Results 101 to 110 of about 14,128,135 (294)
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Kajian Model Hidden Markov untuk Menduga Volatilitas Indeks Harga Saham
Volatility is a measure of uncertainty, which is useful for investor to plan a good investment strategy. The problem is that volatility is unobservable, and estimating volatility is not a trivial task.
Baist, Abdul
core
Modelling the profitability of credit cards by Markov decision processes
This paper derives a model for the profitability of credit cards, which allow lenders to find the optimal dynamic credit limit policy. The model is a Markov decision process, where the states of the system are based on the borrower's behavioural score ...
Thomas, Lyn C., So, Mee Chi
core +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
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 +5 more
wiley +1 more source
results of clinical trials demonstrate that selective vitamin D receptor agonist paricalcitoldecreases proteinuria in patients with chronic kidney disease (CKD) and hyperparathyreosis.
A. V. Rudakova
doaj
Bhavesh Lakhotia,1 Ronan Mahon,1 Florian S Gutzwiller,2 Andriy Danyliv,1 Ivan Nikolaev,2 Praveen Thokala3 1Novartis Ireland Limited, Dublin, Ireland; 2Novartis Pharma, Basel, AG, Switzerland; 3PT Health Economics Ltd, Sheffield, UKCorrespondence: Ronan ...
Lakhotia B +5 more
doaj
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
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 +4 more
wiley +1 more source
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
Forecasting Value-at-Risk Using the Markov-Switching ARCH Model [PDF]
This paper analyzes the application of the Markov-switching ARCH model (Hamilton and Susmel, 1994) in improving value-at-risk (VaR) forecast. By considering a mixture of normal distributions with varying variances over different time and regimes, we find
Wei-Ting Tang, Yin-Feng Gau
core
Neily Zakiyah,1,2 Rano K Sinuraya,1– 3 Arif SW Kusuma,2,4 Auliya A Suwantika,1,2,5 Keri Lestari1,2 1Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, Indonesia; 2Center of Excellence in Higher ...
Zakiyah N +4 more
doaj

