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Deep Learning Approach for Oil Pipeline Leakage Detection Using Image-Based Edge Detection Techniques
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are sent to the base station. Using deep learning approaches such as holistically-nested edge detection (HED) and extreme inception (Xception) networks, images are analyzed at the base station to identify contours using dense extreme inception networks for edge detection (DexiNed). This algorithm is capable of finding many contours in images. Moreover, the CIELAB color space (LAB) is employed to locate black-colored contours, which may indicate oil spills. The suggested method involves eliminating smaller contours to calculate the area of larger contours. If the contour's area exceeds a certain threshold, it is classified as a spill; otherwise, it is stored in a database for further review. In the experiments, spill sizes of 1m2, 2m2, and 3m2 were established at three separate test locations. The drone was operated at three different heights (5 m, 10 m, and 15 m) to capture the scenes. The results show that efficient detection can be achieved at a height of 10 meters using the DexiNed algorithm. Statistical comparison with other edge detection methods using basic metrics, such as perimage best threshold (OIS = 0.867), fixed contour threshold (ODS = 0.859), and average precision (AP = 0.905), validates the effectiveness of the DexiNed algorithm in generating thin edge maps and identifying oil slicks. © 2023 Lavoisier. All rights reserved.

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Main Difficulties Faced by EFL Students in Language Learning
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Many undergraduate learners at English departments who study English as a foreign language are unable to speak and use language correctly in their post -graduate careers.  This problem can be attributed to certain difficulties, which they faced throughout their education years that hinder their endeavors to learn. Therefore, this study aims to discover the main difficulties faced by EFL students in language learning and test the difficulty variable according to gender and college variables then find suitable solutions for enhancing learning.  A questionnaire with 15 items and 5 scales were used to help in discovering the difficulties. The questionnaire was distributed to the selected sample of study wh

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Publication Date
Tue Feb 21 2023
Journal Name
مجلة علوم الرياضة
The Effect of using Linear programming and Branching programming by computer in Learning and Retention of movement concatenation (Linkwork) in Parallel bars in Artistic Gymnastics
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The aim of this study was to Identifying The Effect of using Linear programming and Branching programming by computer in Learning and Retention of movement concatenation(Linkwork) in parallel bars in Artistic Gymnastics. The searchers have used the experimental method. The search subject of this article has been taken (30) male - students in the second class from the College of Physical Education/University of Baghdad divided into three groups; the first group applied linear programming by computer, and the second group has been applicated branching programming by computer, while precision group used traditional method in the college. The researchers concluded the results by using the statistical bag for social sciences (spss) such as both

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ROLE OF THE PROCUREMENT STRATEGY IN ACHIEVING INTEGRATED INDUSTRIAL DISTRIBUTION / CASE STUDY IN THE GENERAL COMPANY FOR THE DISTRIBUTION OF OIL PRODUCTS.: ROLE OF THE PROCUREMENT STRATEGY IN ACHIEVING INTEGRATED INDUSTRIAL DISTRIBUTION / CASE STUDY IN THE GENERAL COMPANY FOR THE DISTRIBUTION OF OIL PRODUCTS.
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This study dealt with the management strategy as an independent variable and the integrated industrial distribution as a variable. The study aimed at finding the integrated industrial distribution that fits with the management strategy in providing the needs of the firm on the one hand and reducing the cost of management that is reflected in increasing its profits.
The researcher selected the data from (130) decision makers in the corporation and used the questionnaire as a tool for collecting data and used a set of statistical tools and tools suitable for the nature of information and were processed using the data analysis system (SPSS version 24) Based on the analysis of the responses of the sample and the test of correlation and

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
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

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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Mon Jul 01 2024
Journal Name
Desalination And Water Treatment
Separation performance of cationic and anionic dyes from water using polyvinylidene fluoride-based ultrafiltration membrane incorporating polyethylene glycol
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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Using Ultraviolet Technique for Well Water Disinfection
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Publication Date
Thu Oct 18 2018
Journal Name
Proceedings Of The Future Technologies Conference (ftc) 2018
Using Mouse Dynamics for Continuous User Authentication
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Nonlinear Finite Element Analysis of Steel Fiber Reinforced Concrete Deep Beams With and Without Opening
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This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an

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Publication Date
Wed Mar 19 2025
Journal Name
Chemical Papers
Natural deep eutectic solvents as a green inhibitor of carbon steel corrosion in sulphuric acid
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