Realisation of green freight: a comparative analysis of alternative fuels in road freight transport: Evaluating Electric Battery Trucks, Hydrogen, and Bio-LNG trucks

Freight transport is a crucial component of our society and economy. However, achieving sustainability in this sector is complex, due to a lack of incentives among stakeholders. The heavy-duty road transport sector is struggling to meet European emission standards. To address this issue, a research study examined the impact of combining Battery...

Nautical safety on Dutch inland waterways, a study to detect anomalous vessel behaviour based on AIS data

Currently, inland waterway safety assessments rely heavily on historic accident data and expert opinions, often lacking comprehensive qualitative and quantitative information. Addressing this gap, this thesis introduces a method based on Automatic Identification System (AIS) data to identify anomalous vessel behaviour for enhancing safety...

Using K-Means clustering to export a NeRF for faster rendering in CG applications while preserving view-dependent appearance

With the current state-of-the-art research, exporting a NeRF to a mesh has the side effect of having to evaluate a Multi Layer Perceptron at render-time, causing a significant decrease in performance. We have found a way to use K-Means clustering to pre-compute values for this MLP, storing them in multiple octahedron maps for the GPU to fetch...

The Optimal European Hydrogen Refueling Station Network for Heavy Duty Trucks

This study researched the optimal network of hydrogen refueling stations. The network is designed on a European scale and with a focus on heavy duty trucks. The design is created by means of a two-step optimization. The first step clusters truck representing datapoints into a predetermined number of stations by means of k-means clustering. The...

Categorizing recipients of evouchers using best practises from marketing theories: Clustering and targeting vulnerable recipients of evouchers using a novel approach of consumer segmentation and machine learning; a case study of Sint Maarten

Cash and Voucher Assistance (CVA), a type of humanitarian aid consisting of giving money instead of products, is being used more frequently because of its effectiveness and efficiency in helping people in need (Cash Learning Partnership, 2020b). The debate on using CVA is currently focusing on improving the quality by better incorporating ...

Two-level preconditioning applied on the ssSNPBLUP model

The single-step single nucleotide polymorphism best linear unbiased prediction (ssSNPBLUP) model can potentially be used in animal breeding for genetic evaluations. It has been reported that this model has convergence issues when the Preconditioned Conjugate Gradient (PCG) method is applied. This is due to the linear system being ill-conditioned...

Developing efficient heuristic approaches to cluster editing, inspired by other clustering problems

Cluster editing attempts to find the minimum number of edge additions and removals on an undirected graph, that will transform the graph to one consisting of only disconnected cliques. In this paper, we propose three heuristic approaches to this problem, based on algorithms used to solve different clustering problems. The algorithms were based...

Predicting software vulnerabilities with unsupervised learning techniques

As software is produced more and more every year, software also gets exploited more. This exploitation can lead to huge monetary losses and other damages to companies and users. The exploitation can be reduced by automatically detecting the software vulnerabilities that leads to exploitation. Unfortunately, the state-of-the-art methods for this...

Customer segmentation using RFM analysis

This paper is a research on the segmentation of customers. The clustering of customers is done based on the variables recency, frequency and monetary value. Such a clustering is called an RFM-model. The clustering is done using the K-means clustering method. To find the optimal number of clusters the following performance metrics are used: Elbow...

An evaluation of image segmentation techniques for MRI scans

In this thesis, several image segmentation techniques will be tested that eventually will be applied to MRI brain scans in order to detect hydrocephalus. The meth- ods include Sobel edge detection, Canny edge detection, active contour model (also known as snakes), k-means clustering and region growing. Furthermore two exten- sions are discussed....

Influence of Climate and Vegetation on Root Zone Storage Capacity: A case study in Australia

Root zone storage capacity Sr is a significant variable for hydrology and climate studies, as it strongly influences the hydrological behaviour of a catchment. A climate-derived method (water-balance between precipitation and transpiration) was applied for estimating Sr values for 113 catchments in Australia. Various climate, hydrological and...

Elucidating families of ship designs using clustering algorithms

The past decade the packing approach was developed at the TU Delft. This tool automatically generates tens of thousands of ship designs in order to fully explore the design space. This is opposed to the traditional way of ship design, where just a limited number of designs can be elaborated. The result is a set of ship designs that can be used...

Use of MWD data for detecting discontinuities

In the last decades, measurement while drilling, or MWD, technology has set foot in the drill and blast tunnelling industry. Penetration rate, thrust, torque pressure, percussive pressure, rotation speed, water flow and water pressure are registered on a centimetre scale and processed to parameters more dependent on geology. These parameters...