Results 61 to 70 of about 85,077 (292)

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset

Energies, 2018
Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera.
Ariana Moncada, Walter Richardson, Rolando Vega-Avila   +2 more
doaj   +1 more source

Quantitative Comparison of Tree Ensemble Learning Methods for Perfume Identification Using a Portable Electronic Nose

Applied Sciences, 2022
Perfume identification (PI) based on an electronic nose (EN) can be used for exposing counterfeit perfumes more time-efficiently and cost-effectively than using gas chromatography and mass spectrometry instruments.
Mengli Cao, Xingwei Ling
doaj   +1 more source

Multimaterial Approach to Improve the Mechanical Properties of a Novel Modified Auxetic Reentrant Honeycomb Structure

Advanced Engineering Materials, EarlyView.
A multimaterial approach is introduced to improve upon auxetic structures by combining two different polymers into the same reentrant honeycomb structure via additive manufacturing. The deformation behavior as well as the resulting Poisson's ratio are thereby improved significantly.
Alexander Engel, Oraib Al‐Ketan, Anne Jung   +2 more
wiley   +1 more source

Stratum Corneum‐Inspired Zwitterionic Hydrogels with Intrinsic Water Retention and Anti‐Freezing Properties for Intelligent Flexible Sensors

Advanced Functional Materials, EarlyView.
A novel stratum corneum‐inspired zwitterionic hydrogel is developed for intelligent, flexible sensors, featuring intrinsic water retention and anti‐freezing properties. The quasi‐gel, composed of hygroscopic polymers and bound water, maintains its softness across a wide range of humidity.
Meng Wu, Chenyu Qiao, Peng‐Fei Sui, Jing‐Li Luo, Zuoli Li, Yi Cao, Renjun Pei, Xuwen Peng, Hongbo Zeng   +8 more
wiley   +1 more source

Scaling‐Up of Structural Superlubricity: Challenges and Opportunities

Advanced Functional Materials, EarlyView.
At increasing length‐scales, structural superlubricity (SSL) faces challenges from physical and chemical energy dissipation pathways. This study reviews recent experimental and theoretical progress on these challenges facing the scaling‐up of SSL, as well as perspectives on future directions for realizing and manipulating macroscale superlubricity ...
Penghua Ying, Xiang Gao, Diana Berman, Oded Hod, Michael Urbakh   +4 more
wiley   +1 more source

Decision Tree Instability and Active Learning [PDF]

, 2007
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable --- they can produce drastically different hypotheses from training sets that differ just slightly. This instability undermines the objective of extracting knowledge from the trees.
Robert C. Holte, Kenneth Dwyer
openaire   +2 more sources

Carbon Nanotube 3D Integrated Circuits: From Design to Applications

Advanced Functional Materials, EarlyView.
As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu, Yun Sun, Dong‐Ming Sun, Hui‐Ming Cheng   +3 more
wiley   +1 more source

Roulette‐Inspired Physical Unclonable Functions: Stochastic yet Deterministic Multi‐Bit Patterning through the Solutal Marangoni Effect

Advanced Functional Materials, EarlyView.
Geometric multi‐bit patterning based on dynamic wetting and dewetting phenomena creates roulette‐like Physical Unclonable Function (PUF) labels with stochastic yet deterministic properties. This method leverages the solutal‐Marangoni effect for high randomness while achieving deterministic multinary patterns through polygonal confinement of binary ...
Yeongin Cho, Jeongsu Pyeon, Hanhwi Jang, Gwangsik Mun, Jaimin Kang, Byong‐Guk Park, Geon Yeong Kim, Hyoungsoo Kim, Yeon Sik Jung   +8 more
wiley   +1 more source