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    Data Fusion Strategy for Multiscale Surface Measurements

    Source: Journal of Micro and Nano-Manufacturing:;2013:;volume( 001 ):;issue: 001::page 11004
    Author:
    Ramasamy, Suresh K.
    ,
    Raja, Jayaraman
    ,
    Boudreau, Brian D.
    DOI: 10.1115/1.4023755
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Interdisciplinary research efforts have started focusing on the development of multiscale models and development of designer multiscale surfaces exhibiting specific properties at different scales for a specific purpose. With the rapid evolution of these new engineered surfaces for microelectromechanical systems (MEMS), microfluidics, etc., there is a strong need for developing tools to measure and characterize these surfaces at different scales. In order to obtain all meaningful details of the surface at various required scales, one is left with the only option of measuring the surface using multiple technologies using a combination of instruments. The majority of hardwarebased approaches focus on the development of systems housing multiple technologies/capabilities into a single frame. These systems enable the user to obtain different surface maps using various technologies, but the user does not readily have the ability to combine all the obtained data into one single dataset. The effective approach toward multiscale measurement and characterization would be to use the individual measurement tools and finding a method to relate the individual coordinate systems and use an offline virtual tool to unify, manipulate, segment, merge, and retrieve data. Shape primitives and focusbased fusion strategies cannot be used as every data point in the data sets under consideration has to be treated as essentially at optimal focus. A multiscale data fusion strategy results in edge effects on nonplanar and high aspect ratio surfaces. An optimized fusion strategy, the “FWR method,â€‌ for the surface metrology domain is proposed where the subimages obtained from discrete wavelet frame (DWF) were separated into three regimes—form, waviness, and roughness—and fusion was not performed on subimages in the form regime. This approach effectively eliminates the edge effects. Individual datapointlevel fusion was successfully demonstrated on Fresnel microlens array surface data as a case study of a nondirectional engineered surface with high aspect ratio.
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      Data Fusion Strategy for Multiscale Surface Measurements

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    http://yetl.yabesh.ir/yetl1/handle/yetl/152851
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    contributor authorRamasamy, Suresh K.
    contributor authorRaja, Jayaraman
    contributor authorBoudreau, Brian D.
    date accessioned2017-05-09T01:01:45Z
    date available2017-05-09T01:01:45Z
    date issued2013
    identifier issn2166-0468
    identifier otherjmnm_1_1_011004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/152851
    description abstractInterdisciplinary research efforts have started focusing on the development of multiscale models and development of designer multiscale surfaces exhibiting specific properties at different scales for a specific purpose. With the rapid evolution of these new engineered surfaces for microelectromechanical systems (MEMS), microfluidics, etc., there is a strong need for developing tools to measure and characterize these surfaces at different scales. In order to obtain all meaningful details of the surface at various required scales, one is left with the only option of measuring the surface using multiple technologies using a combination of instruments. The majority of hardwarebased approaches focus on the development of systems housing multiple technologies/capabilities into a single frame. These systems enable the user to obtain different surface maps using various technologies, but the user does not readily have the ability to combine all the obtained data into one single dataset. The effective approach toward multiscale measurement and characterization would be to use the individual measurement tools and finding a method to relate the individual coordinate systems and use an offline virtual tool to unify, manipulate, segment, merge, and retrieve data. Shape primitives and focusbased fusion strategies cannot be used as every data point in the data sets under consideration has to be treated as essentially at optimal focus. A multiscale data fusion strategy results in edge effects on nonplanar and high aspect ratio surfaces. An optimized fusion strategy, the “FWR method,â€‌ for the surface metrology domain is proposed where the subimages obtained from discrete wavelet frame (DWF) were separated into three regimes—form, waviness, and roughness—and fusion was not performed on subimages in the form regime. This approach effectively eliminates the edge effects. Individual datapointlevel fusion was successfully demonstrated on Fresnel microlens array surface data as a case study of a nondirectional engineered surface with high aspect ratio.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleData Fusion Strategy for Multiscale Surface Measurements
    typeJournal Paper
    journal volume1
    journal issue1
    journal titleJournal of Micro and Nano
    identifier doi10.1115/1.4023755
    journal fristpage11004
    journal lastpage11004
    identifier eissn1932-619X
    treeJournal of Micro and Nano-Manufacturing:;2013:;volume( 001 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian