Expected annual probability of infection: A flood-risk approach to waterborne infectious diseases.

This study introduces a new approach for the investigation of infections after an accidental ingestion of contaminated floodwater. The concept of Expected Annual Probability of Infection (EAPI) is introduced and implemented in an infection risk-model approach, by combining a Quantitative Microbial Risk Assessment (QMRA) with the four steps in flood risk assessment. Two groups and exposure paths are considered: adults wading in floodwater and small children swimming/playing in floodwater.

An Inverse Problem Approach for Parameter Estimation of Cardiovascular System Models.

Left ventricular assist devices (LVADs) are mechanical pumps that help patients with chronic heart failure waiting for a heart transplant. Mathematical models of these devices can be used along cardiovascular system (CVS) models to evaluate the assistance performance under different operating modes. The estimation of the CVS model parameters for a particular patient and numerical simulations allow the implementation of adequate LVAD operation mode.

A scalable flood-resilience-index for measuring climate change adaptation: Munich city.

Climate change is affecting the frequency and intensity of rainfall extreme events worldwide. Despite the growing global awareness, developing flood resilient cities has proven to be a major challenge. This paper investigates the application of an event-based scalable Flood Resilience Index (FRI) for assessing climate change adaptation.

Burst ranking for blind multi-image deblurring.

We propose a new incremental aggregation algorithm for multi-image deblurring with automatic image selection. The primary motivation is that current burst deblurring methods do not handle well situations in which misalignment or out-of-context frames are present in the burst. These real-life situations result in poor reconstructions or manual selection of the images that are used to deblur.

Automated Spatial Pattern Analysis for Identification of Foot Arch Height From 2D Foot Prints.

Arch height is an important determinant for the risk of foot pathology, especially in an aging population. Current methods for analyzing footprints require substantial manual processing time. The current research investigated automated determination of foot type based on features derived from the Gabor wavelet utilizing digitized footprints to allow timely assessment of foot type and focused intervention.

A comparative study of manhole hydraulics using stereoscopic PIV and different RANS models.

Flows in manholes are complex and may include swirling and recirculation flow with significant turbulence and vorticity. However, how these complex 3D flow patterns could generate different energy losses and so affect flow quantity in the wider sewer network is unknown. In this work, 2D3C stereo Particle Image Velocimetry measurements are made in a surcharged scaled circular manhole.

Numerical and experimental study of the fundamental flow characteristics of a 3D gully box under drainage.

Numerical studies regarding the influence of entrapped air on the hydraulic performance of gullies are nonexistent. This is due to the lack of a model that simulates the air-entrainment phenomena and consequently the entrapped air. In this work, we used experimental data to validate an air-entrainment model that uses a Volume-of-Fluid based method to detect the interface and the Shear-stress transport k-ω turbulence model.

A methodology for linking 2D overland flow models with the sewer network model SWMM 5.1 based on dynamic link libraries.

Pluvial flooding in urban areas is characterized by a gradually varying inundation process caused by surcharge of the sewer manholes. Therefore urban flood models need to simulate the interaction between the sewer network and the overland flow in order to accurately predict the flood inundation extents. In this work we present a methodology for linking 2D overland flow models with the storm sewer model SWMM 5.

Characterization of the hydraulic performance of a gully under drainage conditions.

During rainfall events with low return periods (1-20 years) the drainage system can provide some degree of protection to urban areas. The system design is based not only on good hydraulic performance of the surface and the sewer network but also on their linking elements. Although the linking elements are of utmost importance as they allow the exchange of flow between the surface and the sewer network, there is a lack of studies that thoroughly characterize them.

Automated detection of proliferative retinopathy in clinical practice.

Timely intervention for diabetic retinopathy (DR) lessens the possibility of blindness and can save considerable costs to health systems. To ensure that interventions are timely and effective requires methods of screening and monitoring pathological changes, including assessing outcomes. Fractal analysis, one method that has been studied for assessing DR, is potentially relevant in today's world of telemedicine because it provides objective indices from digital images of complex patterns such as are seen in retinal vasculature, which is affected in DR.

Automated segmentation of retinal blood vessels and identification of proliferative diabetic retinopathy.

Proliferative diabetic retinopathy can lead to blindness. However, early recognition allows appropriate, timely intervention. Fluorescein-labeled retinal blood vessels of 27 digital images were automatically segmented using the Gabor wavelet transform and classified using traditional features such as area, perimeter, and an additional five morphological features based on the derivatives-of-Gaussian wavelet-derived data.

Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.

We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales.

Automated morphometric analysis of the cat retinal alpha/Y, beta/X and delta ganglion cells using wavelet statistical moment and clustering algorithms.

Computational morphological analysis comprises the development of measures (indicators) that describe different form attributes of a neuron and provides additional parameters for classification algorithms. Our work addressed the problem of small group sizes often encountered in neuromorphological and neurophysiological research, automated classification tasks (unsupervised learning) and introduced a new morphological measure: the wavelet statistical moment. We analysed cat alpha/Y, beta/X and delta Golgi-stained retinal ganglion cells using six different shape features (circularity, 2(nd) statistical moment and entropy of Gaussian blurred images, wavelet statistical moment, number of terminations and the fractal dimension).