This paper is a research of the challenges associated with detection of online toxicity. It is primarily based on
a machine learning challenge posted to Kaggle.com by Jigsaw and Conversation AI. Thus our research on
machine learning and AI identification of toxic comments is based on an attempt to fulfill this challenge.

This study examines the potential meaning of distance calculating designs for compliance with the danish healthcare system’s guidelines related to keeping distance with the intention to clarify if this would result in better compliance with the guidelines on RUC.

The following paper strives to explain the circumstances relating to the use of solar panels in Danish households. We draw conclusions based on empirical evidence, analysis and theory from the “TRINmodel” and Actor-Network Analysis. Our goal is to create an understanding of what might limit or increase the purchase and installation of solar panels, with the hope that this knowledge might be used to further the use of solar panels.

Our project aims to answer the question: “How can you build a technical design which secures the understanding of the processing regarding personal data to the average citizen as well securing a better understanding of the consequences by sharing personal data”. By utilizing surveys and collecting empirical data this study has found a need to increase the awareness of the average citizen regarding personal data being shared throughout the Internet. Finally, the studies illustrate how complicated it can be to understand what the average citizen is accepting while roaming around the Internet.