A comparison of univariate and multivariate forecasting models predicting emergency department patient arrivals during the COVID-19 pandemic
The COVID-19 pandemic has heightened the existing concern about the uncertainty
surrounding patient arrival and the overutilization of resources in emergency departments …
surrounding patient arrival and the overutilization of resources in emergency departments …
[HTML][HTML] Spatiotemporal integration of GCN and E-LSTM networks for PM2. 5 forecasting
Abstract PM 2.5, inhalable particles, with a size of 2.5 micrometers or less, negatively impact
the environment as well as our health. Monitoring PM 2.5 is critical to guard against extreme …
the environment as well as our health. Monitoring PM 2.5 is critical to guard against extreme …
Detecting inaccurate sensors on a large-scale sensor network using centralized and localized graph neural networks
DY Wu, TH Lin, XR Zhang, CP Chen… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
This article conducts an empirical study on detecting faulty sensors in a large-scale sensor
network containing approximately sensors distributed over. First, we discuss the practical …
network containing approximately sensors distributed over. First, we discuss the practical …
Learning to identify malfunctioning sensors in a large-scale sensor network
TH Lin, XR Zhang, CP Chen, JH Chen… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
This paper proposes a two-stage methodology to discover malfunctioning sensors in an air
quality sensor network. The two-stage methodology consists of a supervised learner to …
quality sensor network. The two-stage methodology consists of a supervised learner to …
Application of artificial neural networks and UAV-based air quality monitoring sensors for simulating dust emission in quarries
This study aims to assess the potential application of low-cost unmanned aerial vehicles
(UAVs) for environmental monitoring and assessment at the open-pit mine, with a case study …
(UAVs) for environmental monitoring and assessment at the open-pit mine, with a case study …
VR Driven Unsupervised Classification for Context Aware Human Robot Collaboration
A Kamali Mohammadzadeh, CL Allen… - … Conference on Flexible …, 2023 - Springer
Human behavior, despite its complexity, follows structured principles that, if understood, will
result in more reliable and effective collaborative automation environments. Characterizing …
result in more reliable and effective collaborative automation environments. Characterizing …
[PDF][PDF] Machine Learning with Applications
ABSTRACT PM2. 5, inhalable particles, with a size of 2.5 micrometers or less, negatively
impact the environment as well as our health. Monitoring PM2. 5 is critical to guard against …
impact the environment as well as our health. Monitoring PM2. 5 is critical to guard against …
[PDF][PDF] VR Driven Unsupervised Classification for Context Aware Human Robot Collaboration
AK Mohammadzadeh, CL Allen, S Masoud - smartimmersivemodeling.com
Human behavior, despite its complexity, follows structured principles that, if understood, will
result in more reliable and effective collaborative automation environments. Characterizing …
result in more reliable and effective collaborative automation environments. Characterizing …
Monitoring PM2. 5 Pollution In The North End Of Hartford, CT
J Phung, K Wagstrom - 2023 - digitalcommons.lib.uconn.edu
Particulate matter (PM) or particle pollution is one of the six criteria air pollutants that can
cause harm to human health and the environment; yet, there is a lack of data in many areas …
cause harm to human health and the environment; yet, there is a lack of data in many areas …