Generative AI can augment chemometrics by automating curation, connecting analytical outputs to textual knowledge, and ...
Understanding how structural defects affect the optoelectronic performance of silicon semiconductor wafers is critical for improving device efficiency and reliability. Simultaneous Raman and ...
Abstract: This survey comprehensively examines the challenges and methodologies for missing data recovery in Multivariate Time Series (MTS) within the context of Internet of Things (IoT) environments.
In precision agriculture (PA), the evaluation of soil spatial variability to optimize crop management requires dense sampling. This costly activity often results in sparser sampling grids and may ...
Adapting to the stream: An instance-attention GNN method for irregular multivariate time series data
Framework of DynIMTS. The model is a recurrent structure based on a spatial-temporal encoder and consists of three main components: embedding learning, spatial-temporal learning, and graph learning.
Analysis of Multivariate Indoor Building Data: A Comparative Study of Time-Series Clustering Methods
Abstract: Clustering multivariate time-series data is crucial for uncovering complex temporal patterns in dynamic environments, such as building indoor conditions and behavior where variables like ...
ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Naphthenic acids (NAs) naturally occur in crude oil and its associated produced water, ...
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