Unsupervised image segmentation with neural networks

The segmentation of colour images (RGB), distinguishing clusters of image points, representing for example background, leaves and flowers, is performed in a multi-dimensional environment. Considering a two dimensional environment, clusters can be divided by lines. In a three dimensional environment by planes and in an n-dimensional environment by n-1 dimensional structures. Starting with a complete data set the first neural network, represents an n-1 dimensional structure to divide the data set into two subsets. Each subset is once more divided by an additional neural network: recursive partitioning. This results in a tree structure with a neural network in each branching point. Partitioning stops as soon as a partitioning criterium cannot be fulfilled. After the unsupervised training the neural system can be used for the segmentation of images

Feedback control of water supply in an NFT growing system

The paper explores a concept of irrigation control, where the supply of nutrient solution is controlled without the use of predictive uptake models but rather by the use of a direct feedback of a drain flow measurement. This concept proves to be a viable approach. Results are presented, showing the compensation of changes in water up-take due to variations in global radiation, with a very tight control of the drain flow, keeping it constant over long periods of time. A tipping-bucket type flow sensor and its use in controlled water supply to a to-mato crop is described. A calibration procedure for the tipping-bucket instrument is presented

In-Situ Wave Observations in the High Resolution Air-Sea Interaction DRI

LONG-TERM GOALS: Ocean wave prediction models, based on a spectral energy balance, are widely used to obtain windwave forecasts and hindcasts on global and regional scales (e.g., Komen et al., 1994). However, these inherently stochastic models assume a Gaussian and homogeneous sea state and thus do not describe the nonlinear instability processes that can dramatically alter the structure of wave groups and produce anomalously large waves, also known as ‘freak’ or ‘rogue’ waves (e.g., Janssen, 2003). Fully deterministic modeling capabilities are now becoming available that incorporate these nonlinear effects and provide the detailed phase-resolved sea surface predictions needed in many applications. Concurrent with the development of new models, advances in radar remote sensing techniques are enabling the detailed observation of the sea surface on the scales of wave groups and individual waves. The long-term goal of this research is to test these emerging new models and measurement technologies in realistic sea states and use them to better understand and predict the wave group structure and occurrence of extreme waves in the ocean.Award Number: N0001407WR2016

In-Situ Wave Observations in the High Resolution Air-Sea Interaction DRI

LONG-TERM GOALS: Ocean wave prediction models, based on a spectral energy balance, are widely used to obtain windwave forecasts and hindcasts on global and regional scales (e.g., Komen et al., 1994). However, these inherently stochastic models assume a Gaussian and homogeneous sea state and thus do not describe the nonlinear instability processes that can dramatically alter the structure of wave groups and produce anomalously large waves, also known as ‘freak’ or ‘rogue’ waves. Fully deterministic modeling capabilities are now becoming available that incorporate these nonlinear effects and provide the detailed phase-resolved sea surface predictions needed in many applications. Concurrent with the development of new models, advances in radar remote sensing techniques are enabling the detailed observation of the sea surface on the scales of wave groups and individual waves. The long-term goal of this research is to test these emerging new models and measurement technologies in realistic sea states and use them to better understand and predict the wave group structure and occurrence of extreme waves in the ocean.Award Numbers: N0001412WX20004, N00014091034

Solitons in the noisy Burgers equation

We investigate numerically the coupled diffusion-advective type field equations originating from the canonical phase space approach to the noisy Burgers equation or the equivalent Kardar-Parisi-Zhang equation in one spatial dimension. The equations support stable right hand and left hand solitons and in the low viscosity limit a long-lived soliton pair excitation. We find that two identical pair excitations scatter transparently subject to a size dependent phase shift and that identical solitons scatter on a static soliton transparently without a phase shift. The soliton pair excitation and the scattering configurations are interpreted in terms of growing step and nucleation events in the interface growth profile. In the asymmetrical case the soliton scattering modes are unstable presumably toward multi soliton production and extended diffusive modes, signalling the general non-integrability of the coupled field equations. Finally, we have shown that growing steps perform anomalous random walk with dynamic exponent z=3/2 and that the nucleation of a tip is stochastically suppressed with respect to plateau formation.Comment: 11 pages Revtex file, including 15 postscript-figure

Dobutamine cardiovascular magnetic resonance

Dobutamine stress cardiovascular magnetic resonance (CMR) is a new diagnostic tool for the noninvasive detection of coronary artery disease. With technological advances, CMR has evolved to become an adequate alternative to standard cardiac stress tests such as ECG exercise stress testing, stress echocardiography, and perfusion scintigraphy. Magnetic resonance imaging technology is widely available, possible in nearly every patient, and not associated with exposure to ionizing radiation. Its high reproducibility and high image quality of the anatomical features of the left ventricle and left ventricular function at rest and during stress make it an ideal technique for the comprehensive evaluation of patients with suspected coronary artery disease. Besides its ability to detect myocardial ischaemia, CMR has proved to be diagnostic for myocardial viability as well. A recent technical refinement in CMR using myocardial tagging has improved the diagnostic accuracy for myocardial ischaemia even further. This article reviews the pathophysiology and methodology of dobutamine stress CMR. The recent literature is discussed.</p

Dobutamine cardiovascular magnetic resonance

Dobutamine stress cardiovascular magnetic resonance (CMR) is a new diagnostic tool for the noninvasive detection of coronary artery disease. With technological advances, CMR has evolved to become an adequate alternative to standard cardiac stress tests such as ECG exercise stress testing, stress echocardiography, and perfusion scintigraphy. Magnetic resonance imaging technology is widely available, possible in nearly every patient, and not associated with exposure to ionizing radiation. Its high reproducibility and high image quality of the anatomical features of the left ventricle and left ventricular function at rest and during stress make it an ideal technique for the comprehensive evaluation of patients with suspected coronary artery disease. Besides its ability to detect myocardial ischaemia, CMR has proved to be diagnostic for myocardial viability as well. A recent technical refinement in CMR using myocardial tagging has improved the diagnostic accuracy for myocardial ischaemia even further. This article reviews the pathophysiology and methodology of dobutamine stress CMR. The recent literature is discussed.</p

Damped finite-time-singularity driven by noise

We consider the combined influence of linear damping and noise on a dynamical finite-time-singularity model for a single degree of freedom. We find that the noise effectively resolves the finite-time-singularity and replaces it by a first-passage-time or absorbing state distribution with a peak at the singularity and a long time tail. The damping introduces a characteristic cross-over time. In the early time regime the probability distribution and first-passage-time distribution show a power law behavior with scaling exponent depending on the ratio of the non linear coupling strength to the noise strength. In the late time regime the behavior is controlled by the damping. The study might be of relevance in the context of hydrodynamics on a nanometer scale, in material physics, and in biophysics.Comment: 9 pages, 4 eps-figures, revtex4 fil

Power laws and stretched exponentials in a noisy finite-time-singularity model

We discuss the influence of white noise on a generic dynamical finite-time-singularity model for a single degree of freedom. We find that the noise effectively resolves the finite-time-singularity and replaces it by a first-passage-time or absorbing state distribution with a peak at the singularity and a long time tail exhibiting power law or stretched exponential behavior. The study might be of relevance in the context of hydrodynamics on a nanometer scale, in material physics, and in biophysics.Comment: 10 pages revtex file, including 4 postscript-figures. References added and a few typos correcte