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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
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
The relationship between the multiple intelligence and the numerical sense of mathematic subject among 4th secondary stage students
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The study aimed to investigate the relationship between the multiple intelligence and the numerical sense. The chosen population of the study was the 4th secondary stage students. The sample consisted of 400 female and male student. The researcher utilized two test; multiple intelligence test which include three categories of intelligence (logical-mathematical, spatial, and linguistics) consisted of (36) item, and the numerical sense test that consisted of (44) item. The two tests were constructed by the researcher himself. The psychometric properties of the test were also verified. The results showed that there was a correlation between the multiple intelligence and the numerical sense as well as the students’ means scores

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19
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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
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Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region
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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
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
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Recurrent Neural Networks and its Applications in Time Series Data
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Correlation between Rheumatoid Factor, Chloroquine Phosphate in Osteoarthritis
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Osteoarthritis (OA) is a series of aggressive destructive inflammatory processes. Synovitis is common both at an early and a late phase. This disease may be uniquely singular in some site but phylogenetically related at some point in time to produce a common outcome of dysfunction, disability, socioeconomic destruction and sometimes socioeconomic failure. Articular cartilage, subchondral bone and synovial membrane are the site of major abnormalities in this disease process. Rheumatoid factor (RF) represents one of the routine laboratory tests that made for all patients have joint complaints.Chloroquine phosphate (CQP) is agent belong to disease modifying osteoathritic drugs (DMOADs). Chloroquine and their derivatives have been used for t

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