Results 91 to 100 of about 117,002 (264)

A just-in-time software defect prediction method based on data augmentation

Nantong Daxue xuebao. Ziran kexue ban
Just-in-time (JIT) software defect prediction aims to predict whether code commits during project development and maintenance will introduce defects.In the field of JIT software defect prediction research,model training relies on high-quality datasets ...
YANG Fan; XIA Hongling
doaj   +1 more source

Augmented Reality Guided Aerodynamic Sampling

AIAA SCITECH 2024 Forum
<p>JH developed the system, created the code base, and implemented the data model. Additionally, JH authored themanuscript. VC and FPC contributed to refining the data model and provided valuable guidance throughout the project.The project, conducted under the chair of TR, benefitted from TR’s conceptual insights and discussions.
Humml, Julian M., Cohen, Victor, Perez-Cruz, Fernando, Gharib, Morteza, Rösgen, Thomas   +4 more
openaire   +1 more source

β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations

Advanced Biology, Volume 9, Issue 3, March 2025.
Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio, B. Spedicato, G. Corallo, A. Inguscio, M. Greco, D. Musarò, D. Vergara, A. F. Muro, G. De Sabbata, L. R. Soria, N. Brunetti Pierri, M. Maffia   +11 more
wiley   +1 more source

Specific emitter identification under extremely small sample conditions via chaotic integration

Electronics Letters
As a potential solution to improve wireless security, specific emitter identification is a lightweight access authentication technology. However, the existed deep learning‐based specific emitter identification methods are highly dependent on the training
Haotian Zhang, Yuan Jiang, Lei Zhao, Bo Peng   +3 more
doaj   +1 more source

Augmenting GAIL with BC for sample efficient imitation learning

, 2020
Imitation learning is the problem of recovering an expert policy without access to a reward signal. Behavior cloning and GAIL are two widely used methods for performing imitation learning. Behavior cloning converges in a few iterations but doesn't achieve peak performance due to its inherent iid assumption about the state-action distribution.
Rohit Jena, Changliu Liu, Katia P. Sycara   +2 more
openaire   +3 more sources

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Generative Dual-Modal Data Augmentation for Motor Fault Diagnosis Under Sample Imbalance

Machines
This study investigates class imbalance in motor fault diagnosis. Fault samples, especially those at different severity levels, are often much fewer than healthy samples.
Ganxin Jie, Cailiang Zhang, Junqing Ma, Yang Yang, Chuan Chen   +4 more
doaj   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Rafting of Ni‐Based Superalloys Under Multiaxial Load as Understood by Phase‐Field Simulations and Critical Experiments

Advanced Engineering Materials, EarlyView.
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan, David Bürger, Gunther Eggeler, Oleg Shchyglo, Ingo Steinbach, Muhammad Adil Ali   +5 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source