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Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in permeability prediction and compared its results with the flow zone indicator methods for a carbonate heterogeneous Iraqi formation. The methodology of the research can be Summarized by permeability was estimated by using two methods: Flow zone indicator and Artificial intelligence, two reservoir models are built, where the difference between them is in permeability method estimation, and the simulation run will be conducted on both of the models, and the permeability estimation methods will be examined by comparing their effect on the model history matching. The results showed that the model with permeability predicted by using artificial intelligence matched the observed data for different reservoir responses more accurately than the model with permeability predicted by the flow zone indicator method. That conclusion is represented by good matching between observed data and simulated results for all reservoir responses such for the artificial intelligence model than the flow zone indicator model.

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Publication Date
Sat Sep 01 2018
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
The Factors Affecting on Managing Sensitive Data in Cloud Computing
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Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of propo

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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
The Eff ffectt off Septtopllastty on IInfferr iiorr Turrbiinatte Siize
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Bac kground:: Septal deviation is one of the commonest anatomical deformities of the nasal skeleton, this deviation is usually accompanied by compensatory hypertrophy of the inferior turbinate on the concave side that will accentuate the severity of nasal obstruction.
Objectives: To evaluate the effect of septoplasty on the size of the inferior turbinate in patients with nasal septum deviation.
Methods: This is a prospective study of 25 patients attending the otolaryngological department at Al-Jirahat teaching hospital from September 2011 to November 2013, complaining mainly of nasal obstruction. Otolaryngological examination had shown nasal septum deviation. The cross sectional areas of inferior turbinates were measured with compu

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Controlling the Unbalanced Voltages of a Series-Connected Lead-Acid Batteries in a PV Power Storage System using Dynamic Capacitor Technique
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Lead-acid batteries have been used increasingly in recent years in solar power systems, especially in homes and small businesses, due to their cheapness and advanced development in manufacturing them. However, these batteries have low voltages and low capacities, to increase voltage and capacities, they need to be connected in series and parallel. Whether they are connected in series or parallel, their voltages and capacities must be equal otherwise the quality of service will be degraded. The fact that these different voltages are inherent in their manufacturing, but these unbalanced voltages can be controlled. Using a switched capacitor is a method that was used in many methods for balancing voltages, but their respons

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Publication Date
Sat Apr 01 2017
Journal Name
International Journal Of Science And Research
Evaluating the Behavior of Ring Footing on Two-Layered Soil Subjected to Inclined Load
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Evaluating the behavior of a ring foundation resting on multi-layered soil is one of the important issues facing civil engineers. Many researchers have studied the behavior of ring foundation rests on multi-layered soil with vertical loads acting on the foundation. In real life ring foundation can be subjected to both vertical and horizontal loads at the same time due to wind or the presence of soil. In this research, the behavior of ring footing subjected to inclined load has been studied using PLAXIS software. Furthermore, the effect of multi-layered soil has been simulated in the model. The results showed that both vertical and horizontal stresses are mainly affected when the inclination angle of the load exceeded 45 degrees with a reduc

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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Population Density of Bemisia tabaci on Sweet Pepper (Capsicum annuum) Varieties in the Greenhouse
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Abstract<p>We conducted an experiment in a greenhouse at the research station belonging to the Department of Plant Protection / Ministry of Agriculture, in Abu Ghraib area during the spring and autumn season 2022-2023, to study the population density of the whitefly on two varieties of sweet pepper plant (Charisma and Sierra Nevada). The experiment was laid out in a randomized complete block design “RCBD” with three replicates for each variety. The results showed that in spring season the population density of <italic>B. tabaci</italic> eggs and nymphs reached the peak in the last week of May, which where 2.667 and 4.444 individual / leaf, respectively while the population density </p> ... Show More
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Publication Date
Wed Jan 08 2020
Journal Name
International Journal Of Advanced Science And Technology
The local stability of an eco-epidemiological model involving a harvesting on predator population
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In this paper a prey - predator model with harvesting on predator species with infectious disease in prey population only has been proposed and analyzed. Further, in this model, Holling type-IV functional response for the predation of susceptible prey and Lotka-Volterra functional response for the predation of infected prey as well as linear incidence rate for describing the transition of disease are used. Our aim is to study the effect of harvesting and disease on the dynamics of this model.

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Scopus
Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Exploring the Effects of European Union Conditionality Language on European Mediterranean Human Rights Dialogue
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Since more than a decade, human rights dialogue in the European Mediterranean Region has been marked by a number of tensions. Although a number of factors contribute to such disputes, the effect of human rights conditionality, which ties EU economic cooperation progression with partner countries human rights advancement, on the dialogue has not been studied. Understanding the aspects, impacts, and effects of conditionality on Euro-Med relations is crucial for furthering dialogue. Yet this variable has been almost entirely neglected in academic and policy research. The research concludes several direct and indirect impacts of conditionality on human rights dialogue using a mixed methodology approach. Direct effects are reflected in the wi

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Publication Date
Sat Mar 29 2014
Journal Name
International Journal Of Academic Research In Progressive Education And Development
The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
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The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

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Publication Date
Wed Jun 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study on Vanadium Recovery from Spent Catalyst Used in the Manufacture of Sulfuric Acid
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Spent catalysts for sulfuric acid production have large amount of vanadium and due to environmental authority it is required to reduce the vanadium contain of the spent catalyst. Experimental investigation was conducted to study the vanadium recovery from spent catalyst via leaching process using sodium hydroxide to study the effect of process variables (temperatures, sodium hydroxide molarities, leaching time and particle size) on vanadium recovery. The effect of process variables (temperature, particle size,molarities of sodium hydroxide and leaching time) on the percentages of vanadium recovery were investigated and discussed .It was found that the percentage of vanadium recovery increased with increasing temperature up to 100 , incre

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