The road to intelligent asphalt concrete mixture design: A Data driven analysis of common asphalt concrete property prediction methods and a solution to the inverse problem

Asphalt concrete is one of the most widely used materials in modern road construction. Predicting its functional properties is crucial in the design of new asphalt concrete mixtures. However, current prediction models are limited in accuracy and applicability due to the complex nature of asphalt concrete properties. This thesis researches the...

Remote prediction of soil types: A working methodology to predict Unified Soil Classification System (USCS) classes based on total geological history

The Dutch Ministry of Defence is interested in developing a tool or workflow that can be used to remotely predict Unified Soil Classification System (USCS) classes of any area to aid mobility-related decisions. Therefore, this study was initiated by Cohere Consultants in collaboration with NEO, a Dutch remote sensing company and Utrecht...

Bed Exit Prediction

This report presents a bed exit prediction model using a decision tree classifier, a machine learning method. This system is designed to alarm a caregiver in a nursing home to prevent bed­ falls among institutionalized elderly. For the input of this algorithm, features are derived from four force sensing resistor sensors and six piezoelectric...

Development of a Bayesian Decision Tree Model for Task Classification and its Validation on Parkinson’s Disease Patients

Freezing of Gait (FoG) is a debilitating walking problem affecting over 50\% of Parkinson's Disease (PD) patients. Rhythmic cues during FoG can help patients to resume walking. FoG can be detected from lower limb acceleration data, but current detection algorithms lack context, resulting in false positive detection and initiation of cues when...