above showed the least significant differences at 0.05 level.The results ofE. Cammldulensis ethanolic tincture analysis has shown the presence of 44 biologically active substances. The main Eucalyptus leaves component was: 2-Bicyclo (2-2.1) heptanol (12.37%), Ledol (8.23%),1,2,4- Benzenetriol (8.45%) and that contain spathul

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Improvement of the monochrome image hologram by using a random phase and increasing number of Samples
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This paper present a study about effect of the random phase and expansion of the scale sampling factors to improve the monochrome image hologram and compared it with previous produced others. Matlab software is used to synthesize and reconstruction hologram.

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Determination of paracetemol in pharmaceutical preparations samples by spectrophotometer using meta phenylenediamine as a chromogenic agent
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Publication Date
Wed Dec 01 2021
Journal Name
Bioresource Technology Reports
Biosynthesis of polyhydroxyalkanoate (PHA) by a newly isolated strain Bacillus tequilensis ARY86 using inexpensive carbon source
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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Optimal Color Model for Information Hidingin Color Images
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In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Geological Journal
Geological Model for Mauddud Reservoir Khabaz Oil Field
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

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Publication Date
Thu Jan 01 2026
Journal Name
Aip Conference Proceedings
Bayesian methodology for spatial quantile autoregressive model estimation
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Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Hydrology
Complementary data-intelligence model for river flow simulation
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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Tue Dec 21 2021
Journal Name
Open Access Macedonian Journal Of Medical Sciences
The Impact of Social Support on Students’ Behavior in the Context of Iraqi Medical Education
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BACKGROUND: Mental health problems are reflected and linked to human behavior in many aspects. Medical students are susceptible to a wide variety of events that compromise their mental well-being, social life as well as their academic achievements. AIM: This study aimed to find the impact of social support on medical students’ behavior in Iraq via assessing their depression, anxiety, and stress status. METHODS: A cross-sectional online survey-based study targeted all medical students in Iraq. The employed questionnaires covered mental health status of participants by evaluating their perceptions of depression, anxiety, and stress using. Data were analyzed using the Statistical Analysis System. RESULTS: The study revealed a signifi

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