Results 81 to 90 of about 14,306 (259)

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

CHPFL: Clustered adaptive hierarchical federated learning for edge-level personalization

High-Confidence Computing
Federated learning faces challenges with non-IID data distributions, often resulting in suboptimal performance for individual clients with the global model. To address this issue, we propose a clustered hierarchical personalized federated learning (CHPFL)
Lihua Song, Jing Li, Honglu Jiang, Shuhua Wei, Yufei Guo   +4 more
doaj   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

Canadian Journal of Statistics, EarlyView.
Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina, Alejandro Román Vásquez, Graciela González Farías, Gabriel Escarela   +3 more
wiley   +1 more source

Large parameter asymptotic analysis for homogeneous normalized random measures with independent increments

Canadian Journal of Statistics, EarlyView.
Abstract Homogeneous normalized random measures with independent increments represent a broad class of Bayesian nonparametric priors and thus are widely used. In this article, we obtain the strong law of large numbers, the central limit theorem (CLT), and the functional central limit theorem (fCLT) of such measures when the concentration parameter a ...
Junxi Zhang, Shui Feng, Yaozhong Hu
wiley   +1 more source

The SIR Model in a Moving Population: Propagation of Infection and Herd Immunity

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT In a collection of particles performing independent random walks on Zd$\mathbb {Z}^d$ we study the spread of an infection with SIR dynamics. Susceptible particles become infected when they meet an infected particle. Infected particles heal and are removed at rate ν$\nu$.
Duncan Dauvergne, Allan Sly
wiley   +1 more source

Edge-Federated Learning-Based Intelligent Intrusion Detection System for Heterogeneous Internet of Things

IEEE Access
Distributed denial of service (DDoS) is an awful cyber threat, becoming more prevalent with mature heterogeneous IoT (HetIoT) applications like intelligent agriculture, wearables, and self-driving cars. Developing intelligent intrusion detection systems (
Shalaka S. Mahadik, Pranav M. Pawar, Raja Muthalagu   +2 more
doaj   +1 more source

Fintech Policy and the Rise of Green Technological Inventions

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Technological transformation can enhance enterprises' green invention by promoting knowledge spillovers, alleviating financial constraints, and supporting innovative business models. Within this framework, our study investigates the effect of technological infrastructure construction on green technology invention, using the ‘Fintech China ...
Tao Huang, Qurat ul Ain, Tahir Yousaf, Kaiyang Zhong   +3 more
wiley   +1 more source

VINO_EffiFedAV: VINO with efficient federated learning through selective client updates for real-time autonomous vehicle object detection

Results in Engineering
The advancement of autonomous vehicle technology relies heavily on sophisticated machine-learning models that facilitate real-time object detection and classification.
K. Vinoth, P. Sasikumar
doaj   +1 more source

2D Implementation of Kinetic‐Diffusion Monte Carlo in Eiron

Contributions to Plasma Physics, EarlyView.
ABSTRACT Particle‐based kinetic Monte Carlo simulations of neutral particles are one of the major computational bottlenecks in tokamak scrape‐off layer simulations. This computational cost comes from the need to resolve individual collision events in high‐collisional regimes.
Oskar Lappi, Emil Løvbak, Thijs Steel, Giovanni Samaey   +3 more
wiley   +1 more source

Complex Versus Parsimonious Site‐Based Stochastic Ground Motion Models: Which One Is Better?

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Stochastic ground motion models (GMMs) provide a probabilistic representation of seismic input and are increasingly important for uncertainty quantification (UQ) in earthquake engineering. This study focuses on site‐based stochastic GMMs, which learn the statistical features of selected datasets of seismic records and generate statistically ...
Maijia Su, Mayssa Dabaghi, Marco Broccardo   +2 more
wiley   +1 more source