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Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism, ‎embryonic haemoglobin (HBE), for early diagnosis. Archived samples in combination with ‎prospective samples collected from dogs with and without lymphoma were used in this ‎study for the retrospective analyses of this tumor based on the same biomarker amplified by ‎real-time quantitative polymerase chain reaction. The HBE mRNA was aberrantly expressed ‎in canine B and T cell lymphoma compared to the normal lymph node tissue and ‎hyperplastic lymph nodes. In conclusion, this study identified a novel potential biomarker for improving lymphoma ‎diagnosis and treatment in dogs. Further studies with larger sample sizes are needed to ‎confirm the suitability of this biomarker for canine lymphoma diagnosis.

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Publication Date
Tue Oct 18 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Publication Date
Sat Jan 02 2010
Journal Name
Journal Of Al-nahrain University
HIDDEN FEATURES DETECTION USING HISTOGRAM MODIFICATION IN MRI IMAGES
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Magnetic Resonance Imaging (MRI) uses magnetization and radio waves, rather than x-rays to make very detailed, cross- sectional pictures of the brain. In this work we are going to explain some procedures belongs contrast and brightness improvement which is very important in the improvement the image quality such as the manipulation with the image histogram. Its has been explained in this worked the histogram shrink i.e. reducing the size of the gray level gives a dim low contrast picture is produced, where, the histogram stretching of the gray level was distributed on a wide scale but there is no increase in the number of pixels in the bright region. The histogram equalization has also been discuss together with its effects of the improveme

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The micronucleated erythrocytes in speeies of Iraqi fish as indieator of dilution
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The micronucleated erythrocytes in fish was used to detect water pollution by genotoxic agents. Fish belonging to different species were collected from three regions from Baghdad during three months (December/2000,January and February/2001 ).The micronucleated erythrocytes was observed in all the specimens. It was concluded that the genotoxic activity' in one region was less than in die other two regions.?

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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
The Treatment of Wastewater of Alcohol Factory by Filtration as Primary Treatment
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Publication Date
Mon Nov 01 2010
Journal Name
Iraqi Journal Of Physics
The Effect of metals as Additives on Thermal conductivity of Epoxy Resin
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A hand lay-up method was used to prepare Epoxy/ metal composites. Epoxy resin (EP) was used as a matrix with metal particles (Al, Cu, and Fe) as fillers.
The preparation method includes preparing square panels of composites with different weight percentage of fillers (10, 20, 30, 40, and 50%). Standard specimens (88mm in diameter) for thermal conductivity tests were prepared to measure thermal conductivity kexp.The result of experimental thermal conductivity kexp, for EP/metal composites show that, kexp increase with increasing weight percentage, For EP/ Al and EP/Cu composites, and it have have maximum values of 0.33 and 0.35 W/m.K, respectively. While kexp for EP/ Fe composite show slight increase with maximum value of 0.186 W/m.K.

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Publication Date
Sat Oct 01 2011
Journal Name
Iraqi Journal Of Physics
The Effect of metals as additives on adhesion properties of epoxy resin
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EP/ metal composites were prepared as adhesives between two steel rods. Epoxy resin (EP) was used as a matrix with metal as fillers (Al, Cu, Fe,).
The preparation method for tensile adhesion tests includes two steel rods with adhesive composites between the rods to measure adhesion strength Sad and adhesion toughness Gad.
Results of tensile adhesion tests show that EP/ metals composite have maximum strength Sad for certain weight percentage of metals 2.95 and 9MPa at 10% for EP/Al and EP/Cu composite and 8.2MPa at 40% for EP/Fe composites

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