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Disc damage likelihood scale recognition for Glaucoma detection
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Abstract<p>Glaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to other eye illness such as myopia and cataracts. The impact of glaucoma can’t be cured; The Disc Damage Likelihood Scale (DDLS) can be used to assess the Glaucoma. The proposed methodology suggested simple method to extract Neuroretinal rim (NRM) region then dividing the region into four sectors after that calculate the width for each sector and select the minimum value to use it in DDLS factor. The feature was fed to the SVM classification algorithm, the DDLS successfully classified Glaucoma disease with 70% percentage; moreover, when the dimensions of both Optic Disc(OD) and Optic Cup(OC) were used as additional features the accuracy rate raised to 91%.</p>
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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Tue Oct 26 2021
Journal Name
Remote Sensing Technologies And Applications In Urban Environments Vi
DTM Extraction and building detection in DSMs having large holes
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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Towards Accurate Pupil Detection Based on Morphology and Hough Transform
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 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris

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Publication Date
Sun Jul 01 2018
Journal Name
Current Research In Microbiology And Biotechnology
Detection of anti-Helicobacter pylori in patients with Multiple Sclerosis
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To determine the relationship between Helicobacter pylori infection and Multiple Sclerosis (MS) disorder, 20 patients with MS aged (25-60) years have been investigated from the period of 2016/12/1 to 2017/3/1 and compared to 15 apparently healthy individuals. All study groups were carried out to measure anti H.pylori IgA and H.pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA) technique. There was a significant elevation (p<0.05) in the concentration of anti H.pylori IgG and IgA antibodies (Abs) compared to control group, and there was no significant difference (p>0.05) in the concentration of IgA and IgG (Abs) of H.pylori according to gender, and there was no significant difference (p>0.05) in the concentration of IgA and I

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Publication Date
Sun Jun 01 2025
Journal Name
Medical Journal Of Babylon
Detection of Human Parvovirus (B19) in Beta Thalassemia Major Patients
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Abstract<sec> <title>Background:

Beta-thalassemia major (β-TM) is inheritable condition with many complications especially in children. The blood-borne viral infection was proposed as a risk factor due to recurrent blood transfusion regimen (hemotherapy).

Objectives:

This study aimed to investigate Human parvovirus B19 (PVB19) prevalence in β-TM patients by serological and molecular means.

Materials and Methods:

This is a cross-section

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
New Approach in Detection MAC Spoofing in a WiFi LAN
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Medium Access Control (MAC) spoofing attacks relate to an attacker altering the manufacturer assigned MAC address to any other value. MAC spoofing attacks in Wireless Fidelity (WiFi) network are simple because of the ease of access to the tools of the MAC fraud on the Internet like MAC Makeup, and in addition to that the MAC address can be changed manually without software. MAC spoofing attacks are considered one of the most intensive attacks in the WiFi network; as result for that, many MAC spoofing detection systems were built, each of which comes with its strength and weak points. This paper logically identifies and recognizes the weak points
and masquerading paths that penetrate the up-to-date existing detection systems. Then the

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Tue Feb 01 2022
Journal Name
Svu-international Journal Of Engineering Sciences And Applications
Water Quality Detection using cost-effective sensors based on IoT
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Publication Date
Wed Aug 25 2021
Journal Name
2021 7th International Conference On Contemporary Information Technology And Mathematics (iccitm)
Anomaly Detection in Flight Data Using the Naïve Bayes Classifier
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