NDLI: An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity

Content Provider	IEEE Xplore Digital Library
Author	Biswas, A. Thompson, D. Wenbin He Qi Deng Chun-Ming Chen Han-Wei Shenk Machiraju, R. Rangarajan, A.
Copyright Year	2015
Description	Author affiliation: Mississippi State Univ., Starkville, MS, USA (Thompson, D.) \|\| Ohio State Univ., Columbus, OH, USA (Biswas, A.; Wenbin He; Chun-Ming Chen; Han-Wei Shenk; Machiraju, R.) \|\| Univ. of Florida, Gainesville, FL, USA (Qi Deng; Rangarajan, A.)
Abstract	Although vortex analysis and detection have been extensively investigated in the past, none of the existing techniques are able to provide fully robust and reliable identification results. Local vortex detection methods are popular as they are efficient and easy to implement, and produce binary outputs based on a user-specified, hard threshold. However, vortices are global features, which present challenges for local detectors. On the other hand, global detectors are computationally intensive and require considerable user input. In this work, we propose a consensus-based uncertainty model and introduce spatial proximity to enhance vortex detection results obtained using point-based methods. We use four existing local vortex detectors and convert their outputs into fuzzy possibility values using a sigmoid-based soft-thresholding approach. We apply a majority voting scheme that enables us to identify candidate vortex regions with a higher degree of confidence. Then, we introduce spatial proximity- based analysis to discern the final vortical regions. Thus, by using spatial proximity coupled with fuzzy inputs, we propose a novel uncertainty analysis approach for vortex detection. We use expert's input to better estimate the system parameters and results from two real-world data sets demonstrate the efficacy of our method.
Starting Page	223
Ending Page	230
File Size	1399882
Page Count	8
File Format	PDF
ISBN	9781467368797
DOI	10.1109/PACIFICVIS.2015.7156381
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Tensile stress Data visualization Detectors Entropy Robustness Electronic mail
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Unified uncertainty analysis using the maximum entropy approach and simulation

Visualization of uncertainty and analysis of geographical data

Robustness analysis of consensus for multi-agents with leader-follower topology

Distance measure in vortex visualization

Uncertainty in spatial data mining

A maximum likelihood approach to texture classification using wavelet transform

Experiences in Image-Based 3D Reconstruction of Underwater Environments

H∞ group consensus for clusters of agents with model uncertainty and external disturbance

Cross-entropy approach to data visualization based on the neural gas network

An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity

Similar Documents

Unified uncertainty analysis using the maximum entropy approach and simulation

Visualization of uncertainty and analysis of geographical data

Robustness analysis of consensus for multi-agents with leader-follower topology

Distance measure in vortex visualization

Uncertainty in spatial data mining

A maximum likelihood approach to texture classification using wavelet transform

Experiences in Image-Based 3D Reconstruction of Underwater Environments

H∞ group consensus for clusters of agents with model uncertainty and external disturbance

Cross-entropy approach to data visualization based on the neural gas network

An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity