Results 121 to 130 of about 601,161 (266)

Human error probability in the emergency evacuation

Sigurnost
Mehrzad Ebrahemzadih
doaj   +1 more source

Corrigendum: Energy dissipation and error probability in fault-tolerant binary switching. [PDF]

Sci Rep, 2016
Fashami MS, Atulasimha J, Bandyopadhyay S.   +2 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source

Type I Error Probability Spending for Post-Market Drug and Vaccine Safety Surveillance With Poisson Data. [PDF]

Methodol Comput Appl Probab, 2018
Silva IR.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks. [PDF]

Sensors (Basel), 2016
Nasir H, Javaid N, Sher M, Qasim U, Khan ZA, Alrajeh N, Niaz IA.   +6 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Use of attribute association error probability estimates to evaluate quality of medical record geocodes. [PDF]

Int J Health Geogr, 2015
Klaus CA, Carrasco LE, Goldberg DW, Henry KA, Sherman RL.   +4 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source