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Prediction of Shear Wave velocity for carbonate rocks
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In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of empirical models were considered to predict VS from VP. The models had been correlated and a general equation, based on statistical method, was established for carbonate rocks.

   The proposed equation, then, was examined using log data and good results observed.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
The potential of nonparametric model in foundation bearing capacity prediction
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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Medicine And Life
Renal stone density on native CT-scan as a predictor of treatment outcomes in shock wave lithotripsy
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Extracorporeal shock wave lithotripsy (ESWL) is considered a standard treatment for nephrolith or kidney stones measuring less than 20 mm. Anatomical, machine-related, and stone factors play pivotal roles in treatment outcomes, the latter being the leading role. This paper examined the relationship between stone density on native CT scans and ESWL treatment to remove renal stones concerning several treatments. One hundred and twenty patients (64 males and 56 females) were enrolled and completed the study from April 2019 to September 2020. Inclusion criteria were a single renal pelvis stone of 5–20 mm to be treated for the first time in adult patients with no urinary or musculoskeletal anatomical abnormalities. We assessed patients

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Sat Sep 08 2018
Journal Name
Modeling Earth Systems And Environment
Sedimentary units-layering system and depositional model of the carbonate Mishrif reservoir in Rumaila oilfield, Southern Iraq
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Tue Dec 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Studying the Radial and Tangential Velocity Components of the Epithelization Healing Post Photorefractive Keratectomy Surgery of the Human Eye
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Photorefractive keratectomy (PRK) is the refractive technique that began with a physical scraping of the epithelial layer of cornea subsequent by laser treatment. Post this procedure to about 48 hours the removed epithelial layer regenerated to protect the eye again. The regeneration process (called re-epithelization) started from the limbus of the cornea toward the central part of it. The re-epithelization mechanism consists of a change in cell density (mitosis) and cell concentration (migration) with a velocity in two directions: radial and tangential. In the present study, an estimation for both radial (responsible for the overlapped layers toward the outward direction of the cornea) and tangential comp

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Non-Linear Behavior of Strengthened Steel-Concrete Composite Beams with Partial Interaction of Shear Connectors
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In this research a theoretical study has been carried out on the behavior and strength of simply supported composite beams strengthened by steel cover plate taking into consideration partial interaction of shear connectors and nonlinear behavior of the materials and shear connectors. Following the procedure that already has been adopted by Johnson (1975), the basic differential equations of equilibrium and compatibility were reduced to single differential equation in terms of interface slip between concrete slab and steel beam. Furthermore, in order to consider the nonlinear behavior of steel, concrete and shear connectors, the basic equation was rearranged so that all terms related to materials are isol

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Clinical Dentistry
THE EFFECT OF A PROTECTIVE BARRIER ON THE SHEAR BOND STRENGTH OF DIFFERENT ORTHODONTIC BRACKETS
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Background and objectives: This study aimed at testing the effect of plastic sleeve or barrier, used to cover the guide of the light cure unit to prevent cross-infection, on the shear bond strength and site of bond failure of stainless steel and ceramic orthodontic brackets. Materials and methods: Forty orthodontic brackets; twenty stainless steel and twenty ceramic brackets bonded to forty extracted human maxillary first premolars using light cure adhesive cured with and without the use of a protective plastic barrier on the guide. Comparing the effect of this barrier on the shear bond strength and adhesive remnant index was performed using an independent t-test and Chi-square test. Results: The protective barrier had decreased the shear b

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