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The Determination of Critical-Sampling Scheme of Preprocessing for Multiwavelets Decomposition as 1st and 2nd Orders of Approximations.
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One of the important differences between multiwavelets and scalar wavelets is that each channel in the filter bank has a vector-valued input and a vector-valued output. A scalar-valued input signal must somehow be converted into a suitable vector-valued signal. This conversion is called preprocessing. Preprocessing is a mapping process which is done by a prefilter. A postfilter just does the opposite.

The most obvious way to get two input rows from a given signal is to repeat the signal. Two rows go into the multifilter bank. This procedure is called “Repeated Row” which introduces oversampling of the data by a factor of 2.

 For data compression, where one is trying to find compact transform representations for a dataset, it is imperative to find critically sampled multiwavelet transforms schemes which this paper focuses on finding a simple and easy to follow algorithm for its computation.

One famous multiwavelet filter used here is the GHM filter proposed by Geronimo, Hardian, and Massopust. The GHM basis offers a combination of orthogonality, symmetry, and compact support, which can not be achieved by any scalar wavelet basis. Using a computer program for the proposed method, an example test on Lena image is verified which shows image properties after a single level decomposition and the reconstructed image after reconstruction.

 

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
Callus Induction and Shoot Formation for Mexican Red Bean (Phaseolus vulgaris L.) Pinto Cultivar in Vitro
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The current study aimed to adopt a method for inducing callus cells and regenerating the important common red bean using different types of growth regulators such as N6-benzylaminopurine (BAP), Naphthalene acetic acid (NAA), and Thidiazuron (TDZ). Different types of common bean pinto cultivar explants, such as internodes, cotyledons and roots, were inoculated on Murashige and Skoog medium (MS) provided with different combinations of plant growth regulators, including 1- BAP (5 mg/l) 2-BAP (4.5 mg/l) NAA (0.5 mg/l), 3- BAP (4.5 mg/l), and TDZ (0.1mg/l). Callus was initiated on MS culture medium supplied with 5 mg/l BAP for all explants (internodes, cotyledons, and roots) at 50, 20, and 10% respectively, while adding NAA with 0.5mg/l showed

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Publication Date
Tue Sep 01 2015
Journal Name
2015 7th Computer Science And Electronic Engineering Conference (ceec)
An experimental investigation on PCA based on cosine similarity and correlation for text feature dimensionality reduction
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Publication Date
Fri Jan 05 2018
Journal Name
International Journal Of Science And Research (ijsr)
Image Steganography Based on Discrete Wavelet Transform and Chaotic Map, IJSR, Call for Papers, Online Journal
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'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal

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Publication Date
Sun Sep 01 2019
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving Convective Straight and Radial Fins with Temperature-Dependent Thermal Conductivity Problems
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In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Wed Apr 01 2020
Journal Name
Medico-legal Update
Knowledge and protective health behaviors concerning risk factors for coronary heart disease among baghdad university students
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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Wed May 10 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Block-based Image Steganography for Text Hiding Using YUV Color Model and Secret Key Cryptography Methods
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Publication Date
Thu Oct 01 2020
Journal Name
Upstream Oil And Gas Technology
Integrated approach for non-Darcy flow in hydraulic fractures considering different fracture geometries and reservoir characteristics
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