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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
Tue Jun 30 2020
Journal Name
Iraq Journal Of Market Research And Consumer Protection
DETECTION OF HEAVY METALS POLLUTION INTYPES OF MILK SAMPLES IN BAGHDAD MARKETS
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Publication Date
Wed Feb 03 2016
Journal Name
Nanoscience And Nanotechnology
Fabrication of Functionalize Reduce Graphene Oxide and Its Application in Ampicillin Detection
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Graphene oxide (GO) was prepared from graphite (GT) with Hammer method, the GO was reduced with hydrazine hydrate to produce a reduced graphene oxide (RGO). The RGO was reacted with thiocarbohydrazide (TCH) to functionalize the RGO with 4-amino-3-symbol-1h-1, 2, 4-triazol-5 (4H) –thion group and to obtain (RGOT). All the prepared nanomaterial and the product of the functionalization RGOT were characterized with Fourier transformer infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) analysis. RGOT mixed with ultrasonic device at different pH values of phosphate buffer solution (PBS), the mixture used to modifying a screen printed carbon electrodes SPCE and with cyclic voltammetry the sensitivity of selectivity of the new modifying elect

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Publication Date
Sat Jan 01 2022
Journal Name
Tropical Journal Of Natural Product Research
Detection of Herpes Simplex Virus Type 1 in Patients Affected by Conjunctivitis
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Herpes simplex virus (HSV) is a common human pathogen that causes severe infections in newborns and immunocompromised patients. Conjunctivitis or corneal epithelial keratitis is caused by HSV type 1 all over the world and at all times of the year. The present study was aimed at detecting HSV in patients suffering from conjunctivitis. One hundred and ten (110) clinical samples (90 patients and 20 controls, both males and females) of eye conjunctiva swabs were collected from patients of different ages. The samples were analyzed using qPCR and ELISA techniques. The qPCR results revealed that HSV was present in 47 (52.2%) of the 90 patients who were infected. Of these patients, 25 (48.0%) were males and 22 (57.8%) were females, indicati

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Scopus
Publication Date
Tue Jan 01 2019
Journal Name
Biochemical And Cellular Archives
Phenotypic and molecular detection of Escherichia coli efflux pumps from UTI patients
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Scopus
Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Crossref
Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Global Pharma Technology
Detection of HBME-1 and galectin-3 by immunohistochemistry in follicular lesions
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The main problem established by a discovery of a thyroid nodule is to discriminate between a benign and malignant lesion. Differential diagnosis between follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. A developing number of some encouraging IHC markers for the differential diagnosis of thyroid lesions have emerged, including, Hector Battifora mesothelial (HBME-1) and galectin-3 (Gal-3). There was significant positive correlation between Galectin-3 and HBME-1 in follicular carcinoma and follicular variant of papillary carcinoma (r= 0.380, P= 0.041) and (r= 0.315, P=0.047) respectively. There was no significant correlation between

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Scopus
Publication Date
Tue Apr 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Molecular Detection and Antiserum Preparation of Begomoviruses Infecting Zucchini Squash in Iraq
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Abstract<p>Begomoviruses infecting zucchini squash were investigated. Leaf samples were collected from zucchini squash growing areas in Baghdad (Jhadryaa and Yusufiyah), Babylon (Jibela and Mahmudiyah) and Diyala (Khan Bani Saad) Provinces. Samples were screened for the presence of begomoviruses using polymerase chain reaction (PCR) and Deng genus specific primers. Sixteen out of 40 samples were begomovirus positive. Sequence analysis confirmed the detection of Tomato leaf curl Palampur virus (TLCPALV) <italic>Begomovirus solanumpalampurense</italic>, Squash leaf curl virus (SLCuV) <italic>B. cucurbitapeponis</italic> and Tomato yellow leaf curl virus (TYLCV) <italic>B. </italic></p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
مجلة الأطروحة العلمية المحكمة-العلوم الصرفة والتطبيقية
Detection of Lead (Pb) and Cadmium (Cd) Concentrations in Some Indomie Samples
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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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Scopus Crossref
Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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