Characterization of the THz quasi-optical channel for the measurement of the power radiated by photoconductive antennas

In this paper a rigorous electromagnetic characterization of the setup for measuring the THz power radiated by pulsed photoconductive antenna is discussed. Such characterization is expressed in terms of efficiencies which quantify how much power is lost in the coupling between the various components involved in the measurement setup. The...

A geometric approach to nonlinear dissipative balanced reduction: Continuous and sampled-time

In almost every field of applied science and engineering, dynamical models are widely used as a professional tool to describe in a compact format the scientific knowledge we have about the phenomena we are analyzing. Such models are widely used for the estimation, optimization, detection of failures and even for real-time control. The relevance...

Modeling geometrical uncertainties for radiotherapy plan optimization without margins

Radiotherapy is one of the methods used to treat cancer. One common approach for radiotherapy is exposing the patient to external beams of high-energy X-ray photons. Using the intensity-modulated radiation therapy (IMRT) technique, the fluence (radiation energy per unit area) of the radiation beams can be modulated to optimally shape the 3D high...

Integration and exploration of High Dimensional data

In modern Life Sciences, high dimensional correlated data matrices are often dealt with. Ordinary linear regression fail and PCA does not take into account the outcome variable(s). Also there might be large amount of orthogonal variation present. To deal with this, the O2PLS model (which is based on the PLS model) is derived. O2PLS is symmetric...

Ensemble-Based History Matching for Channelized Petroleum Reservoirs

The oil industry is at the backbone of global economy and, as natural resources are becoming scarce, there is a pressing need for efficient extraction strategies. This has led to the development of reservoir models and simulators, able to predict future field behaviour, when paired with accurate geological information. However, the data obtained...

Four Chairs and All the Others - Eigenchair

By contemplating on the Eigenchair project, we ponder upon strategies and concepts of designing by using information technologies. What are the potentials of data driven design? What happens with objects when they are abstracted and reduced to a set of data? The emphasis is no longer on the creation of physical objects, but on conceiving meta...

A simple algorithm to generate small geostatistical ensembles for subsurface flow simulation

This note describes the theory behind a simple Matlab program to generate ensembles of geological realizations of relatively small-scale reservoir models (permeability fields) for subsurface flow simulation. The algorithm makes use of Principal Component Analysis (PCA) to parameterize the spatial covariance of a reference image, and a Bayesian...

Prediction of Market Value of Used Commercial Aircraft

Aviation financers are interested in the current/future market value of used commercial aircraft, as this information is precious knowledge for them to support collateral position in the aircraft loan. In this paper, variables from general economy, airline industry and aviation fleet are explored to find out the factors predictive for used...

Improving riverbed sediment classification using backscatter and depth residual features of multi-beam echo-sounder systems

Riverbed and seafloor sediment classification using acoustic remote sensing techniques is of high interest due to their high coverage capabilities at limited cost. This contribution presents the results of riverbed sediment classification using multi-beam echo-sounder data based on an empirical method. Two data sets are considered, both taken at...

Rider motion identification during normal bicycling by means of principal component analysis

Recent observations of a bicyclist riding through town and on a treadmill show that the rider uses the upper body very little when performing normal maneuvers and that the bicyclist may, in fact, primarily use steering input for control. The observations also revealed that other motions such as lateral movement of the knees were used in low...

Sparse principal component analysis

Principal component analysis (PCA) is a widespread exploratory data analysis tool. Sparse principal component analysis (SPCA) is a method that improves upon PCA by increasing the number of zeros in the loading vectors of PCA results. This makes the results more understandable and more usable. This bachelor's thesis introduces both methods, and...

Dynamic response characterization of complex systems through operational identification and dynamic substructuring- An application to gear noise propagation in the automotive industry

This thesis deals with new methods, which can determine the dynamic response of a complex system identified in operation, based on the knowledge of its subsystem dynamics and excitation. In the first part of this thesis, the identification of component excitation and its transmission into the total system will be addressed. The identification of...

A Quantitative Model for Hardware/Software Partitioning

Heterogeneous System Development needs Hardware/Software Partitioning performed early on in the development process. In order to do this early on predictions of hardware resource usage and delay are necessary. In this thesis a Quantitative Model is presented that can make early predictions to support the partitioning process. The model is based...

Clinical study for classification of benign, dysplastic, and malignant oral lesions using autofluorescence spectroscopy