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The Value of Longitudinal Strain versus Coronary Angiography in Detection of Coronary Artery Disease
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Aims: The aim of this study was to evaluate the value and accuracy of longitudinal strain in detection of coronary artery disease compared to coronary angiography. Results: The left ventricular longitudinal strain-speckle tracking showed evidence of stenosis of left anterior descending artery, circumflex artery and right coronary artery in (86.1%), (76.4%), and (84.7%) respectively. For the stenosis in left anterior descending artery, the current study showed that the longitudinal strain was a good predictor for presence of significant stenosis with a sensitivity of (93.8%), specificity (75%) and accuracy (91.7%) compared with coronary angiography. For the stenosis in right coronary artery, the left ventricular longitudinal strain had a sensitivity of (93.5%), specificity of (70.0%) and accuracy of (90.3%) compared with coronary angiography. Conclusion: Speckle-tracking echocardiography technique has a good performance and validity in detection of coronary artery stenosis with good agreement with angiography.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Sun Dec 10 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Detection of Multiple Sclerosis Lesions in Supra- and Infra-Tentorial Anatomical Regions by Double Inversion Recovery, Flair, and T2 MRI Sequences: A Comparative Study in Iraqi Patients
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Background: In young adults, multiple sclerosis is a prevalent chronic inflammatory demyelinating condition. It is characterized by white matter affection, but many individuals also have significant gray matter involvement. A double-inversion recovery pulse (DIR) pattern was recently proposed to improve the visibility of multiple sclerosis lesions. Objective: To find out how well a DIR sequence, FLAIR, and T2-weighted pulse sequences can find MS lesions in the supratentorial and infratentorial regions. Methods: A total of 37 patients with established diagnoses of multiple sclerosis were included in this cross-sectional study. Brain MRI was done using double inversion recovery, T2, and FLAIR sequences. The number of lesions was count

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Publication Date
Mon Apr 29 2024
Journal Name
Journal Of The College Of Basic Education
Detection Of Biofilm Formation By Beta- Lactam Resistance Klebsiella Pneumoniae Isolated From Clinical Specimens And Aquatic Samples
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Publication Date
Sun Feb 01 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Early detection of periodontitis among young adult cigarette smokers and non-smokers using cone beam computed tomography
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Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth exc

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Publication Date
Fri Dec 07 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Effects of Aldosterone, Osteoprotegerin and Fibroblast Growth Factor-23 and Some Biochemical Markers in Chronic Kidney Disease Patients (Stage II-IV) among Patients with or without Cardiovascular Events
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Chronic Kidney Disease (CKD) is a public health problem and many studies support the link between kidney dysfunction and cardiovascular events.  Aldosterone has been shown for decades that a plasma aldosterone concentration is elevated in CKD. Whilst, Osteoprotegerin (OPG), after its capacity to protect bone, also osteoprotegerin is elevated in patients with chronic kidney disease (CKD), where it could predict the deterioration of kidney function, cardiovascular, vascular events and all-cause mortality. On the other hand, fibroblast growth factors (FGFs), in patients with CKD, its levels seem to increase progressively as kidney function worsens. The aim of the present study is to assess the correlations between serum osteoprotegerin

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Publication Date
Sat Aug 31 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Credit Card Fraud Detection Using an Autoencoder Model with New Loss Function
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

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Publication Date
Tue Jan 18 2022
Journal Name
Photonic Sensors
Arsenic Detection Using Surface Plasmon Resonance Sensor With Hydrous Ferric Oxide Layer
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Abstract<p>The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub> to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb<sup>−1</sup> and 0.922 °·ppb<jats></jats></p> ... Show More
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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Producing Coordinate Time Series for Iraq's CORS Site for Detection Geophysical Phenomena
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Global Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.

In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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