Tennis Stroke Recognition: Stroke classification using inertial measuring unit and machine learning algorithm in Tennis

One interesting part of the application of human activity recognition is sports motion recognition and classification. In recent years, many commercial wearable devices have been used for recording and supervising motion data information during sports. However, their claimed high-accuracy results but motion recognition and classification method...

Interpretable Machine Learning for Biomarker Discovery in Imaging Mass Spectrometry Data

Imaging mass spectrometry (IMS) is a multiplexed chemical imaging technique that enables the spatially targeted molecular mapping of biological samples at cellular resolutions. Within a single experiment, IMS can measure the spatial distribution and relative concentration of thousands of distinct molecular species across the surface of a tissue...

Advanced Set Bounding Methods for Fault Detection

Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...

Vibration-based Monitoring of the Zwartewaterbrug: a Machine Learning Approach

In the Netherlands there are many bridges that crosses waterways, which are key nodes in the transportation system. The safety and integrity of these bridges is nowadays assessed by (visual) inspections at regular intervals. This approach cannot provide information about damage development in between inspections, leading to potential failure or...

Machine Learning Revealing Insights into Soil Stratification: An Application for Dikes and Dams

In the Netherlands, robust dike and dam design is a major concern in the context of flood defence. Due to heterogeneity of the subsoil on which these structures are founded, the validity range of in situ tests decreases drastically. Consequently, large uncertainties regarding spatial variation of soil stratification and soil layer parameters are...

Learning Autonomous Grasping Strategies for a Care Robot: A Machine Learning approach

Autonomous grasping is a key requisite for the autonomy of robots.<br/>However, grasping of unknown objects in domestic environments is difficult due to the presence of unpredictability and clutter.<br/>In this paper, a novel algorithm capable of finding an unobstructed grasping pose on unknown regular object shapes in cluttered environments is...

The potential of advanced data analytics using machine learning to increase overall equipment effectiveness in an underground mining operation

Changing market dynamics make that mining companies need to increase their equipment utilization and use their equipment more effectively. The growing availability of data from mining equipment and mining operations enables the use of data analytics to achieve that goal. This thesis explores the potential of data analytics and machine learning...