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Skull Stripping Based on the Segmentation Models
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Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor the removal of brain sections can be addressed in the subsequent steps, resulting in an unfixed mistake during further analysis. Therefore, accurate skull stripping is necessary for neuroimaging diagnostic systems. This paper proposes a system based on deep learning and Image processing, an innovative method for converting a pre-trained model into another type of pre-trainer using pre-processing operations and the CLAHE filter as a critical phase. The global IBSR data set was used as a test and training set. For the system's efficacy, work was performed based on the principle of three dimensions and three sections of MR images and two-dimensional images, and the results were 99.9% accurate.

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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Text Cryptography based on Arabic Words Characters Number
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Cryptography is a method used to mask text based on any encryption method, and the authorized user only can decrypt and read this message. An intruder tried to attack in many manners to access the communication channel, like impersonating, non-repudiation, denial of services, modification of data, threatening confidentiality and breaking availability of services. The high electronic communications between people need to ensure that transactions remain confidential. Cryptography methods give the best solution to this problem. This paper proposed a new cryptography method based on Arabic words; this method is done based on two steps. Where the first step is binary encoding generation used t

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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Iris Data Compression Based on Hexa-Data Coding
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Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Scopus
Publication Date
Mon May 15 2017
Journal Name
International Journal Of Image And Data Fusion
Image edge detection operators based on orthogonal polynomials
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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Science
Keystroke Dynamics Authentication based on Naïve Bayes Classifier
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Authentication is the process of determining whether someone or something is, in fact, who or what it is declared to be. As the dependence upon computers and computer networks grows, the need for user authentication has increased. User’s claimed identity can be verified by one of several methods. One of the most popular of these methods is represented by (something user know), such as password or Personal Identification Number (PIN). Biometrics is the science and technology of authentication by identifying the living individual’s physiological or behavioral attributes. Keystroke authentication is a new behavioral access control system to identify legitimate users via their typing behavior. The objective of this paper is to provide user

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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Publication Date
Mon Mar 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Speech Enhancement Algorithm Based on a Hybrid Estimator
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Abstract<p>Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra</p> ... Show More
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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Ebonite linings Based on Natural and Synthetic Rubber
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 The corrosion of metals is of great economic importance. Estimates show that the quarter of the iron and the steel produced is destroyed in this way. Rubber lining has been used for severe corrosion protection because NR and certain synthetic rubbers have a basic resistance to the very corrosive chemicals particularly acids. The present work includes producing ebonite from both natural and synthetic rubbers ; therefore, the following materials were chosen to produce ebonite rubber: a) Natural rubber (NR). b) Styrene butadiene rubber (SBR). c) Nitrile rubber (NBR). d) Neoprene rubber (CR) [WRT]. The best ebonite vulcanizates are obtained in the presence of 30 Pphr sulfur, and carbon black as reinforcing filler. The relation between

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Forecasting the use of Generalized Autoregressive Conditional Heteroscedastic Models (GARCH) Seasonality with practical application
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In this paper  has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi

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Publication Date
Thu Oct 15 2015
Journal Name
Al Mustansyriah Journal Of Science
Comparison between (ARIMA) and (ANNs) models for estimating the relative humidity for Baghdad city
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The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.