Preliminary evaluation of infrared and radar imagery, Washington and Oregon coasts

Airborne infrared and radar photography of Oregon and Washington coastal region

Impacts of Reduced Water Availability on Lower Murray Irrigation, Australia

This article evaluates irrigated agriculture sector response and resultant economic impacts of climate change for a part of the Murray Darling Basin in Australia. A water balance model is used to predict reduced basin inflows for mild, moderate and severe climate change scenarios involving 10, 20, 40 Celcius warming, and predict 13%, 38% and 63% reduced inflows. Impact on irrigated agricultural production and profitability are estimated with a mathematical programming model using a two-stage approach that simultaneously estimates short and long-run adjustments. The model accounts for a range of adaptive responses including: deficit irrigation, temporarily fallowing some areas, and permanently reducing irrigated area and changing the mix of crops. The results suggest that relatively low cost adaptation strategies are available for moderate reduction in water availability and thus costs of such reduction are likely to be relatively small. In more severe climate change scenarios greater costs are estimated, adaptations predicted include a reduction in total area irrigated, investments in efficient irrigation, and a shift away from perennial to annual crops as the latter can be managed more profitably when water allocations in some years are very low.water availability, irrigation, Murray Darling Basin, climate change

Hierarchical Subquery Evaluation for Active Learning on a Graph

To train good supervised and semi-supervised object classifiers, it is critical that we not waste the time of the human experts who are providing the training labels. Existing active learning strategies can have uneven performance, being efficient on some datasets but wasteful on others, or inconsistent just between runs on the same dataset. We propose perplexity based graph construction and a new hierarchical subquery evaluation algorithm to combat this variability, and to release the potential of Expected Error Reduction. Under some specific circumstances, Expected Error Reduction has been one of the strongest-performing informativeness criteria for active learning. Until now, it has also been prohibitively costly to compute for sizeable datasets. We demonstrate our highly practical algorithm, comparing it to other active learning measures on classification datasets that vary in sparsity, dimensionality, and size. Our algorithm is consistent over multiple runs and achieves high accuracy, while querying the human expert for labels at a frequency that matches their desired time budget.Comment: CVPR 201

Applications of inertial navigation and modern control theory to the all weather landing problem

Inertial navigation and automatic landing control theory applied to instrument landing proble

Endomorphisms and automorphisms of locally covariant quantum field theories

In the framework of locally covariant quantum field theory, a theory is described as a functor from a category of spacetimes to a category of *-algebras. It is proposed that the global gauge group of such a theory can be identified as the group of automorphisms of the defining functor. Consequently, multiplets of fields may be identified at the functorial level. It is shown that locally covariant theories that obey standard assumptions in Minkowski space, including energy compactness, have no proper endomorphisms (i.e., all endomorphisms are automorphisms) and have a compact automorphism group. Further, it is shown how the endomorphisms and automorphisms of a locally covariant theory may, in principle, be classified in any single spacetime. As an example, the endomorphisms and automorphisms of a system of finitely many free scalar fields are completely classified.Comment: v2 45pp, expanded to include additional results; presentation improved and an error corrected. To appear in Rev Math Phy

A study to develop neutron activation for measuring bone calcium content

Neutron activation analysis for measuring calcium in monkey bone

The distribution of shock waves in driven supersonic turbulence

Supersonic turbulence generates distributions of shock waves. Here, we analyse the shock waves in three-dimensional numerical simulations of uniformly driven supersonic turbulence, with and without magnetohydrodynamics and self-gravity. We can identify the nature of the turbulence by measuring the distribution of the shock strengths. We find that uniformly driven turbulence possesses a power law distribution of fast shocks with the number of shocks inversely proportional to the square root of the shock jump speed. A tail of high speed shocks steeper than Gaussian results from the random superposition of driving waves which decay rapidly. The energy is dissipated by a small range of fast shocks. These results contrast with the exponential distribution and slow shock dissipation associated with decaying turbulence. A strong magnetic field enhances the shock number transverse to the field direction at the expense of parallel shocks. A simulation with self-gravity demonstrates the development of a number of highly dissipative accretion shocks. Finally, we examine the dynamics to demonstrate how the power-law behaviour arises.Comment: accepted to Astron. & Astrophys.; ten page

EXAFS Analysis of Size-Constrained Semiconducting Materials

Semiconducting materials such as CdSe, CdS, PbS and GaP are included in crystalline zeolite Y and mordenite and structurally flexible ethylene-methacrylic acid copolymer solid matrices. EXAFS analysis reveals formation of species with dimensions of molecular size up to ca. 13 A in the crystalline hosts, while the polymer matrices allow agglomeration of larger semiconducting particles. Zeolite anchored structures are distinctively different to small particles with bulk crystal structure as usually found in colloidal systems