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Epileptic EEG activity detection for children using entropy-based biomarkers
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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
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Scopus (36)
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
COMPARATIVE STUDY FOR EDGE DETECTION OF NOISY IMAGE USING SOBEL AND LAPLACE OPERATORS
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
edge detection using modification prewitt operators
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in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

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Publication Date
Mon Oct 23 2023
Journal Name
Journal Of Optics
Single mode optical fiber sensor based on surface plasmon resonance for the detection of the oil aging for the electrical transformers
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This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3

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Publication Date
Fri Aug 15 2025
Journal Name
The Eurasia Proceedings Of Science Technology Engineering And Mathematics
Detection of Antimicrobial Activity of Aspergillus terreus Against Clinical Isolates of Serratia marcescens
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Out of a total of fifty samples, thirty-five isolates were identified as Serratia marcescens. Thesediverse clinical samples were collected over a three-month period, from October 2023 to December 2023, fromseveral hospitals in Baghdad, including Fatima Al-Zahraa Hospital, Al-Sader Hospital, Ibn Al-Balady Hospital,and Al-Imam Ali Hospital. The clinical samples primarily included urine from patients with urinary tractinfections (UTIs). All isolates were cultured on nutrient agar, MacConkey agar, and blood agar, and theiridentities were confirmed through biochemical testing and the Vitek 2 compact system. Based on phenotypicvirulence factors, the S. marcescens isolates showed varying positive patterns: 32 out of 35 (91.42%) forprotease

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Publication Date
Tue Jun 01 2021
Journal Name
Food Chemistry
Development of cellulose Nanofiber-based substrates for rapid detection of ferbam in kale by Surface-enhanced Raman spectroscopy
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Publication Date
Tue Jul 22 2025
Journal Name
Retos
Evaluating the impact of neurophysiological fatigue patterns on tactical decision-making in elite football players using wearable EEG technology
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Introduction: Elite football performance hinges on rapid tactical decision-making under physical and cognitive strain. While peripheral fatigue’s effects on motor output are well documented, the neurophysiological markers of mental fatigue and their impact on in-game decision making remain underexplored. Objective: To determine how EEG-derived central fatigue indices—frontal theta power and the theta/alpha ratio—relate to tactical decision accuracy and speed in elite football players. Methodology: Twenty male national-level footballers (age 22.4 ± 2.1 years; ≥ 5 years’ experience) completed the Yo-Yo Intermittent Recovery Test Level 1 while wearing an 8-channel dry-electrode frontal EEG headset. Frontal theta

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Publication Date
Fri Jun 30 2023
Journal Name
Pakistan Heart Journal
Music Medicine Intervention--Based Program for Reducing Pain and Anxiety of Children Undergoing Bone Marrow Aspiration and Lumber Puncture Procedures
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