Abstract Changes in process states and properties can be observed through measured
variables. In this way, by classifying time series segments of measured data, changes in …

Time series classification is an increasingly attractive field with the appearance of new
problems in an expanding digitalized world. Most of the proposals in the state-of-the-art …

Classification of uncertain conditions requires computational modeling to obtain exact non-
vague results for making the right decision, such as opening and closing school cases …

Subsequence matching algorithms have many applications on time-series, such as
detecting specific patterns on Electrocardiogram (ECG) and temperature data. To the best of …

Classification is one of the most popular techniques in the data mining area. In supervised
learning, a new pattern is assigned a class label based on a training set whose class labels …

Nowadays, large datasets of alloys designed for various purposes exist. This allows using
computer-guided methods for alloy synthesis and selection instead of costly experiments …

Nowadays, we have to deal with fast-growing and permanently evolving data, including
social networks and sensor data recorded from smart phones or vehicles. Data evolving in …

Approaches for time mining are frequently used to build a model of how the dynamic of
certain (productive or non-productive) activities, statuses, and events occurring in a system …