Results 131 to 140 of about 36,988 (280)

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
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

Estimation of mean square error of empirical best linear unbiased predictors under a random error variance linear model

, 1992
A linear model with random effects, μi, and random error variances, σi, is considered. The linear Bayes estimator or the best linear unbiased predictor (BLUP) of μi is first obtained, and then the unknown parameters in the model are estimated to arrive ...
Kleffe, J, Rao, J.N.K
core   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
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, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Particle Swarm Optimisation Aided MIMO Multiuser Transmission Designs

, 2012
Bio-inspired computational methods have found wide-ranging applications in signal processing and other walks of engineering. The main attraction of adopting bio-inspired computational intelligence algorithms is that they may facilitate global or near ...
W. Yao, S. Chen, Chen, Sheng, L. Hanzo, Hanzo, Lajos, Yao, Wang   +5 more
core  

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
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, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Empowering smart cities: Leveraging advanced forecasting models for proactive rainfall prediction and resilient urban planning

AIP Advances
This study highlights the pivotal role of rainfall prediction within the dynamic landscape of smart cities. Accurate rainfall forecasts in such urban environments are foundational for bolstering infrastructure resilience, optimizing resource allocation ...
Abdulnoor A. J. Ghanim, Ahmad Shaf, Muhammad Irfan, Fawaz Alzabari, Muawia Abdelkafi Magzoub Mohamed Ali   +4 more
doaj   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Mean-squared error calculations for the subband adaptive filter system,” [PDF]

, 1995
In this paper we develop theoretical equations for calculating the reconstructed mean-square error (MSE), E
Delores M Etter, II Phillip L De León
core  

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source