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Fast Recursive Computation of Krawtchouk Polynomials
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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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Publication Date
Tue Jun 07 2016
Journal Name
International Journal Of Scientific & Engineering Research
Fast Response Photoconductive for Fe3O4:Ce Nanoparticles
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Fe3O4:Ce thin films were deposited on glass and Si substrates by Pulse Laser Deposition Technique (PLD). Polycrystalline nature of the cubic structure with the preferred orientation of (311) are proved by X-ray diffraction. The nano size of the prepared films are revealed by SEM measurement. Undoped Iron oxide and doped with different concentration of Ce films have direct allowed transition band gap with 2.15±0.1 eV which is confirmed by PL Photoluminescence measurements. The PL spectra consist of the emission band located at two sets of peaks, set (A) at 579±2 nm , and set (B) at 650 nm, respectively when it is excited at an excitation wavelength of 280 nm at room temperature. I-V characteristics have been studied in the dark and under v

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Fast Processing RNA-Seq on Multicore Processor
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RNA Sequencing (RNA-Seq) is the sequencing and analysis of transcriptomes. The main purpose of RNA-Seq analysis is to find out the presence and quantity of RNA in an experimental sample under a specific condition. Essentially, RNA raw sequence data was massive. It can be as big as hundreds of Gigabytes (GB). This massive data always makes the processing time become longer and take several days. A multicore processor can speed up a program by separating the tasks and running the tasks’ errands concurrently. Hence, a multicore processor will be a suitable choice to overcome this problem. Therefore, this study aims to use an Intel multicore processor to improve the RNA-Seq speed and analyze RNA-Seq analysis's performance with a multiproce

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Frequency analyses of human voice using fast Fourier transform
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Quantitative analysis of human voice has been subject of interest and the subject gained momentum when human voice was identified as a modality for human authentication and identification. The main organ responsible for production of sound is larynx and the structure of larynx along with its physical properties and modes of vibration determine the nature and quality of sound produced. There has been lot of work from the point of view of fundamental frequency of sound and its characteristics. With the introduction of additional applications of human voice interest grew in other characteristics of sound and possibility of extracting useful features from human voice. We conducted a study using Fast Fourier Transform (FFT) technique to analy

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Publication Date
Fri May 17 2013
Journal Name
International Journal Of Computer Applications
Fast Lossless Compression of Medical Images based on Polynomial
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In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

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Publication Date
Sun Dec 16 2018
Journal Name
Al-academy
The Symmetries of the Interior Design of Fast Food Restaurants
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The present research deals with the study of the symmetries of the design of interior spaces in fast food restaurants in terms of formality as it is an important element and plays a direct role in the spatial configuration, which is designed in both of its performance, aesthetic and expressive aspects. Since the choice of shapes is a complex subject that has many aspects imposed by functional and aesthetic correlations, the problem of the research is represented by the following question: (To what extent can the symmetries of the interior design be used in the spaces of fast food restaurants?)
The research acquires its importance by contributing to the addition of knowledge to researchers, scholars, companies and the specialized publ

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Publication Date
Fri Jan 10 2025
Journal Name
International Journal Of Scientific Research In Science, Engineering And Technology
Image Cryptography Based on Chebyshev Polynomials and Transposition- Substitution Transformations
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The confirming of security and confidentiality of multimedia data is a serious challenge through the growing dependence on digital communication. This paper offers a new image cryptography based on the Chebyshev chaos polynomials map, via employing the randomness characteristic of chaos concept to improve security. The suggested method includes block shuffling, dynamic offset chaos key production, inter-layer XOR, and block 90 degree rotations to disorder the correlations intrinsic in image. The method is aimed for efficiency and scalability, accomplishing  complexity order for n-pixels over specific cipher rounds. The experiment outcomes depict great resistant to cryptanalysis attacks, containing statistical, differential and brut

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Publication Date
Sun Apr 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fast Training Algorithms for Feed Forward Neural Networks
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 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Adaptive Canny Algorithm Using Fast Otsu Multithresholding Method
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   In this research, an adaptive Canny algorithm using fast Otsu multithresholding method is presented, in which fast Otsu multithresholding method is used to calculate the optimum maximum and minimum hysteresis values and used as automatic thresholding for the fourth stage of the Canny algorithm.      The new adaptive Canny algorithm and the standard Canny algorithm (manual hysteresis value) was tested on standard image (Lena) and satellite image. The results approved the validity and accuracy of the new algorithm to find the images edges for personal and satellite images as pre-step for image segmentation.  
 

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Publication Date
Fri Apr 01 2022
Journal Name
Symmetry
Fast Overlapping Block Processing Algorithm for Feature Extraction
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In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

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