A cluster can be defined as a collection of objects which are “homogeneous” between them and are “heterogeneous” to the objects belonging to other clusters. Clustering technique is mainly used to perform the energy-efficient data transmission that consumes the minimum energy and also prolongs the lifetime of the network. Recently, professional team sport organizations have invested their resources to analyze their own and opponents' performance. However, parents will commonly hear from members of staff more informally throughout the year with stories of their daughter’s success and if any concerns arise.

Windsurfing About Content Windsurfing as an adventurous sport and recreational pastime first peaked in 1980s only to fall. Since its appearance from more than a decade ago, Firefly Algorithm (FA), a stochastic meta- heuristic in nature inspired algorithms has shown significant performance in giving solutions to many optimization problems. High Energy lightweight court SPEED shoe with well ventilated toe box for advanced level of badminton players.To investigate the performance of the proposed hybrid algorithm, it is compared with four popular metaheuristic methods from literature using twelve standard datasets from the UCI Machine Learning Repository and the two moons dataset. Lots of excellent games played by everyone and a special congratulations to Isha for getting to the semi-final of the plate competition!

The minimum Redundancy Maximum Relevance (mRMR)-based feature selection method is also adopted to reduce feature dimensionality.Clustering is a popular unsupervised data analysis process which can be used to identify similar or dissimilar set of objects based on their characteristics. It presents an introduction to clustering and the performance of FA, briefly reviews and summarizes some of the recent firefly-based algorithms used for data clustering with the emphasis on how FA has been combined/ hybridized with other methods to contribute to the problem of data clustering. Clustering goes under unsupervised learning where no labels are given to the learning algorithm, leaving it on its own to find structure in its input. The proposed combined algorithm was tested on commonly used images from Harvard Whole Brain Atlas and the results were compared to other method from literature.