Application of materials informatics to vapor-grown carbon nanofiber/vinyl ester nanocomposites through self-organizing maps and clustering techniques

2019 ◽  
Vol 158 ◽  
pp. 98-109 ◽  
Author(s):  
O. Abuomar ◽  
S. Nouranian ◽  
R. King ◽  
T.E. Lacy
Keyword(s):  
Vinyl Ester ◽  
Carbon Nanofiber ◽  
Materials Informatics ◽  
Self Organizing Maps ◽  
Clustering Techniques ◽  
Vapor Grown Carbon Nanofiber ◽  
Self Organizing

Creep characterization of vapor-grown carbon nanofiber/vinyl ester nanocomposites using a response surface methodology

2015 ◽  
Vol 132 (26) ◽  
pp. n/a-n/a
Author(s):  
Daniel A. Drake ◽  
Rani W. Sullivan ◽  
Thomas E. Lacy ◽  
Charles U. Pittman ◽  
Hossein Toghiani ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Vinyl Ester ◽  
Carbon Nanofiber ◽  
Vapor Grown Carbon Nanofiber

Molecular dynamics simulations of oxidized vapor-grown carbon nanofiber surface interactions with vinyl ester resin monomers

Carbon ◽  
2012 ◽  
Vol 50 (3) ◽  
pp. 748-760 ◽  
Author(s):  
Changwoon Jang ◽  
Sasan Nouranian ◽  
Thomas E. Lacy ◽  
Steven R. Gwaltney ◽  
Hossein Toghiani ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Vinyl Ester ◽  
Carbon Nanofiber ◽  
Surface Interactions ◽  
Vinyl Ester Resin ◽  
Dynamics Simulations ◽  
Vapor Grown Carbon Nanofiber

Line Segment-Based Clustering Approach With Self-Organizing Maps

2021 ◽  
Vol 14 (4) ◽  
pp. 33-44
Author(s):  
G. Chamundeswari ◽  
G. P. S. Varma ◽  
C. Satyanarayana
Keyword(s):  
Neural Network ◽  
Line Segment ◽  
Feature Vector ◽  
Input Image ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Clustering Techniques ◽  
Hough Transformation ◽  
The Neural Network ◽  
Self Organizing

Clustering techniques are used widely in computer vision and pattern recognition. The clustering techniques are found to be efficient with the feature vector of the input image. So, the present paper uses an approach for evaluating the feature vector by using Hough transformation. With the Hough transformation, the present paper mapped the points to line segment. The line features are considered as the feature vector and are given to the neural network for performing clustering. The present paper uses self-organizing map (SOM) neural network for performing the clustering process. The proposed method is evaluated with various leaf images, and the evaluated performance measures show the efficiency of the proposed method.

COLLABORATIVE CLUSTERING USING PROTOTYPE-BASED TECHNIQUES

2012 ◽  
Vol 11 (03) ◽  
pp. 1250017 ◽  
Author(s):  
MOHAMAD GHASSANY ◽  
NISTOR GROZAVU ◽  
YOUNES BENNANI
Keyword(s):  
Original Data ◽  
Experimental Results ◽  
Self Organizing Maps ◽  
Clustering Techniques ◽  
Common Structure ◽  
Collaborative Clustering ◽  
Gradient Based ◽  
The Common ◽  
Self Organizing

The aim of collaborative clustering is to reveal the common structure of data distributed on different sites. In this paper, we present a formalism of topological collaborative clustering using prototype-based clustering techniques; in particular we formulate our approach using Kohonen's Self-Organizing Maps. Maps representing different sites could collaborate without recourse to the original data, preserving their privacy. We present two different approaches of collaborative clustering: horizontal and vertical. The strength of collaboration (confidence exchange) between each pair of datasets is determined by a parameter, we call coefficient of collaboration, to be estimated iteratively during the collaboration phase using a gradient-based optimization, for both the approaches. The proposed approaches have been validated on several datasets and experimental results have shown very promising performance.

Response surface predictions of the viscoelastic properties of vapor-grown carbon nanofiber/vinyl ester nanocomposites

2013 ◽  
Vol 130 (1) ◽  
pp. 234-247 ◽  
Author(s):  
Sasan Nouranian ◽  
Thomas E. Lacy ◽  
Hossein Toghiani ◽  
Charles U. Pittman ◽  
Janice L. DuBien
Keyword(s):  
Response Surface ◽  
Viscoelastic Properties ◽  
Vinyl Ester ◽  
Carbon Nanofiber ◽  
Vapor Grown Carbon Nanofiber
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