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Improvement of Gypseous Soil Using Cutback Asphalt
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Gypseous soils are widely distributed and especially in Iraq where arid area of hot climatic is present. These soils are considered as problematic soils; therefore this work attends to improve the geotechnical properties of such soil and reduce the dangers of collapse due to wetting process. In this research, undisturbed soil sample of 30 % gypsum content from Karbala city is used. The Single Oedometer collapse test is used in order to investigate the collapse characteristics of natural soil and after treatment with 3%, 6%, 9%, 12% and 15% of Cutback Asphalt. Moreover, two selected additive percentages (9% and 12%) are used to evaluate the suitability of using the Cutback Asphalt for improvement of the bearing capacity of gypseous soils. A steel model box is used for this purpose, the treatment depth is equal to one and twice the footing width. The tests results showed that the total settlement of 25 mm of treated soil with (MC-30) material can be achieved at vertical stress lower than that value required for natural soil. Also, thickness of treated layer with (MC-30) material below the proposed foundation has a significant effect on the value of bearing capacity of the soil. The rate of salt dissolved (C.V) is extremely decreased especially at all percentages of Cutback Asphalt.  The best bearing improvement ratio is found at 9% asphalt and at a depth equal to foundation width. However, the Cutback Asphalt can be successfully used by 12% for collapse potential treatment while it is not suitable for improvement of the bearing capacity of gypseous soils.

 

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Publication Date
Fri Aug 22 2025
Journal Name
Journal Of Physical Education
Unbalanced Strength Exercises Using Designed Tools and Their Effects on Some Biomechanical Variables in Young 110m Hurdles
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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
A Modified Approach by Using Prediction to Build a Best Threshold in ARX Model with Practical Application
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

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Publication Date
Sat Jan 01 2022
Journal Name
3rd International Scientific Conference Of Alkafeel University (iscku 2021)
Exposure and etching time effects on the fission track density in CR-39 detectors using teeth samples
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Publication Date
Thu Sep 28 2017
Journal Name
Medycyna Pracy
MTS-6 detectors calibration by using <sup>239</sup>Pu-Be neutron source
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Publication Date
Mon Jul 11 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Dynamic Background Subtraction in Video Surveillance Using Color-Histogram and Fuzzy C-Means Algorithm with Cosine Similarity
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The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

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Publication Date
Mon May 01 2017
Journal Name
Nano Hybrids And Composites
White Light Generation from Electroluminescence Devices Using TPD:PMMA/QDs/Alq<sub>3</sub>
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Quantum dots of CdSe, CdS and ZnS QDs were prepared by chemical reaction and used to fabricate organic quantum dot hybrid junction device. QD-LEDs were fabricated using layers of ITO/TPD: PMMA/CdSe/Alq3, ITO/TPD: PMMA/CdS/Alq3 and ITO/TPD: PMMA/ZnS/Alq3 devices which prepared by phase segregation method. The hybrid white light emitting devices consists, of three-layers deposited successively on the ITO glass substrate; the first layer was of N, N’-bis (3-methylphenyl)-N, N’-bis (phenyl) benzidine (TPD) polymer mixed with polymethyl methacrylate (PMMA) polymers. The second layer was QDs while the third layer was tris (8-hydroxyquinoline) aluminium (Alq3

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Enhancing Assurance Services Using Non-Renewable Resources Standard (NR0401) “Constructive Materials: Applied Research for Kufa Cement Factory
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The importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Fri Jun 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Using game theory models to determine the profit maximization policies for PepsiCo and Coca Cola in Baghdad
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(Use of models of game theory in determining the policies to maximize profits for the Pepsi Cola and Coca-Cola in the province of Baghdad)

Due to the importance of the theory of games especially theories of oligopoly in the study of the reality of competition among companies or governments and others the researcher linked theories of oligopoly to Econometrics to include all the policies used by companies after these theories were based on price and quantity only the researcher applied these theories to data taken from Pepsi Cola and Coca-Cola In Baghdad Steps of the solution where stated for the models proposed and solutions where found to be balance points is for the two companies according to the princi

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