Results 71 to 80 of about 55,666 (218)

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

Advanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning, Lu Lu, Sophie Leanza, Ruike Renee Zhao   +3 more
wiley   +1 more source

FedDrip: Federated Learning With Diffusion-Generated Synthetic Image

IEEE Access
In the realm of machine learning in healthcare, federated learning (FL) is often recognized as a practical solution for addressing issues related to data privacy and data distribution.
Karin Huangsuwan, Timothy Liu, Simon See, Aik Beng Ng, Peerapon Vateekul   +4 more
doaj   +1 more source

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

Advanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BMC Bioinformatics
Background The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive.
Bertil Schmidt, Felix Kallenborn, Alejandro Chacon, Christian Hundt   +3 more
doaj   +1 more source

Multi-process thermodynamic graph learning for 2D fluid simulation

Virtual Reality & Intelligent Hardware
Solving partial differential equations (PDEs) for fluid simulation is computationally expensive, especially when dealing with complex geometries and high-resolution meshes.
Yidi WANG, Aik Beng NG, Simon SEE, Zhengkui WANG, Frank GUAN   +4 more
doaj   +1 more source

Quantum simulation of CO2 chemisorption in an amine-functionalized metal–organic framework [PDF]

AIP Advances
We perform a series of calculations using simulated quantum processing units (QPUs), accelerated by the NVIDIA CUDA-Q platform, focusing on a molecular analog of an amine-functionalized metal–organic framework, a promising class of materials for CO2 ...
Jonathan R. Owens, Marwa H. Farag, Pooja Rao, Annarita Giani   +3 more
doaj   +1 more source

Arterial Blood‐Mediated Deep‐Tissue Photoacoustic Oximetry

Advanced Science, EarlyView.
The arterial prior method (APM+) for photoacoustic oximetry is introduced, which leverages the high arterial blood oxygenation to calibrate the fluence at the artery and estimate the oxygenation of the surrounding tissue, thus circumventing the spectral coloring problem. APM+’s accuracy and consistency are shown in a series of phantom and in vivo human
Karteekeya Sastry, Junhao Zhu, Joshua Olick‐Gibson, Li Lin, Lei Li, Jigmi Basumatary, Yang Zhang, Lihong V. Wang   +7 more
wiley   +1 more source

Solar Irradiance Forecasting Using a Hybrid Quantum Neural Network: A Comparison on GPU-Based Workflow Development Platforms

IEEE Access
Modern renewable power operations can be enhanced by integrating deep neural networks, particularly for forecasting solar irradiance. Recent advancements in quantum computing have shown potential improvements in classical deep neural networks.
Ying-Yi Hong, Dylan Josh Domingo Lopez, Yun-Yuan Wang   +2 more
doaj   +1 more source

Multiscale Coupling From Mastication to Retronasal Aroma Perception: The PG‐DTCFN Model and Multiphysics Simulation

Advanced Science, EarlyView.
Using grilled lamb skewers as a model system, this work builds a multiscale coupling framework from oral processing to retronasal aroma perception, reveals dual‐kinetic release patterns and Electroencephalogram‐characterized central encoding features, and proposes an interpretable physics‐guided deep learning model validated by multiphysics simulation,
Che Shen, Xiongfeng He, Zihao Li, Zidong Chen, Jiajin Sun, Xinyu Jiang, Yunhui Zhang, Lizhang Wu, Ran Wang, Jingnan Lu, Bo Wang, Kezhou Cai, Baocai Xu   +12 more
wiley   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source