NMGroup – Power Line Route Optimisation in a Finite Spatial Grid
Building new infrastructure such as transmission lines, roads, rail, etc. is always a source of controversy. High voltage transmission lines blight the landscape they are constructed on, bringing social, environmental, and economic detriment to the areas they run through, equally they form the fabric of modern infrastructure enabling efficient transfer of power across the country.View problem details
NKI – Accurate Dose Delivery for Radiation Therapy: Adapting Treatment to Daily Anatomy
For radiation oncology, we treat patients with head and neck tumours over the course of 6-7 weeks. This treatment is usually based on one CT scan prior to treatment. We use that as an input for dose calculations in the patient based on a collapsed cone superposition algorithm. To optimise the dose distribution we useView problem details
Mobidot – Mobility Profiling from Smartphone Sensor Data: Confidently Know How People Travel
Our SWI problem formulation focuses on advancing the quality of our data derivation. Mobidot infers the route, role, objective, and mode of transportation from Smartphone data. Smartphones possess a variety of sensors, including GPS, mobile telephone (4G) and wi-fi signals, accelerometer-based mode, etc. that can be used to determine the motion and position of theView problem details
KNMI – Synchronizing Numerical Models of the Atmosphere to Improve Weather and Climate Predictions
Systems as diverse as clocks, singing crickets, cardiac pacemakers, firing neurons and applauding audiences exhibit a tendency to operate in synchrony. The phenomenon that dynamical systems synchronise their behaviour by some form of information exchange is known as synchronisation. In recent years, the concept of synchronisation is being applied in weather and climate research. ObservedView problem details
SKF – Statistical Modelling of Mechanical Bearing Life Testing
The goal is to model and optimize bearing life testing time under constraints. The constraints are from various kinds: Number of available test machines (each machine has 2 test positions): Number of life tests to be run: Statistical distribution assumed for individual bearing life: Weibull (,) Assessed precision: the expected maximum ratio between confidence boundsView problem details
Philips – Patient Adaptive Compressed Sensing
The Problem The sampling density function in Compressed Sensing can best be optimized once the -space density is known for the object under investigation. This is characterized by an MRI scan (fast pre-acquired data set), from which the -space extent is estimated by a Fourier Transform. In addition, the data is acquired with multiple, spatially-localized,View problem details
