Results 101 to 110 of about 1,704,441 (287)

Multivariate phase‐dependent optimization of bioprocesses boosts performance and quality—Why timing (of exposure) matters

open access: yesBiotechnology Progress, EarlyView.
Abstract Applying a single parameter set to describe complex mammalian kinetics often is too simplistic, as it fails to capture sensitive cell‐to‐environment interactions that may be exploited to optimize production performance. To resolve this time dependency, intra‐experimental parameter shifts as part of design of dynamic experiments (DoDE) can be ...
Samuel Kienzle   +7 more
wiley   +1 more source

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

open access: yesIEEE 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   +2 more
doaj   +1 more source

Analyzing the Impact of Non-IID Data on IoT-Enabled Federated Learning for ECG Arrhythmia Detection

open access: yes
The integration of Federated Learning (FL) in the Internet of Medical Things (IoMT) represents a cutting-edge solution, enabling the training of Artificial Intelligence (AI) models directly on edge devices without the need to share sensitive patient ...
Massimo De Vittorio   +6 more
core   +1 more source

Jackknife bias‐corrected variance estimation for the generalized regression estimator

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

Non-IID latent variable models [PDF]

open access: yes, 2019
University of Technology Sydney. Faculty of Engineering and Information Technology.Latent Variable Model (LVM) is the statistical model that aims to uncover hidden information behind data.
Do, Trong Dinh Thac
core  

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

open access: yesCanadian 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

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

open access: yesResults 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

Feature matching data synthesis for non-IID federated learning

open access: yes
Federated learning (FL) has emerged as a privacy-preserving paradigm that trains neural networks on edge devices without collecting data at a central server.
Sun, Yuchang   +5 more
core   +1 more source

Home - About - Disclaimer - Privacy