ayaz isazadeh

Reduction is a concept first introduced by Descartes in explaining his view of the rationalization of philosophy through mathematics. He seeks to consider length, breadth, and depth for phenomena so that reducing the phenomenon to his own analytical geometric apparatus; thus shrinking the whole world into a small machine. In the present study, the authors took into account the deficiency in defining the reduction of phenomena to a mathematically sound system as the reason for a large group of problems and therefore they came to redefine the Cartesian reductionism of phenomena by removing the search space through a learning system. In due definition, it is possible to reduce the NP problems to P space without using a quantum algorithm that requires a quantum computer to exist. The present study points out that the problems arising from the mathematical modeling of the Covid-19 pandemic are due to a deficiency in the definition of Cartesian reduction, which leads to an increase in the computational complexity of its diagnosis and treatment using computational tools.

There are several ways for bandwidth allocation for users acting based on policy of network administrators in computer networks. Due to the diversity of users and so amount of bandwidth usage per user, providing suitable bandwidth rate to meet their needs in various situations play an important role in terms of performance and implementation of bandwidth management systems. In this paper, we propose a dynamic and balanced approach, called normal weight allocation for determining amount of bandwidth for each user taking into account the importance of user in caomparision with other online concurrent users. In this regard, to obtain a user weight as the importance of user, we apply Fuzzy AHP technique for eliciting indecisive expert ideas. Ease of implementation and taking the advantage of maximal usage of available bandwidth are the features of the proposed approach.