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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 Apr 13 2019
Journal Name
Journal Of The College Of Languages (jcl)
Certains aspects techniques Chez Henri Barbusse dans L'ENFER
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L’Enfer est un roman de chambre par excellence. Tous les événements s'y sont presque déroulés. Le sujet de ce roman se résume: un jeune homme quitte la campagne pour vivre à Paris .Il loue une chambre dans un hôtel. Il tombe, par un pur hasard, sur une fente dans le mur de sa par laquelle chambre il peut voir tout ce qui se passe dans la chambre voisine .L'histoire racontée par ce narrateur, est la vie intime des couples venant dans cette chambre. Il médite sur sa propre condition à la lumière de ce qui se déroule dans la chambre voisine .C'est pour cette raison,que le roman se caractérise par une stabilité.Quoi qu’elle soit manifeste, le héros démontre une mobilité à son niveau psychique. Car il y a une évolution

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Publication Date
Fri May 17 2013
Journal Name
Sensors
Evolution of Electroencephalogram Signal Analysis Techniques during Anesthesia
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Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG sig

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Publication Date
Fri Mar 19 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
New cost control techniques in mega construction projects
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Publication Date
Thu Apr 13 2023
Journal Name
International Journal Of Research In Social Sciences And Humanities
Subject Review: The Effectiveness Of Integrating E-Learning On Learning Outcome And Student Perceptions In Tertiary Education
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The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claim

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Publication Date
Thu Dec 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Oil Removal from Wastewater of Al-Bezerqan Crude Oil Fields by Air Flotation
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
marked as licensing oil and its role in future oil industry in Iraq
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Iraq's oil industry  has been passed  in different periods , began with domination  of  Western companies to invest in Iraqi oil at twenties of the last century ,  through the process of nationalization of the shares of those companies ,  beginning of the seventies , and ending with the new policies adopted by the government recently, which was contracting with international companies to develop the oil industry , because of what the outcome of the oil industry from a decline in artistic and  physical ability as a result to the  conditions of war and embargo imposed on Iraq before 2003.

The Iraqi government has introduced licensing of a contract to

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Publication Date
Tue Jun 30 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Immiscible CO2-Assisted Gravity Drainage Process for Enhancing Oil Recovery in Bottom Water Drive reservoir
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The CO2-Assisted Gravity Drainage process (GAGD) has been introduced to become one of the mostinfluential process to enhance oil recovery (EOR) methods in both secondary and tertiary recovery through immiscibleand miscible mode. Its advantages came from the ability of this process to provide gravity-stable oil displacement forenhancing oil recovery. Vertical injectors for CO2 gas have been placed at the crest of the pay zone to form a gas capwhich drain the oil towards the horizontal producing oil wells located above the oil-water-contact. The advantage ofhorizontal well is to provide big drainage area and small pressure drawdown due to the long penetration. Manysimulation and physical models of CO2-AGD process have been implemented

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Publication Date
Mon Jun 15 2026
Journal Name
Chemengineering
Nanofluid Flooding as a Sufficient Alternative to Waterflooding for Incremental Oil Recovery from Carbonate Reservoirs
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Oil recovery from carbonate reservoirs is one of the critical challenges in the oil industry due to the strongly oil-wet nature, natural fractures, and the heterogeneity of carbonate rocks. Subsequently, waterflooding can only displace oil from large fractures, leaving the majority of oil trapped in the rock matrix. This work suggests that nanofluid flooding, as a predesigned flooding method, is an alternative to conventional waterflooding. Various concentrations of silica nanofluid at different nanoparticle concentrations were formulated and systematically investigated for their characteristics, stability at reservoir conditions, and their influence on wettability and oil recovery. Silica nanoparticles were sustainably synthesized

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Publication Date
Tue Mar 12 2019
Journal Name
Lubricants
Absorption Wavebands for Discriminating Oxidation Time of Engine Oil as Detected by FT-IR Spectroscopy
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Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.

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