Results 91 to 100 of about 2,848,958 (338)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Empirical and Kernel Estimation of the ROC Curve
Acta Universitatis Lodziensis. Folia Oeconomica, 2015 The paper presents chosen methods for estimating the ROC (Receiver Operating Characteristic) curve, including parametric and nonparametric procedures.
Aleksandra Katarzyna Baszczyńska
doaj
Advanced Functional Materials, EarlyView.This study introduces a novel chloro boron subphthalocyanine/polymer blend OFET sensor achieving 0.005 ppb limit of detection for ammonia at room temperature and high selectivity against similar amines. An original theoretical framework is proposed to describe the sensing mechanism, relating analyte molecular volume and Lewis basicity to sensor ...
Kavinraaj Ella Elangovan +6 more
wiley +1 more source
Estimation of Dynamic Networks for High-Dimensional Nonstationary Time Series
Entropy, 2019 This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes.
Mengyu Xu, Xiaohui Chen, Wei Biao Wu
doaj +1 more source
Wind Power Prediction Based on LSTM Networks and Nonparametric Kernel Density Estimation
IEEE Access, 2019 Wind energy is a kind of sustainable energy with strong uncertainty. With a large amount of wind power injected into the power grid, it will inevitably affect the security, stability and economic operation of the power grid.
Bowen Zhou +3 more
semanticscholar +1 more source
Advanced Functional Materials, EarlyView.Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +1 more source
Blind Image Deblurring via Local Maximum Difference Prior
IEEE Access, 2020 Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required.
Jing Liu +4 more
doaj +1 more source
Regularized system identification using orthonormal basis functions
, 2015 Most of existing results on regularized system identification focus on regularized impulse response estimation. Since the impulse response model is a special case of orthonormal basis functions, it is interesting to consider if it is possible to tackle ...
Chen, Tianshi, Ljung, Lennart
core +1 more source
Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?
Advanced Functional Materials, EarlyView.This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee +7 more
wiley +1 more source
A Two-Stage Plug-In Bandwidth Selection and Its Implementation in Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation [PDF]
The performance of a kernel HAC estimator depends on the accuracy of the estimation of the normalized curvature, an unknown quantity in the optimal bandwidth represented as the spectral density and its derivative.
Hirukawa Masayuki
core