Results 211 to 220 of about 145,155 (289)

Mid‐Infrared Spectroscopy and Machine Learning for Chlorogenic Acid Quantification in Coffee

Chemie Ingenieur Technik, EarlyView.
Chlorogenic acid (CGA) concentration in coffee was predicted using mid‐infrared (MIR) spectroscopy and a machine learning approach. Forty‐four roasting stages (140–220 °C) plus a green coffee control were analyzed. A multilayer perceptron regressor, trained on preprocessed MIR data, outperformed traditional peak analysis, enabling accurate and ...
Deborah Herdt, Felix Wühler, Thomas Kunz, Victoria Schiwek, Sarah Kühnemuth, Brian Gibson, Matthias Rädle   +6 more
wiley   +1 more source

Hand, foot and mouth disease incidence in mainland China: temporal trends and projections to 2030. [PDF]

BMC Public Health
Tian G, Long S, Zheng Y, He Y, Chen C, Du Y, Yang S, Jiang T, Li L.   +8 more
europepmc   +1 more source

Intelligent online process fault diagnosis through integrating Andrews function, autoencoder, and neural networks

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This paper proposes an online process fault diagnosis scheme that integrates principal component analysis, Andrews function, autoencoder, and multilayer feedforward neural network to enhance the fault diagnosis performance. Useful features are extracted from the online monitoring data by using Andrews function (also known as Andrews plot).
Shengkai Wang, Jie Zhang
wiley   +1 more source

Accurate prediction of geometrical parameters of an ultra-broadband metamaterial absorber using machine learning. [PDF]

Sci Rep
Ahmed MR, Jyoti O, Sarkar PP, Motin MA, Habib MS, Habib MS.   +5 more
europepmc   +1 more source

Predicting solar cell efficiencies using historical data from a manufacturing process

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract The solar cell manufacturing data of a passivated emitter and rear cell solar cell manufacturing plant was studied to assess the effects of tool usage and the processing time spent on each tool on the solar cell efficiency. Since manufacturing processes involve several steps with multiple tools, tracing their quality parameters back to the ...
Sushmita Mittra, Vinay Prasad
wiley   +1 more source

AI-driven classification and precision cutting algorithms using machine vision in a customer-operated fish processing system. [PDF]

Sci Rep
Azarmdel H, Mohtasebi SS, Jafary A, Rezvanivand Fanaei A, Rosado Muñoz A.   +4 more
europepmc   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey   +3 more
wiley   +1 more source

Variational Deep Alliance: A Generative Auto-Encoding Approach to Longitudinal Data Analysis. [PDF]

Entropy (Basel)
Feng S, Xie W, Nie Y.
europepmc   +1 more source

Rank‐based estimation of propensity score weights via subclassification

Canadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang, Yuexia Zhang, Thomas S. Richardson, Xiaohua Zhou   +3 more
wiley   +1 more source

Modeling the effect of longitudinal markers on left-truncated time-to-event outcomes in twin studies. [PDF]

Stat Methods Med Res
Muli A, Rodriguez-Girondo M, Houwing-Duistermaat J.   +2 more
europepmc   +1 more source