Article
Chemistry, Analytical
Jamile Mohammad Jafari, Roma Tauler, Hamid Abdollahi
Summary: The paper introduces a new method - Balanced Scaling (BS) method, combined with Multivariate Curve Resolution Alternating Least Squares (BSMCR-ALS) method, for analyzing data sets with heteroscedastic noise, showing good performance especially in environmental data analysis. Comparisons with other methods revealed that BS-MCR-ALS and MLPCA-MCR-ALS solutions were very similar in performance.
MICROCHEMICAL JOURNAL
(2021)
Article
Automation & Control Systems
Mohamad Ahmad, Raffaele Vitale, Marina Cocchi, Cyril Ruckebusch
Summary: This study proposes a novel weighting scheme to address the impact of noise on minor components and demonstrates its application in two simulated cases and one Raman imaging case. The proposed method achieves a balance between the benefits of standard multivariate curve resolution-alternating least squares and essential spectral pixel selection.
JOURNAL OF CHEMOMETRICS
(2023)
Article
Multidisciplinary Sciences
Xiangdong Qing, Xiaohong Zhou, Ling Xu, Jin Zhang, Yi Huang, Li Lin, Zhi Liu, Xiaohua Zhang
Summary: The ATLD-MCR method was applied for the first time to analyze complex GC-MS data for simultaneous identification and quantification of PAHs in aerosols, demonstrating high sensitivity and low limits of detection. Compared with MCR-ALS and the GC-MS-based external standard method, ATLD-MCR accurately identified PAHs and achieved similar recovery rates.
ROYAL SOCIETY OPEN SCIENCE
(2021)
Article
Engineering, Environmental
Meiping Tian, Camilo L. M. Morais, Heqing Shen, Weiyi Pang, Li Xu, Qingyu Huang, Francis L. Martin
Summary: Microplastics contamination is widespread in global environmental matrices, and efficient methods for direct identification and visualization of these pollutants are needed. This study used MCR-ALS analysis of Raman hyperspectral imaging data to successfully identify and visualize microplastics in complex backgrounds, demonstrating a novel imaging approach for direct identification of microplastics. By extracting chemical spectra of microplastics within biological or environmental backgrounds, this method eliminates overlapping Raman bands and fluorescence interference.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Computer Science, Information Systems
K. N. R. Surya Vara Prasad, Vijay K. Bhargava
Summary: This paper focuses on localization using received signal strength, addressing unknown transmit power and log-distance pathloss exponent. It proposes maximum-likelihood estimation, two-step linear least squares estimation, and a maximum-a-posteriori estimator for joint estimation of source location and PLE, demonstrating improved localization accuracy.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Food Science & Technology
Lorenzo Strani, Silvia Grassi, Cristina Alamprese, Ernestina Casiraghi, Roberta Ghiglietti, Francesco Locci, Nicolo Pricca, Anna De Juan
Summary: The effect of physicochemical factors and use of skim milk powder on milk rennet-coagulation was investigated using NIR spectroscopic monitoring and MCR-ALS models, revealing the significant impact of milk powder type on the coagulation process. The models successfully described the process evolution, explaining over 99.9% of variance and providing non-destructive and online tools for evaluating rennet-induced coagulation of reconstituted milks under various conditions.
Article
Chemistry, Analytical
Kutluyil Dogancay, Hatem Hmam
Summary: This paper presents a new algorithm for localizing emitters in the 3D space using time difference of arrival (TDOA) measurements and conic approximations. It converts TDOA measurements to 1D angle of arrival (1D-AOA) measurements and calculates the emitter location through triangulation. The algorithm consists of an iterative weighted least squares (IWLS) estimator and a Taylor series estimator, and it outperforms the maximum likelihood estimator in poor sensor-emitter geometries and high noise.
Article
Computer Science, Interdisciplinary Applications
Pratyush Kumar, James B. Rawlings
Summary: This paper proposes a novel model-free Q-learning approach to estimate linear feedback controllers from noisy process data. The approach is modified to handle unknown noise covariances and is applied to estimate feedback controllers for linear systems with both process and measurement noise. A model-based approach is also presented for comparison.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Chemistry, Analytical
Irina Matveeva, Ivan Bratchenko, Yulia Khristoforova, Lyudmila Bratchenko, Alexander Moryatov, Sergey Kozlov, Oleg Kaganov, Valery Zakharov
Summary: Raman spectroscopy has been used to study biological tissues, but the analysis of experimental Raman spectra is still challenging. In this study, the MCR-ALS method was used to decompose Raman spectra into components and evaluate their contribution. The results showed that this method can provide new information on the biochemical profiles of skin tissues, which can be applied in medical diagnostics and various fields of science and industry.
Article
Medicine, Legal
Norimitsu Akiba, Atsushi Nakamura, Takayuki Sota, Kazuhito Hibino, Hidetoshi Kakuda, Maurice C. G. Aalders
Summary: This study presents a method for separating overlapping fingerprints using the difference in fluorescence spectra. Hyperspectral data was recorded using a hyperspectral imager, and PCA and MCR-ALS were applied to determine the optimal method for obtaining high-contrast individual fingerprint images. The results showed that using MCR-ALS combined with PCA-based initialization can successfully separate overlapping fingerprints into individual fingerprints, and a parameter-free separation method was proposed.
JOURNAL OF FORENSIC SCIENCES
(2022)
Article
Chemistry, Analytical
Alejandro C. Olivieri
Summary: Rotational ambiguity is a phenomenon in protocols using MCR-ALS that can lead to uncertainty in analyte concentration estimation, especially when unexpected constituents are present in unknown samples. Analytical chemists developing second-order multivariate calibration methods using MCR-ALS need to acknowledge and assess the impact of this potential source of uncertainty on estimated analyte concentrations. It is crucial to estimate and report rotational ambiguity uncertainties, regardless of their magnitude, in order to ensure the accuracy of analyte predictions.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Analytical
Alejandro C. Olivieri
Summary: The present tutorial aims to demonstrate the importance of applying constraints when processing second-order analytical data with MCR-ALS, and show how these constraints can reduce or eliminate the impact of rotational ambiguity. Additionally, it provides details on a newly developed method for estimating uncertainty in predicted analyte concentrations.
MICROCHEMICAL JOURNAL
(2022)
Article
Automation & Control Systems
Haiquan Zhao, Zian Cao
Summary: This article proposes a GMBZTC algorithm based on the generalized maximum Blake-Zisserman robust loss function for handling generalized Gaussian noise in adaptive filtering arithmetic. It also provides a detailed performance evaluation of the algorithm under such noise conditions.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Economics
Jing Zhou, Jin Liu, Feifei Wang, Hansheng Wang
Summary: This paper investigates an autoregressive model with spatially correlated error terms and missing data. A logistic regression model is used to model the missingness mechanism, while an autoregressive model accommodates time series dependence and a spatial error model captures spatial dependence. Weighted least squares and weighted maximum likelihood estimators are developed for estimation. Asymptotic properties and finite sample performance are studied, and a real data example on Beijing's PM2.5 data is provided.
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2022)
Article
Automation & Control Systems
Longjin Wang, Shun An, Yan He, Jianping Yuan
Summary: This paper focuses on maximum likelihood estimation for bilinear systems with colored noise. It eliminates the state variables in the model and provides an input-output expression. The input-output data of the system is filtered using an estimated noise transfer function, and the system is transformed into two subsystems. A filtering-based maximum likelihood recursive least squares algorithm is proposed to improve identification accuracy and computational efficiency. Numerical simulations demonstrate the superior performance of the developed methods.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Automation & Control Systems
Haifei Peng, Jian Long, Cheng Huang, Shibo Wei, Zhencheng Ye
Summary: This paper proposes a novel multi-modal hybrid modeling strategy (GMVAE-STA) that can effectively extract deep multi-modal representations and complex spatial and temporal relationships, and applies it to industrial process prediction.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2024)
