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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
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
SYNTHESIS OF NEW LEVOFLOXACIN SELECTIVE MEMBRANE SENSOR BASED ON MOLECULARLY IMPRINTED POLYMERS.: SYNTHESIS OF NEW LEVOFLOXACIN SELECTIVE MEMBRANE SENSOR BASED ON MOLECULARLY IMPRINTED POLYMERS.
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Two molecular imprinted polymer (MIP) membranes for Levofloxacin (LEV) were prepared based on PVC matrix. The imprinted polymers were prepared by polymerization of styrene (STY) as monomer, N,N methylene di acrylamide as a cross linker ,benzoyl peroxide (BPO) as an initiator and levofloxacin as a template. Di methyl adepate (DMA) and acetophenone (AOPH) were used as plasticizers , the molecular imprinted membranes and the non molecular imprinted membranes were prepared.  The slopes and detection limits of the liquid electrodes ranged from -21.96 – -19.38 mV/decade and 2×10-4M- 4×10-4M, and Its response time was around 1 minute, respectively. The liquid  electrodes were packed with 0.1 M standar

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Thu Jun 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Innovations in t-way test creation based on a hybrid hill climbing-greedy algorithm
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<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

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Publication Date
Tue Oct 29 2019
Journal Name
Journal Of Engineering
Demand Priority in a Power System With Wind Power Contribution Load Shedding Scheme Based
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The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
Combined effect of fineness modulus and grading zones of fine aggregate on fresh properties and compressive strength of self compacted concrete
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Self-compacted concrete (SCC) considered as a revolution progress in concrete technology due to its ability for flowing through forms, fusion with reinforcement, compact itself by its weight without using vibrators and economic advantages. This research aims to assess the fresh properties of SCC and study their effect on its compressive strength using different grading zones and different fineness modulus (F.M) of fine aggregate. The fineness modulus used in this study was (2.73, 2.82,2.9& 3.12) for different zones of grading (zone I, zone II& marginal zone(between zone I&II)) according to Iraqi standards (I.Q.S No.45/1984).Twelve mixes were prepared, each mix were tested in fresh state with slump, V-Funnel and L-Box tests, t

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