There has been considerable effort in the last decade to increase the participation of women
in engineering through various policies. However, there has been little empirical research …

Exploratory data analysis (EDA) using data clustering is extremely important for
understanding the basic characteristics of a novel data set before developing complex …

Layout algorithms provide an intuitive way of visualizing and understanding complex
networks. Complex networks such as social networks, coauthorship networks, and protein …

Policymakers and scholars are increasingly concerned with how nanotechnology can
reduce inequalities and provide benefits for disadvantaged and poor communities. This …

Graph datasets are gaining popularity in various applications. Analyzing graph data using
data clustering could help reveal underlying patterns and understand them better. However …

Analyzing multiplex small world networks (SWNs) using community detection (CD) is a
challenging task. We propose the use of visual analytics to probe and extract communities in …

VAT family of algorithms). Various members of the VAT family have been applied to many
applications, including image segmentation, urban mobility, transportation, speech …

While there are several visualizations of the small world networks (SWN), how does one find
an appropriate set of visualizations and data analytic processes in a data science workflow …

Nanotechnology has been hailed as a disruptive technology that would revolutionize
existing products and processes, open up new markets and business opportunities, as well …

Multivariate data has been routinely used in the form of feature vectors for
identifying/determining, assessing, and analyzing child malnutrition. Using machine learning …