Results 101 to 110 of about 5,903 (242)
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Rapid Assignment of Chemical Shifts From Crystal Structures in Solid‐State NMR
Chemical shift assignment in solids is a long and tedious process that relies on complex 1D and 2D NMR experiments. With prior knowledge of the 3D structure, this process can be significantly sped up by a Bayesian probabilistic assignment approach based on predicted chemical shifts.
Ruben Rodriguez‐Madrid +2 more
wiley +2 more sources
Limit theorems in free probability theory II
Chistyakov Gennadii, Götze Friedrich
doaj +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source
Abstract Crop insurance is undoubtedly an extremely valuable element in protecting agricultural businesses, but in many cases standard indemnity‐based products have had very low uptake due to high transaction costs elevating premiums to unaffordable levels.
Amogh Prakasha Kumar +2 more
wiley +1 more source
ABSTRACT This study investigates the rheological behavior of industrial phosphoric acids (H3PO4) produced at the JORF–LASFAR phosphoric plant in Morocco, with P2O5 concentrations of 18%, 29%, 42%, and 54%. Rheological measurements were performed using a rotary cylinder rheometer over a shear rate range of 1–1000 s−1.
Hamza Belbsir +6 more
wiley +1 more source

