Results 261 to 270 of about 613,974 (314)

Measuring Student Engagement in Community College: Construct Validity of the Community College Survey of Student Engagement

open access: yesNew Directions for Community Colleges, EarlyView.
ABSTRACT Using data from the 2019 Community College Survey of Student Engagement (CCSSE) 3‐year cohort, this article presents a validation study of the 2017 version of CCSSE. Exploratory and confirmatory factor analyses were implemented to investigate the psychometric properties and construct validity with strategies to address missing data.
Yi Wang   +2 more
wiley   +1 more source

Experimental studies on multi‐scale data‐driven methods within the framework of structural health monitoring

open access: yesCivil Engineering Design, EarlyView.
Abstract The German Research Foundation has established the priority program SPP 100+. Its subject is monitoring bridge structures in civil engineering. The data‐driven methods cluster deals with the use of measurements and their special global and local analysis methods, which complement each other in an overall multi‐scale concept in order to realize
Maximilian Rohrer   +13 more
wiley   +1 more source

Automatic inventory of retaining walls from aerial lidar data using 3D deep learning

open access: yesCivil Engineering Design, EarlyView.
Abstract Infrastructure management along highways and railways requires inventories of critical structures like retaining walls, which traditionally rely on manual inspection and documentation. Unfortunately, data in infrastructure databases is often incomplete.
Ivo Gasparini   +2 more
wiley   +1 more source

A probabilistic diagnostic for Laplace approximations: Introduction and experimentation

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Many models require integrals of high‐dimensional functions: for instance, to obtain marginal likelihoods. Such integrals may be intractable, or too expensive to compute numerically. Instead, we can use the Laplace approximation (LA). The LA is exact if the function is proportional to a normal density; its effectiveness therefore depends on ...
Shaun McDonald, Dave Campbell
wiley   +1 more source

Robust multitask feature learning with adaptive Huber regressions

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract When data from multiple tasks have outlier contamination, existing multitask learning methods perform less efficiently. To address this issue, we propose a robust multitask feature learning method by combining the adaptive Huber regression tasks with mixed regularization. The robustification parameters can be chosen to adapt to the sample size,
Yuan Zhong, Xin Gao, Wei Xu
wiley   +1 more source

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