A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data.
One of the crystalline materials structures is cubic. An experimental study has been done about developing a scheme to identify the cubic structure types in single or multi component materials. This scheme is using fingerprints created from the calculation of quadratic Miller indices ratios and mat...
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| Format: | Article |
| Language: | en |
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Dr. Sang H. Lee
2007
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| Online Access: | http://eprints.usm.my/9385/1/A_Neural_Network-Based_Application_to_Indentify_Cubic_Structures_in_Multi_Component_Crystalline_Materials_Using_X-Ray_Diffraction_Data.pdf http://eprints.usm.my/9385/ http://ijcsns.org/index.htm |
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| _version_ | 1834437020792913920 |
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| author | Syukur, Mohammad Pasha, Muhammad Fermi Budiarto, Rahmat |
| author_facet | Syukur, Mohammad Pasha, Muhammad Fermi Budiarto, Rahmat |
| author_sort | Syukur, Mohammad |
| building | Hamzah Sendut Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Malaysia |
| content_source | USM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | One of the crystalline materials structures is cubic. An
experimental study has been done about developing a scheme to identify the cubic structure types in single or multi component materials. This scheme is using fingerprints created from the calculation of quadratic Miller indices ratios and matches it with the ratio of the sin20 values from the diffracted data of material obtained by X-Ray Diffraction (XRD) method. These manual matching processes are complicated and sometimes are tedious because the diffracted data are complex and may have more than
one fingerprint inside. This paper proposes an application of multi-layered back-propagation neural network in matching the fingerprints with the diffracted data of crystalline material to quickly and correctly identify its cubic structure component types.
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| format | Article |
| id | my.usm.eprints.9385 |
| institution | Universiti Sains Malaysia |
| language | en |
| publishDate | 2007 |
| publisher | Dr. Sang H. Lee |
| record_format | eprints |
| spelling | my.usm.eprints.9385 http://eprints.usm.my/9385/ A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. Syukur, Mohammad Pasha, Muhammad Fermi Budiarto, Rahmat QA75.5-76.95 Electronic computers. Computer science One of the crystalline materials structures is cubic. An experimental study has been done about developing a scheme to identify the cubic structure types in single or multi component materials. This scheme is using fingerprints created from the calculation of quadratic Miller indices ratios and matches it with the ratio of the sin20 values from the diffracted data of material obtained by X-Ray Diffraction (XRD) method. These manual matching processes are complicated and sometimes are tedious because the diffracted data are complex and may have more than one fingerprint inside. This paper proposes an application of multi-layered back-propagation neural network in matching the fingerprints with the diffracted data of crystalline material to quickly and correctly identify its cubic structure component types. Dr. Sang H. Lee 2007-02 Article PeerReviewed application/pdf en http://eprints.usm.my/9385/1/A_Neural_Network-Based_Application_to_Indentify_Cubic_Structures_in_Multi_Component_Crystalline_Materials_Using_X-Ray_Diffraction_Data.pdf Syukur, Mohammad and Pasha, Muhammad Fermi and Budiarto, Rahmat (2007) A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. International Journal Of Computer Science And Network Security, 7 (2). pp. 49-54. ISSN 1738-7906 http://ijcsns.org/index.htm |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Syukur, Mohammad Pasha, Muhammad Fermi Budiarto, Rahmat A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title | A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title_full | A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title_fullStr | A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title_full_unstemmed | A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title_short | A Neural Network-Based Application to Identify Cubic Structures in Multi Component Crystalline Materials Using X-Ray Diffraction Data. |
| title_sort | neural network-based application to identify cubic structures in multi component crystalline materials using x-ray diffraction data. |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/9385/1/A_Neural_Network-Based_Application_to_Indentify_Cubic_Structures_in_Multi_Component_Crystalline_Materials_Using_X-Ray_Diffraction_Data.pdf http://eprints.usm.my/9385/ http://ijcsns.org/index.htm |
| url_provider | http://eprints.usm.my/ |