Results 231 to 240 of about 2,530,049 (324)

A novel improved high-gain quadratic DC-DC converter based on two synchronous power switches and a two-winding coupled inductor. [PDF]

Sci Rep
Paşaoğlu A, Nadermohammadi A, Shams H, Sedighnejad H.   +3 more
europepmc   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

AutoMamba: Efficient Autonomous Driving Segmentation Model with Mamba. [PDF]

Sensors (Basel)
Sun H, Li Z, Zhu S.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

QSPR analysis of anticancer drugs using the Euler-Sombor index and theoretical insights on its minimum value for unicyclic graphs. [PDF]

Sci Rep
Shetty S, Rakshith BR, Udupa NVS.
europepmc   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

GEORCE: a fast new control algorithm for computing geodesics. [PDF]

Inf Geom
Rygaard FM, Hauberg S.
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Characterisation of quadratic spaces over the Hilbert field by means of the orthogonality relation. [PDF]

J Geom
Korbelář M, Paseka J, Vetterlein T.
europepmc   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source