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TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumor through MRI image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumor detection.

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Publication Date
Wed Mar 28 2018
Journal Name
Indian Journal Of Natural Sciences
Detection of the Main Mycotoxins in Feed of Horses in Al-Zawra'a Park and Study their Effects on Hematological Feature
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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Applied And Natural Science
Detection of some virulence genes (esp, agg, gelE, CylA) in Enterococcus faecalis isolated from different clinical cases at Baghdad
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The virulent genes are the key players in the ability of the bacterium to cause disease. The products of such genes that facilitate the successful colonization and survival of the bacterium in or cause damage to the host are pathogenicity determinants. This study aimed to investigate the prevalence of virulence factors (esp, agg, gelE, CylA) in E. faecalis isolated from diverse human clinical collected in Iraqi patient , as well as to assess their ability to form biofilm and to determine their haemolytic and gelatinase activities. Thirty-two isolates of bacteria Enterococcus faecalis were obtained, including 15 isolates (46.87%) of the urine, 6 isolates (18.75%) for each of the stool and uterine secretions, and 5 isolates (15.62%) of the wo

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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
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Aug 01 2021
Journal Name
Sensors And Actuators B: Chemical
Sensitive and simple colorimetric methods for visual detection and quantitative determination of semicarbazide in flour products using colorimetric reagents
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After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

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Publication Date
Tue Jan 10 2023
Journal Name
College Of Islamic Sciences
The Approach of Sheikh Abdul Qadir Al-Muhajir in Proving the Existence of God through his book (Rafa’ Al-Hajib fi Sharh ethbat Al-Wajib) An analytical study
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This research is drawn from a doctoral dissertation, studying the approach of Sheikh Abd al-Qadir al-Muhajir al-Sanandji al-Kurdi (1303 AH) on the issue of proving the existence of God Almighty.
Sheikh Abd al-Qadir al-Sanandji was one of the scholars well versed in mental sciences. He has many books, all of them in the sciences of speech and wisdom, and among his books is the book (Raising the Eyebrow in Explanation of Ithbat al-Wajib), which is still a manuscript that has not been printed.
Through this book, the researcher studied the evidence of Sheikh Abdul Qadir to prove the existence of God Almighty, and compared it with the evidence of philosophers and theologians.
At the beginning, he presented a study on the import

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Publication Date
Sat Jan 01 2022
Journal Name
Swinburne University Of Technology
Numerical Modeling of Flow through Foam Nodes in the Presence of Solid Particles for Foams within the Dry Limit and for Foams that are Approaching the Wet Limit
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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Detection of Extraintestinal Pathogenic Escherichia coli among Normal Stool Flora of Young, Healthy, Unmarried Males & Females as Predisposing Factor to Extraintestinal Infections:A Comparison Study
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In this study we surveyed the dominant normal stool flora of randomly selected healthy, young (18-23 years old), unmarried (doctrinal) Iraqi college students (males and females) for the carriage of extraintestinal pathogenic E. coli (ExPEC). ExPEC virulence was detected phenotypically by mannose resistant hemagglutination of human red blood cells (MRHA) and mannose sensitive (MS) agglutination of Bakers' yeast (Saccharomyces cerevisceae). From 88 college students, 264 E. coli isolates were obtained (3 isolates per person): 123 from 41 females and 141 from 47 males. Of these isolates, 56% (149/264) caused MS agglutination of yeast cells and 4.16% (11/264) showed MRHA. Eighty two percent (9/11) of the isolates with MRHA also caused MS agglu

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Crossref
Publication Date
Wed Jun 26 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
VSM Based Models and Integration of Exact and Fuzzy Similarity For Improving Detection of External Textual Plagiarism admin June 29, 2019
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