Results 111 to 120 of about 25,017 (253)
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
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 +1 more
wiley +1 more source
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
On the Siegel zeros of quadratic fields and their applications
Razakarinoro, Faratiana Brice. 2024. On the Siegel zeros of quadratic fields and their applications. Unpublished doctoral dissertation. Stellenbosch : Stellenbosch University [online].
Razakarinoro, Faratiana Brice
core
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
A linear metric reconstruction by complex eigen-decomposition
This paper proposes a linear algorithm for metric reconstruction from projective reconstruction. Metric reconstruction problem is equivalent to estimating the projective transformation matrix that converts projective reconstruction to Euclidean ...
Hong, KS, Seo, Y
core
Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh +3 more
wiley +1 more source
This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem
Al-Hadithi, Basil M. +2 more
core +1 more source
Pre‐Curved Everting Robots With Embedded Steering Intelligence Fabricated by CO2 Laser Welding
Design and experimental demonstration of a laser welded growing robot for anatomically guided navigation. The robot follows an aortic arch phantom entering the branchiocephalic branch through steering by design. The figure shows the physical phantom setup, CAD defined weld geometry and full robot eversion.
Brandon Saldarriaga +5 more
wiley +1 more source
CSAKD: Determining Absolute Ligand Affinities From 19F NMR Chemical Shift Anisotropy
Affinity determination is crucial in drug discovery, yet remains difficult for weakly binding fragments. We introduce chemical shift anisotropy KD$K_{\text{D}}$ (CSAKD) by 19F$^{19}{\rm F}$ NMR relaxation experiments, a titration‐free method that requires no isotopic labeling.
Simon H. Rüdisser +2 more
wiley +2 more sources
Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source

