Uncertainty Propagation in Model-Based Recognition

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

Progress in front propagation research

We review the progress in the field of front propagation in recent years. We survey many physical, biophysical and cross-disciplinary applications, including reduced-variable models of combustion flames, Reid's paradox of rapid forest range expansions, the European colonization of North America during the 19th century, the Neolithic transition in Europe from 13 000 to 5000 years ago, the description of subsistence boundaries, the formation of cultural boundaries, the spread of genetic mutations, theory and experiments on virus infections, models of cancer tumors, etc. Recent theoretical advances are unified in a single framework, encompassing very diverse systems such as those with biased random walks, distributed delays, sequential reaction and dispersion, cohabitation models, age structure and systems with several interacting species. Directions for future progress are outlined

Beyond divide and rule : weak dictators, natural resources and civil conflict

We propose a model where an autocrat rules over an ethnically divided society. The dictator selects the tax rate over domestic production and the nation’s natural resources to maximize his rents under the threat of a regime-switching revolution. We show that a weak ruler may let the country plunge in civil war to increase his personal rents. Inter-group fighting weakens potential opposition to the ruler, thereby allowing him to increase fiscal pressure. We show that the presence of natural resources exacerbates the incentives of the ruler to promote civil conflict for his own profit, especially if the resources are unequally distributed across ethnic groups. We validate the main predictions of the model using cross-country data over the period 1960-2007, and show that our empirical results are not likely to be driven by omitted observable determinants of civil war incidence or by unobservable country-specific heterogeneity.

International propagation of shocks: an evaluation of contagion effects for some Latin American countries

In this paper we analyze the spread of shocks across assets markets in eight Latin American countries. First, we measure the extent of markets reactions with the Principal Components Analysis. And second, we investigate the volatility of assets markets based in ARCH-GARCH models in function of the principal components retained in the first stage. Our results do not support the existence of financial contagion, but of interdependence in most of the cases and a slight increase in the sensibility of markets to recent shocks.

Evolving graphs: dynamical models, inverse problems and propagation

Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

Tissue culture propagation alters plant-microbe interactions in tobacco rhizosphere

We have compared properties of roots from different lines (genotypes) of tobacco raised either in tissue culture or grown from seed. The different lines included unmodified plants and plants modified to express reduced activity of the enzyme cinnamoyl-CoA reductase, which has a pivotal role in lignin biosynthesis. The size and structure of the rhizosphere microbial community, characterized by adenosine triphosphate and phospholipid fatty acid analyses, were related to root chemistry (specifically the soluble carbohydrate concentration) and decomposition rate of the roots. The root material from unmodified plants decomposed faster following tissue culture compared with seed culture, and the faster decomposing material had significantly higher soluble carbohydrate concentrations. These observations are linked to the larger microbial biomass and greater diversity of the rhizosphere communities of tissue culture propagated plants.

Tissue culture propagation alters plant-microbe interactions in tobacco rhizosphere

We have compared properties of roots from different lines (genotypes) of tobacco raised either in tissue culture or grown from seed. The different lines included unmodified plants and plants modified to express reduced activity of the enzyme cinnamoyl-CoA reductase, which has a pivotal role in lignin biosynthesis. The size and structure of the rhizosphere microbial community, characterized by adenosine triphosphate and phospholipid fatty acid analyses, were related to root chemistry (specifically the soluble carbohydrate concentration) and decomposition rate of the roots. The root material from unmodified plants decomposed faster following tissue culture compared with seed culture, and the faster decomposing material had significantly higher soluble carbohydrate concentrations. These observations are linked to the larger microbial biomass and greater diversity of the rhizosphere communities of tissue culture propagated plants.

Depth by The Rule

This note corrects a previous treatment of algorithms for the metric DTR, Depth by the Rule.