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Dynamic Background Subtraction in Video Surveillance Using Color-Histogram and Fuzzy C-Means Algorithm with Cosine Similarity
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The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art background subtraction models.

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Publication Date
Sat Mar 13 2021
Journal Name
Al-nahrain Journal Of Science
Hiding Multi Short Audio Signals in Color Image by using Fast Fourier Transform
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Many purposes require communicating audio files between the users using different applications of social media. The security level of these applications is limited; at the same time many audio files are secured and must be accessed by authorized persons only, while, most present works attempt to hide single audio file in certain cover media. In this paper, a new approach of hiding three audio signals with unequal sizes in single color digital image has been proposed using the frequencies transform of this image. In the proposed approach, the Fast Fourier Transform was adopted where each audio signal is embedded in specific region with high frequencies in the frequency spectrum of the cover image to sa

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Publication Date
Sun Sep 16 2018
Journal Name
British Journal Of Educational Technology
Group tagging: Using video tagging to facilitate reflection on small group activities
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Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Compensation of the Nonlinear Power Amplifier by Using SCPWL Predistorter with Genetic Algorithm in OFDM technique
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The High Power Amplifiers (HPAs), which are used in wireless communication, are distinctly characterized by nonlinear properties. The linearity of the HPA can be accomplished by retreating an HPA to put it in a linear region on account of power performance loss. Meanwhile the Orthogonal Frequency Division Multiplex signal is very rough. Therefore, it will be required a large undo to the linear action area that leads to a vital loss in power efficiency. Thereby, back-off is not a positive solution. A Simplicial Canonical Piecewise-Linear (SCPWL) model based digital predistorters are widely employed to compensating the nonlinear distortion that introduced by a HPA component in OFDM technology. In this paper, the genetic al

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Investigating the Color Distribution of Young and Old Galaxies Using Observations from SDSS
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     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and

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Publication Date
Wed Sep 30 2015
Journal Name
European Journal Of Chemistry
Reaction pathways and transition states of the C-C and C-H bond cleavage in the aromatic pyrenemolecule - A Density Functional study
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The activation and reaction energies of the C-C and C-H bonds cleavage in pyrene molecule are calculated applying the Density Functional Theory and 6-311G Gaussian basis. Different values for the energies result for the different bonds, depending on the location of the bond and the structure of the corresponding transition states. The C-C bond cleavage reactions include H atom migration, in many cases, leading to the formation of CH2 groups and H-C≡C- acetylenic fragments. The activation energy values of the C-C reactions are greater than 190.00 kcal/mol for all bonds, those for the C-H bonds are greater than 160.00 kcal/mol. The reaction energy values for the C-C bonds range between 56.497 to 191.503 kcal/mol. As for the C-H cleavage rea

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Molecular and Immunological Detection of Hepatitis C Virus in Patients with Chronic Renal Failure
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Due to its association with hepatocellular carcinoma and being one of the ten most common malignancies worldwide, hepatitis C viral infection has become a severe public health concern. Therefore, establishing an accurate, reliable and sensitive diagnostic test for this infection is strongly advised. Real-time polymerase chain reaction (PCR) has been created to achieve this purpose. The current study was established to investigate the hepatitis C virus among Iraqi patients with chronic renal failure and to detect the virus immunologically by the fourth generation enzyme-linked immunosorbent assay technique and molecularly by real-time PCR. As a result, out of 50 patients with chronic renal failure undergoing dialysis, 39 patients tes

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Publication Date
Sun Apr 02 2017
Journal Name
Journal Of The Faculty Of Medicine-baghdad
CA-125, plasma fibrinogen and C-reactive protein in correlation with severity of preeclampsia.
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Pathological And Immunological Study On Infection With Escherichia Coli In ale BALB/c mice
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