Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Conditional expectation <i>G</i>_<i>v</i>(<i>m</i>) of the surrogate model <i>g</i> given each design variable. by Ava Souaille (17721138)

DataSheet1_Urban Catchment-Scale Blue-Green-Gray Infrastructure Classification with Unmanned Aerial Vehicle Images and Machine Learning Algorithms.docx by Jinlin Jia (11954603)

Categories with its number of samples. by Himanshi Babbar (20448110)

“…By leveraging a minimal subset of features from a given dataset, a comparative study is conducted to determine the optimal sample size for maximizing model accuracy. …”

Categories with its number of samples. by Himanshi Babbar (20448110)

“…By leveraging a minimal subset of features from a given dataset, a comparative study is conducted to determine the optimal sample size for maximizing model accuracy. …”

Study design flow chart. by Müge Yalçin (16486563)

Pulsed Blue Laser Diode Thermal Desorption Microplasma Imaging Mass Spectrometry by Alexander Knodel (8538882)

“…In spot-by-spot scanning, a novel algorithm is presented to unfold and to reconstruct the imaging data. …”

Pmd analysis of the SST-CRN model with several CR users. by Saraswathi M. (19353597)

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Probability of detection analysis of SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

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A summary of related work in CRN. by Saraswathi M. (19353597)

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Analysis of SST-CRN model results for spectral hole exploitation probability. by Saraswathi M. (19353597)

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Illustration for the SST-CRN model. by Saraswathi M. (19353597)

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Pe investigation of the SST-CRN under fading channels. by Saraswathi M. (19353597)

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Pnf analysis of the SST-CRN model. by Saraswathi M. (19353597)

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Flowchart of CSA. by Saraswathi M. (19353597)

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Pe analysis of the SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

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Probability of detection analysis of SST-CRN model under fading channels. by Saraswathi M. (19353597)

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Pd analysis of the SST-CRN model under fading channels. by Saraswathi M. (19353597)

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Probability of error analysis of SST-CRN under fading channels. by Saraswathi M. (19353597)

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