Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important rol

Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important role in d

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 imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify 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 specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

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

     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c