Linear polarization of light by two wheat canopies measured at many view angles

The linear polarization and reflection of visible light by wheat as a function of sun-view directions, crop development stage, and wavelength were examined. Two-hundred spectra were taken continuously in wave-lengths from 0.45 to 0.72 Micron in 33 view directions using an Exotech model 20C spectroradiometer six meters above two wheat canopies in the boot and fully headed maturity stages. The analysis results show that the amount of linearly polarized light from the wheat canopies is greatest in the blue spectral region and decreases gradually with increasing wavelength. The results also show that the linearly polarized light from the canopies is generally greatest in the azimuth direction of the Sun and tends toward zero as the view direction tends toward the direction of the hot spot or anti-solar point. It is demonstrated that the single, angle of incidence of sunlight on the leaf, explains almost all of the variation of the amount of polarized light with Sun-view direction

Simulated response of a multispectral scanner over wheat as a function of wavelength and view/illumination direction

The reflectance response with view angle of wheat, was analyzed. The analyses, which assumes there are no atmospheric effects, and otherwise simulates the response of a multispectral scanner, is based upon spectra taken continuously in wavelength from 0.45 to 2.4 micrometers at more than 1200 view/illumination directions using an Exotech model 20C spectra radiometer. Data were acquired six meters above four wheat canopies, each at a different growth stage. The analysis shows that the canopy reflective response is a pronounced function of illumination angle, scanner view angle and wavelength. The variation is greater at low solar elevations compared to high solar elevations

Agricultural scene understanding and supporting field research, volume 1

There are no author-identified significant results in this report

Globally optimal on-line learning rules for multi-layer neural networks

We present a method for determining the globally optimal on-line learning rule for a soft committee machine under a statistical mechanics framework. This rule maximizes the total reduction in generalization error over the whole learning process. A simple example demonstrates that the locally optimal rule, which maximizes the rate of decrease in generalization error, may perform poorly in comparison

Agricultural scene understanding, volume 1

There are no author-identified significant results in this report

Biopolitical precarity in the permeable body: the social lives of people, viruses and their medicines

This article is based on multi-sited ethnography that traced a dynamic network of actors (activists, policy-makers, health care systems, pharmaceutical companies) and actants (viruses and medicines) that shaped South African women’s access to, and embodiment of, antiretroviral therapies (ARVs). Using actor network theory and post-humanist performativity as conceptual tools, the article explores how bodies become the meeting place for HIV and ARVs, or non-human actants. The findings centre around two linked sets of narratives that draw the focus out from the body to situate the body in relation to South Africa’s shifting biopolitical landscape. The first set of narratives articulate how people perceive the intra-action of HIV and ARVs in their sustained vitality. The second set of narratives articulate the complex embodiment of these actants as a form biopolitical precarity. These narratives flow into each other and do not represent a totalising view of the effects of HIV and ARVs in the lives of the people with whom I worked. The positive effects of ARVs (as unequivocally essential for sustaining life) were implicit and the precarious vitality of the people in this ethnography was fundamental. However, a related and emergent set of struggles become salient during the study that complicate a view of ARVs as a ‘technofix’. These emergent struggles were biopolitical, and they related first to the intra-action of HIV and ARVs ‘within’ the body; and second, to the ‘outside’ socio-economic context in which people’s bodies were situated

Retarded Learning: Rigorous Results from Statistical Mechanics

We study learning of probability distributions characterized by an unknown symmetry direction. Based on an entropic performance measure and the variational method of statistical mechanics we develop exact upper and lower bounds on the scaled critical number of examples below which learning of the direction is impossible. The asymptotic tightness of the bounds suggests an asymptotically optimal method for learning nonsmooth distributions.Comment: 8 pages, 1 figur

Unconventional MBE Strategies from Computer Simulations for Optimized Growth Conditions

We investigate the influence of step edge diffusion (SED) and desorption on Molecular Beam Epitaxy (MBE) using kinetic Monte-Carlo simulations of the solid-on-solid (SOS) model. Based on these investigations we propose two strategies to optimize MBE growth. The strategies are applicable in different growth regimes: During layer-by-layer growth one can exploit the presence of desorption in order to achieve smooth surfaces. By additional short high flux pulses of particles one can increase the growth rate and assist layer-by-layer growth. If, however, mounds are formed (non-layer-by-layer growth) the SED can be used to control size and shape of the three-dimensional structures. By controlled reduction of the flux with time we achieve a fast coarsening together with smooth step edges.Comment: 19 pages, 7 figures, submitted to Phys. Rev.

Multifractal Analysis of the Coupling Space of Feed-Forward Neural Networks

Random input patterns induce a partition of the coupling space of feed-forward neural networks into different cells according to the generated output sequence. For the perceptron this partition forms a random multifractal for which the spectrum $f(\alpha)$ can be calculated analytically using the replica trick. Phase transition in the multifractal spectrum correspond to the crossover from percolating to non-percolating cell sizes. Instabilities of negative moments are related to the VC-dimension.Comment: 10 pages, Latex, submitted to PR

Slowly evolving geometry in recurrent neural networks I: extreme dilution regime

We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic equations which on average aim to reduce frustration. The (fast) neurons and (slow) connectivity variables equilibrate separately, but at different temperatures. Our model is exactly solvable in equilibrium. We obtain phase diagrams upon making the condensed ansatz (i.e. recall of one pattern). These show that, as the connectivity temperature is lowered, the volume of the retrieval phase diverges and the fraction of mis-aligned spins is reduced. Still one always retains a region in the retrieval phase where recall states other than the one corresponding to the `condensed' pattern are locally stable, so the associative memory character of our model is preserved.Comment: 18 pages, 6 figure