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Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of the proposed strategy of Maysan Oil Company for the years 2020-2024
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ناقش البحث في طياته عدداً من القضايا الرئيسة المتعلقة بالتقييم الاستراتيجي والإطار العام للخطة الاستراتيجية المقترحة لشركة نفط ميسان للسنوات الخمس المقبلة (2020_2024)، وهدف هذا البحث يتمحور في تقييم عملية صياغة استراتيجية شركة نفط ميسان لتحديد نقاط القوة وتعضيدها ومواطن الضعف ومحاولة معالجتها لتجنب الوقوع بها عند وضع استراتيجية للسنوات القادمة، وعلى هذا الاساس فان مشكلة البحث تكمن في مدى نجاح الاستراتي

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Publication Date
Fri Sep 30 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Addition of Super Absorbent Polymer for Upgrading of Cement Quality in Iraqi Oil Wells
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This study focuses on the use of an optimum amount of Sodium Polyacrylate (SP) for designing cement slurry with the high performance of rheological properties and displacement efficiency. A laboratory study has been carried out on the cement slurry which prepared with SP as superabsorbent polymer. SP has been providing an internal water source that helps in the hydration process, and curing and ultimately increases the cement strength. Also improves the cement performance by improving the cement stability. Several batches were prepared to determine the proper amount of SP to add it in the cement slurry. Also, we studied its effect on cement density, amount of free water in order to observe the rheological properties, and thickening time.

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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
     Influent Flow Rate Effect On Sewage Pump Station Performance Based On Organic And Sediment Loading
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The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Revolutionizing Systematic Reviews and Meta-analyses: The Role of Artificial Intelligence in Evidence Synthesis
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Publication Date
Wed Sep 01 2021
Journal Name
International Scientific Congress Of Pure, Applied And Technological Sciences (minar Congress)
Evaluation Of Electromagnetic Pollution Of Cellular Mobile Network
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Wireless communications are characterized by their fastest growth in history, as they used ever-evolving and renewed technologies, which have allowed them to spread widely. Every day, communication technology introduces a new invention with features that differ from its predecessor. Bell Laboratories first suggested mobile wireless communication services to the general population in the late 1940s. Still, it wasn't easy at that time to use on a large scale due to its high costs. This paper aims to describe the state of cellular mobile networks; by comparing the sources of electromagnetic pollution caused by these networks, measure the level of power density in some residential areas, and compare them with international standards adopted in

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Publication Date
Wed Dec 05 2018
Journal Name
Italian Journal Of Gynaecology & Obstetrics
Prediction of Fetal Lung Maturity by Ultrasonic Thalamic Echogenicity and Ossification Centers of Fetal Femur and Tibia
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Publication Date
Mon May 01 2017
Journal Name
Journal Of Nuclear Medicine
Capability of a novel small field of view hybrid gamma camera (HGC) for sentinel lymph node and small organ imaging
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Objectives: Small field of view gamma detection and imaging technologies for monitoring in vivo tracer uptake are rapidly expanding and being introduced for bed-side imaging and image guided surgical procedures. The Hybrid Gamma Camera (HGC) has been developed to enhance the localization of targeted radiopharmaceuticals during surgical procedures; for example in sentinel lymph node (SLN) biopsies and for bed-side imaging in procedures such as lacrimal drainage imaging and thyroid scanning. In this study, a prototype anthropomorphic head and neck phantom has been designed, constructed, and evaluated using representative modelled medical scenarios to study the capability of the HGC to detect SLNs and image small organs. Methods: An anthropom

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Lab on-a-chip-based, an integrated microfluidic device lo-cost, rapid, and sensitive analysis of Augmentin
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Microfluidic devices provide distinct benefits for developing effective drug assays and screening. The microfluidic platforms may provide a faster and less expensive alternative. Fluids are contained in devices with considerable micrometer-scale dimensions. Owing to this tight restriction, drug assay quantities are minute (milliliters to femtoliters). In this research, a microfluidic chip consisting of micro-channels carved on substrate materials built using an Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO2) laser machine. The CO2 parameters influence the chip’s width, depth, and roughness. To have a regular channel surface, and low roughness, the laser power (60 W), with scanning speed (250 m/s)

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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