Results 141 to 150 of about 2,103,105 (303)

Exponentiated gamma constant-stress partially accelerated life tests with unified hybrid censored data: Statistical inferences

open access: yesAlexandria Engineering Journal
This study considers one of the partially accelerated life testing models, mainly a constant-stress approach with unified hybrid censored data. The data represents the lifetime of units following the exponentiated gamma distribution (EGD). The estimation
Afaf Alrashidi   +7 more
doaj   +1 more source

On consistency of nonparametric normal mixtures for Bayesian density estimation. [PDF]

open access: yes
The past decade has seen a remarkable development in the area of Bayesian nonparametric inference both from a theoretical and applied perspective. As for the latter, the celebrated Dirichlet process has been successfully exploited within Bayesian mixture
Antonio Lijoi   +2 more
core  

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

open access: yesAdvanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais   +32 more
wiley   +1 more source

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

open access: yesAdvanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang   +4 more
wiley   +1 more source

Uncertainty analysis of varying inertia estimation based on Bayesian method

open access: yesInternational Journal of Electrical Power & Energy Systems
Power system inertia is important for maintaining power system frequency stability. Because of the integration of renewable energy sources (RESs) and the complexity of power system frequency response, the power system inertia response becomes intricate ...
Dongdong Li, Wei Hua, Yang Mi
doaj   +1 more source

A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation [PDF]

open access: yes
Financial time series analysis deals with the understanding of data collected on financial markets. Several parametric distribution models have been entertained for describing, estimating and predicting the dynamics of financial time series ...
Concepción Ausín   +2 more
core  

A Robotic Testing Platform for Pipelined Discovery of Resilient Dielectric Elastomer Actuators

open access: yesAdvanced Science, EarlyView.
This work introduces a robotic testing platform enabling high‐throughput, multi‐parameter lifetime mapping of linear dielectric elastomer actuators (DEAs). By integrating programmable high‐voltage control and automated electromechanical measurements, the system identifies material and operating conditions that double actuator lifetime.
Ang (Leo) Li   +10 more
wiley   +1 more source

Bayesian parameter estimation and failure time prediction under double Type-II hybrid censoring for the generalized inverse exponential distribution

open access: yesAlexandria Engineering Journal
This study examines parameter estimation and failure time prediction for products following the Generalized Inverse Exponential Distribution (GIED) under double Type-II hybrid censored data.
Shi Wei, Guoyuan He, Dalong Mo
doaj   +1 more source

Machine Learning of Temperature‐Dependent Chemical Kinetics Using Parallel Droplet Microreactors

open access: yesAdvanced Science, EarlyView.
An integrated droplet microfluidics and machine learning framework enables high‐throughput characterization of temperature‐dependent reaction kinetics. Time‐resolved measurements from thousands of droplets train Neural ODE models that accurately predict nonlinear reaction dynamics across diverse thermal environments, bridging large‐scale ...
Mamoru Saita, Yutaka Hori
wiley   +1 more source

Perceived Time Shapes Physical Fatigue Accumulation and Its Neural Oscillatory Correlates

open access: yesAdvanced Science, EarlyView.
Can a clock change the course of physical fatigue? By covertly manipulating the clock calibration during repeated isometric contractions, we showed that perceived time shapes fatigue accumulation and frontal oscillatory dynamics. While fatigue accumulation was only reduced when the clock was slowed down, frontal oscillatory dynamics followed perceived ...
Pierre‐Marie Matta   +3 more
wiley   +1 more source

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