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Michael Turner

dblp:145/1691 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
mesh generation
0.312018
Curvilinear mesh generation using a variational framework · Comput. Aided Des. 2018
Parallel and multicore computing
parallel computing
0.112018
Curvilinear mesh generation using a variational framework · Comput. Aided Des. 2018
Parallel and multicore computing › parallel computing › parallel scientific computing
parallel mesh generation
0.112018
Curvilinear mesh generation using a variational framework · Comput. Aided Des. 2018
YearPublicationVenuePosition
2018 Statistical Modeling of Temperature Trajectories to Assess Risk of Postoperative Complications
Rema Padman, Jennifer Grant, Urmila Ravichandran, Michael Turner, Prashanth Raja, Yazhini Mathiyalagan, Ronak Parikh, Ari Robicsek, Nirav Shah 0004
AMIA4
2018 Curvilinear mesh generation using a variational framework
abstract
We aim to tackle the challenge of generating unstructured high-order meshes of complex three-dimensional bodies, which remains a significant bottleneck in the wider adoption of high-order methods. In particular we show that by adopting a variational approach to the generation process, many of the current popular high-order generation methods can be encompassed under a single unifying framework. This allows us to compare the effectiveness of these methods and to assess the quality of the meshes they produce in a systematic fashion. We present a detailed overview of the theory and formulation of the variational framework, and we highlight how such formulation can be effectively exploited to yield a highly-efficient parallel implementation. The effectiveness of this approach is examined by considering a number of two- and three-dimensional examples, where we show how the proposed approach can be used for both mesh quality optimisation and untangling of invalid high-order meshes.
Michael Turner, Joaquim Peiró, David Moxey
Comput. Aided Des.1
2014 Context-Aware Multifactor Authentication Based on Dynamic Pin
Yair Diaz-Tellez, Eliane L. Bodanese, Theodosis Dimitrakos, Michael Turner
SEC4