Results 121 to 130 of about 369,068 (270)

Estimating Variable Returns to Scale Production Frontiers with Alternative Stochastic Assumptions [PDF]

open access: yes
A stochastic production frontier model is formulated within the generalized production function framework popularized by Zellner and Revankar (1969) and Zellner and Ryu (1998).
Christopher J. O’Donnell   +1 more
core  

Detecting Dengue in Flight: Leveraging Machine Learning to Analyze Mosquito Flight Patterns for Infection Detection

open access: yesAdvanced Biology, EarlyView.
Dengue infection alters mosquito flight behavior, enabling detection using machine learning classifiers. This study analyzes 3D flight trajectories and evaluates multiple models, showing that longer sequence lengths improve classification performance.
Nouman Javed   +3 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani   +2 more
wiley   +1 more source

A prospective study on association between comprehensive lifestyle scores and cognitive function changes in community-dwelling older adults in Tianjin city

open access: yesZhongguo gonggong weisheng
ObjectiveTo investigate the association between comprehensive lifestyle scores and changes in cognitive function among community-dwelling older adults in Tianjin city. MethodsA prospective cohort study was conducted.
Muya ZHANG   +7 more
doaj   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy