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Regression Analysis Models to Predict the 28 -day Compressive Strength Using Accelerated Curing Tests
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Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.

      The experimental results showed that the accelerated strength were equal to about (0.356), (0.492) and (0.595) of the 28-day compressive strength for warm water, autogenous and British curing methods respectively. A statistical regression analysis using SPSS program is implemented for the experimental results of the 28-day compressive strength ranging from (16 to 55.2)Mpa and accelerated strength for different curing methods. The linear models with high R2 and F-value are adopted for different curing methods while the Power model with constant is the best model for non parametric analysis.

 

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Publication Date
Mon May 26 2025
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Cone Projections and Quadratic programming in Estimation of Constrained Regression
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Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Thu Jan 01 2015
Journal Name
Mj Journal On Applied Mathematics
Mathematical models for estimation the concentration of heavy metals in soil
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Publication Date
Tue Sep 01 2020
Journal Name
Ain Shams Engineering Journal
Estimating server utilization rate in single server queuing models using an approximate solution of stiff fluid flow model
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Publication Date
Tue Mar 01 2022
Journal Name
Jordan Journal Of Biological Sciences
Characterization, Biofilm and Plasmid Curing Effect of Silver Nanoparticles Synthesis by Aqueous Extract of Myristica fragrans Seeds
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Publication Date
Thu Jan 13 2022
Journal Name
Jordan Journal Of Biological Sciences
Characterization, Biofilm and Plasmid Curing Effect of Silver Nanoparticles Synthesis by Aqueous Extract of Myristica fragrans Seeds
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Nowadays nanoparticles are used in many fields of life all over the world, and there are numerous ways to obtain them: chemical, physical and biological processes. In recent times, the biological method for the synthesis of nanoparticles associated with using plant extract is widely spread. Optimal conditions for synthesis of silver nanoparticles using aqueous seeds extract of Myristica fragrance were highlighted in this research, such as type of plant extract, weight of extracted plant material, volume ratio of plant extract to AgNO3 and temperature of reaction. The study proved that the optimal status for AgNPs synthesis by using 10 g of M. fragrance seeds powder were added to 100 mL boiled distilled water, then homogenized and f

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Publication Date
Fri Apr 01 2022
Journal Name
Jordan Journal Of Biological Sciences
Characterization, Biofilm and Plasmid Curing Effect of Silver Nanoparticles Synthesis by Aqueous Extract of Myristica fragrans Seeds
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Nowadays nanoparticles are used in many fields of life all over the world, and there are numerous ways to obtain them: chemical, physical and biological processes. In recent times, the biological method for the synthesis of nanoparticles associated with using plant extract is widely spread. Optimal conditions for synthesis of silver nanoparticles using aqueous seeds extract of Myristica fragrance were highlighted in this research, such as type of plant extract, weight of extracted plant material, volume ratio of plant extract to AgNO3 and temperature of reaction. The study proved that the optimal status for AgNPs synthesis by using 10 g of M. fragrance seeds powder were added to 100 mL boiled distilled water, then homogenized and filt

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Publication Date
Fri Jan 31 2025
Journal Name
Aip Conference Proceedings
Classification of oral cavity cancer using linear discriminant analysis (LDA) and principal component analysis (PCA)
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Publication Date
Wed Nov 08 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Analysis of x-ray diffraction lines of cuprous oxide nanoparticles by using variance analysis method
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In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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