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Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.

Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
A Parallel Clustering Analysis Based on Hadoop Multi-Node and Apache Mahout
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     The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive sc

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Smartphones as Smart Tools for Science and Engineering Laboratory: A Review
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     This article reviews a decade of research in transforming smartphones into smart measurement tools for science and engineering laboratories. High-precision sensors have been effectively utilized with specific mobile applications to measure physical parameters. Linear, rotational, and vibrational motions can be tracked and studied using built-in accelerometers, magnetometers, gyroscopes, proximity sensors, or ambient light sensors, depending on each experiment design. Water and sound waves were respectively captured for analysis by smartphone cameras and microphones. Various optics experiments were successfully demonstrated by replacing traditional lux meters with built-in ambient light sensors. These smartphone-based measurement

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
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Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

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Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Transfocation Technique to Overcome Atmospheric Scintillation Effect on a Laser Detection and Tracking System (LDTS)
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Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom

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Publication Date
Tue Jun 14 2016
Journal Name
Applied Organometallic Chemistry
Synthesis and antioxidant activities of Schiff bases and their complexes: a review
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Schiff bases, named after Hugo Schiff, are aldehyde- or ketone-like compounds in which the carbonyl group is replaced by imine or azomethine group. They are widely used for industrial purposes and also have a broad range of applications as antioxidants. An overview of antioxidant applications of Schiff bases and their complexes is discussed in this review. A brief history of the synthesis and reactivity of Schiff bases and their complexes is presented. Factors of antioxidants are illustrated and discussed. Copyright © 2016 John Wiley & Sons, Ltd.

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Based on Deep Learning: An Overview
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      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Tue Jul 13 2021
Journal Name
Journal Of The Faculty Of Medicine Baghdad
A Comparative Study of Colorectal Cancer Based on Patient’s Age
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Abstract:

Background: The alteration of bowel habits, bleeding per-rectum and anemia were common features in both groups in this study, but in young patients there was a delay of 6 months between the presenting symptoms and the definitive diagnosis because the disease was not suspected and investigated in them. The most common site for the tumors in young patients was the rectum and in patients above the age of 40 years was the Sigmoid.

The pathological finding showed that classification of the colorectal tumors in young patients appear moderately to poorly differentiated adenocarcinoma , this indicate a more malignant course of the disease in young patients.

This study sen

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Electrical stimulation for the treatment of Knee joint osteoarthritis
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Abstract 20 patients with osteoarthritis of the knee joint were treated by electrical stimulation in the form of 6 sessions every other day each sessions of diphase fixe (DF) for 4 minutes followed by rest for 4 minutes then treated with a monophase fixe (MF) for 2 minutes. By clinical & statistical analysis ( P value < 0.05) we conclude that the electrical stimulation is effective as one method in the treatment of osteoarthritis.

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