Climate change induced uncertainties in future coastal ecosystem state

This thesis presents a doctoral research where statistical concepts and techniques are applied to problems at the interface of marine and atmospheric processes. The research was conducted at the Statistics group of the Delft Institute of Applied Mathematics (TU Delft) and the Marine and Coastal unit of Deltares. The main objective of the work is...

Prioritizing Cyclists at Signalized Intersections Using Observations from Connected Autonomous Vehicles

When making trips in urban environments, cyclists lose time as they stop and idle at signalized intersections. The main objective of this study was to show how augmenting the situational awareness of traffic signal controllers, using observations from moving sensor platforms, can enable prioritization of cyclists and reduce lost time within...

Naval engineering and ship control special edition editorial

Editorial Special Issue: Naval Engineering and Ship Control II

Data Fusion Approach to Identify Distribution Chain Segments in Freight Shipment Databases

Understanding the logistic determinants of freight trips is an important goal in freight transport modeling. Freight shipments move between nodes in the supply chain for different logistic purposes, including production, storage, transshipment, and consumption. A key problem with data availability is that databases generally do not identify...

Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework

Accurate recognition of driver behaviours is the basis for a reliable driver assistance system. This paper proposes a novel fusion framework for driver behaviour recognition that utilises the traffic scene and driver gaze information. The proposed framework is based on the graph neural network (GNN) and contains three modules, namely, the...

“How sweet are your strawberries?”: Predicting sugariness using non-destructive and affordable hardware

Global soft fruit supply chains rely on trustworthy descriptions of product quality. However, crucial criteria such as sweetness and firmness cannot be accurately established without destroying the fruit. Since traditional alternatives are subjective assessments by human experts, it is desirable to obtain quality estimations in a consistent and...

Intelligent Data Fusion for Anomaly Detection in Dutch Railway Catenary Condition Monitoring

Aiming to handle the increasing variety and volume of railway infrastructure monitoring data, this paper explores the use of intelligent data fusion methods for automatic anomaly detection of railway catenaries. Three classical data dimensionality reduction methods, namely the principal component analysis (PCA), the autoencoder neural network,...

The Need for Multi-Sensor Data Fusion in Structural Health Monitoring of Composite Aircraft Structures

With the increased use of composites in aircraft, many new successful contributions to the advancement of the structural health monitoring (SHM) field for composite aerospace structures have been achieved. Yet its application is still not often seen in operational conditions in the aircraft industry, mostly due to a gap between research focus...

A Machine learning approach for rapid disaster response based on multi- modal data: The case of housing & shelter needs

Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is finding shelter. While the proliferation of data on disasters is already helping to save lives, identifying...

Automation in sensing and raw material characterization - A conceptual framework

The use of sensor technologies for material characterization is rapidly growing and innovative advancement is observed. However, the use of sensor combinations for a raw material characterization in mining is very limited and automation of the material identification process using a combined sensor signal is not defined. Potential sensor...

Robust Hand Motion Tracking through Data Fusion of 5DT Data Glove and Nimble VR Kinect Camera Measurements

Vision based interfaces for human computer interaction have gained increasing attention over the past decade. This study presents a data fusion approach of the Nimble VR vision based system, using the Kinect camera, with the contact based 5DT Data Glove. Data fusion was achieved through a Kalman filter. The Nimble VR and filter output were...

Robust hand motion tracking through data fusion of 5dt data glove and nimble VR kinect camera measurements

Vision based interfaces for human computer interaction have gained increasing attention over the past decade. This study presents a data fusion approach of the Nimble VR vision based system, using the Kinect camera, with the contact based 5DT Data Glove. Data fusion was achieved through a Kalman filter. The Nimble VR and filter output were...

Fusing Heterogeneous Traffic Data: Parsimonious Approaches using Data-Data Consistency

Reliable and accurate estimation of traffic states play an important role in traffic management and traffic theory development, which therefore has significant social and scientific relevance. Data for traffic estimation normally from different sources and have different types, characteristics, etc, so data fusion techniques are used. Traffic...

Multi-modal aggression detection in trains

In many public places multiple sensing devices, such as cameras, are installed to help prevent unwanted situations such as aggression and violence. At the moment, the best solution to reach a safe environment requires human operators to monitor the camera images and take appropriate actions when necessary. In the wake of the terrorist attacks of...