Article
Biochemical Research Methods
Ruoyu Tang, Xinyu He, Ruiqi Wang
Summary: The study presents a general computational method for constructing maps between different cell fates and parametric conditions by systematic perturbations. The method does not require accurate parameter measurements or bifurcations. The maps obtained can help in understanding how systematic perturbations drive cell fate decisions and transitions, providing valuable information for predicting and controlling cell states.
Article
Automation & Control Systems
Ping Ma, Yongkai Chen, Xinlian Zhang, Xin Xing, Jingyi Ma, Michael W. Mahoney
Summary: In this article, we develop an asymptotic analysis to derive the distribution of RandNLA sampling estimators for the least-squares problem. We show that the sampling estimator is asymptotically normally distributed under mild regularity conditions and is asymptotically unbiased in both full sample approximation and model parameter inference settings. Based on our asymptotic analysis, we identify optimal sampling probabilities using two criteria and propose several new optimal sampling probability distributions. Our theoretical and empirical results provide insights on the role of leverage in the sampling process and demonstrate improvements over existing methods.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Environmental Sciences
Muhammad Kashif, Abdullah M. Almarashi, Muhammad Aslam, Muhammad Imran Khan
Summary: In wastewater treatment processes, parameters such as BOD, COD, and TSS play a crucial role. This research aims to monitor these variables more effectively by constructing a neutrosophic Hotelling's T-2 control chart using neutrosophic data. The effectiveness of the proposed method is compared with other existing methods, and the sources of variability for each variable are identified using a MYT-decomposition approach.
WATER AIR AND SOIL POLLUTION
(2023)
Article
Automation & Control Systems
Zhonghao Xie, Xi'an Feng, Xiaojing Chen
Summary: This paper proposes a robust method for PLS based on the idea of least trimmed squares (LTS), which effectively deals with high-dimensional regressors. By formulating the LTS problem as a concave maximization problem, the complexity of solving LTS is simplified. The results from simulation and real data sets demonstrate the effectiveness and robustness of the proposed approach.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Chemistry, Applied
Gilson Augusto Helfer, Jorge Luis Victoria Barbosa, Eduardo Hermes, Brunno Jose Fagundes, Roberta Oliveira Santos, Adilson Ben da Costa
Summary: Parallel data analysis was conducted to optimize variable selection and develop predictive models for beer quality control. Through distributing the dataset to multiple Raspberry Pi devices running Machine Learning services, the time to find the best linear regression coefficient was reduced by 57% compared to a single desktop computer. This approach significantly accelerates the process of finding the best fitting model during variable selection.
Article
Multidisciplinary Sciences
Emilio Gomez-Gonzalez, Alejandro Barriga-Rivera, Beatriz Fernandez-Munoz, Jose Manuel Navas-Garcia, Isabel Fernandez-Lizaranzu, Francisco Javier Munoz-Gonzalez, Ruben Parrilla-Giraldez, Desiree Requena-Lancharro, Pedro Gil-Gamboa, Cristina Rosell-Valle, Carmen Gomez-Gonzalez, Maria Jose Mayorga-Buiza, Maria Martin-Lopez, Olga Munoz, Juan Carlos Gomez-Martin, Maria Isabel Relimpio-Lopez, Jesus Aceituno-Castro, Manuel A. Perales-Esteve, Antonio Puppo-Moreno, Francisco Jose Garcia-Cozar, Lucia Olvera-Collantes, Raquel Gomez-Diaz, Silvia de los Santos-Trigo, Monserrat Huguet-Carrasco, Manuel Rey, Emilia Gomez, Rosario Sanchez-Pernaute, Javier Padillo-Ruiz, Javier Marquez-Rivas
Summary: This study demonstrates the feasibility of using hyperspectral image analysis in the visible and near-infrared range for primary screening of SARS-CoV-2. By applying spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence, information can be extracted from fluid samples and analyzed quantitatively and descriptively. The proposed technology is reagent-free, fast, scalable, and could significantly reduce the number of molecular tests required for COVID-19 mass screening, even in resource-limited settings.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Freeh N. Alenezi
Summary: The study introduces a method for variable selection in high dimensional data modeling, using majority scoring with backward elimination in PLS to improve prediction accuracy. The method performs well in predicting corn and diesel contents, while also examining the impact of data properties on prediction behavior.
SCIENTIFIC REPORTS
(2021)
Article
Chemistry, Analytical
Marina Antonio, Renato L. Carneiro, Ruben M. Maggio
Summary: This study evaluated the feasibility of using middle- and near-infrared spectroscopy, as well as Raman spectroscopy, coupled with multivariate calibration to quantify MLXForm I in commercial raw material. The results showed that NIR-PLS had the best predictive capacity.
MICROCHEMICAL JOURNAL
(2022)
Article
Environmental Sciences
Onuwa Okwuashi, Christopher E. Ndehedehe, Dupe Nihinlola Olayinka
Summary: This research explores the novel application of Tensor Partial Least Squares (TPLS) for hyperspectral image classification. The results show that TPLS performed better than unfolded PLS, but fell short of traditional classifiers.
GEOCARTO INTERNATIONAL
(2022)
Article
Automation & Control Systems
Zhonghao Xie, Xi'an Feng, Limin Li, Xiaojing Chen
Summary: In this study, a new robust PLS method called partial least median of squares (PLMS) regression is proposed by incorporating the idea of least median of squares. Unlike most existing robust methods, the PLMS problem is solved using modern optimization techniques rather than heuristic processes or reweighting strategies. Comparisons are made with a classical PLS method and two efficient robust PLS methods, demonstrating the effectiveness and robustness of the proposed approach through simulations and real-world data sets.
JOURNAL OF CHEMOMETRICS
(2022)
Article
Engineering, Chemical
Hye Ji Lee, Shinje Lee, Jong Min Lee
Summary: The proposed method improves trajectory tracking performance and reduces tracking error by applying online alignment, selecting multiple models, and adaptively applying future reference based on current batch measurements. Additionally, the method adaptively decides batch duration, leading to improved overall performance in industrial penicillin production.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Shih-Chou Kao
Summary: This study proposes two types of square A estimators based on different screenings and compares their mean squared errors with existing estimators under different disturbances. The results show that the proposed estimators perform the best against disturbances and are closer to the normal cases.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2022)
Article
Engineering, Biomedical
Jose Henrique Ferreira de Souza, Tiago Zanotelli, Leonardo Bonato Felix, Felipe Antunes
Summary: Auditory Steady-State Responses (ASSR) are evoked potentials used for estimating hearing thresholds. This study proposes an alternative technique to the discrete Fourier transform (DFT) called the least squares method with phase compensation. Results showed a small calibration error in the dataset and demonstrated the performance degradation of the magnitude-squared coherence (MSC) when using either very small or very large epoch lengths in real data. The proposed method allows for analysis with varying epoch lengths and frequencies, which was not possible with DFT.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Zhonghao Xie, Xi'an Feng, Xiaojing Chen
Summary: Partial least squares (PLS) is effective for high-dimensional regression problems. It was developed based on empirical risk minimization and assumes that the test and training data are drawn from the same distribution. Subsampling via an influence function is a promising technique to address the violation of this assumption.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Chemistry, Analytical
Dariusz Bismor
Summary: This paper investigates the application of partial update adaptive algorithms in structural active noise control (ANC) systems, and introduces leaky versions of the PU LMS algorithms. Two simulation examples are presented to confirm the high performance of the proposed algorithms.
Article
Operations Research & Management Science
Marco S. Reis, Ricardo Rendall, Biagio Palumbo, Antonio Lepore, Christian Capezza
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2020)
Review
Operations Research & Management Science
Grazia Vicario, Shirley Coleman
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2020)
Article
Operations Research & Management Science
Christian Capezza, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2020)
Article
Engineering, Marine
Saeed Jamei, Adi Maimun, Rasul Niazmand Bilandi, Nor Azwadi, Simone Mancini, Luigi Vitiello, Maria De Carlini
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2020)
Editorial Material
Engineering, Industrial
Shirley Coleman
QUALITY ENGINEERING
(2020)
Article
Statistics & Probability
Christian Capezza, Iagio Palumbo, Yannig Goude, Simon N. Wood, Matteo Fasiolo
Summary: Future grid management systems will manage increasing loads and variability caused by the electrification of transportation and weather-dependent production by coordinating distributed production and storage resources. The researchers propose a new ensemble method for probabilistic forecasting at the individual household level, which adapts to the diverse demand dynamics across households by utilizing a set of models capturing different patterns and adapting weights based on covariates.
ANNALS OF APPLIED STATISTICS
(2021)
Article
Operations Research & Management Science
Christian Capezza, Fabio Centofanti, Antonio Lepore, Biagio Palumbo
Summary: This article explores the potential and practical applicability of clustering methods to curve data and functional data, demonstrating the ability to separate DRCs into homogeneous groups without the need for arbitrary and problem-specific feature extraction.
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2021)
Biographical-Item
Social Sciences, Mathematical Methods
Sarah Barker, Shirley Coleman
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY
(2021)
Article
Engineering, Multidisciplinary
Christian Capezza, Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini
Summary: This paper presents the application of functional regression control chart (FRCC) in monitoring CO2 emissions on modern ships, demonstrating its applicability through a real-case study and comparing it with other alternatives in the literature, discussing its advantages over practical examples.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2022)
Article
Engineering, Multidisciplinary
Daniel Walker, Martin Ruane, Jaume Bacardit, Shirley Coleman
Summary: Facilities management of large public services is often outsourced to specialist providers, who can harness data science solutions to enhance efficiency. Through a partnership between Newcastle University and a FM provider, data science has been effectively applied to improve service delivery.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2022)
Article
Engineering, Marine
R. Pigazzini, F. De Luca, F. Balsamo, A. Migali, L. Vitiello
Summary: This study presents an in-depth analysis of both head and following sea trials of a leisure planing hull yacht, with a focus on the relationship between propulsion and motion. The analysis is conducted in both frequency and time domain, providing a comprehensive assessment of torque response and hull motions.
Review
Engineering, Marine
Flaminia Spinelli, Simone Mancini, Luigi Vitiello, Rasul Niazmand Bilandi, Maria De Carlini
Summary: In recent years, research on ships has focused on reducing emissions and energy consumption, leading to a green and sustainable direction in the maritime industry. Improving fuel efficiency and decarbonizing shipping are important to reduce fuel consumption and greenhouse gas emissions. This paper reviews the current literature on stern hydrodynamic ESDs, analyzing different available solutions, working principles, design and performance improvement evaluation methods, and relevant issues.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Management
Radouane Oudrhiri, Mustafa Al-Balushi, Stuart Anwyl, Anthony Bendell, Sabet Chamie, Shirley Yvonne Coleman, Mark Hayman, Roger Hilton, Osama Ahmad Melhem, Jayeshkumat Patel, Steve Ward, Simon White, Peter Whitehouse
Summary: This paper aims to correct misconceptions and erroneous statements about the ISO 18404:2015 standard and demonstrate its usefulness in various sectors. By reviewing reports and conducting interviews, it is found that most Lean Six Sigma professionals have positive experiences with the standard and recognize the advantages of a common standard for continuous improvement. The paper provides valuable insights for organizations considering the implementation of the standard.
Article
Engineering, Marine
Luigi Vitiello, Simone Mancini, Rasul Niazmand Bilandi, Abbas Dashtimanesh, Fabio De Luca, Vincenzo Nappo
Summary: This work presents an experimental study of a new series of stepped planing hulls, aiming to address the lack of a comprehensive systematic series of stepped hulls. Towing tank tests were conducted on eight different models with variations in step configurations, speeds, and static trim conditions.
Article
Engineering, Industrial
Christian Capezza, Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini
Summary: This article introduces the funcharts R package, which implements the real-time statistical process monitoring of multivariate functional quality characteristics and can adjust for additional variables. The package is demonstrated through both a built-in data generator and a real-case study.
JOURNAL OF QUALITY TECHNOLOGY
(2023)
