background: in recent years, there has been an increase in the amount and variety of data generated in the field of healthcare, (e.g., data related to the prevalence of contagious diseases in the society). various patterns of individuals’ relationships in the society make the analysis of the network a complex, highly important process in detecting and preventing the incidence of diseases. there...

We present a new cycle flow based method for finding fuzzy partitions of weighted directed networks coming from time series data. We show that this method overcomes essential problems of most existing clustering approaches, which tend to ignore important directional information by considering only one-step, one-directional node connections. Our method introduces a novel measure of communication...

Let graph energy is a graph--spectrum--based quantity‎, ‎introduced in the 1970s‎. ‎After a latent period of 20--30 years‎, ‎it became a popular topic of research both‎ ‎in mathematical chemistry and in ``pure'' spectral graph theory‎, ‎resulting in‎ ‎over 600 published papers‎. ‎Eventually‎, ‎scores of different graph energies have‎ ‎been conceived‎. ‎In this article we...

A good compiler which implements many optimizations during its compilation phases must be able to perform several static analysis techniques such as control flow or data flow analysis. Besides compilers, these techniques are common for static analyzers as well to retrieve information from source code, for example for code auditing, quality assurance or testing purposes. Implementing control flo...

Effective data imputation demands rich latent ``structure" discovery capabilities from ``plain" tabular data. Recent advances in graph neural networks-based solutions show their structure learning potentials by translating as bipartite graphs. However, due to a lack of relations between samples, they treat all samples equally which is against one important observation: ``similar sample should g...

Optimal transportation distances are valuable for comparing and analyzing probability distributions, but larger-scale computational techniques for the theoretically favorable quadratic case are limited to smooth domains or regularized approximations. Motivated by fluid flowbased transportation on Rn, however, this paper introduces an alternative definition of optimal transportation between dist...

Hierarchical Control Flow Graph Models deene a modeling paradigm for discrete event simulation modeling based upon hierarchical extensions to Control Flow Graph Models. Conceptually, models consist of a set of encapsulated, concurrently operating model components that interact solely via message passing. The primary objectives of Hierarchical Control Flow Graph Models are: (1) to facilitate mod...

Dynamic Parallel Schedules (DPS) is a flow graph based framework for developing parallel applications on clusters of workstations. The DPS flow graph execution model enables automatic pipelined parallel execution of applications. DPS supports graceful degradation of parallel applications in case of node failures. The fault-tolerance mechanism relies on a set of backup threads stored in the vola...