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Stavros D. Nikolopoulos

Researcher at University of Ioannina

Publications -  159
Citations -  1512

Stavros D. Nikolopoulos is an academic researcher from University of Ioannina. The author has contributed to research in topics: Chordal graph & Indifference graph. The author has an hindex of 20, co-authored 148 publications receiving 1377 citations. Previous affiliations of Stavros D. Nikolopoulos include Pierre-and-Marie-Curie University & National and Kapodistrian University of Athens.

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Unfolding the procedure of characterizing recorded ultra low frequency, kHZ and MHz electromagetic anomalies prior to the L'Aquila earthquake as pre-seismic ones – Part 1

TL;DR: In this article, the authors proposed a procedure for the designation of detected EM anomalies as seismogenic ones, which can be used to quantify the time to global failure and the identification of distinguishing features beyond which the evolution towards global failure becomes irreversible.
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A graph-based model for malware detection and classification using system-call groups

TL;DR: A graph-based model that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families, measuring its detection rates and classification accuracy.
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Preseismic electromagnetic signals in terms of complexity

TL;DR: It is attempted to demonstrate that an easily computable complexity measure, such as T-complexity or approximate entropy, gives evidence of state changes leading to the point of global instability, and suggests an important principle: significant complexity decrease and accession of persistence in electromagnetic time series can be confirmed at the tail of the preseismic EM emission.
Proceedings ArticleDOI

Addressing network survivability issues by finding the K-best paths through a trellis graph

TL;DR: This paper aims to offer a solution in the selection of the K-best disjoint paths through a network by using graph theoretic techniques to map an arbitrary network graph into a trellis graph which allows the application of computationally efficient methods to find disjointed paths.