The efficiency with which an integer may be factored into its prime factors determines several public key cryptosystems’ security in use today. Although there is a quantum-based technique with a polynomial time for integer factoring, on a traditional computer, there is no polynomial time algorithm. We investigate how to enhance the wheel factoring technique in this paper. Current wheel factorization algorithms rely on a very restricted set of prime integers as a base. In this study, we intend to adapt this notion to rely on a greater number of prime integers, resulting in a considerable improvement in the execution time. The experiments on composite numbers n reveal that the proposed algorithm improves on the existing wheel factoring algorithm by about 75%.
Employing the inverse power transformation technique, we have proposed a new continuous three-parameter probability distribution and named it inverse power generalized Maxwell distribution. This distribution is the generalized version of the generalized Maxwell distribution. For this model, we have derived some functions related to survival analysis. Several statistical properties of the model are provided. This study also focused on the estimation of the unknown model parameters. Six different parameter estimation methods are employed and studied extensively through numerical simulation. To investigate the applications of the suggested model, two real engineering data sets are considered and empirically found that the suggested model can provide a superior fit as compared to some candidate models under study.\\ \\ \textbf{Keywords:} Generalize Maxwell distribution, Moments, Estimation, Inverse power, Entropy.
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