Some topological properties on C-α-Normality and C-β-Normality

A topological space (Y,τ) is called C-α-normal (C-β-normal) if there exist a bijective function g from Y onto α-normal (β-normal) space Z such that the restriction map g|B from B onto g(B) is a homeomorphism for any compact subspace B of Y. We discuss some relationships between C-α-normal (C-β-normal) and other properties

stochastic NLSEs, soliton waves, explosive, envelope, solver technique, fiber communications

In this paper, the concepts of $(\ell, \jmath)$-symmetrical functions and the concept of $q$-calculus are combined to define a new subclasses defined in the open unit disk. In particular. We look into a convolution property, and we'll use the results to look into our task even more, we deduce the sufficient condition, coefficient estimates investigate related neighborhood results for the class $\mathcal{S}^{\ell, \jmath}_q(\lambda)$ and some interesting convolution results are also pointed out

Convolution Properties of <i>q</i>-Janowski-Type Functions Associated with (<i>x</i>,<i>y</i>)-Symmetrical Functions

The purpose of this paper is to define new classes of analytic functions by amalgamating the concepts of q-calculus, Janowski type functions and (x,y)-symmetrical functions. We use the technique of convolution and quantum calculus to investigate the convolution conditions which will be used as a supporting result for further investigation in our work, we deduce the sufficient conditions, Po´lya-Schoenberg theorem and the application. Finally motivated by definition of the neighborhood, we give analogous definition of neighborhood for the classes S˜qx,y(α,β) and K˜qx,y(α,β), and then investigate the related neighborhood results, which are also pointed out

Topological Modeling for Symptom Reduction of Corona virus

World Health Organization announced Coronavirus as a globalepidemic virus, and the search for approximating uncertain concepts andmeasuring the accuracy of the approximation is an important goal for researchersin many theoretical and applied fields. Therefore this paper suggesteda specific mathematical approach with the support of the confidenceand strength of an association to determine the most important attribute.Our approach is based on removing redundant attributes to produce thesuccessfully reduced set and formulate the core set of attributes. Additionally,we give new insight into the attribute reduction application andin order to get the result, we use MATLAB programming. We want youto know that this research paper lasted more than two months, in order toconfirm the results reached

SutteARIMA: A Novel Method for Forecasting the Infant Mortality Rate in Indonesia

This study focuses on the novel forecasting method (SutteARIMA) and its application in predicting Infant Mortality Rate data in Indonesia. It undertakes a comparison of the most popular and widely used four forecasting methods: ARIMA, Neural Networks Time Series (NNAR), Holt-Winters, and SutteARIMA. The data used were obtained from the website of the World Bank. The data consisted of the annual infant mortality rate (per 1000 live births) from 1991 to 2019. To determine a suitable and best method for predicting Infant Mortality rate, the forecasting results of these four methods were compared based on the mean absolute percentage error (MAPE) and mean squared error (MSE). The results of the study showed that the accuracy level of SutteARIMA method (MAPE: 0.83% and MSE: 0.046) in predicting Infant Mortality rate in Indonesia was smaller than the other three forecasting methods, specifically the ARIMA (0.2.2) with a MAPE of 1.21% and a MSE of 0.146; the NNAR with a MAPE of 7.95% and a MSE of 3.90; and the Holt-Winters with a MAPE of 1.03% and a MSE: of 0.083