Bayesian Estimation of a Monotone Regression Function: A method described by Neelon and Dunson applied to climate data

The goal of this thesis is to implement and experiment with a Bayesian way of estimating a (smooth) monotone regression function by applying it to climate data. The method we use is proposed by Neelon and Dunson. This method uses a piece-wise linear model for the unknown regression function and enforces the monotonicity constraint by the...

Understanding headwater baseflow contributions to the overall water supply of the Kathmandu Valley, Nepal

The Kathmandu Valley in Nepal is facing the combined effects of population growth, rapid urbanization, economic development, and climate change. This results in serious water management challenges: growing freshwater demands, declining water tables, drying of streams, and deteriorating water quality. Insufficient surface water supplies have led...

Adaptations for CNN-LSTM Network for Remaining Useful Life Prediction: Adaptable Time Window and Sub-Network Training

Estimating the RUL (Remaining Useful Life) of machinery is a useful tool for maintenance and performance operations. This results in lower costs, improved safety and operational improvements.<br/>This paper proposes two adaptations to the CNN-LSTM network provided by Li et al. \cite{Li2019APrediction}, as well as exploring reproducibility,...

Predicting Manufacturing Times using Building Information Models: A case study at Oostingh Staalbouw

In the construction industry, it is common to predict manufacturing times of structural elements based on the experience of shop managers. With the increasing use of Building Information Models (BIM) and data analysis in manufacturing processes an opportunity for improving the accuracy of predicted manufacturing times arises. This research...

Reduced Order Modelling methodologies for proton therapy applications

In proton therapy, the calculation of the dose distribution is of great importance in order to find the best treatment plan. For a treatment plan with high quality, several error scenarios are investigated, in order to come up with a general plan that suits best in these scenarios. All of the scenarios have a different simulated error, e.g., in...

Short term wind power forecasting using hybrid models

This study improves the Short term wind power forecasting to help bid the wind power in the electricity market. Supplying power lesser/greater than the expected power creates imbalance in the Electricity system. Hence electricity markets impose penalty for supplying power lesser/greater than expected power. Bidding right amount of power is an...

Layered Regression Analysis on Multimodal Approach for Personality and Job Candidacy Prediction and Explanation

Video blogs (vlogs) are a popular media form for people to present themselves. In case a vlogger would be a job candidate, vlog content can be useful for automatically assessing the candidate's traits, as well as potential interviewability. Using a dataset from the CVPR ChaLearn competition, we build a model predicting Big Five personality trait...

Categorical based feature modeling on a zero inflated performance measure

ASML produces TwinScan NXT machines that are used for the production of microchips. The machines ensure that an accurate pattern of DUV-light passes a lens and that it is projected as accurate as possible on the wafer. To ensure that the focal point of the converged DUV-light falls exactly onto the wafer, the leveling functionality is of great...

The future of car parks: Influencing factors on occupancy rates in the period 2015-2025 based on a study of The Netherlands and Western European countries.

In the past decennium, parking received growing attention within real estate as a niche market for real estate investors. Since car park investments outperformed other types of real estate in the period 2008-2013, it is supposed to be the ideal investment within real estate due to its stable and secured cash flows with long-term leases....