A typical industrial scenario encounters thousands of devices with millions of sensors,
consistently generating billions of data points. It poses new requirements of time series data …

Intention offloading involves using external reminders such as diaries, to-do lists, and digital
alerts to help us remember delayed intentions. Recent studies have provided evidence for …

Median absolute deviation (MAD), the median of the absolute deviations from the median,
has been found useful in various applications such as outlier detection. Together with …

Background Outliers can influence regression model parameters and change the direction
of the estimated effect, over-estimating or under-estimating the strength of the association …

In this study, we employ both targeted and untargeted approaches to explore the
metabolomic profiles of Vanilla spp., with a particular focus on V. cribbiana (VCR) and its …

The increasing breast weight of modern broilers highlights the convenience of studying the
dynamics of processing weights across the grow-out period. For models predicting these …

Abstract Simple Moving Average (SMA) is a method used to forecast a state of affairs in the
next period. This method is applied to determine the number of blood requests in PMI in the …

There is a growing demand for time series data analysis in industry areas. Apache IoTDB is
a time series database designed for the Internet of Things (IoT) with enhanced storage and …

Quantiles are costly to compute exactly but can be efficiently estimated by quantile sketches.
Extensive works on summarizing streaming data, such as KLL sketch, focus on minimizing …

Quantiles are fundamental statistics in various data science tasks, but costly to compute, eg,
by loading the entire data in memory for ranking. With limited memory space, prevalent in …