Results 131 to 140 of about 1,986,261 (302)

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

Biclustering Gene Expression Data with Subspace Evolution

Algorithms
Biclustering is crucial for gene expression data analysis, but evolutionary algorithm-based methods often suffer from high computational costs. To address this, we propose a novel subspace evolution-based biclustering method that significantly reduces ...
Jianjun Sun, Bin Jiang, Xinyi Zhang, Pengyu Zhang, Qin Yi   +4 more
doaj   +1 more source

Evaluating a Standard Benchmark for Gene Prioritization: The InheriNext® Algorithm’s Integration of Genomic and Phenotypic Information

Abstract This study presents a comprehensive benchmark analysis of InheriNext ® , a domain-specific, AI-powered tool designed for phenotype-driven pathogenic variant prioritization.
Ju-Yuan Chang, Kuan-Tsung Li, Yu-Shen Tsai, Michael Kubal, Aaron M. Hamby, Naomi Thomson, Jonathan Sheridan, Shiloh Barfield, Randy Rutz, Frank S. Ong, Ramon Felciano, Scott Kahn, Shao-Min Wu   +12 more
openaire   +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

Routing and Scheduling in Time-Sensitive Networking by Evolutionary Algorithms

Biomimetics
Routing and scheduling in Time-Sensitive Networking (TSN) is an NP-hard problem. In this paper, we propose a novel routing and scheduling approach for TSN based on evolutionary algorithm.
Zengkai Wang, Weizhi Liao, Xiaoyun Xia, Zijia Wang, Yaolong Duan   +4 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

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, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Proteins Combined Score Prediction Based on Improved Gene Expression Programming Algorithm and Protein–Protein Interaction Network Characterization

IET Systems Biology
Predicting the combined score in protein–protein interaction (PPI) networks represents a critical research focus in bioinformatics, as it contributes to enhancing the accuracy of PPI data and uncovering the inherent complexity of biological systems ...
Sicong Huo, Pengying Deng, Jie Zhou, Tao Lu, Qingnian Li, Xiaowei Wang   +5 more
doaj   +1 more source

3D Hydrodynamic Flow Lithography

Advanced Functional Materials, EarlyView.
ABSTRACT Continuous‐ and stop‐flow lithography are widely used to fabricate multi‐dimensional microstructures whose cross‐sectional morphology is dictated by the flow profile of multiple co‐flowing streams. Here, we introduce three‐dimensional hydrodynamic flow lithography (3D HFL), a platform for programmable generation of multi‐layered flow profiles ...
Yiying Zou, Mehmet Akif Sahin, Muhammad Zia Ullah Khan, Muhammad Usman Akhtar, Daniel Stoecklein, Ghulam Destgeer   +5 more
wiley   +1 more source