Results 61 to 70 of about 61,045 (270)

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

EVALUATION OF SVR AND RANDOM FOREST MODELS FOR ACCURATE PREDICTION OF ELECTRONIC FUEL INJECTOR BEHAVIOR IN COMMON-RAIL SYSTEMS [PDF]

Scientific Journal of Silesian University of Technology. Series Transport
In this study, machine learning algorithms were applied to predict the main injection quantity in a high-pressure common rail system on a diesel engine test bench.
Quyet TA DUC, Khoa NGUYEN XUAN, Nghia NGUYEN TUAN, Vinh NGUYEN THANH, Manh LE DINH, Hung TRINH DUY   +5 more
doaj   +1 more source

The effectiveness of assessment instruments in measuring change in persons with an intellectual disability who have sexually offended [PDF]

, 2010
The present research was designed to examine a set of assessment measures for their effectiveness in evaluating risk and treatment needs in a small sample of intellectually disabled sex offenders (IDSOs).
Burrett, Vanessa Mary
core  

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Predicting the capillary water absorption values of building stones by hybrid models

Journal of Applied Science and Engineering
The determination of rock’s Capillary water absorption (CWA) requires extensive and complex empirical investigations, while forecasting algorithms could reduce the cost and time required.
Gang Li, Yufei Fu, Zixin Deng, Yuan Huang   +3 more
doaj   +1 more source

Non-invasive quantification of liver fibrosis regression following successful treatment of chronic hepatitis C with direct acting antivirals

Romanian Journal of Laboratory Medicine, 2017
Introduction. The past years have revolutionized the treatment of hepatitis C virus (HCV) infection, with high rates of sustained virologic response (SVR). Furthermore, liver fibrosis has recently been redefined as a dynamic, reversible process. Methods.
Nițescu Maria, Vâjâitu Cristina, Săndulescu Oana, Streinu-Cercel Adrian, Pițigoi Daniela, Preoțescu Liliana Lucia, Streinu-Cercel Anca   +6 more
doaj   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

Advanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu, Peiling Xie, Ruitong Song, Banghan Liu, Rui Guo, Jiu‐an Lv   +5 more
wiley   +1 more source

Non‐Buckling Stacks of Nanocarbon Molecules

Angewandte Chemie, EarlyView.
A nanometer‐sized nanocarbon molecule with a central octagon was synthesized by optimizing a tetrameric macrocyclization via concentration‐dependent yield analysis (CYAN). The slightly contorted molecular structure was found to be frozen in a dimeric stack in solution, whereas dissociation into monomers liberated the molecule to undergo buckling ...
Koki Ikemoto, Reijiro Yamamoto, Renki Sakai, Yuzuka Shoji, Shunji Takemura, Elisa Nobre, Toshiya M. Fukunaga, Xinyi Xiao, Hiroyuki Isobe   +8 more
wiley   +2 more sources

HKF-SVR Optimized by Krill Herd Algorithm for Coaxial Bearings Performance Degradation Prediction

Sensors, 2020
In real industrial applications, bearings in pairs or even more are often mounted on the same shaft. So the collected vibration signal is actually a mixed signal from multiple bearings.
Fang Liu, Liubin Li, Yongbin Liu, Zheng Cao, Hui Yang, Siliang Lu   +5 more
doaj   +1 more source