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Listar por autor "Ferrer Riquelme, Alberto José"

Mostrando ítems 1-20 de 122

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"Nonstationarity in statistical process control issues, cases, ideas" by B. De Ketelaere, K. Mertens, F. Mathijs, D. Sabin Diaz and J. De Baerdemaeker

Ferrer Riquelme, Alberto José (Wiley-Blackwell, 2011)
A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control

Vidal Puig, Santiago; Ferrer, Alberto (Taylor & Francis Inc., 2014-01)

Different methodologies for fault diagnosis in multivariate quality control have been proposed in recent years. These methods work in the space of the original measured variables and have performed reasonably well when ...
A graphical user interface for PCA-based MSPC: A benchmark software for multivariate statistical process control in MATLAB

Villalba-Torán, Pedro Miguel; Sanchís Saez, Javier; Ferrer, Alberto (Elsevier, 2019-02-15)

[EN] A Graphical User Interface (GUI) is developed in MATLAB as a tutorial for understanding the PCA-based MSPC strategy. The software allows users to analyze both simulated and external data sets. Simulated data are ...
A kernel-based approach for fault diagnosis in batch processes

Vitale, R.; de Noord, O. E.; Ferrer, Alberto (Wiley, 2014-08)

This article explores the potential of kernel-based techniques for discriminating on-specification and off-specification batch runs, combining kernel-partial least squares discriminant analysis and three common approaches ...
ADVANCES ON BILINEAR MODELING OF BIOCHEMICAL BATCH PROCESSES

González Martínez, José María (Universitat Politècnica de València, 2015-10-07)

[EN] This thesis is aimed to study the implications of the statistical modeling approaches proposed for the bilinear modeling of batch processes, develop new techniques to overcome some of the problems that have not been ...
Aplicación de métodos estadísticos multivariantes para la modelación y la monitorización de un reactor discontinuo secuencial para el tratamiento de aguas residuales

Aguado García, Daniel (Universitat Politècnica de València, 2008-05-06)

Como consecuencia del incremento de los problemas de eutrofización en ríos, lagos y costas, se ha producido en las últimas décadas un notable aumento del interés por la eliminación de nutrientes en las aguas residuales ...
Aplicación del análisis multivariante al control estadístico de procesos y a la caracterización química de muestras de pintura

Hervás García, Alicia (Universitat Politècnica de València, 2019-01-16)

En el presente trabajo se empelan técnicas estadísticas multivariantes para resolver dos problemas, uno del ámbito industrial y otro del ámbito cultural. En la primera parte del trabajo se resuelve el problema de la ...
Application of multivariate image analysis for on-line monitoring of a freeze-drying process for pharmaceutical products in vials

Colucci, D.; Prats-Montalbán, José Manuel; Fisore, D.; Ferrer, Alberto (Elsevier, 2019)

[EN] A new Process Analytical Technology (PAT) has been developed and tested for on-line process monitoring of a vacuum freeze-drying process. The sensor uses an infrared camera to obtain thermal images of the ongoing ...
ARSyN: a method for the identification and removal of systematic noise in multifactorial time-course microarray experiments

Nueda, María J.; Ferrer Riquelme, Alberto José; Conesa, Ana (Oxford University Press (OUP): Policy B - Oxford Open Option A, 2011-11-14)

Transcriptomic profiling experiments that aim to the identification of responsive genes in specific biological conditions are commonly set up under defined experimental designs that try to assess the effects of factors ...
Assessment of maximum likelihood PCA missing data imputation

Folch Fortuny, Abel; Arteaga Moreno, Francisco Javier; Ferrer, Alberto (Wiley, 2016-07)

Maximum likelihood principal component analysis (MLPCA) was originally proposed to incorporate measurement error variance information in principal component analysis (PCA) models. MLPCA can be used to fit PCA models in the ...
Automatic Individual Arterial Input Functions Calculated From PCA Outperform Manual and Population-Averaged Approaches for the Pharmacokinetic Modeling of DCE-MR Images

Sanz Requena, Roberto; Prats-Montalbán, José Manuel; Marti Bonmati, Luis; Alberich Bayarri, Ángel; García Martí, Gracián; Pérez, Rosario; Ferrer Riquelme, Alberto José (Wiley, 2015-08)

[EN] Background: To introduce a segmentation method to calculate an automatic arterial input function (AIF) based on prin- cipal component analysis (PCA) of dynamic contrast enhanced MR (DCE-MR) imaging and compare it with ...
Bilinear modeling of batch processes. Part III: Parameter Stability

González Martínez, José María; Camacho Páez, José; Ferrer, Alberto (Wiley, 2014-01)

A paramount aspect in the development of a model for a monitoring system is the so-called parameter stability. This is inversely related to the uncertainty, i.e., the variance in the parameters estimates. Noise affects the ...
Biomarker comparison and selection for prostate cancer detection in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI)

Aguado-Sarrió, Eric; Prats-Montalbán, José Manuel; Sanz-Requena, R.; Garcia-Marti, G.; Marti-Bonmati, L.; Ferrer, Alberto (Elsevier, 2017)

[EN] In this work, the capability of imaging biomarkers obtained from multivariate curve resolution-alternating least squares (MCR-ALS), in combination with those obtained from first and second-generation pharmacokinetic ...
Building covariance matrices with the desired structure

Arteaga Moreno, Francisco Javier; Ferrer, Alberto (Elsevier, 2013-08-15)

[EN] The problem of building a covariance matrix by fixing their diagonal values (variances) and all or a subset of its eigenvalues has been solved in different ways in the literature. In this paper we propose an iterative ...
Calibration transfer between NIR spectrometers: new proposals and a comparative study

Folch-Fortuny, Abel; Vitale, Raffaele; De Noord, Onno E.; Ferrer, Alberto (John Wiley & Sons, 2017)

[EN] Calibration transfer between near-infrared (NIR) spectrometers is a subtle issue in chemometrics and process industry. In fact, as even very similar instruments may generate strongly different spectral responses, ...
Causal latent space-based models for scientific learning in Industry 4.0

Borràs Ferrís, Joan (Universitat Politècnica de València, 2023-10-30)

[ES] La presente tesis doctoral está dedicada a estudiar, desarrollar y aplicar metodologías basadas en datos, fundamentadas en modelos estadísticos multivariantes de variables latentes, para abordar el paradigma del ...
Cálculo de biomarcadores basados en el tensor de difusión a partir de imágenes de MRI DTI de cáncer de mama

Robles Lozano, Guillermo (Universitat Politècnica de València, 2017-10-03)

[ES] El objetivo principal de este trabajo es el cálculo de una serie de biomarcadores basados en la difusión de los tejidos de la mama a partir de imágenes de resonancia magnética para poder desarrollar a posteriori un ...
Chemometric Approaches for Systems Biology

Folch Fortuny, Abel (Universitat Politècnica de València, 2017-01-23)

The present Ph.D. thesis is devoted to study, develop and apply approaches commonly used in chemometrics to the emerging field of systems biology. Existing procedures and new methods are applied to solve research and ...
Chemometric approaches to improve PLSDA model outcome for predicting human non-alcoholic fatty liver disease using UPLC-MS as a metabolic profiling tool

Quintás, Guillermo; Portillo Poblador, Nuria; García Cañaveras, Juan Carlos; Castell, José Vicente; Ferrer, Alberto; Lahoz, Agustín (Springer Verlag (Germany), 2012-02)

An MS-based metabolomics strategy including variable selection and PLSDA analysis has been assessed as a tool to discriminate between non-steatotic and steatotic human liver profiles. Different chemometric approaches for ...
Comparación de técnicas de machine learning y estadística multivariante para la predicción del cáncer de mama utilizando biomarcadores obtenidos a partir de imágenes de resonancia magnética

Alcalá Belmonte, Miguel (Universitat Politècnica de València, 2022-09-05)

[ES] La motivación del presente trabajo es abordar un estudio acerca de la implementación de técnicas de machine learning y estadística multivariante a un problema real y muy grave, como es el diagnóstico del cáncer de ...