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Chakguy Prakasvudhisarn, Ph.D.

Affiliations: 
2002 University of Oklahoma, Norman, OK, United States 
Area:
Industrial Engineering
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"Chakguy Prakasvudhisarn"
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Shivakumar Raman grad student 2002 University of Oklahoma
 (Dimensional measurement of conical features using coordinate metrology.)

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Publications

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Schoch M, Prakasvudhisarn C, Praditsmanont A. (2011) Volume Optimization (BVO) Using a Constraint Programming Approach for Life-Cycle Cost Based Sustainable Design International Journal of Sustainable Building Technology and Urban Development. 2: 307-317
Schoch M, Prakasvudhisarn C, Praditsmanont A. (2011) Building-volume designs with optimal life-cycle costs International Journal of Architectural Computing. 9: 55-76
Prakasvudhisarn C, Wolschann P, Lawtrakul L. (2009) Predicting complexation thermodynamic parameters of β-cyclodextrin with chiral guests by using swarm intelligence and support vector machines. International Journal of Molecular Sciences. 10: 2107-21
Prakasvudhisarn C, Kunnapapdeelert S, Yenradee P. (2009) Optimal cutting condition determination for desired surface roughness in end milling International Journal of Advanced Manufacturing Technology. 41: 440-451
Prakasvudhisarn C, Lawtrakul L. (2008) Feature set selection in QSAR of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio) thymine (HEPT) analogues by using swarm intelligence Monatshefte Fur Chemie. 139: 197-211
Lawtrakul L, Prakasvudhisarn C. (2005) Correlation studies of HEPT derivatives using swarm intelligence and support vector machines Monatshefte Fur Chemie. 136: 1681-1691
Prakasvudhisarn C, Raman S. (2004) Framework for cone feature measurement using coordinate measuring machines Journal of Manufacturing Science and Engineering, Transactions of the Asme. 126: 169-177
Prakasvudhisarn C, Trafalis TB, Raman S. (2003) Support vector regression for determination of minimum zone Journal of Manufacturing Science and Engineering, Transactions of the Asme. 125: 736-739
Prakasvudhisarn C, Trafalis TB, Raman S. (2002) Determination of the minimum enclosing zone for straightness and flatness using support vector regression Intelligent Engineering Systems Through Artificial Neural Networks. 12: 937-944
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