Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th

A study is made about the size and dynamic activity of sunspot using automatically detecting Matlab code ''mySS .m'' written for this purpose which mainly finds a good estimate about Sunspot diameter (in km). Theory of  the Sunspot size has been described using  equations, where the growth and decay phases and the area of Sunspot could be calculated. Two types of images, namely H-alpha and HMI magnetograms, have been implemented. The results are divided into four main parts. The first part is sunspot size automatic detection by the Matlab program. The second part is numerical calculations of Sunspot growth and decay phases. The third part is the calculation of  Sunspot area. The final part is to explain the Sunspot activit

The objective of the study to develop an amorphous solid dispersion for poorly soluble raltegravir by hot melt extrusion (HME) technique. A novel solubility improving agent plasdone  s630 was utilized. The HME raltegravir was formulated into tablet by direct compression method. The prepared tablets were assessed for all pre and post-compression parameters. The drug- excipients interaction was examined by FTIR and DSC. All formulas displayed complying with pharmacopoeial measures. The study reveals that formula prepared by utilizing drug and plasdone S630 at 1:1.5 proportion and span 20 at concentration about 30mg (trail-6) has given highest dissolution rate than contrasted with various formulas of raltegravir.

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        People are comfortable with e-banking services, but they are exposed to a great deal of danger these days due to fraudulent acts such as password hacking and personal information theft. Everything individuals do online relies heavily on passwords. Using a password protects one's identity online, in forums, and through email. Online transactions are vulnerable to identity theft if they do not have a secure password. Internet users with critical statements are vulnerable to various assaults, including the theft and exploitation of user IDs and passwords. This paper introduces novel password encryption by fingerprint and a random number to make each password unique and robust against attacks, with a magnificent time elapsed o

Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia