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Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm and 40 mm. The second plate contains four rectangular wells to simulate background activity uptake surrounding the SLNs. The activity used ranged between 4 MBq and 0.025 MBq for the SLNs. The background activity was 1/10 of the SLNs activity. The collimator to source distance was 120 mm. Results Signal to Noise Ratio (SNR) analysis and spatial resolution measurements of the simulated SLN were used to compare the imaging sets over acquisition times ranging between 60s and 240s. The HGC successfully detected 87.5% to 100% of the SLNs through 20mm of scattering material, and it could detect 75% to 93.75% of the SLNs through 40mm of scattering material. Measurement of Full-Width-at-Half-Maximum (FWHM) for the detected SLNs ranged between 9.5 mm and 12 mm. Conclusion The HGC is capable of detecting low activity uptake in small SLNs indicating its usefulness as an intraoperative imaging system during surgical SLN procedures.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Monitoring of south Iraq marshes using classification and change detection techniques
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Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Sat Sep 28 2024
Journal Name
Asia-pacific Journal Of Molecular Biology And Biotechnology
A novel method for the degradation of human blood clot by immobilised bromelain using multi-walled carbon nanotube and polyphenol oxidase
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Pathological blood clot in blood vessels, which often leads to cardiovascular diseases, are one of the most common causes of death in humans. Therefore, enzymatic therapy to degrade blood clots is vital. To achieve this goal, bromelain was immobilized and used for the biodegradation of blood clots. Bromelain was extracted from the pineapple fruit pulp (Ananas comosus) and purified by ion exchange chromatography after precipitation with ammonium sulphate (0-80 %), resulting in a yield of 70%, purification fold of 1.42, and a specific activity of 1175 U/mg. Bromelain was covalently immobilized on functionalized multi-walled carbon nanotubes (MWCNT), with an enzyme loading of 71.35%. The results of the characterization of free and immobilized

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Publication Date
Sun Dec 22 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Ex-vivo Ex-Vivo Absorption Study of a Novel Dabigatran Etexilate Loaded Nanostructured Lipid Carrier Using Non-Everted Intestinal Sac Model
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Abstract

The purpose of our study was to develop Dabigatran Etexilate loaded nanostructured lipid carriers (DE-NLCs) using Glyceryl monostearate and Oleic acid as lipid matrix, and to estimate the potential of the developed delivery system to improve oral absorption of low bioavailability drug, different Oleic acid ratios effect on particle size, zeta potential, entrapment efficiency and loading capacity were studied, the optimized DE-NLCs shows a particle size within the nanorange, the zeta potential (ZP) was 33.81±0.73mV with drug entrapment efficiency (EE%) of  92.42±2.31% and a loading capacity (DL%) of 7.69±0.17%. about 92% of drug was released in 24hr in a controlled manner, the ex-vivo intestinal p

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Publication Date
Wed Jul 01 2026
Journal Name
South African Journal Of Chemical Engineering
Enhancement of water-based drilling fluid using novel composite of silica and alumina nanoparticles
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One of the most recent research areas in subsurface applications, including well drilling, is the use of eco-friendly and sustainably synthesized nanoparticles to improve drilling fluid efficiency. Typically, Shale formations present significant challenges to traditional drilling fluids, including fluid infiltration and shale swelling, which jeopardize wellbore stability. Although water-based drilling fluids (WBM) are environmentally preferred, their performance often requires enhancement through advanced additives. This study thus examines the synthesis of silica (SiO₂) and alumina (Al₂O₃) nanoparticles (NPs) using sustainable methods, employing Iraqi bentonite for silica and recycled aluminum scrap for alumina, to improve WBM effici

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Publication Date
Wed May 01 2019
Journal Name
Materials Science And Engineering
Analysis of Wind Turbine Using QBlade Software
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Engineering
A High Resolution 3D Geomodel for Giant Carbonate Reservoir- A Field Case Study from an Iraqi Oil Field
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Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distribution along

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