Personal and ubiquitous sensing technologies such as smartphones have allowed the
continuous collection of data in an unobtrusive manner. Machine learning methods have been …

This book is the first ever to focus on the emerging field of self-aware computing from an
engineering perspective. It first comprehensively introduces fundamentals for self-awareness …

Wearable sensors measuring different parts of people's activity are a common technology
nowadays. In research, data collected using these devices also draws attention. Nevertheless, …

Although deep neural networks have achieved state-of-the-art performance in several artificial
intelligence applications in the past decade, they are still hard to understand. In particular, …

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and
other services that advance population health and wellbeing. However, the use of AI in …

This paper introduces and validates a real-time dynamic predictive model based on a neural
network approach for soft continuum manipulators. The presented model provides a real-…

This paper summarizes the information technology-related research findings after 5 years
with the INTROducing Mental health through Adaptive Technology project. The aim was to …

This paper presents the derivation and experimental validation of algorithms for modeling and
estimation of soft continuum manipulators using Lie group variational integration. Existing …

Through dance, a wide range of emotions can be expressed. As virtual agents and robots
continue to become part of our daily lives, the need for them to efficiently convey emotion and …

We present preliminary results on sensor data prediction in a smart home environment with
a limited number of binary sensors. The data has been collected from a real home with one …