A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm competes favorably with SWT, and SLT based algorithms, and obtain up to 1.23 dB PSNR improvement.
The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:
There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group
... Show MoreThe aim of this research is to construct a cognitive behavior program based on the theory of Meichenbaum in reducing the emotional sensitivity among Intermediate school students. To achieve the aims of the research, two hypotheses were formulated and the experimental design with equal groups was chosen. The population of research and its sample are determined. The test of negative emotional sensitivity, which is constructed by the researcher, was adopted. The test contains (20) items proved validity and reliability as a reliable test by presenting it to a group of arbitrators and experts in education and psychology. An educational program is constructed based on the theory of Meichenbaum. The test was applied to a sample of (60) second i
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
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A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for clus
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Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit
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Community structures are fundamental in understanding the structure and functionality of complex networks. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of community detection. Recently, multi-objective evolutionary algorithms (MOEAs) have attracted many researchers to identify communities in static networks. Many algorithms have been proposed to find a solution that achieves a trade-off between exploring new areas of the solution space and improving the quality of existing solutions. In this trade-off is crucial; whereas exploitation improves existing solutions, it may fail to find better solutions from insufficiently explored regions o
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