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Enhancing Gas Sensing Performance of TiO2-ZnO nanostructures: Effect of ZnO Concentration
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Gas sensors based on titanium dioxide (TiO2) and zinc oxide (ZnO) nanocomposites are considered energy-saving devices that are utilized to find dangerous or harmful gases in an environment. The performance of nitrogen dioxide (NO2) gas sensors have been improved by spin-coating a TiO2 and TiO2:ZnO nanocomposite with varying concentrations (90TiO2:10ZnO, 70TiO2:30ZnO, and 50TiO2:50ZnO). To correlate structural properties with gas-sensing behavior, structural and morphological characterization has been done using FESEM, XRD, and EDX.  Without any ZnO-specific crystalline phase, TiO2 X-ray diffraction was found to be indexed in the anatase crystalline structure. The ZnO is synthesized in the wurtzite phase with (002) orientation and has a smooth surface, according to the morphologies and crystalline structure of the films, which also indicated the presence of ZnO components with various crystallite sizes and lattice strains. Responses to NO2 are increased by low ZnO content. Additionally, at the average operating temperature of 250 oC, TiO2:ZnO shows a good response.

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Publication Date
Sun Jun 23 2019
Journal Name
American Rock Mechanics Association
Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

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Publication Date
Thu Mar 18 2010
Journal Name
Spe Projects, Facilities & Construction
Correlating Optimum Stage Pressure for Sequential Separator Systems
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Summary<p>A study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.</p><p>A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of t</p> ... Show More
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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Hybrid CNN-SMOTE-BGMM Deep Learning Framework for Network Intrusion Detection using Unbalanced Dataset
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This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Technique
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

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Publication Date
Mon Jan 27 2025
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Techniques
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

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