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Credit Risk Analysis is a process adapted by loan associations to evaluate the risk -based pricing for sanctioning loans. The chances of approving loans depend on the customer's credit score, which includes annual income, banking history, loan, insurance and different elements of risks such as default risk, credit correlation risk, collateral risk, credit concentration risk, rating migration risk and recovery risk. Results of the calculation allow lenders and customers to assess credit profile characteristics. Data Science allows discovering of new patterns within a complex data set which can be an efficient method to compute risk percentage by means of non – hierarchical clustering. K-means is an iterative algorithm - the idea is to use small unstructured groups of data of fixed size, assigned to clusters to be stored in the memory depending on the previous locations of the cluster centroids. It is validated that the suggested technique predicts better accuracy, is a faster and targeted approach than existing methods. [ABSTRACT FROM AUTHOR]

In the present situation COVID-19 global pandemic, an overall world got embrace with covid-19 virus. Moreover every country went under quarantine and firm mitigation measures by temporary shutdown in people crowded place like schools, restaurants, theatres and domestic and international transport facilities[1]. So government made these measures to be effective to support and compliance of public[2]. Advanced medical technology put up with new vaccines to control infection of virus. Vaccination is one of the most effective step to control the virus from affecting the entire population. This paper aims to explore the optimal effectiveness of Vaccination for novel COVID-19 non clinical approach. We need smart solutions and decisions to mitigate the coronavirus's impact. We formulate the mathematical model to Analyse the vaccination effectiveness[3]. The objective function is designed to reduce both awareness of vaccination and effectiveness of vaccination using WHO data/ Indian dashboard data[4]. The degree of protection As a part we can analyse the risk factors of immunization using multivariate models using statistical analysis. [ABSTRACT FROM AUTHOR]

The core goal of the article is to inspect the effect of thermally radiative heat transmission and heat source on peristalsis of a couplestress liquid in the asymmetric microfluidics conduit. The normalized 2D flow governing equations for momentum and energy are balanced using non dimensional quantities and simplify using the approximation wavelength is so long compared with Reynolds number is too small. All the solutions like velocity flow and temperature profile are illustrated with MATLAB software under the effects of important parameters like Hartmann number, Darcy number, Prandtl number, heat source/sink parameter and thermal radiation parameter. It is observed that increasing in Prandtl (Pr) number and Eckert (E) number will lead to increase in temperature distribution. These types of observations may be applicable to develop EMHD for drug delivery system and blood transport in micro vessels. [ABSTRACT FROM AUTHOR]

The movement of a Williamson fluid is studied in a micro asymmetric walls and it is initiated by the movement of peristalsis waves with the constant speed, however with distinct amplitudes and phase on the stretchy walls under LWL wavelength and LRN assumption. The perturbation method in the power of We is constructed to get explicit forms for velocity, pressure rise, frictional forces and shear stress. The properties of several developing parameters on the fluid motion are presented graphically. In addition, the streamlines prototype is designed and it is examined that trapping happens near the walls and the magnitude of the trapped bolus varies with changing inserted flow parameters. [ABSTRACT FROM AUTHOR]