Maja Skrjanc

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We have begun to develop a new annotated long term ambulatory ST-T database. The aim of the database is to be a reference set containing a number of well documented ischemic ST episodes, axis-related non-ischemic ST episodes, episodes of slow ST level drift and mixed episodes to support development and evaluation of detectors capable of accurate(More)
This paper presents a two level lexical stress assignment model for out of vocabulary Slovenian words used in our text-to-speech system. First, each vowel (and consonant 'r') is determined, whether it is stressed or un-stressed, and a type of lexical stress is assigned for every stressed vowel (and consonant 'r'). We applied a machine-learning technique(More)
Detection rules represent one of the components of the rule models in event processing systems. These rules can be discovered from data using data mining techniques or domain experts' knowledge. We demonstrate a system that provides its users the means for creating and validating such rules. The system is applied on real-life environmental scenarios, where(More)
This paper presents a methodology for data cleaning of sensor data using the Kalman filter. The Kalman filter is an on-line algorithm and as such is ideal for usage on the sensor data streams. The Kalman filter learns parameters of a user-specified underlying model which models the phenomena the sensor is measuring. Usage of the Kalman filter is proposed to(More)
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