Research

Intro …

Predictive API and Decision as a Service

The key challenge that existing predictive analytics software has not been able to solve is how to extract knowledge from data quickly and put it into the hands of data owners to make better, more informed decisions. Separating decision-making from application process logic is often beneficial, hence designing adaptive predictive models based on Software as …

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Daily Living Dynamics

An analysis of daily-living behavior is an important approach to assess the wellbeing of an elderly person that lives at home alone. This study focuses on approaches to monitoring an individual in the home environment by an ambient-intelligence system in order to detect anomalies in daily-living patterns. We propose a method that is based on …

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Semi-Supervised Learning

When a classifier is deployed in a particular environment, its performance could often be improved if it were adapted to that environment. We study how to adapt the initial classifier with a small set of labeled data form the new environment. We proposed a novel adaptive-training algorithm, which uses three additional classifiers to improve the …

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Suspicious Pattern Detection

In many multiagent domains, no single observation event is sufficient to determine that the behavior of individuals is suspicious. Instead, suspiciousness must be inferred from a combination of multiple events, where events refer to the individual’s interactions with other individuals. Hence, a detection system must employ a detector that combines evidence from multiple events, in …

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Multimodal Sensor Integration

The main focus of this study was how to combine the output of specific intelligent sensors, which are able to decide on their own if a situation is alarming or not. We presented a fusion approach that constructs a situational awareness from different sensors and uses a Bayesian network for final reasoning. We built a …

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Activity Recognition

Activity recognition is an essential task that enables analysis of human behavior. We focused on recognition of activities from sensors that provide 3D coordinates (such as Vicon and Ubisense) using machine learning algorithms. We analyzed how sensor placement and amount of noise affects recognition accuracy and developed a series of filters to reduce noise in …

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