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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
Sun Feb 15 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Early and delayed effect of 2% chlorhexidine on the shear bond strength of composite restorative material to dentin using a total etch adhesive
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Background: Lack of durability of the bond of the dental adhesive systems to tooth structure is one of the most important problems in tooth colored restorative work. This in vitro study was performed to evaluate the effect of 2% chlorhexidine gluconate(CHX) on dentin bond strength by using total etch adhesive system at twenty-four hours and three months of water storage. Material and methods:A flat dentin surface was prepared for forty sound human maxillary premolar teeth which were acid etched with 36% phosphoric acid gel after being divided randomly into four groups of ten teeth each according to storage time and CHX application, theCHX was applied for 60 seconds before adhesive application for groups I and III which were tested after twe

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
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The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
Comparative Transfer Learning Models for End-to-End Self-Driving Car
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Comparison among variable selection models and its application to health dataset
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modified Grid Clustering Technique to Predict Heat Transfer Coefficient in a Duct of Arbitrary Cross Section Area
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A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between Bayesian Method and Full Maximum Likelihood to estimate Poisson regression model hierarchy and its application to the maternal deaths in Baghdad
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Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

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Publication Date
Fri Sep 15 2023
Journal Name
Al-academy
The preoccupations of the compressive references and their impact on the formations of postmodern art
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The artistic process operates whether in general in all arts or specifically in one type of arts or one of the genres of arts types on the preoccupations of the pressing artistic references as the founder of the artistic work in the material formulations on the one hand and on the other hand as a translator to understand the artistic achievement in general and plastic art in particular and for the importance The researcher chose the title of her research tagged (the preoccupations of the pressing reference and its impact on the formations of postmodern arts).
The first chapter of the methodological framework deals with the problem of research, importance, objective, limits, and then terminology and its definition, and then the secon

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Water Movement through Soil under Drip Irrigation using Different Hydraulic Soil Models
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Drip irrigation is one of the conservative irrigation techniques since it implies supplying water directly on the soil through the emitter; it can supply water and fertilizer directly into the root zone. An equation to estimate the wetted area in unsaturated soil is taking into calculating the water absorption by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, HYDRUS comprises analytical types of the estimate of different soil hydraulic properties. Used one soil type, sandy loam, with three types of crops; (corn, tomato, and sweet sorghum), different drip discharge, different initial soil moisture content was assumed, and different time durations. The relative error for the different hydrauli

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Publication Date
Sun Feb 15 2026
Journal Name
Journal Of Physical Education
The impact of a computerized program (cogniplus) to develop the strength to focus and perform kinetic chain on the balance beam
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