Machine Learning is omnipresence nowadays, for example face and speech recognition on your smartphone and other smart devices. The recent breakthroughs in many modern AI applications are due to deep learning (specifically deep neural networks). That is because deep learning scales better to big data, enables native end-to-end learning, and has established new state-of-the-art performance on many applications. However to get an accurate deep learning model, users have to make many important... more

Sharing Economy businesses like Airbnb and Uber have become very popular recently but there is little guidance available on how to develop the respective business models. We faced this problem during a consortium research project for developing a service for electric vehicle charging (CrowdStrom) that adopts the paradigm of Peer-to-Peer Sharing and Collaborative Consumption (P2P SCC) - a specific branch of the Sharing Economy. In this talk, I will explain how we developed and applied an... more

In this talk we will present a framework for processing knowledge inconsistency in a collective using consensus computing. The model of knowledge inconsistency has been built with several inconsistency measures. We will show that inconsistency degree of a collective has an essential impact on the quality of collective knowledge. In addition to inconsistency degree, the number of collective members, the problem of collective knowledge increase, additional knowledge elements, multi-stage... more

Humanitarian aid organizations respond to disasters by delivering relief items in highly complex and dynamic environments. To plan and execute logistics operations therein, it is crucial to build and maintain situation awareness. That is, to perceive the relevant elements of the environment, to comprehend their meaning and to project their status in the near future. Traditional data sources, such as direct observation by assessment teams, are limited in terms of speed and coverage.... more