In hierarchical clustering, the most important factor is the selection of the linkage method
which is the decision of how the distances between clusters will be calculated. It extremely …

Currently, we are witnessing a growing trend in the study and application of problems in the
framework of Big Data. This is mainly due to the great advantages which come from the …

Parallel processing has turned into one of the emerging fields of machine learning due to
providing consistent work by performing several tasks simultaneously, enhancing reliability …

Since the complexity of large-scale and scientific computation, workflow has been used for
task decomposition in cloud computing. A dynamic resource allocation algorithm based on …

Quite often, complex systems or phenomena are observed from various points of view
yielding the particular subsets of data usually being composed of locally available attributes …

Two of the most popular approaches for dealing with big data are distributed computing and
stream mining. In this paper, we incorporate both approaches in order to bring a competitive …

When it is impractical to rigorously assess all parts of complex systems, test engineers use
defect detectors to focus their limited resources. We define some properties of an ideal …

Using images in case investigation may doubt that the image are forged or not. Image
forensics is an approach for image validity. In this paper, we propose a new method for …

Wireless sensor networks (WSNs) are ubiquitous nowadays and have applications in variety
of domains such as machine surveillance, precision agriculture, intelligent buildings …

Increase in data volume and need for analytics has led towards innovation of big data. To
speed up the query responses models like NoSQL has emerged. Virtualized platforms using …