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Color Image Denoising Using Stationary Wavelet Transform and Adaptive Wiener Filter
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The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by using MATLAB R2010a with color images contaminated by white Gaussian noise. Compared with stationary wavelet and wiener filter algorithms, the experimental results show that the proposed method provides better subjective and objective quality, and obtain up to 3.5 dB PSNR improvement.

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Foavedur mass media for children and modifyin Their behaviour from point of their parents view: Foavedur mass media for children and modifyin Their behaviour from point of their parents view
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Abstract:
The research aimed to know favoured mass media for children and
modifying their behaviour ,the child became aquires the information from
mass media that he exposure them without any guidance , where upon the
quidance proqrammes becomes real danger whereas qet out their civil

style and converting to deadly poisons,and because of little study for this
supject the two researchers opined to perform astudy to know the favoured
mass media to the children and what are the mass media that modify their
behavior according to ther parent points of view ,after propring the research
measurement and the suilable statical methods it has shown that there are
mass media affect in children behavior ,they are st

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Publication Date
Wed May 04 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Dextran Production From Locally Isolated Bacteria (Leuconostoc mesenteroides) And Its Utilization In Some Food Application: Dextran Production From Locally Isolated Bacteria (Leuconostoc mesenteroides) And Its Utilization In Some Food Application
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Leuconostoc bacteria was isolated from local pickled cabbage (Brassica oleracea capitata) and identified as Leuconostoc mesenteroides by morphology,biochemical and physiological. The local isolated L. mesenteroides bacteria under the optimal conditions of dextran production showed that, the highly production of dextran was 7.7g achieved by using a modified natural media comprised of 100ml whey, 10g refined sugar, 0.5g heated yeast extract, 0.01g CaCl2, 0.001g MgSO4, 0.001g MnCl2 and 0.001g NaCl at pH 6 and 25̊C for 24 hr of fermentation and by using 1ᵡ106 cell/ml as initial inoculums volume. Some applications in food technology (Ice cream, Loaf, Ketchup and Beef preservation) have been performed with processed dextran. The result

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of The College Of Languages (jcl)
L’alternance codique ou le code switching dans l’échange verbal
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Le mot anglais code switching ou l’équivalent français alternance codique est un terme très utilisé dans des recherches qui traitent des problèmes en sociolinguistique. Le bilingue dispose, dans son répertoire linguistique, de moyens de communication qui lui permettent d’adapter son langage à des situations de communication plus variées que ceux du monolingue. Le code-switching ou l’alternance codique qui est un lieu de structuration de stratégies de communication en est un moyen indispensable.
L’alternance codique dans la conversation est l’utilisation d’un mot ou plus appartenant à une langue B à l’intérieur d’une phrase qui appartient à une langue A. Dans la plupart des cas, le locuteur se sert de l’a

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Sustainable ENERGY by using AI
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As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Shadow Removal Using Segmentation Method
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Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Dewatering of Kerosene using Hydrocyclone
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Water/oil emulsion is considered as the most refractory mixture to separate because of the interference of the two immiscible liquids, water and oil. This research presents a study of dewatering of water / kerosene emulsion using hydrocyclone. The effects of factors such as: feed flow rate (3, 5, 7, 9, and 11 L/min), inlet water concentration of the emulsion (5%, 7.5%, 10%, 12.5%, and 15% by volume), and split ratio (0.1, 0.3, 0.5, 0.7, and 0.9) on the separation efficiency and pressure drop were studied. Dimensional analysis using Pi theorem was applied for the first time to model the hydrocyclone based on the experimental data. It was shown that the maximum separation efficiency; at split ratio 0.1, was 94.3% at 10% co

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
strong criminal capabilities، Using simulation .
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The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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