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Prediction of Urban Spatial Changes Pattern Using Markov Chain
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Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to analyze time series based on current values to predict the series values in the future without relying on the past or historical values of the studied series. The research questions in this study are formulated thus: What are the trends in the patterns of urban land use functions in Al-Najaf, Iraq, between 2005 to 2015? How can the values of the changes be predicted for the year 2025? The hypothesis is based on the increasing spatial functional change of land use patterns in the city during the study period due to various economic and social factors. Making accurate predictions of the size of spatial changes motivates this study as a guide to urban management towards developing possible solutions to address the effects of this change, as well as the need to understand its causes and future upward trends. The contribution of this article is the presented outlook for spatial functions for the next 10 years. The computations using the Markov chain model will enable management to understand future relations and develop appropriate policies to reduce the hazards of unplanned changes in the city. Results show that residential posts, slums, and commercial activities are getting worse, while change values for industrial functions and other things are going down. 

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
REMOVAL of HEAVY METALS IONS from AQUEOUS SOLUTIONS USING BIOSORPTION onto BAMBOO
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Feasibility of biosorbent of England bamboo plant origin was tested for removal of priority metal ions such as Cu and Zn from aqueous solutions in single metal state. Batch single metal state experiments were performed to determine the effect of dosage (0.5, 1 and 1.5 g), pH (3, 4, 4.5, 5 and 6), mixing speed (90, 111, 131, 156 and 170 rpm), temperature (20, 25, 30 and 35 °C) and metal ion concentration (10, 50, 70, 90 and 100 mg/L) on the ability of dried biomass to remove metal from solutions which were investigated. Dried powder of bamboo removed (for single metal state) about 74 % Cu and 69% Zn and maximum uptake of Cu and Zn was 7.39 mg/g and 6.96 mg/g respectively, from 100 mg/L of synthetic metal solution in 120 min. of contact t

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Publication Date
Mon Oct 21 2019
Journal Name
Civil Engineering Journal
Non-Smooth Behavior of Reinforced Concrete Beam Using Extended Finite Element Method
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Flexure members such as reinforced concrete (RC) simply supported beams subjected to two-point loading were analyzed numerically. The Extended Finite Element Method (XFEM) was employed for the treatment the non-smooth h behaviour such as discontinuities and singularities. This method is a powerful technique used for the analysis of the fracture process and crack propagation in concrete. Concrete is a heterogeneous material that consists of coarse aggregate, cement mortar and air voids distributed in the cement paste. Numerical modeling of concrete comprises a two-scale model, using mesoscale and macroscale numerical models. The effectiveness and validity of the Meso-Scale Approach (MSA) in modeling of the reinforced concrete beams w

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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Physical Education
The Effect of Using Mental Maps On Cognitive Achievement In Rhythmic Gymnastics
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Strengthening of Reinforced Concrete T- Section Beams Using External Post-Tensioning Technique
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This research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section  RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (dps). So that the depth of strands to overall depth of the section ratio (dps

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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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Publication Date
Wed Jan 01 2014
Journal Name
Our Dermatology Online
Treatment of active acne vulgaris by chemical peeling using 88% lactic acid
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KE Sharquie, AA Noaimi, EA Al-Janabi, Our Dermatology Online, 2014 - Cited by 11

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Publication Date
Tue Jan 10 2012
Journal Name
Iraqi Journal Of Community Medicine
Evaluation of physical parameters in mitral valve stenosis by using Doppler Ultrasound
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Background: Mitral valve stenosis is a condition in which the hearts mitral valve is narrowed (stenosis), This narrowing blocks the valve from opening properly obstructing blood flow through the heart and the rest of the body and this causes changes in physical parameters (resistance and conductance). Aim of the study: To assess the changes in the physical parameters in mitral valve stenosis disease in different gender and age by using Doppler ultrasound. Methods : The examination of patients at the Division of Echo - at the Iraqi Center for Heart Disease in Medical City for surgery specialist - Baghdad - Iraq, during(February2009 till November2010). The current study included fifty eight cases containing (27 males and 31 females) ages rang

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Petroleum Research And Studies
Modeling of Oil Viscosity for Southern Iraqi Reservoirs using Neural Network Method
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The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu

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Publication Date
Mon Nov 24 2025
Journal Name
Scientific Reports
Bearing capacity improvement of medium clay soil using sodium silicate sand columns
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