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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 Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Evaluating Filtration and Thermal Stability of Water-Based Mud Using Green Synthesized Zinc Oxide Nanoparticles
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   Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the pra

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Publication Date
Thu Jul 31 2025
Journal Name
Computers, Materials & Continua
A Secure Audio Encryption Method Using Tent-Controlled Permutation and Logistic Map-Based Key Generation
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The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Enhancing Nitrate Ion Removal from Water using Fixed Bed Columns with Composite Chitosan-based Beads
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    Water contamination is a pressing global concern, especially regarding the presence of nitrate ions. This research focuses on addressing this issue by developing an effective adsorbent for removing nitrate ions from aqueous solutions. two adsorbents Chitosan-Zeolite-Zirconium (Cs-Ze-Zr composite beads and Chitosan-Bentonite-Zirconium Cs-Bn-Zr composite beads were prepared. The study involved continuous experimentation using a fixed bed column with varying bed heights (1.5 and 3 cm) and inlet flow rates (1 and 3 ml/min). The results showed that the breakthrough time increased with higher bed heights for both Cs-Ze-Zr and Cs-Bn-Zr composite beads. Conversely, an increase in flow rate led to a decrease in breakthrough time. Notab

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Real-Time Cloth Simulation on Virtual Human Character Using Enhanced Position Based Dynamic Framework Technique
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     Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

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Publication Date
Mon Apr 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Sustainable approach for seed stimulating and sowing date to enhance field emergence and growth of sorghum (Sorghum bicolor L. Moench)
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Sorghum cultivation is often accompanied by low field emergence rates and weak seedlings, which may be due to genetic or environmental stress. A factorial experiment was conducted in the spring and fall seasons of 2022 using a randomized complete block design with split-plot arrangement and four replications. Planting dates (spring season: Feb. 15th, Mar. 1st, 15th, and Apr. 1st, 15th; fall season: Jun. 15th, Jul. 1st, 15th, and Aug. 1st, 15th) were allocated to the main plots. Seeds stimulation treatments (35% banana peel extract + 100 mg L-1 citric acid and distilled water soaking treatment only) were allocated to the subplots. The interaction treatment (banana peel extract + citric acid) with the planting date of April 15 showed the high

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Publication Date
Thu Jul 01 2021
Journal Name
University Of Northampton Pue
Validating a Proposed Data Mining Approach (SLDM) for Motion Wearable Sensors to Detect the Early Signs of Lameness in Sheep
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Publication Date
Sun Sep 01 2019
Journal Name
Yazyk I Kul'tura
Cognitive-communicative approach in the system of teaching Russian language for foreign students (in the condition of no language environment)
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Publication Date
Fri Jan 01 2016
Journal Name
Proceedings Of The Eleventh International Network Conference (inc 2016)
A review on power consumption reduction techniques on OFDM
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Publication Date
Mon Aug 21 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
New techniques to estimate the solution of autonomous system
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This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Improve Data Mining Techniques with a High-Performance Cluster
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