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Enhancement in Lubricating, Rheological, and Filtration Properties of Unweighted Water-Based Mud Using XC Polymer NPs
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In this research, an enhancement in lubricating, rheological, and filtration properties of unweighted water-based mud is fundamentally investigated using XC polymer NPs with 0.2gm, 0.5gm, 1gm, 2gm, and 4gm concentrations. Bentonite, that had been used in the preparation of unweighted water-based mud, was characterized using XRF-1800 Sequential X-ray Fluorescence Spectrometer, XRD-6100/7000 X-ray Diffractometer, and Malvern Mastersizer 2000 particle size analyzer, respectively. Lubricating, rheology and filtration properties of unweighted water-based mud were measured at room temperature (35°C) using OFITE EP and Lubricity Tester, OFITE Model 900 Viscometer, and OFITE Low-Pressure Filter Press, respectively. XC Polymer NPs show a good enhancement in lubricating, rheology and filtration properties of unweighted water-based mud. The effect of XC Polymer NPs on lubricating properties was denoted at 4gm concentration, where the reduction percentage in COF was 30%.  An increase in PV, YP, AV, gel strength of unweighted water-based mud was obtained due to the addition of XC Polymer NPs at concentrations up to 4gm. A reduction in filtrate volume and mud cake thickness of unweighted water-based mud was obtained due to the addition of XC Polymer NPs at 2gm and 4gm concentrations, the best result was obtained with using 4gm concentration, the reduction percentage of filtrate volume was 20.7% and mud cake thickness was 41%.

 

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Publication Date
Sun Jun 23 2024
Journal Name
Asee Annual Conference And Exposition
Undergraduate Research Impact on Students' Retention and Academic Development Based on Their Study Field and the Mentoring Approach
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The impact of undergraduate research experiences on students' academic development and retention in STEM fields is significant. Students' success in STEM fields is based on developing strong research and critical thinking skills that make it essential for students to engage in research activities throughout their academic programs. This work evaluates the effectiveness of undergraduate research experiences with respect to its influence on student retention and academic development. The cases presented are based on years of experience implementing undergraduate research programs in various STEM fields at Colorado State University Pueblo (CSU Pueblo) funded by HSI STEM Grants. The study seeks to establish a correlation between students' reten

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Scopus
Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
Study of the effect of using nanomaterial in radiological shielding
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Publication Date
Tue Jan 10 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Importance of Using the Internet of Things in Education
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The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern

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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Advanced Computer Science And Applications
Fast Hybrid String Matching Algorithm based on the Quick-Skip and Tuned Boyer-Moore Algorithms
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Publication Date
Thu Dec 03 2015
Journal Name
Iraqi Journal Of Science
New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Multi -Focus Image Fusion Based on Stationary Wavelet Transform and PCA on YCBCR Color Space
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The multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).

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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
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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