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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
Mon Dec 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Heterogeneously Catalyzed Esterification Reaction: Experimental and Modeling Using Langmuir- Hinshelwood Approach
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The esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac

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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Wed Dec 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Online medical consultation: covid-19 system using software object-oriented approach
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The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

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Publication Date
Fri Jan 07 2022
Journal Name
International Journal Of Early Childhood Special Education
Hierarchical learning and its effect on learning some basic skills in fencing for third stage students.
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MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

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Publication Date
Wed Aug 01 2012
Journal Name
I-manger's Journal On Information Technology
A MODULE FOR ENHANCING RECOGNITION SYSTEM FOR QR CODE SCANNED IMAGE
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A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Publication Date
Thu May 02 2024
Journal Name
Petroleum And Coal
Wellbore Instability Analysis to Determine the Failure Criteria for Deep Well/H Oilfield
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Scopus
Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Treating Wet Oil in Amara Oil Field Using Nanomaterial (SiO2) With Different Types of De emulsifiers
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One of the most important problems in the oil production process and when its continuous flow, is emulsified oil (w/o emulsion), which in turn causes many problems, from the production line to the extended pipelines that are then transported to the oil refining process. It was observed that the nanomaterial (SiO2) supported the separation process by adding it to the emulsion sample and showed a high separation rate with the demulsifiers (RB6000) and (sebamax) where the percentage of separation was greater than (90 and 80 )%  respectively, and less than that when dealing with (Sodium dodecyl sulfate and Diethylene glycol), the percentage of separation was (60% and 50%) respectively.

   The high proportion

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Publication Date
Mon Dec 03 2018
Journal Name
Journal Of Engineering
Error Investigation for Free Form Surfaces in Bezier Techniques
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Surface modeling utilizing Bezier technique is one of the more important tool in computer aided geometric design (CAD). The aim of this work is to design and implement multi-patches Bezier free-form surface. The technique has an effective contribution in technology domains and in ships, aircrafts, and cars industry, moreover for its wide utilization in making the molds. This work is includes the synthesis of these patches in a method that is allow the participation of these control point for the merge of the patches, and the confluence of patches at similar degree sides due to degree variation per patch.  The model has been implemented to represent the surface. The interior data of the desired surfaces designed by M

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Publication Date
Sun Jan 01 2017
Journal Name
Proceedings Of The Conference “recent Trends In Engineering Sciences And Sustainability”, Baghdad
GNSS positioning techniques for enhancing Google Earth data quality
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Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

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Publication Date
Sat Aug 06 2022
Journal Name
Ijci. International Journal Of Computers And Information
Techniques for DDoS Attack in SDN: A Comparative Study
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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

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