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Correlation for fitting multicomponent vapor-liquid equilibria data and prediction of azeotropic behavior
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Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol – Hexane, Hexane – Benzene and 1-Propanol – Benzene” and the other ternary system is “Toluene – Cyclohexane – iso-Octane (2,2,4-Trimethyl-Pentane)” and its binaries “Toluene – Cyclohexane, Cyclohexane – iso-Octane and Toluene – iso-Octane” have been measured at 101.325 KPa. The measurements were made in recirculating equilibrium still with circulation of both the vapor and liquid phases. The ternary system “1-Propanol – Hexane – Benzene” which contains polar compound (1-Propanol) and the two binary systems “1-Propanol – Hexane and 1-Propanol – Benzene” form a minimum azeotrope, the other ternary system and the other binary systems do not form azeotrope.

            All the data passed successfully the test for thermodynamic consistency using McDermott-Ellis test method (McDermott and Ellis, 1965).

            The maximum likelihood principle is developed for the determination of correlations parameters from binary and ternary vapor-liquid experimental data which provides a mathematical and computational guarantee of global optimality in parameters estimation for the case where all the measured variables are subject to errors and the non ideality of both vapor and liquid phases for the experimental data for the ternary and binary systems have been accounted.

            The agreement between prediction and experimental data is good. The exact value should be determined experimentally by exploring the concentration region indicated by the computed values.

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Publication Date
Fri Apr 21 2023
Journal Name
Aip Conference Proceedings
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Study the contrast of thermal expansion behavior for PMMA denture base, single and hybrid reinforced using the thermomechanical analysis technique (TMA)
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Publication Date
Sat Dec 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
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The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

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Publication Date
Sat Oct 01 2022
Journal Name
Environmental Advances
Stability and performance studies of emulsion liquid membrane on pesticides removal using mixture of Fe3O4Â nanoparticles and span80
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Publication Date
Thu Nov 01 2012
Journal Name
2012 International Conference On Advanced Computer Science Applications And Technologies (acsat)
Data Missing Solution Using Rough Set theory and Swarm Intelligence
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of consolidation due to dewatering by using MATLAB software
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
The potential of nonparametric model in foundation bearing capacity prediction
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Publication Date
Wed Aug 26 2020
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE CORRELATION BETWEEN IRAQI EFL UNIVERSITY STUDENTS WORKING MEMORY CAPACITY AND THEIR LANGUAGE PROFICIENCY
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Publication Date
Mon Jul 04 2022
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
The Correlation between Insulin Resistance and Urotensin II in Patients with Gestational Diabetes Mellitus
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Gestational diabetes mellitus is glucose intolerance of varying degree with onset or first detection duringpregnancy,it can causelong and short term morbidities in both the mother and the child, such as shoulder dystocia,preeclampsia, and high blood pressure. The most powerful endogenous vasoconstrictor peptide, urotensin II, andits receptor are involved in the etiology of gestational diabetes mellitus.Aim of the study: The study’s goal was to see if there is a link between Urotensin II levels and insulin resistancein pregnant women with gestational diabetes.Patients and method: A case-control study that was conducted in obstetrics and gynecology department atBaghdad Teaching hospital from the first of January 2019 to the end of D

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