Shaji Krishnan - Academia.edu (original) (raw)
Papers by Shaji Krishnan
Workshop on Design and Diagnostics of Electronic Circuits and Systems, 2008
A new approach for efficient estimation of die-level process parameter variations based on the ex... more A new approach for efficient estimation of die-level process parameter variations based on the expectation- maximization algorithm is proposed. To estimate the parameters and enhance diagnostic analysis, dedicated embedded sensors have been designed. Additionally, to guide the test with the information obtained through monitoring process variations, maximum-likelihood method and adjusted support vector machine classifier is employed. The information acquired is
Rapid Communications in Mass Spectrometry, 2013
RATIONALE: Mass spectra obtained by deconvolution of liquid chromatography/high-resolution mass s... more RATIONALE: Mass spectra obtained by deconvolution of liquid chromatography/high-resolution mass spectrometry (LC/HRMS) data can be impaired by non-informative mass-over-charge (m/z) channels. This impairment of mass spectra can have significant negative influence on further post-processing, like quantification and identification. METHODS: A metric derived from the knowledge of errors in isotopic distribution patterns, and quality of the signal within a pre-defined mass chromatogram block, has been developed to pre-select all informative m/z channels. RESULTS: This procedure results in the clean-up of deconvoluted mass spectra by maintaining the intensity counts from m/z channels that originate from a specific compound/molecular ion, for example, molecular ion, adducts, 13 C-isotopes, multiply charged ions and removing all m/z channels that are not related to the specific peak. The methodology has been successfully demonstrated for two sets of high-resolution LC/MS data.
Chemometrics and Intelligent Laboratory Systems, 2010
a b s t r a c t Extraction of peak areas and mass spectral information from chromatography mass s... more a b s t r a c t Extraction of peak areas and mass spectral information from chromatography mass spectral data such as obtained in metabolomics measurements requires much effort and the quality is often subjective to the operator that handles the data at hand. In multiple file deconvolution, all samples are processed simultaneously and alignment issues are part of the modeling strategy. However, processing the total data set as a whole is an impossible task and therefore the data processing task requires segmentation. Two intertwined divide and conquer strategies are proposed. The first strategy divides the retention time axis into equal parts and the second strategy divides the total data set into a model and a prediction data set. Dividing the data into smaller segments allows us to conquer the total problem. Post processing of the resulting matrices with peak areas and mass spectra ensures that a matrix with peak areas ready for statistics and a matrix with mass spectral information ready for peak annotation is obtained. The proposed methodology is implemented within a package called TNO-DECO but can easily be implemented in other data pre-processing approaches.
Analytica Chimica Acta, 2012
Appropriately collating the m/z values over time is an effective machine independent scheme for a... more Appropriately collating the m/z values over time is an effective machine independent scheme for aggregating a metabolite profile from a mass chromatogram. Entropy is an effective metric for baseline correction. The efficacy of each was proven on two LC-HR-MS datasets. g r a p h i c a l a b s t r a c t
IEEE Design & Test, 2013
ABSTRACT Mahalanobis distance is commonly used for fault classification in analogue testing. Howe... more ABSTRACT Mahalanobis distance is commonly used for fault classification in analogue testing. However, it cannot guarantee a robust mean value and covariance matrix, which makes it an unreliable metric in the presence of outliers. In this case study the authors therefore work with a multi-variate classifier based on multiple Mahalanobis distances from selected sets of test-response measurements. For an industrial automotive product they show that their classifier can both qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones.
2012 17TH IEEE EUROPEAN TEST SYMPOSIUM (ETS), 2012
Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defe... more Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the presence of outliers to test-response measurements, and only a sub-sample from the population is available, the distance metric becomes unreliable. To circumvent this problem, multiple Mahalanobis distances are calculated from selected sets of test-response mea- surements. They are then suitably formulated to derive a metric that has a reduced variance and robust to shifts or deviations in measurements. In this paper, such a formulation is proposed to qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones. The application of method is exemplified over a test set of an industrial automobile product.
2011 Sixteenth IEEE European Test Symposium, 2011
Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defe... more Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the presence of outliers to test-response measurements, and only a sub-sample from the population is available, the distance metric becomes unreliable. To circumvent this problem, multiple Mahalanobis distances are calculated from selected sets of test-response mea- surements. They are then suitably formulated to derive a metric that has a reduced variance and robust to shifts or deviations in measurements. In this paper, such a formulation is proposed to qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones. The application of method is exemplified over a test set of an industrial automobile product.
2010 15th IEEE European Test Symposium, 2010
A systematic approach to construct an effective multivariate test response model for capturing ma... more A systematic approach to construct an effective multivariate test response model for capturing manufacturing defects in electronic products is described. The effectiveness of the model is demonstrated by its capability in reducing the number of test-points, while achieving the maximal coverage attainable by the specific test method on an industrial circuit.
Theoretical Biology and Medical Modelling, 2014
Workshop on Design and Diagnostics of Electronic Circuits and Systems, 2008
A new approach for efficient estimation of die-level process parameter variations based on the ex... more A new approach for efficient estimation of die-level process parameter variations based on the expectation- maximization algorithm is proposed. To estimate the parameters and enhance diagnostic analysis, dedicated embedded sensors have been designed. Additionally, to guide the test with the information obtained through monitoring process variations, maximum-likelihood method and adjusted support vector machine classifier is employed. The information acquired is
Rapid Communications in Mass Spectrometry, 2013
RATIONALE: Mass spectra obtained by deconvolution of liquid chromatography/high-resolution mass s... more RATIONALE: Mass spectra obtained by deconvolution of liquid chromatography/high-resolution mass spectrometry (LC/HRMS) data can be impaired by non-informative mass-over-charge (m/z) channels. This impairment of mass spectra can have significant negative influence on further post-processing, like quantification and identification. METHODS: A metric derived from the knowledge of errors in isotopic distribution patterns, and quality of the signal within a pre-defined mass chromatogram block, has been developed to pre-select all informative m/z channels. RESULTS: This procedure results in the clean-up of deconvoluted mass spectra by maintaining the intensity counts from m/z channels that originate from a specific compound/molecular ion, for example, molecular ion, adducts, 13 C-isotopes, multiply charged ions and removing all m/z channels that are not related to the specific peak. The methodology has been successfully demonstrated for two sets of high-resolution LC/MS data.
Chemometrics and Intelligent Laboratory Systems, 2010
a b s t r a c t Extraction of peak areas and mass spectral information from chromatography mass s... more a b s t r a c t Extraction of peak areas and mass spectral information from chromatography mass spectral data such as obtained in metabolomics measurements requires much effort and the quality is often subjective to the operator that handles the data at hand. In multiple file deconvolution, all samples are processed simultaneously and alignment issues are part of the modeling strategy. However, processing the total data set as a whole is an impossible task and therefore the data processing task requires segmentation. Two intertwined divide and conquer strategies are proposed. The first strategy divides the retention time axis into equal parts and the second strategy divides the total data set into a model and a prediction data set. Dividing the data into smaller segments allows us to conquer the total problem. Post processing of the resulting matrices with peak areas and mass spectra ensures that a matrix with peak areas ready for statistics and a matrix with mass spectral information ready for peak annotation is obtained. The proposed methodology is implemented within a package called TNO-DECO but can easily be implemented in other data pre-processing approaches.
Analytica Chimica Acta, 2012
Appropriately collating the m/z values over time is an effective machine independent scheme for a... more Appropriately collating the m/z values over time is an effective machine independent scheme for aggregating a metabolite profile from a mass chromatogram. Entropy is an effective metric for baseline correction. The efficacy of each was proven on two LC-HR-MS datasets. g r a p h i c a l a b s t r a c t
IEEE Design & Test, 2013
ABSTRACT Mahalanobis distance is commonly used for fault classification in analogue testing. Howe... more ABSTRACT Mahalanobis distance is commonly used for fault classification in analogue testing. However, it cannot guarantee a robust mean value and covariance matrix, which makes it an unreliable metric in the presence of outliers. In this case study the authors therefore work with a multi-variate classifier based on multiple Mahalanobis distances from selected sets of test-response measurements. For an industrial automotive product they show that their classifier can both qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones.
2012 17TH IEEE EUROPEAN TEST SYMPOSIUM (ETS), 2012
Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defe... more Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the presence of outliers to test-response measurements, and only a sub-sample from the population is available, the distance metric becomes unreliable. To circumvent this problem, multiple Mahalanobis distances are calculated from selected sets of test-response mea- surements. They are then suitably formulated to derive a metric that has a reduced variance and robust to shifts or deviations in measurements. In this paper, such a formulation is proposed to qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones. The application of method is exemplified over a test set of an industrial automobile product.
2011 Sixteenth IEEE European Test Symposium, 2011
Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defe... more Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the presence of outliers to test-response measurements, and only a sub-sample from the population is available, the distance metric becomes unreliable. To circumvent this problem, multiple Mahalanobis distances are calculated from selected sets of test-response mea- surements. They are then suitably formulated to derive a metric that has a reduced variance and robust to shifts or deviations in measurements. In this paper, such a formulation is proposed to qualitatively screen product outliers and quantitatively measure the reliability of the non-defective ones. The application of method is exemplified over a test set of an industrial automobile product.
2010 15th IEEE European Test Symposium, 2010
A systematic approach to construct an effective multivariate test response model for capturing ma... more A systematic approach to construct an effective multivariate test response model for capturing manufacturing defects in electronic products is described. The effectiveness of the model is demonstrated by its capability in reducing the number of test-points, while achieving the maximal coverage attainable by the specific test method on an industrial circuit.
Theoretical Biology and Medical Modelling, 2014