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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
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
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Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Biotechnology Research Center
Treatment of Waste Paper Using Ultrasound and Sodium Hydroxide for Bioethanol Production
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Bioethanol produced from lignocellulose feedstock is a renewable substitute to declining fossil fuels. Pretreatment using ultrasound assisted alkaline was investigated to enhance the enzyme digestibility of waste paper. The pretreatment was conducted over a wide range of conditions including waste paper concentrations of 1-5%, reaction time of 10-30 min and temperatures of 30-70°C. The optimum conditions were 4 % substrate loading with 25 min treatment time at 60°C where maximum reducing sugar obtained was 1.89 g/L. Hydrolysis process was conducted with a crude cellulolytic enzymes produced by Cellulomonas uda (PTCC 1259).The maximum amount of sugar released and hydrolysis efficiency were 20.92 g/L and 78.4 %, respectively. Sugars

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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Publication Date
Thu Apr 01 2010
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Using Computer in program BasedStudying for Student in Jordan
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This study aimed at investigating the effect of using computer in
Efficiency of Training Programme of Science Teachers in Ajloun District in
Jordan.
1- What is the effect of using computer in program for the two groups
2- ( the experimental and control group ) .
3- Are there any statistics different in the effect of using computer
program for the two groups ?
4- Are there any statistics (comparison ) or different of the effect of the
effect of using computer program refer to the sex (male or female )?
The community of the study consisted of all the science student in
educational directorate of Ajloun district for the academic year 2009 –
2010, they are (120) ( male and female) . The sample of the study<

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Publication Date
Mon Aug 06 2018
Journal Name
Indian Journal Of Applied Research
STATISTICAL METHOD FOR SOLVING TRANSPORTATION PROBLEMS OF USING THE PROGRAMMING LANGUAGE MATLAB
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Original Research Paper Mathematics 1-Introduction : In the light of the progress and rapid development of the applications of research in applications fields, the need to rely on scientific tools and cleaner for data processing has become a prominent role in the resolution of decisions in industrial and service institutions according to the real need of these methods to make them scientific methods to solve the problem Making decisions for the purpose of making the departments succeed in performing their planning and executive tasks. Therefore, we found it necessary to know the transport model in general and to use statistical methods to reach the optimal solution with the lowest possible costs in particular. And you know The Transportatio

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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Wed Nov 30 2016
Journal Name
International Business Management
ESTIMATE OF THE MULTIPLIER EFFECT OF THE MONETARY AND FISCAL POLICY ON NON-OIL GROSS DOMESTIC PRODUCT IN THE IRAQI ECONOMY FOR THE PERIOD OF 1990-2014
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The monetary policy is a vital method used in implementing monetary stability through: the management of income and adjustment of the price (monetary targets) in order to promote stability and growth of real output (non-cash goals); the tool of interest rate and direct investment guides or movement towards the desired destination; and supervisory instruments of monetary policy in both quantitative and qualitative. The latter is very important as a standard compass to investigate the purposes of the movement monetary policy in the economy. The public and businesses were given monetary policy signals by those tools. In fiscal policy, there are specific techniques to follow to do the spending and collection of revenue. This is done in order to

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
The impact of e-learning on the cognitive level in the Corona crisis: أسماء غازي عبد
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E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Publication Date
Fri Aug 19 2022
Journal Name
Mathematical Statistician And Engineering Applications (msea)
Application of TOPSIS method for Multi-Criteria Decision Making for poultry fields By using GIS in Hilla district
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Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the popu

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