Results 71 to 80 of about 151,138 (245)

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

Advanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith, Ryan D. McKenzie, Alban Joseph, Robert L. Stamps, Rair Macêdo   +4 more
wiley   +1 more source

Two approaches for effective modelling of rain-rate time-series for radiocommunication system simulations [PDF]

, 2006
The paper presents a model which allows to synthetically generate rain rate time-series for a fixed location. Rain rate time-series are very much correlated with signal attenuation in Ka band and above and, thus, enable to realistically simulate ...
Alasseur, Clémence, Fiebig, Uwe-Carsten, Fontán, Fernando Perez, Husson, Lionel, Mariño, P., Núñez, A.   +5 more
core  

Directed nonabelian sandpile models on trees

, 2015
We define two general classes of nonabelian sandpile models on directed trees (or arborescences) as models of nonequilibrium statistical phenomena. These models have the property that sand grains can enter only through specified reservoirs, unlike the ...
Ayyer, Arvind, Schilling, Anne, Steinberg, Benjamin, Thiery, Nicolas M.   +3 more
core   +3 more sources

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +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

Integrated hydrological modeling and water resource assessment in the Mayurakshi River Basin: A comprehensive study from historical data to future predictions

Geosystems and Geoenvironment
This study employs the SWAT hydrologic model to integrate climatological and hydrological processes for an in-depth analysis of the Mayurakshi River Basin.
Swetasree Nag, Malabika Biswas Roy, Pankaj Kumar Roy   +2 more
doaj   +1 more source

Automatic and Accurate Measurement of High Precision Thread Based on AA R2Unet and HMM

Nantong Daxue xuebao. Ziran kexue ban, 2021
The thread measurement methods based on machine vision are easily disturbed by the environment(e.g. dust,iron filings, oil stains, etc.), resulting in inaccurate measurement results. This paper improves the R2 Unet model by adding the Attention mechanism,
ZHANG Kun, LI Zijie, QU Hongjun, WU Jianguo, HUA Liang   +4 more
doaj   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models [PDF]

, 2015
In this paper, we consider the filtering and smoothing recursions in nonparametric finite state space hidden Markov models (HMMs) when the parameters of the model are unknown and replaced by estimators.
Corff, Sylvain Le, De Castro, Yohann, Gassiat, Elisabeth   +2 more
core