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Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological properties of water-based drilling fluid using other simple measurable properties. While mud density, marsh funnel, and solid% are key input parameters in this study, the output models are plastic viscosity, yield point, apparent viscosity and gel strength. The prediction methods have been applied on datasets taken from the final reports of two wells drilled in the Ahdeb oil field, eastern Iraq. To test the performance ability of the developed models, two error-based metrics (determination coefficient R2 and root mean square error have been used in this study. The current results support the evidence that MW, MF, and solid% are consistent indexes for the prediction of rheological mud properties. Both mud density and solid content have a relative-significant effect on increasing PV, YP, AV, and gel strength. The results also reveal that both MRA and ANN are conservative in estimating the fluid rheological properties, but ANN is more precise than MRA. Eight empirical mathematical models with high performance capacity have been developed in this study to determine the rheological fluid properties using simple and quick equipment such as mud balance and marsh funnel. This study presents cost-effective models to determine the rheological fluid properties for future well planning in Iraqi oil fields.

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Publication Date
Sun Mar 12 2023
Journal Name
Egyptian Journal Of Chemistry
Studying the Molecular Interactions for Potash Alum with Distilled Water and Aqueous Solution of Ethylene Glycol at Different Temperatures.
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Publication Date
Fri Oct 30 2020
Journal Name
International Journal Of Agronomy
Molybdenum Induces Growth, Yield, and Defence System Mechanisms of the Mung Bean (Vigna radiata L.) under Water Stress Conditions
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Water stress has a negative impact on the yield and growth of crops worldwide and consequently has a global impact on food security. Many biochemical changes occur in plants as a response to water stress, such as activation of antioxidant systems. Molybdenum (Mo) plays an important part in activating the expression of many enzymes, such as CAT, POD, and SOD, as well as increasing the proline content. Mo therefore supports the defence system in plants and plays an important role in the defence system of mung bean plants growing under water stress conditions. Four concentrations of Mo (0, 15, 30, and 45 mg·L−1) were applied to plants, using two approaches: (a) seed soaking and (b) foliar application. Mung bean plants were subject

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Mon Dec 21 2020
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A CONTRIBUTION TO THE CHECKLIST OF THE JUMPING SPIDERS (ARANEAE: SALTICIDAE) OF ARMENIA
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The paper presents an annotated checklist of the Salticidae of Armenia. This study was carried out in 2019-2020 in order to provide an inventory of the Salticidae fauna. Thirteen species are reported for the Armenian fauna for the first time: Afraflacilla epiblemoides (Chyzer, 1891); Aelurillus v-insignitus (Clerck, 1757); Asianellus festivus (C. L. Koch, 1834); Heliophanus dubius C. L. Koch, 1835; Heliophanus kochii Simon, 1868; Heliophanus tribulosus Simon, 1868; Heliophanus curvidens (O. Pickard-Cambridge, 1872); Macaroeris nidicolens (Walckenaer, 1802); Pellenes diagonalis (Simon, 1868); Pellenes geniculatus (Simon, 1868); Pellenes seriatus (Thorell, 1875); Pellenes tripunctatus (Walckenaer, 1802) and Phlegra fasciata (Hahn, 1826).

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The study of the literature review of hybrid classification approaches to credit scoring
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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
The Relationship of Noise Pollution to the Mental Health of Among University Students
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The present study deals with the relationship of noise pollution to the mental health of university students, through the researcher field study with the use of descriptive Correlative approach to investigate this relationship. Noise is one of the elements of environmental pollution that people often expose to in their environment. The problem of noise has been exacerbated now because of cultural and technological progress in crowded cities. As a result, the researchers studied noise as an environmental stimulus that affects the mental health of the human being.The researchers, through their current research try to study a very serious problem, which is the problem of noise pollution on the health side of university students as a

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
The use of Mixed Bacterial Culture to improve the Biodegradation of Diesel Pollution
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This study was conducted to evaluate the hydrocarbon biodegradation abilities of Enterobacter cloacae, Staphylococcus aureus, Sphingomonas paucimobilis, and Pentoae species which were isolated from different diesel-contaminated soil samples. The isolates were identified by the Vitek 2 system. Fourier-transform spectroscopy (FT-IR) tested the potential of these isolates to biodegrade the diesel according to the peak areas, a significant decrease in the area of the peaks at 2856-2928 cm−1 corresponds to aliphatic hydrocarbons. The appearance of small peaks at 900-1032 cm−1 refers to substituted benzene derivative compounds. An appearance of some new peaks at 3010- 3030 cm−1 which indicate the presence of alcohol (-OH) and ketones (RC=O)

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Publication Date
Wed Jan 01 2020
Journal Name
Materials Chemistry And Physics
Natural dye extracted from Areca catechu fruits as a new sensitiser for dye-sensitised solar cell fabrication: Optimisation using D-Optimal design
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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Study the Effect of Using Google Classroom on the Academic Performance Under the Covid19 Pandemic Using Data Mining Technique
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— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra

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Publication Date
Fri Jun 19 2020
Journal Name
Eurasian Journal Of Biosciences
Study the Adhesion Capacity on abiotic surfaces by Acinetobacter baumannii isolated from drinking water.
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Acinetobacter baumannii ability to form biofilm makes it to be opportunistic pathogen causing of nosocomial infections and to be good survivor in adverse environmental conditions including medical devices and hospital environments. Six isolates of A. baumannii were isolated from drinking water and tested to investigate biofilm formation capacity on three different type of abiotic surface, also several factors were examined such as hydrophobicity, PH and temperature. All A. baumannii isolates displayed a positive biofilm on congored aga test CRA (pigmented colonies with black color) and Christensen's test (adhesive layer of stained material to the inside surface of the tube).The obtained data of microbial adhesion to hydrocarbons assay (MATH

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