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A Predictive Model for Estimating Unconfined Compressive Strength from Petrophysical Properties in the Buzurgan Oilfield, Khasib Formation, Using Log Data
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Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute relative error (AARE%) and the standard deviation error (SD%). It has been found that the developed equation is reliable and capable of predicting the UCS with an acceptable degree of confidence R², AARE% and SD% are 0.8549, 2.619%, and 0.0569%, respectively when compared with field data. Furthermore, when compared to other known correlations, showed better prediction results.

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Designing and Application of Mathematical Model A Multi – Objectives for Assessment The Quality Of The Project : A Case Study at Saad Public Construction Company
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Abstract

This research aims to design a multi-objective mathematical model to assess the project quality based on three criteria: time, cost and performance. This model has been applied in one of the major projects formations of the Saad Public Company which enables to completion the project on time at an additional cost that would be within the estimated budget with a satisfactory level of the performance which match with consumer requirements. The problem of research is to ensure that the project is completed with the required quality Is subject to constraints, such as time, cost and performance, so this requires prioritizing multiple goals. The project

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Publication Date
Fri Oct 01 2021
Journal Name
Saudi Pharmaceutical Journal
Organization factors influencing nurse ability to prevent and detect adverse drug events in public hospitals using a patient safety model
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Eyewitnesses’ Visual Recollection in Suspect Identification by using Facial Appearance Model
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Facial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Penetration of charged particles in ZnO using energy loss function model
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In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

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Publication Date
Wed Sep 21 2022
Journal Name
Biochemical And Cellular Archives
ANTIBIOTIC SUSCEPTIBILITY AND BIOFILM FORMATION OF PSEUDOMONAS AERUGINOSA ISOLATED FROM CLINICAL AND ENVIRONMENTAL HOSPITAL SAMPLES
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Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen and a model bacterium for studying virulence and bacterial social traits. While it can be isolated in low numbers from a wide variety of environments including soil and water, it can readily be found in almost any human/animal-impacted environment. It is a major cause of illness and death in humans with immunosuppressive and chronic conditions, and infections in these patients are difficult to treat due to a number of antibiotic resistance mechanisms and the organism’s propensity to form multicellular biofilms. One hundred twenty clinical samples and forty hospital environmental samples (various sources) were collected from hospitals in Baghdad city during the period from Oc

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Publication Date
Wed Jul 12 2017
Journal Name
Der Chemica Sinica
An Efficient One-Pot Approach for the Formation of Phenanthridine Derivative; Synthesis and Spectral Characterisation
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The preparation of the phenanthridine derivative compound was achieved by adopting an efficient one-pot synthetic approach. The condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 mole ratio resulted in the formation of the title compound. Analytical and spectroscopic techniques were used to confirm the nature of the new compound. A mechanism for the formation of the phenanthridine moiety that is based on three steps has been suggested

Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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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
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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