Fraud detection in credit cards is one of the best test beds in computational intelligence algorithms. As fraudsters are increasing day by day and fallacious transactions are done credit cards, the safeguarding of credit card is an important application for prediction techniques. Fraud detection problem that realistically describes the operating conditions of fraud detection system (FDSs) that everyday analyze massive stream of credit card transaction. Several learning algorithm have been proposed for fraud detection, which are based on certain assumptions that hardly hold in real world Fraud detection system

The object moving at high speeds encounter forces which tend to decelerate the objects. This resistance in the medium is termed as drag which is one of the major concerns while designing high speed aircrafts. Another key factor which influences the design is the air drag. The main challenges faced by aerospace industries is to design the shape of nose cone of flying object that travels at high speeds with optimum values of air drag. This study deals with computational analysis on elliptical nose cone profiles of a commercial aircraft.

For the last few decades, hospitals have taken the hospital-acquired pollutions seriously. Several hospitals have established infection tracking and surveillance structures in place, along with robust avoidance strategies to decrease the rate of hospital-acquired infections. The impact of hospital-acquired infections is seen not just at an individual patient level, but also at the community level as they have been linked to multidrug-resistant pollutions. Recognizing patients with risk elements for hospital-acquired infections and multidrug-resistant contaminations is very important in the prevention with minimization of these infections.