Results 211 to 220 of about 624,831 (326)

Productivity‐Driven Optimization of Laser Powder Bed Fusion Parameters for IN718 Superalloy: Process Control, Microstructure, and Mechanical Properties

Advanced Engineering Materials, EarlyView.
This study demonstrates how optimizing laser power, scanning speed, and hatching distance in laser powder bed fusion can boost the productivity of Inconel 718 manufacturing by up to 29% while maintaining mechanical integrity. The work delivers a validated process window and cost–time analysis, offering industry‐ready guidelines for efficient additive ...
Amir Behjat, Guido Barale, John Stavridis, Ehsan Norouzi, Jin‐Yoo Suh, Dong‐Ik Kim, Luca Iuliano, Abdollah Saboori   +7 more
wiley   +1 more source

Dissociation in cross-feature integration between behavioral and pupil dilation responses in auditory deviant detection. [PDF]

iScience
Fatemi N, Liao HI, Elhilali M.
europepmc   +1 more source

An Analysis of Finite-Memory Random Linear Coding on Packet Streams

International Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks, 2006
Desmond S. Lun, Payam Pakzad, Christina Fragouli, Muriel Médard, Ralf Koetter   +4 more
semanticscholar   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Accurate prediction of candidate lncRNAs associated with DNA damage response based on gene expression patterns from graph neural networks. [PDF]

Bioinform Adv
Shah S, Wang L.
europepmc   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

CancerSubtypeXplore: A Modular Platform for Multiomics Cancer Subtype Prediction and Biomarker Consensus Discovery. [PDF]

Comput Struct Biotechnol J
Jin D, Bian B, Saito Y.
europepmc   +1 more source

Understanding the Stochastic Nature of Process Parameter Development of Blown Powder Laser Beam Directed Energy Deposition Additive Manufacturing of Pure Molybdenum

Advanced Engineering Materials, EarlyView.
Identified through the use of statistical design of experiments and metallographic investigation, this study exposes the stochastic origins of intergranular cracks in blown powder laser beam directed energy deposition additive manufacturing of pure molybdenum. It further demonstrates a successful crack mitigation approach with direct correlation to the
Nathaniel J. Lies, Daniel E. Driemeyer, Aaron P. Stebner   +2 more
wiley   +1 more source

Digital Twin-Enabled Waveform Optimization for VHF Radio Communication Systems. [PDF]

Sensors (Basel)
Zhong C, Liu B, Zhu W, Wang B, Tan Y, Wang X.   +5 more
europepmc   +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