Results 71 to 80 of about 325,728 (267)

A semi-Markov model with memory for price changes

, 2011
We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday returns are described by a discrete time homogeneous semi-Markov which depends also on a memory ...
D’Amico G Petroni F, Filippo Petroni, Guglielmo D’Amico, Limnios N   +3 more
core   +1 more source

Computational study of permeability in cardboard coating layers

AIChE Journal, EarlyView.
Abstract We develop a virtual material structure model based on a combination of tessellations and Gaussian random fields for a coating layer of paperboard used for packaging and designed to facilitate printing on the surface. To fit the model to tomographic image data acquired using combined focused ion beam and scanning electron microscopy (FIB‐SEM),
Sandra Barman, Torben Nilsson Pingel, Niklas Lorén, Tobias Gebäck, Eva Olsson, Aila Särkkä, Magnus Röding   +6 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

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

An empirical Bayes procedure for the selection of Gaussian graphical models

, 2011
A new methodology for model determination in decomposable graphical Gaussian models is developed. The Bayesian paradigm is used and, for each given graph, a hyper inverse Wishart prior distribution on the covariance matrix is considered.
Donnet, Sophie, Marin, Jean-Michel
core   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
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, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Variable-order sequence modeling improves bacterial strain discrimination for Ion Torrent DNA reads

BMC Bioinformatics, 2017
Background Genome sequencing provides a powerful tool for pathogen detection and can help resolve outbreaks that pose public safety and health risks. Mapping of DNA reads to genomes plays a fundamental role in this approach, where accurate alignment and ...
Thomas M. Poulsen, Martin Frith
doaj   +1 more source

Constructing Merger Trees that Mimic N-Body Simulations

, 2007
We present a simple and efficient empirical algorithm for constructing dark-matter halo merger trees that reproduce the distribution of trees in the Millennium cosmological $N$-body simulation. The generated trees are significantly better than EPS trees.
Amosov, Avishai Dekel, Bardeen, Benson, Birnboim, Bond, Bullock, Cole, Cole, Croton, Davis, Diemand, Eyal Neistein, Gao, Gottlöber, Governato, Harker, Hernquist, Kauffmann, Lacey, Lacey, Li, Mo, Navarro, Neistein, Neto, Prada, Press, Seljak, Sheth, Sheth, Somerville, Somerville, Springel, Springel, Van Den Bosch, Van Den Bosch, Wechsler, Zentner   +38 more
core   +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

Avoiding Overfitting in Variable-Order Markov Models: a Cross-Validation Approach

Higher$\text{-}$order Markov chain models are widely used to represent agent transitions in dynamic systems, such as passengers in transport networks. They capture transitions in complex systems by considering not only the current state but also the path of previously visited states. For example, the likelihood of train passengers traveling from Paris (
Secchini, Valeria, Garcia-Bernardo, Javier, Janský, Petr   +2 more
openaire   +2 more sources