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3-Level Techniques Comparison based Image Recognition
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Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third level. The two techniques that have the best results which are (sww and www) are chosen, then image recognition is applied to these two techniques using Euclidean distance and Manhattan distance and a comparison between them has been implemented., it is concluded that, sww technique is better than www technique in image recognition because it has a higher match performance (100%) for Euclidean distance and Manhattan distance than that in www..

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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Image Hiding Using Discrete Cosine Transform
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Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.

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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Image Zooming Using Inverse Slantlet Transform
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Digital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.

      First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the   signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by  box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .

  &nbs

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Publication Date
Mon Jan 02 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Image encryption technique using Lagrange interpolation
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Publication Date
Sat Oct 01 2022
Journal Name
Medical Journal Of Babylon
Plasma Sclerostin Level in Multiple Myeloma
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Background:

Multiple myeloma (MM) is a heterogenous plasma cell malignancy with various complications. Sclerostin is a Wingless-type (Wnt) inhibitor specifically expressed by osteocytes; it acts as a negative regulator of bone formation.

Objectives:

To assess plasma sclerostin level in MM patients and find its correlations with clinical and laboratory data, including osteolytic bone disease and international staging system (ISS).

Materials and Methods:

This cr

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Publication Date
Fri Jan 01 2010
Journal Name
Journal Of The College Of Education, Al-mustansiriya University
Synthesis and ldentification of metal complexes of 1- phenyl -3, (2'(S'phenyl amine)'l, 3, 4-thiad iazole'Z'yl) phenyl thiourea.
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Complexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4- thiadiazole-2-yl)phenyl) thiourea have been prepared and characteized by elemental analysis, Ff-[R, and u.v./ visible spectra moreover, determination of metal content M%o by flame atomic absorption spectroscopy, molar conductance in DMSO solution and magnetic moments (peffl. The result showed that the ligand (L) was coordinated to Mn*2, Ni*2, Ct*2,2n*2,Cd*2, and Hg*2 ions through the nitrogen atoms and sulpher atoms. From the result obtained, rhe following general formula [MLClz] has been given for the prepared complexes with an octahedral geometry around the metal ions for all complexes. where M= Mn*2, Ni*2, cu*2, zn*z, cd*z, and Hg*2 l= l-phenyl-3-(2-(5-(phenyl amino)-1, 3,

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Publication Date
Mon Jan 01 2024
Journal Name
Dyes And Pigments
3′,3′,4′,4′,5′,5′,6′,6′,6′-nonafluoro-hexyloxy groups substituted phthalocyanines: Synthesis, characterization and their biological properties
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Publication Date
Wed Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Partial Level Densities for Neutron Induced Pre-equilibrium Nuclear Reactions
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The state and partial level densities were calculated using the corresponding formulas that are obtained in the frame work of the exciton model with equidistant spacing model (ESM) and non-ESM (NESM). Different corrections have been considered, which are obtained from other nuclear principles or models. These corrections are Pauli Exclusion Principle, surface effect, pairing effect, back shift due to shell effect and bound state effect . They are combined together in a composite formula with the intention to reach the final formula. One-component system at energies less than 100 MeV and mass number range (50-200) is assumed in the present work. It was found that Williams, plus spin formula is the most effective approach to the composite

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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