With increasing demands for lowering emissions from diesel engines, bio fuel has been introduced to the fuel mixture. This fuel is based on vegetable oil with a much smaller carbon footprint than fossil fuel. The chemical composition of bio fuel has lead to deposits forming inside the fuel injector in diesel engines, these deposits are usually denoted as Internal Diesel Injector Deposits (IDID). At Scania CV AB an injector test rig is designed with the goal of creating and investigating IDID. This project has made a theoretical investigation of how IDID are formed and how this affects the mechanics inside the injector. It has also analysed injector components from a worst case scenario perspective in order to find a testing method for creating IDID in the test rig. By analysing performance changes from a build-up perspective, where IDID decreases the tolerances inside the injector, as well as friction, formed when deposits cause injector mechanics to stick together, it has been found that injector performance does hardly change from build-up and that performance changes only occur when friction is introduced. From the injector component analysis it is found that the limiting factors in rig testing come from fuel system components rather than the injector itself. This is the base for a rig running test method presented.

The outbreak of the Ebola virus was declared a Public Health Emergency of International Concern by the World Health Organisation (WHO). Due to the complex nature of the outbreak, the Centers for Disease Control and Prevention (CDC) had created interim guidance for monitoring people potentially exposed to Ebola and for evaluating their intended travel and restricting the movements of carriers when needed. Tools to evaluate the risk of individuals and groups of individuals contracting the disease could mitigate the growing anxiety and fear. The goal is to understand and analyze the nature of risk an individual would face when he/she comes in contact with a carrier. This thesis presents a tool that makes use of contextual data intelligence to predict the risk factor of individuals who come in contact with the carrier.