Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...

Data mining is a method that is used to select the information from large datasets and it performs the principal task of data analysis. The Clustering is a technique that consist groups of data and elements into disjoined clusters of data. The same cluster data are related to similar cluster and different cluster data belong to different cluster. Clustering can be done different methods like pa...

The analysis of changes in water quality in a monitoring network system is important because the sources of pollution vary in time and space. This study utilized analysis of the water quality index calculation, hierarchical cluster analysis, and mapping. This was achieved by assessing the water quality parameters of the samples collected from Galma River in Zaria, Northwestern Nigeria in wet an...

A protein network shows physical interactions as well as functional associations. An important usage of such networks is to discover unknown members of partially known complexes and pathways. A number of methods exist for such analyses, and they can be divided into two main categories based on their treatment of highly connected proteins. In this paper, we show that methods that are not affecte...

Energy constraint is the biggest challenge in wireless sensor networks because the power supply of each sensor node is a battery that is not rechargeable or replaceable due to the applications of these networks. One of the successful methods for saving energy in these networks is clustering. It has caused that cluster-based routing algorithms are successful routing algorithm for these networks....