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determination algorithm » detection algorithm (Expand Search), generation algorithm (Expand Search), identification algorithm (Expand Search)
dose optimization » based optimization (Expand Search), model optimization (Expand Search), wolf optimization (Expand Search)
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Showing 1 - 20 results of 26 for search '(( binary also structure determination algorithm ) OR ( binary wave dose optimization algorithm ))*', query time: 0.64s Refine Results
  1. 1
    Fig 1 -

    Fig 1 - by Dillion M. Fox (4043159)

    Published 2022
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  2. 2
    Fig 2 -

    Fig 2 - by Dillion M. Fox (4043159)

    Published 2022
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  3. 3
    Table_1_On the Origin of Biomolecular Networks.pdf

    Table_1_On the Origin of Biomolecular Networks.pdf by Heeralal Janwa (6574409)

    Published 2019
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  4. 4
    Data_Sheet_1_On the Origin of Biomolecular Networks.PDF

    Data_Sheet_1_On the Origin of Biomolecular Networks.PDF by Heeralal Janwa (6574409)

    Published 2019
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  5. 5
    Table_2_On the Origin of Biomolecular Networks.pdf

    Table_2_On the Origin of Biomolecular Networks.pdf by Heeralal Janwa (6574409)

    Published 2019
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  6. 6
    DataSheet2_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF

    DataSheet2_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF by András Micsonai (801004)

    Published 2022
    “…The mathematical analysis applies the k-nearest neighbor algorithm with cosine distance function, which is independent of the spectral amplitude and thus free of concentration determination errors. …”
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  7. 7
    DataSheet3_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.xlsx

    DataSheet3_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.xlsx by András Micsonai (801004)

    Published 2022
    “…The mathematical analysis applies the k-nearest neighbor algorithm with cosine distance function, which is independent of the spectral amplitude and thus free of concentration determination errors. …”
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  8. 8
    DataSheet1_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF

    DataSheet1_Disordered–Ordered Protein Binary Classification by Circular Dichroism Spectroscopy.PDF by András Micsonai (801004)

    Published 2022
    “…The mathematical analysis applies the k-nearest neighbor algorithm with cosine distance function, which is independent of the spectral amplitude and thus free of concentration determination errors. …”
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  9. 9
    the functioning of BRPSO.

    the functioning of BRPSO. by Hossein Jarrahi (22530251)

    Published 2025
    “…The proposed framework not only enhances structural resilience but also minimizes construction costs by ensuring an efficient damper layout. …”
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  10. 10
    Characteristic of 6- and 10-story SMRF [99,98].

    Characteristic of 6- and 10-story SMRF [99,98]. by Hossein Jarrahi (22530251)

    Published 2025
    “…The proposed framework not only enhances structural resilience but also minimizes construction costs by ensuring an efficient damper layout. …”
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  11. 11
    The RFD’s behavior mechanism (2002).

    The RFD’s behavior mechanism (2002). by Hossein Jarrahi (22530251)

    Published 2025
    “…The proposed framework not only enhances structural resilience but also minimizes construction costs by ensuring an efficient damper layout. …”
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  12. 12
    Video1_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4

    Video1_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  13. 13
    Video3_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4

    Video3_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  14. 14
    Video2_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4

    Video2_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  15. 15
    Video3_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4

    Video3_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  16. 16
    Video2_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4

    Video2_Self-Organization of Binary Colloidal Mixtures via Diffusiohporesis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  17. 17
    Video1_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4

    Video1_Self Organization of Binary Colloidal Mixtures via Diffusiophoresis.MP4 by Lijie Lei (8604411)

    Published 2022
    “…In this paper, we simulate mixtures of active and passive colloids via a Brownian dynamics algorithm. These particles interact via phoretic interactions, which are determined by two independent parameters, surface activity and surface mobility. …”
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  18. 18
    Data_Sheet_3_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx

    Data_Sheet_3_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx by Pijush Das (3196647)

    Published 2020
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  19. 19
    Data_Sheet_2_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx

    Data_Sheet_2_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx by Pijush Das (3196647)

    Published 2020
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  20. 20
    Data_Sheet_1_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx

    Data_Sheet_1_sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.docx by Pijush Das (3196647)

    Published 2020
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