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Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved the prediction of bubble sizes. The developed correlation also shows better prediction over a wide range of operation parameters in bubble columns.

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq
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The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstractio

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Publication Date
Mon Mar 18 2019
Journal Name
Civil Engineering Journal
Circularization Technique for Strengthening of Plain Concrete Short Square Columns Subjected to a Uniaxial Compression Compressive Pressure
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This paper presents an experimental study for strengthening existing columns against axial compressive loads. The objective of this work is to study the behavior of concrete square columns strengthening with circulation technique. In Iraq, there are significantly more reinforced rectangular and square columns than reinforced circular columns in reinforced concrete buildings. Moreover, early research studies indicated that strengthening of rectangular or square columns using wraps of CFRP (Carbon Fiber Reinforced Polymer) provided rather little enhancement to their load-carrying capacity. In this paper, shape modification technique was performed to modify the shape (cross section) of the columns from square columns into circular colu

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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PREDICTION OF FINITE CONCENTRATIONBEHAVIOR FROM INFINITE DILUTION EGUILIBRIUM DATA
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Experimental activity coefficients at infinite dilution are particularly useful for calculating the parameters needed in an expression for the excess Gibbs energy. If reliable values of γ∞1 and γ∞2 are available, either from direct experiment or from a correlation, it is possible to predict the composition of the azeotrope and vapor-liquid equilibrium over the entire range of composition. These can be used to evaluate two adjustable constants in any desired expression for G E. In this study MOSCED model and SPACE model are two different methods were used to calculate γ∞1 and γ∞2

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Fri Jan 01 2021
Journal Name
Lecture Notes In Networks And Systems
Evaluating the Efficiency of Regional Transport Network
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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Improvement of Traffic Movement for Roads Network in Al-Kadhimiya City Center
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Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

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Publication Date
Mon Jun 23 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of the effect of root canal preparation size and flaring on the depth of irrigant penetration (In vitro study)
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Background: Cleaning and shaping of root canals successfully requires high volumes of irrigation solutions that can only be applied to the apical third of root canal after enlargement with instrument, so the aim of this study was to evaluate and to compare the efficiency of Maxi-I-probe (side-vented needle), in the amount of root canal irrigant penetration for five different master apical file sizes (MAF) and four different degrees of coronal and middle thirds flaring. Materials and Methods: Two hundred resin blocks with simulated root canals were used in this study and divided into 5 major groups (40 for each) based on the size of master apical files (#20, #25, #30, #35, and #40). Each major group was subdivided into 4 subgroups depending

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Publication Date
Fri Aug 30 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Artificial Intelligence and Cybersecurity in Face Sale Contracts: Legal Issues and Frameworks
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The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera

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Publication Date
Mon Mar 01 2021
Journal Name
World Heart Journal
Change in Left Ventricular Size and Ejection Fraction in Patients at Rest vs. Stress with Different Degrees of Ischemic Heart Failure
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Background and Aim. Coronary artery disease (CAD) is a major risk factor for the progression to heart failure (HF), which is associated with an increase in left ventricular volume (LVV). This study aims to measure ventricular function and myocardial perfusion imaging markers of the left side of the heart, which can be performed with injection of a 99mTc at stress and rest by using single-photonemission-computed-tomography (SPECT). Subject and methods. The study included 121 patients with CAD, comprising 53 females and 68 males with ages between 25 to 88 years and 265 healthy subjects comprising 84 males and 181 females. All patients and healthy subjects volunteered to participate in this study. They were classified according to

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