In this paper, a nonlinear fault diagnosis scheme is established for the hot strip mill process (HSMP). In HSMP, the faults affecting quality index are denoted as quality-related faults, which should be taken care as soon as possible. Projection to latent structures (PLS) is a basic model for quality-related fault detection in linear processes. In the presented work, a total kernel PLS (T-KPLS)...

We present a novel signal de-noising algorithm for recovery of signals corrupted by a high levels of noise and applicable in the situations of low sampling rates. This method uses a modi cation of kernel partial least squares regression (KPLS) de ned in reproducing kernel Hilbert space [1]. We treat signal de-noising as a regression problem, in which de-noising consists of estimation of functio...

This study is an extensive comparison of the predictive performance a bagging neural network (BANN), partial least squares (PLS) regressor, and kernel-based, nonlinear PLS (KPLS) given experimentally obtained CO2-N2-Ar plasma emission spectra. The spectra, 3,62,31 in total, were from controlled gas mixtures with varying CO2 concentrations fed to stripline split-ring resonator microplasma source...

Kernel learning based soft sensor model has been focus of the machine learning domain. Kernel partial least squares (KPLS) algorithm can construct nonlinear models using the extract latent variables from the input and output data space simultaneously. However, the generalization of KPLS model relies on the model’s kernel type and kernel parameter for different modeling data. Thus, linear combin...

Inspired by kernel methods that have been used extensively in achieving efficient facial animation retargeting, this paper presents a solution to retargeting facial animation in virtual character’s face model based on the kernel projection of latent structure (KPLS) regression between semantically similar facial expressions. Specifically, a given number of corresponding semantically similar fac...

We develop the Kernel Multitask Latent Analysis (KMLA) method for modeling many-to-many relationships between inputs and responses, and show how it can be applied to inductive transfer problems in bioseparations. KMLA performs dimensionality reduction targeted towards a multitask loss function much like Kernel Partial Least Squares (KPLS). KPLS is limited to least squares multiple regression wh...

The runtime for Kernel Partial Least Squares (KPLS) to compute the fit is quadratic in the number of examples. However, the necessity of obtaining sensitivity measures as degrees of freedom for model selection or confidence intervals for more detailed analysis requires cubic runtime, and thus constitutes a computational bottleneck in real-world data analysis. We propose a novel algorithm for KP...

The authenticity of milk and milk products is important and has extended health, cultural, and financial implications. Current analytical methods for the detection of milk adulteration are slow, laborious, and therefore impractical for use in routine milk screening by the dairy industry. Fourier transform infrared (FT-IR) spectroscopy is a rapid biochemical fingerprinting technique that could b...