esports pro-players behavior during the game events: Statistical analysis of data obtained using the smart chair
Today's competition between the professional eSports teams is so strong that in-depth
analysis of players' performance literally crucial for creating a powerful team. There are two …
analysis of players' performance literally crucial for creating a powerful team. There are two …
Sequence embeddings help to identify fraudulent cases in healthcare insurance
Fraud causes substantial costs and losses for companies and clients in the finance and
insurance industries. Examples are fraudulent credit card transactions or fraudulent claims. It …
insurance industries. Examples are fraudulent credit card transactions or fraudulent claims. It …
On construction of early warning systems for predictive maintenance in aerospace industry
EV Burnaev - Journal of communications technology and electronics, 2019 - Springer
The problem of constructing predictive models for early warning systems for diagnostic
maintenance in the aerospace industry is considered. A new approach to predicting rare …
maintenance in the aerospace industry is considered. A new approach to predicting rare …
UniMAP: model-free detection of unclassified noise transients in LIGO-Virgo data using the temporal outlier factor
Data from current gravitational wave detectors contains a high rate of transient noise
(glitches) that can trigger false detections and obscure true astrophysical events. Existing …
(glitches) that can trigger false detections and obscure true astrophysical events. Existing …
Breakpoint based online anomaly detection
E Krönert, D Hattab, A Celisse - arXiv preprint arXiv:2402.03565, 2024 - arxiv.org
The goal of anomaly detection is to identify observations that are generated by a distribution
that differs from the reference distribution that qualifies normal behavior. When examining a …
that differs from the reference distribution that qualifies normal behavior. When examining a …
Robust Outlier Detection Method Based on Local Entropy and Global Density
K Zhang, W Huang, B Zhang, J Xu, X Yang - arXiv preprint arXiv …, 2023 - arxiv.org
By now, most outlier-detection algorithms struggle to accurately detect both point anomalies
and cluster anomalies simultaneously. Furthermore, a few K-nearest-neighbor-based …
and cluster anomalies simultaneously. Furthermore, a few K-nearest-neighbor-based …
Usage of multiple RTL features for earthquakes prediction
P Proskura, A Zaytsev, I Braslavsky, E Egorov… - … Science and Its …, 2019 - Springer
We construct a classification model, that predicts if an earthquake with the magnitude above
a threshold will take place at a given location in a time range 30–180 days from now. A …
a threshold will take place at a given location in a time range 30–180 days from now. A …
Rare failure prediction via event matching for aerospace applications
E Burnaev - 2019 3rd International Conference on Circuits …, 2019 - ieeexplore.ieee.org
In this paper, we consider a problem of failure prediction in the context of predictive
maintenance applications. We present a new approach for rare failures prediction, based on …
maintenance applications. We present a new approach for rare failures prediction, based on …
Detection of dataset shifts in learning-enabled cyber-physical systems using variational autoencoder for regression
Cyber-physical systems (CPSs) use learning-enabled components (LECs) extensively to
cope with various complex tasks under high-uncertainty environments. However, the dataset …
cope with various complex tasks under high-uncertainty environments. However, the dataset …
Harnessing Feature Clustering For Enhanced Anomaly Detection With Variational Autoencoder And Dynamic Threshold
We introduce an anomaly detection method for multivariate time series data with the aim of
identifying critical periods and features influencing extreme climate events like snowmelt in …
identifying critical periods and features influencing extreme climate events like snowmelt in …