Vertical Clustering of 3D Elliptical Helical Data
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © - December Issue 2013 by IJCTT Journal | ||
| Volume-6 Issue-2 | ||
| Year of Publication : 2013 | ||
| Authors :Wasantha Samarathunga , Masatoshi Seki , Hidenobu Saito , Ken Ichiryu , Yasuhiro Ohyama |
Wasantha Samarathunga , Masatoshi Seki , Hidenobu Saito , Ken Ichiryu , Yasuhiro Ohyama"Vertical Clustering of 3D Elliptical Helical Data"International Journal of Computer Trends and Technology (IJCTT),V6(2):95-98 December Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- -This research proposes an effective vertical clustering strategy of 3D data in an elliptical helical shape based on 2D geometry. The clustering object is an elliptical cross-sectioned metal pipe which is been bended in to an elliptical helical shape which is used in wearable muscle support designing for welfare industry. The aim of this proposed method is to maximize the vertical clustering (vertical partitioning) ability of surface data in order to run the product evaluation process addressed in research [2]. The experiment results prove that the proposed method outperforms the existing threshold no of clusters that preserves the vertical shape than applying the conventional 3D data. This research also proposes a new product testing strategy that provides the flexibility in computer aided testing by not restricting the sequence depending measurements which apply weight on measuring process. The clustering algorithms used for the experiments in this research are self-organizing map (SOM) and K-medoids.
References:-
[1] Wasantha Samarathunga, Masatoshi Seki, Hidenobu Saito, Ken Ichiryu, Yasuhiro Ohyama, “A Discreate Computation Approach for Helical Pipe Bending in Wearable Muscle Supports Designing”, International Conference on Information and Communication Technology for Education, Dec. 1-2, 2013,Singapore, Accepted.
[2] Wasantha Samarathunga, Masatoshi Seki, Hidenobu Saito, Ken Ichiryu, Yasuhiro Ohyama, “Product Evaluation in Elliptical Helical Pipe Bending”, International Journal of Computer Trends and Technology (IJCTT), ISSN 2231-2803, vol. 4, Issue 10-Oct 2013, pp.3701-3705.
[3] Kaufman, L. and Rousseeuw, P.J. (1987), clustering by means of Medoids, in Statistical Data Analysis Based on the L1-Norm and Related Methods, edited by Y. Dodge, North-Holland, pp.405-416.
[4] Wasantha Samarathunga, “Computational Models of Emotion using graphical parameters of pictures, An Emotion Estimation Modeling Approach”, LAP LAMBERT Academic Publishing, ISBN 978-3-659- 35796-1, Chapter 2, pp. 33-66.
Keywords:-3D Vertical Clustering, SOM, K-medoids, Computer Aided Testing, Elliptical Helical Bending