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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 29 2025
Journal Name
Acta Microbiologica Bulgarica
Molecular detection of fimH, gipA, and ibeA genes in adherent invasive Escherichia coli isolated from patients with ulcerative colitis
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Recently, there has been an increase in the prevalence of ulcerative colitis (UC), and inflammatory bowel diseases (IBD) worldwide, especially in certain recently industrialized countries like China and In¬dia. Globally, the prevalence of UC, a chronic illness that affects the large intestine, is rising. Fifty adherent invasive Escherichia coli (AIEC) isolates were identified from ulcerative colitis biopsy samples originating from the Gastrointestinal tract (GIT) and Hepatology teaching hospitals/medical city in Baghdad City. The test’s results demonstrated that the AIEC isolates had a high level of resistance to the majority of the an-tibiotics under investigation. Enterobacterial Repetitive Intergenic Consensus (ERIC-PCR) and m

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Publication Date
Thu Oct 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Study the Ability of Pseudomonas Aeruginosa Isolated from Different Clinical Cases to Biofilm Formation and Detection of Algd Gene.
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98 samples were collected from various clinical sources included (Burns, wounds, urines, sputums, blood) From the city of Baghdad, After performing the biochemical and microscopic examination, 52 isolates were obtained for Pseudomonas aeruginosa, 17 (32.7%) isolates from burn infection, 12 (23%) isolates from Wound infection 11 (21.2%) isolates from urine infection, 7 (13.5%) isolates of sputum and 5 (9.6%) isolates from blood. Bacteria susceptibility to form biofilm has been detectedby microtiter plate method, The results showed that 80% of the bacterial isolates were produced the biofilm with different proportions, alg D gene (alginate production) has been detected by polymerase chain reaction (PCR) Which plays an essential role in the fo

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Molecular detection by some virulence genes of Salmonella enterica subsp. enterica isolated from the stool of children with diarrhea
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Diarrhea is a real disease in childhood which could cause death. Therefore, this study was conducted to isolate Salmonella from 350 stool samples taken from children under five years in age, suffering from diarrhea during the period from March 2019 to March 2020 in Tikrit city / Iraq. The results showed the possibility to isolate ten isolates of Salmonella enterica subsp. Enterica, an infection rate, represents 2.875% of the total rate of patients who suffer from diarrhea. The virulence genes were investigated for ten isolates of S. enterica subsp. enterica, the result is that all isolates possessed the genes stn, invA, lpfA with an appearance percentage of 100%, whi

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in the Detection of Osteoporosis in Postmenopausal Women
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Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

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Publication Date
Sun Apr 01 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Hiding Data in Color Image Using Least Significant Bits of Blue Sector
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Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Image Compression Using Tap 9/7 Wavelet Transform and Quadtree Coding Scheme
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This paper is concerned with the design and implementation of an image compression method based on biorthogonal tap-9/7 discrete wavelet transform (DWT) and quadtree coding method. As a first step the color correlation is handled using YUV color representation instead of RGB. Then, the chromatic sub-bands are downsampled, and the data of each color band is transformed using wavelet transform. The produced wavelet sub-bands are quantized using hierarchal scalar quantization method. The detail quantized coefficient is coded using quadtree coding followed by Lempel-Ziv-Welch (LZW) encoding. While the approximation coefficients are coded using delta coding followed by LZW encoding. The test results indicated that the compression results are com

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
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The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES
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Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

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Publication Date
Sat Nov 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Optimizing Irrigation Water Quality Index Along the Tigris River Using Gravitational Search Algorithm: A Novel Approach for Sustainable Water Management
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Abstract<p>The Tigris River, a vital water resource for Iraq, faces significant challenges due to urbanization, agricultural runoff, industrial discharges, and climate change, leading to deteriorating water quality. Traditional methods for assessing irrigation water quality, such as laboratory testing and statistical modeling, are often insufficient for capturing dynamic and nonlinear relationships between parameters. This study proposes a novel application of the Gravitational Search Algorithm (GSA) to estimate the Irrigation Water Quality Index (IWQI) along the Tigris River. Using data from multiple stations, the study evaluates spatial variability in water quality, focusing on key paramete</p> ... Show More
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