Results 81 to 90 of about 158,004 (250)

Leveraging L-BFGS Optimization and Activation Functions in Multi-Layer Perceptron for Small-Scale Credit Risk Assessment Dataset

Transactions on Informatics and Data Science
The urgent need for accurate credit risk models often clashes with the practical reality of operating with small, imbalanced datasets, where standard deep learning configurations can be inefficient. This research addresses the critical gap in optimizing
Ngọc Thiện Nguyễn
doaj   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

High-precision non-contact probes based on spectral confocal technology

Journal of Measurement Science and Instrumentation, 2023
To solve the problems of small measurement range and poor accuracy of the spectral confocal non-contact probes, a four-piece lens group with a large measurement range is designed.
LI Haiteng, LI Xinghua
doaj  

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

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

Lightweight CNN SE transformer for robust weed classification with optimizer aware performance

Scientific Reports
During the early growth stages of crops, the weeds present can severely affect crop yields. Accurate and fast identification of the types of weeds present using robots can help mitigate this problem, allowing agronomists and farmers to employ more ...
Priyadharshini G, Vetriselvi T
doaj   +1 more source

Old Testament hospitality as reciprocity, Adam Smith and business ethics

HTS Teologiese Studies/Theological Studies
This article aims to underscore the progression of Old Testament hospitality as reciprocity for moral guidance and, specifically, business ethics in contemporary society.
Mark Rathbone
doaj   +1 more source

Trendsetters and imagination

Aisthema: International Journal, 2021
This paper presents a reconstruction and interpretation of the process of change in Adam Smith’s philosophy basing on the example of changes in fashion. I shall focus on the role of imagination, as well as on the role of the wealthy in the process.
Anna Markwart
doaj  

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +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