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Empirical model for predicting slug-pseudo slug and slug-churn transitions of upward air/water flow
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A pseudo-slug flow is a type of intermittent flow characterized by short, frothy, chaotic slugs that have a structure velocity lower than the mixture velocity and are not fully formed. It is essential to accurately estimate the transition from conventional slug (SL) flow to pseudo-slug (PSL) flow, and from SL to churn (CH), by precisely predicting the pressure losses. Recent research has showed that PSL and CH flows comprise a significant portion of the conventional flow pattern maps. This is particularly true in wellbores and pipelines with highly deviated large-diameter gas-condensate wellbores and pipelines. Several theoretical and experimental works studied the behavior of PSL and CH flows; however, few models have been suggested to predict SL/CH and are very limited for SL/PSL transitions. Based on the experimental data, an empirical model was suggested to predict the SL/PSL/CH transition for air/water upward inclined flow. The proposed model correlates the modified gas Froude number with the inclination angle and modified liquid Froude number. The inclined flow dataset includes 125 data points of SL, PSL, and CH covering angle of inclination (θ) from 2o to 89.4 °with a relatively large pipe diameter (D) of 0.1016 m. The developed model accurately predicted all data and captured the expected influence of inclination angle, pipe diameter, and gas density on the SL/PSL/CH transition. The developed model was tested favorably against three datasets (681 points) collected from twelve independent studies: 549 air/water two-phase points, 65 air/viscous liquid two-phase points, and 67 air/oil/water three-phase points.

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Publication Date
Sun Jun 01 2014
Journal Name
2014 International Conference On Computer And Information Sciences (iccoins)
Proposed conceptual model for E-service quality in Malaysian universities
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Tue Nov 27 2018
Journal Name
The Iraqi Geological Journal
CHRONOSTRATIGRAPHICALLY BASED RESERVOIR MODEL FOR CENOMANIAN CARBONATES, SOUTHEASTERN IRAQ OILFIELDS
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The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Phase Behavior Compositional Model for Jambour Cretaceous Oil Reservoir
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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Factors Affecting Timeliness Issuance of Corporate Financial Reporting Listed Companies in Palestine Exchange (PEX) (An Empirical Study)
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This study examined the relationship between the reporting lag (the timeliness of corporate financial reporting) and several independent variables: (1) Audit reporting lag,(2)Company Size,(3) Profitability of the company,(4)Company Age,(5) Sector Type.(6)Audit’s Opinion,(7) Market Type,(8) Gearing,(9) Concentration of ownership,(10) Audit Firm Size(11)Profit or Loss Company(12) Companies Listed lag on the PEX. In order to achieve the objectives of the study and testing its hypotheses, the data Obtained through actual data of a financial reports, and based on me

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Synergistic Interaction in the adsorbed mixed surfactants film of Sodium Dodecyl Sulfate and Cocamidopropyl Betaine on Liquid – Air Interfacial
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In the present work, the critical micelle concentration (CMC) of the solution of Sodium dodecyl sulfate (SDS) as anionic surfactant, Cocamidopropyl Betaine (CAPB) as amphoteric surfactant, and their mixture have been determined using surface tension and conductivity measurements at a temperature range 293 -323 K. The adsorption and thermodynamic micellization parameters (?G?m, ?G?ads, ?max ,Amin,?cmc ) for individual surfactants was calculated. Rosen model which is focuses on the adsorbed mixed surfactant film at the air/solution interface was used to calculate the interaction parameter ( ?? ) at the interface and the activity coefficients g1 and g2. The results indicate that the CMC of the individual surfactants was affected by

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Publication Date
Sun Nov 16 2025
Journal Name
Wasit Journal Of Sports Sciences
The impact of the Needham model on learning the skills of dribbling and handling in football for students
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of weighted estimated method and proposed method (BEMW) for estimation of semi-parametric model under incomplete data
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Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

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