With the rapid growth of edge-assisted solutions in Internet of Things (IoT) networks,
connected healthcare progressively relies on such solutions. This refers to systems in which …

Many graph-based semi-supervised learning methods for large datasets have been
proposed to cope with the rapidly increasing size of data, such as Anchor Graph …

We briefly survey recent proposals that seek to capture in numerical terms the resilience and
the robustness of a graph. After a brief introduction and the establishment of notation and …

The variable sum exdeg index, initially introduced by Vukicevic (2011)[20] for predicting the
octanol water partition co-efficient of certain chemical compounds, is an invariant for a graph …

Graph robustness-the ability of a graph to preserve its connectivity after the loss of nodes
and edges-has been extensively studied to quantify how social, biological, physical, and …

Complex networks have become high-dimensional, sparse, and redundant due to the rapid
expansion of the Internet. Effective link prediction techniques are needed to obtain the most …

In this work we obtain new lower and upper optimal bounds for general (exponential)
indices of a graph. In the same direction, we show new inequalities involving some well …

The essence of social networks is that they can influence people's public opinions and
group behaviors form quickly. Negative group behavior influences societal stability …

Alzheimer's Disease (AD) is an incurable neurodegenerative disorder which mainly affects
older adults. An early diagnosis is essential because medical treatments can slow down the …

Graph-based semi-supervised learning methods have been used in a wide range of real-
world applications, eg, from social relationship mining to multimedia classification and …