Results 131 to 140 of about 5,787,304 (258)
A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration
Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti +6 more
wiley +1 more source
ABSTRACT Sustainability labels can help support consumers select more socially and environmentally friendly options, thereby enhancing returns for conscientious producers and promoting the transition to a more sustainable food system. However, consumer confusion regarding labels' meaning undermines their effectiveness.
Monika Hartmann +4 more
wiley +1 more source
Is Precision Agriculture Technology Adoption Persistently Overestimated?
ABSTRACT Precision agriculture is sometimes assumed to diffuse steadily over time, and industry planning frequently extrapolates early adoption trends forward. This study evaluates the accuracy of such expectations by comparing agricultural input dealers' forecasts of future service offerings with the actual levels of offerings that dealerships ...
Trey Malone +5 more
wiley +1 more source
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin +2 more
wiley +1 more source
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
"Mixed Effects Prediction under Benchmarking and Applications to Small Area Estimation" [PDF]
The empirical best linear unbiased predictor (EBLUP) in the linear mixed model (LMM) is useful for the small area estimation in the sense of increasing the precision of estimation of small area means.
Tatsuya Kubokawa
core
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification
This paper presents a new Proportionate Normalized Least Mean Square (PNLMS) adaptive algorithm using a soft maximum operator for sparse system identification.
Mehdi Bekrani, Hadi Zayyani
doaj
Difference based Ridge and Liu type Estimators in Semiparametric Regression Models [PDF]
We consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the partial linear semiparametric regression model, y = Xβ + f + ε.
Wolfgang Karl Härdle +2 more
core
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source

