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Mathematical Modeling of Compaction Curve Using Normal Distribution Functions
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Compaction curves are widely used in civil engineering especially for road constructions, embankments, etc. Obtaining the precise amount of Optimum Moisture Content (OMC) that gives the Maximum Dry Unit weight gdmax. is very important, where the desired soil strength can be achieved in addition to economic aspects.

In this paper, three peak functions were used to obtain the OMC and gdmax. through curve fitting for the values obtained from Standard Proctor Test. Another surface fitting was also used to model the Ohio’s compaction curves that represent the very large variation of compacted soil types.

The results showed very good correlation between the values obtained from some published sample tests and the values obtained from curve fitting for both cases of the single curve and multiple Ohio’s curves.

The easiness of obtaining OMC and gdmax. From the results of curve fitting encourage users to utilize this procedure, in addition to its accuracy.

 

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Performance Evaluation of Scalar Multiplication in Elliptic Curve Cryptography Implementation using Different Multipliers Over Binary Field GF (2233)
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This paper presents a point multiplication processor over the binary field GF (2233) with internal registers integrated within the point-addition architecture to enhance the Performance Index (PI) of scalar multiplication. The proposed design uses one of two types of finite field multipliers, either the Montgomery multiplier or the interleaved multiplier supported by the additional layer of internal registers. Lopez Dahab coordinates are used for the computation of point multiplication on Koblitz Curve (K-233bit). In contrast, the metric used for comparison of the implementations of the design on different types of FPGA platforms is the Performance Index.

The first approach attains a performance index

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Feeble regular and feeble normal spaces in α-topological spaces using graph
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This paper introduces some properties of separation axioms called α -feeble regular and α -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our α -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.

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Publication Date
Wed Dec 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATING NONPARAMETRIC AUTOREGRESSIVE CURVE BY SMOOTHING SPLINES METHOD
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Publication Date
Thu Apr 03 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Cephalometric evaluation of a sample of Iraqi adults with normal occlusion using tetragon analysis
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Background: This study aimed to determine the cephalometric values of tetragon analysis on a sample of Iraqi adults with normal occlusion. Material and methods: Forty digital true lateral cephalometric radiographs belong to 20 males and 20 females having normal dental relation were analyzed using AutoCAD program 2009. Descriptive statistics and sample comparison with Fastlicht norms were obtained. Results: The results showed that maxillary and mandibular incisors were more proclined and the maxillary/mandibular planes angle was lower in Iraqi sample than Caucasian sample. Conclusion: It's recommended to use result from this study when using tetragon analysis for Iraqis to get more accurate result.

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
Achieving an optimum slowing-down energy distribution functions and corresponding reaction rates for the (D+3He and T+3He) fusion reactions
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A new results for fusion reactivity and slowing-down energy distribution functions for controlled thermonuclear fusion reactions of the hydrogen isotopes are achieved to reach promising results in calculating the factors that covered the design and construction of a given fusion system or reactor. They are strongly depending upon their operating fuels, the reaction rate, which in turn, reflects the physical behavior of all other parameters characterization of the system design

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Asabe
Effects of Pressure and Moisture Content on Bulk Density of Triticale Grain under Compaction
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Highlights

Compaction of triticale grain with three moisture contents (8%, 12%, and 16% wet basis) was measured at five applied pressures (0, 7, 14, 34, and 55 kPa).

Bulk density increased with increasing pressure for all moisture contents and was significantly (p < 0.0001) dependent on both moisture content and applied pressure.

A Verhulst logistic equation was found to model the changes in bulk density of triticale grain with R2 of 0.986.

The model showed similar beha

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Activation Function in Approximate Periodic Functions Using Neural Networks
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The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Decisions making for fraction functions By Using Goal Programming Method
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Decision making is vital and important activity in field operations research ,engineering ,administration science and economic science with any industrial or service company or organization because the core of management process as well as improve him performance . The research includes decision making process when the objective function is fraction function and solve models fraction programming by using some fraction programming methods and using goal programming method aid programming ( win QSB )and the results explain the effect use the goal programming method in decision making process when the objective function is
fraction .

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The effect of using cognitive strategies on mathematical competence among Fourth Scientific students
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The research aims to find out the impact of cognitive strategies in the mathematical competence of the students of the fourth scientific in the preparatory mahmoudiyah in the Directorate General of The Education of Karkh 2. A post-test of the mathematical competence prepared by (Jassim, 2018) was applied to the sample of (65) students, distributed into two groups of (33) students as experimental group and (32) students as a control group. The results found there are significant differences between the experimental group and the control group in testing the mathematical competence of students for the experimental group.

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