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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 Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Assessment of Elongation Percentage, Tensile, and Tear Strength of Filler Particles: An In Vitro Study
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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
DNA Encoding for Misuse Intrusion Detection System based on UNSW-NB15 Data Set
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Recent researches showed that DNA encoding and pattern matching can be used for the intrusion-detection system (IDS), with results of high rate of attack detection. The evaluation of these intrusion detection systems is based on datasets that are generated decades ago. However, numerous studies outlined that these datasets neither inclusively reflect the network traffic, nor the modern low footprint attacks, and do not cover the current network threat environment. In this paper, a new DNA encoding for misuse IDS based on UNSW-NB15 dataset is proposed. The proposed system is performed by building a DNA encoding for all values of 49 attributes. Then attack keys (based on attack signatures) are extracted and, finally, Raita algorithm is app

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Interior Visual Intruders Detection Module Based on Multi-Connect Architecture MCA Associative Memory
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Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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Publication Date
Mon Jan 10 2022
Journal Name
Iraqi Journal Of Science
Genetic Algorithm based Clustering for Intrusion Detection
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Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A review on Active Constituents and Pharmacological Effects of Eriobotrya Japonica Lindl. (Loquat)
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Eriobotrya japonica Lindl., named as loquat, is a subtropical fruit tree of the family Rosaceae which is well known medical plant originated in  Japan and China. Loquat portions, like leaves, peels and fruits have been shown to possess various health usefulnesses.  In Chinese classical medicine, it is vastly utilized in many illnesses, like gastroenteric disorders, diabetes mellitus, pulmonary inflammatory diseases and chronic bronchitis. Loquat plant contain many active constituents, such as flavonoids, carotenoids, vitamins, polyphenolic compounds, other that have many biological effects like anti-tumor, anti-diabetic, anti-inflammatory, anti-mutagenic, antioxidant, antiviral, antitussive, hepatoprotective and hypoli

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Publication Date
Fri Jul 30 2021
Journal Name
Coatings
A Past, Present, and Prospective Review on Microwave Nondestructive Evaluation of Composite Coatings
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Recent years have witnessed an increase in the use of composite coatings for numerous applications, including aerospace, aircraft, and maritime vessels. These materials owe this popularity surge to the superior strength, weight, stiffness, and electrical insulation they exhibit over conventional substances, such as metals. The growing demand for such materials is accompanied by the inevitable need for fast, accurate, and affordable nondestructive testing techniques to reveal any possible defects within the coatings or any defects under coating. However, typical nondestructive testing (NDT) techniques such as ultrasonic testing (UT), infrared thermography (IRT), eddy current testing (ECT), and laser shearography (LS) have failed to p

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Symmetric- Based Steganography Technique Using Spiral-Searching Method for HSV Color Images
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Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

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Publication Date
Thu Jan 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Subject Review on a Some Analytical Methods for the Determination of Chloroquine and Hydroxychloroquine Drugs
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Chloroquine and Hydroxychloroquine drugs are widely prescribed for malaria disease. Since the end of 2019, humans have been under threat due to a disease called (COVID-19), which was first reported in China. Many methodical approaches have been reported to quantify chloroquine and hydroxychloroquine in blood, urine, plasma, serum, and pharmaceutical dosage form. Some of these techniques are spectrophotometry, liquid chromatography with a mass detector, gas chromatography, and ultra-performance, high-performance liquid chromatography (HPLC), in addition to electrochemical methods. This literature review discusses various analytical methods for the determining hydroxychloroquine and chloroquine.

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Publication Date
Wed Oct 25 2023
Journal Name
Urban Planning And Construction
A Review on Urban Planning and Its Role in Managing Flood Risks
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This review delves deep into the intricate relationship between urban planning and flood risk management, tracing its historical trajectory and the evolution of methodologies over time. Traditionally, urban centers prioritized defensive measures, like dikes and levees, with an emphasis on immediate solutions over long-term resilience. These practices, though effective in the short term, often overlooked broader environmental implications and the necessity for holistic planning. However, as urban areas burgeoned and climate change introduced new challenges, there has been a marked shift in approach. Modern urban planning now emphasizes integrated blue-green infrastructure, aiming to harmonize human habitation with water cycles. Resil

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