Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

In the last two decades, machine learning research and practice has focused on batch
learning, usually with small datasets. Nowadays there are applications in which the data are …

Accurate, continuous real-time perception of surrounding rock conditions on the tunnel
boring machine (TBM) tunnel face provides particularly important prior information to ensure …

Anomaly detection has received much attention due to its various applications. Generally,
the first step to discover anomalies is a data representation method which reduces …

In spite of being a small country, concerning geographic area and population size, Portugal
has a very active and respected Artificial Intelligence community, with a good number of …

Abstract Machine or system failures have high impact both at technical and economic levels.
Most modern equipment has logging systems that allow us to collect a diversity of data …

Abnormal pattern detection is an important task in series data anomaly detection. Because
of the noise interference, the accuracy of abnormal detection method based on deterministic …

Recently, predicting multivariate time-series (MTS) has attracted much attention to obtain
richer semantics with similar or better performances. In this paper, we propose a tri-partition …

Alarm fatigue caused by false alarms and alerts is an extremely important issue for the
medical staff in Intensive Care Units. The ability to predict electrocardiogram and arterial …

This dissertation is a study of methods to automatedly detect and produce approximations of
eddy current differential coil defect signatures in terms of a summed collection of Gaussian …