Relational Database for its huge success in data management has been used here as a scalable repository for storing webservices in UDDI framework.The operator 'join' has been used to derive service composition by matching inputs of a service to outputs of another.Adopting three modes of composability for a desired service, the possibility of having different kinds of compositions is demonstrated in form of a Composition Search Tree.

No abstract

No abstract

Diabetes is a chronic condition that strike how your body burns food for energy. Much of the food you consume is converted by your body into sugar (glucose), which is then released into your bloodstream. Your pancreas releases insulin when your blood sugar levels rise. Over the years, several scholars have sought to create reliable diabetes prediction models. Due to a lack of adequate data sets and prediction techniques, this discipline still faces many unsolved research issues, which forces researchers to apply big data analytics and ML-based methodology. Four distinct machine learning algorithms are used in the study to analyze healthcare prediction analytics and solve the issues. In this investigation, the Pima and Early detection datasets were employed. We applied the Decision Tree, MLP, Naive Bayes, and Random Forest algorithms to these datasets and evaluated the accuracy and F-Measure. The goal of this research is to develop a system that could more precisely predict a patient's risk of developing diabetes.

No abstract