Results 81 to 90 of about 16,855 (254)
Towards Cross-Project Defect Prediction with Imbalanced Feature Sets
CoRR, 2014 10 pages, 8 figures, 7 ...
Peng He, Bing Li 0010, Yutao Ma
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Advanced Engineering Materials, EarlyView.Dislocation cutting of γ′ precipitates in Ni‐based superalloys is investigated by linking atomistic simulations with discrete dislocation dynamics. The critical cutting stress is shown to be governed by the antiphase boundary energy, while line tension effects promote edge‐preferred cutting.
Frédéric Houllé +9 more
wiley +1 more source
An Abstract Syntax Tree Encoding Method for Cross-Project Defect Prediction
IEEE Access, 2019 In the last few years, with the development of deep learning theory, researchers have tried to introduce the method of artificial intelligence into the field of software defect prediction (SDP) to improve its prediction effect.
Ziyi Cai, Lu Lu, Shaojian Qiu
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
A Systematic Study of Cross-Project Defect Prediction With Meta-Learning
CoRR, 2018 The prediction of defects in a target project based on data from external projects is called Cross-Project Defect Prediction (CPDP). Several methods have been proposed to improve the predictive performance of CPDP models. However, there is a lack of comparison among state-of-the-art methods.
Faimison Rodrigues Porto +3 more
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Advanced Engineering Materials, EarlyView.Grain boundary triple junctions are an essential ingredient of the microstructure of polycrystalline materials. In this study, a triple junction is observed using atomic‐resolution scanning transmission electron microscopy and characterized. Computer simulations reveal that the junction has a dislocation character that is determined by the joining ...
Tobias Brink +4 more
wiley +1 more source
CLEI Electronic Journal, 2016 The defect prediction models can be a good tool on organizing the project´s test resources. The models can be constructed with two main goals: 1) to classify the software parts - defective or not; or 2) to rank the most defective parts in a decreasing ...
Faimison Porto, Adenilso da Silva Simao
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Advanced Engineering Materials, EarlyView.Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati +11 more
wiley +1 more source
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
Advanced Engineering Materials, EarlyView.This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Manufacturing problems such as heat treatment‐induced cracking hinder the widespread application of the laser powder bed fusion (LPBF) process to superalloys. In this study, cracks in the LPBF components of Inconel 738LC superalloy are characterized after heat treatment at various temperature ranges, revealing two distinct cracking behaviors.
Kosuke Kuwabara +4 more
wiley +1 more source