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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
Fri Dec 01 2023
Journal Name
Inorganic Chemistry Communications
A comprehensive review highlights the photocatalytic heterojunctions and their superiority in the photo-destruction of organic pollutants in industrial wastewater
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Publication Date
Wed Aug 30 2023
Journal Name
مجلة نسق
The Effectiveness of a Program Based on the Theory of the Five Minds in Developing Focused Reading and Extensive Reading Skills among Second-Year Middle School Students
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Tue May 24 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
A Blind Video Copyright Protection Technique in Maximum and Minimum Energy Frames Based on The Fast Walsh Hadamard Transform (FWHT) and Discrete Wavelet Transform (DWT) and Arnold Map
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Video copyright protection is the most generally acknowledged method of preventing data piracy. This paper proposes a blind video copyright protection technique based on the Fast Walsh Hadamard Transform (FWHT), Discrete Wavelet Transform (DWT), and Arnold Map. The proposed method chooses only frames with maximum and minimum energy features to host the watermark. It also exploits the advantages of both the fast Walsh Hadamard transform (FWHT) and discrete wavelet transforms (DWT) for watermark embedding. The Arnold map encrypts watermarks before the embedding process and decrypts watermarks after extraction. The results show that the proposed method can achieve a fast embedding time, good transparency, and robustness against various

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Publication Date
Fri Jun 02 2023
Journal Name
Bandaoti Guangdian/semiconductor Optoelectronics
NMUSING AN INNOVATIVE DEVICE TO IMPROVE THE EFFICIENCY OF THE ANTERIOR QUADRICEPS MUSCLE OF THE INJURED KNEE JOINT AFTER SURGICAL INTERVENTION OF THE ANTERIOR CRUCIATE LIGAMENT IN ADVANCED SOCCER PLAYERS
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This study aimed to manufacture an innovative device that enables the player to walk after the operation and improves the functional efficiency through the improvement in the range of motion as well as the improvement in the size of the muscles working on the knee joint. The research, the study population consisted of players with severing the anterior cruciate ligament of the advanced soccer players, and the number of the research sample was (5) injured for the control sample and (5) for the experimental sample in Abu Ghraib Hospital and some rehabilitation centers for a period of six months, and the pre-tests were conducted after two weeks of The cruciate ligament surgery was performed, and the innovative device was used for the e

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Publication Date
Sun Aug 15 2021
Journal Name
Al-qadisiyah Journal Of Pure Science
Review On Elucidation Of The Risk Factors Associated With The Prevalence Of Coccidiosis In Buffaloes
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The research was performed in order to investigate the prevalence of Eimeria spp in buffalo. Coccidiosis, is a common livestock disease include water buffaloes and nothing is known about the most pathogenic species of Eimeria. Since the highest prevalence of oocyst shedding and incidence of disease occurs in buffalo calves less than one year of age. The omnipresent occurrence and negative effects of the infection on health and buffalo growth output are taken into account. Therefore, both farmers and veterinarians should pay greater attention to infections with Eimeria spp. And there is little analysis of data reported in Iraq and the world regarding Eimeria infection in river buffalo spp.

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Tue Mar 01 2022
Journal Name
Malaysian Journal Of Medicine & Health Sciences
Detection of Iron and Ferritin in Diabetes Mellitus Type 2 Patients
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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Detection of Aflatoxin B1 among Early and Middle Childhood Iraqi Patients
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      The study was conducted for the detection of Aflatoxin B1(AFB1) in the serum and urine of 42 early and middle childhood patients (26 male and  16 female ) with renal function disease, liver function disease, in additional to atrophy in the growth and other symptoms depending on the information within consent obtained from each patient, in addition to 8 children, apparently healthy, as  the control. The technique of HPLC was used for the detection of AFB1 from all samples. The results showed that out of 42 patient children, 19 (45.2%) gave positive detection of AFB1 in the serum among all age groups patients with a mean of 0.88 ng/ml and a range of (0.12-3.04) ng/ml. This was compared with the cont

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