Detection and classification of cotton foreign fibers based on polarization imaging and improved YOLOv5
R Wang, ZF Zhang, B Yang, HQ Xi, YS Zhai, RL Zhang… - Sensors, 2023 - mdpi.com
It is important to detect and classify foreign fibers in cotton, especially white and transparent
foreign fibers, to produce subsequent yarn and textile quality. There are some problems in …
foreign fibers, to produce subsequent yarn and textile quality. There are some problems in …
[HTML][HTML] Assessing the influence of sensor-induced noise on machine-learning-based changeover detection in CNC machines
VG Biju, AM Schmitt, B Engelmann - Sensors, 2024 - mdpi.com
The noise in sensor data has a substantial impact on the reliability and accuracy of (ML)
algorithms. A comprehensive framework is proposed to analyze the effects of diverse noise …
algorithms. A comprehensive framework is proposed to analyze the effects of diverse noise …
[HTML][HTML] Unleashing the power of artificial intelligence in phonon thermal transport: Current challenges and prospects
M Hu - Journal of Applied Physics, 2024 - pubs.aip.org
The discovery of advanced thermal materials with exceptional phonon properties drives
technological advancements, impacting innovations from electronics to superconductors …
technological advancements, impacting innovations from electronics to superconductors …
[HTML][HTML] Unraveling phase prediction in high entropy alloys: A synergy of machine learning, deep learning, and ThermoCalc, validation by experimental analysis
The phase formation in high entropy alloys (HEAs) presents a significant challenge due to
the complexity of their composition and the intricate interactions between multiple elements …
the complexity of their composition and the intricate interactions between multiple elements …
Physics-informed machine learning prediction of the martensitic transformation temperature for the design of “NiTi-like” high entropy shape memory alloys
The present study proposes a physics-informed machine learning (PIML) algorithm-based
approach aimed at predicting the martensitic transformation temperature (Ms) for the design …
approach aimed at predicting the martensitic transformation temperature (Ms) for the design …
[HTML][HTML] Machine learning based prediction of Young's modulus of stainless steel coated with high entropy alloys
N Radhika, M Sabarinathan, S Ragunath… - Results in …, 2024 - Elsevier
Abstract The High Entropy Alloy (HEA) coatings exhibit diverse properties contingent upon
their composition and microstructure, addressing current industrial requirements. Machine …
their composition and microstructure, addressing current industrial requirements. Machine …
Machine learning aided process design of Fe-Cr-Ni-Al/Ti multi-principal element alloys for excellent mechanical properties
K Xu, L Zhang, C Bai, J Tu, J Luo - Computational Materials Science, 2024 - Elsevier
Abstract Fe-Cr-Ni-Al/Ti multi-principal element alloys (MPEAs) with the good mechanical
properties were designed by utilizing machine learning (ML) methods in our previous work …
properties were designed by utilizing machine learning (ML) methods in our previous work …
[HTML][HTML] Application of machine learning approaches to predict ammonium nitrogen transport in different soil types and evaluate the contribution of control factors
B Feng, J Ma, Y Liu, L Wang, X Zhang, Y Zhang… - Ecotoxicology and …, 2024 - Elsevier
The loss of nitrogen in soil damages the environment. Clarifying the mechanism of
ammonium nitrogen (NH 4+-N) transport in soil and increasing the fixation of NH 4+-N after …
ammonium nitrogen (NH 4+-N) transport in soil and increasing the fixation of NH 4+-N after …
[HTML][HTML] Machine learning guided prediction of dynamic energy release in high-entropy alloys
F Zhao, Z Zhang, Y Ye, Y Li, S Li, Y Tang, S Bai - Materials & Design, 2024 - Elsevier
High-entropy alloy (HEA) type energetic structural materials (ESMs) offer exceptional
strength, adequate ductility and reactivity upon dynamic loading, thus demonstrating great …
strength, adequate ductility and reactivity upon dynamic loading, thus demonstrating great …
Prediction of storey drift for reinforced concrete structures subjected to pulse-like ground motions using machine learning classification models
Purpose Near-fault pulse-like ground motions have distinct and very severe effects on
reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near …
reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near …