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Evangelos Kranakis
Researcher at Carleton University
Publications - 515
Citations - 10789
Evangelos Kranakis is an academic researcher from Carleton University. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 46, co-authored 502 publications receiving 10330 citations. Previous affiliations of Evangelos Kranakis include Purdue University & Carleton College.
Papers
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Proceedings ArticleDOI
Learning to Communicate Underwater: An Exploration of Limited Mobility Agents
TL;DR: The adaptive control system suggested attempts to improve communication in underwater networks where environmental conditions are stochastic and time-variant and the algorithm presented is capable of adapting to the optimal performance depth in unimodal Stochastic stationary and non-stationary environments.
Proceedings ArticleDOI
Online routing in quasi-planar and quasi-polyhedral graphs
TL;DR: It is shown that the quasi-planar routing algorithm is inherently flexible in its path-finding, and as an application demonstrate computational results for a network load problem.
Book ChapterDOI
Geocaching-Inspired Navigation for Micro Aerial Vehicles with Fallible Place Recognition
TL;DR: This paper augments the navigation algorithm with a decisional framework resolving conflicts resulting from errors made by place recognition methods, and proposes four decisional algorithms to resolve conflicts among members of a swarm due to place recognition errors.
Book ChapterDOI
Partitions and homogeneous sets for admissible ordinals
Evangelos Kranakis,Iain Phillips +1 more
TL;DR: In this paper, the authors explore partition properties of admissible ordinals and give characterizations of partition properties which are satisfied by certain definable subsets of κ, which are used to investigate the strength of certain partition properties.
Journal ArticleDOI
Asymptotic Number of Hairpins of Saturated RNA Secondary Structures
TL;DR: The asymptotic expected number of hairpins in saturated structures is computed and a novel algorithm to compute the hairpin profile of a given RNA sequence is described, which is expected to provide more accurate structure prediction for particular RNAs, such as tRNAs and purine riboswitches, known to have a particular number ofhairpins.