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bsj-1301
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image recovery after applying JPEG coding to the watermarking image are included.

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Publication Date
Wed Aug 11 2021
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Image Denoising Using Multiwavelet Transform with Different Filters and Rules
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<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi

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Publication Date
Mon May 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Improvement Using The Combination of Wavelet and Multiwavelet Transform
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      This paper introduces method of image enhancement using the combination of both wavelet and Multiwavelet transformation. New technique is proposed for image enhancement using one smoothing filter.

    A critically- Sampled Scheme of preprocessing method is used for computing the Multiwavelet.It is the 2nd norm approximation used to speed the procedures needed for such computation.

  An improvement was achieved with the proposed method in comparison with the conventional method. 

The performance of this technique has been done by computer using Visual Baisec.6 package.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Image Steganography using Dynamic Threshold based on Discrete Cosine Transform
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The art of preventing the detection of hidden information messages is the way that steganography work. Several algorithms have been proposed for steganographic techniques. A major portion of these algorithms is specified for image steganography because the image has a high level of redundancy. This paper proposed an image steganography technique using a dynamic threshold produced by the discrete cosine coefficient. After dividing the green and blue channel of the cover image into 1*3-pixel blocks, check if any bits of green channel block less or equal to threshold then start to store the secret bits in blue channel block, and to increase the security not all bits in the chosen block used to store the secret bits. Firstly, store in the cente

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
linear equivalence determination of key-stream sequence using Z-Transform
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the research ptesents a proposed method to compare or determine the linear equivalence of the key-stream from linear or nonlinear key-stream

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Image Compression Using Tap 9/7 Wavelet Transform and Quadtree Coding Scheme
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This paper is concerned with the design and implementation of an image compression method based on biorthogonal tap-9/7 discrete wavelet transform (DWT) and quadtree coding method. As a first step the color correlation is handled using YUV color representation instead of RGB. Then, the chromatic sub-bands are downsampled, and the data of each color band is transformed using wavelet transform. The produced wavelet sub-bands are quantized using hierarchal scalar quantization method. The detail quantized coefficient is coded using quadtree coding followed by Lempel-Ziv-Welch (LZW) encoding. While the approximation coefficients are coded using delta coding followed by LZW encoding. The test results indicated that the compression results are com

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The New Complex Integral Transform "Complex Sadik Transform" and It's Applications
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In this paper, we introduce a new complex integral transform namely ”Complex Sadik Transform”. The
properties of this transformation are investigated. This complex integral transformation is used to reduce
the core problem to a simple algebraic equation. The answer to this primary problem can than be obtained
by solving this algebraic equation and applying the inverse of complex Sadik transformation. Finally,
the complex Sadik integral transformation is applied and used to find the solution of linear higher order
ordinary differential equations. As well as, we present and discuss, some important real life problems
such as: pharmacokinetics problem ,nuclear physics problem and Beams Probem

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
An Embedded 5(4) Pair of Optimized Runge-Kutta Method for the Numerical Solution of Periodic Initial Value Problems
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      This paper presents an alternative method for developing effective embedded optimized Runge-Kutta (RK) algorithms to solve oscillatory problems numerically.   The embedded scheme approach has algebraic orders of 5 and 4. By transforming second-order ordinary differential equations (ODEs) into their first-order counterpart, the suggested approach solves first-order ODEs. The amplification error, phase-lag, and first derivative of the phase-lag are all nil in the embedded pair. The alternative method’s absolute stability is demonstrated. The numerical tests are conducted to demonstrate the effectiveness of the developed approach in comparison to other RK approaches. The alternative approach outperforms the current RK methods

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
An Application of Data Mining Algorithms for Analyzing Psychological Researches
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     Computer science has evolved to become the basis for evolution and entered into all areas of life where the use of computer has been developed in all scientific, military, commercial and health institutions. In addition, it has been applied in residential and industrial projects due to the high capacity and ability to achieve goals in a shorter time and less effort. In this research, the computer, its branches, and algorithms will be invested in the psychological field. In general, in psychological fields, a questionnaire model is created according to the requirements of the research topic. The model contains many questions that are answered by the individuals of the sample space chosen by the researcher. Often,

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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