We reconcile trade theory with plant-level export behavior, extending the Ricardian model to accommodate many countries, geographic barriers, and imperfect com-petition. Our model captures qualitatively basic facts about U.S. plants: (i) pro-ductivity dispersion, (ii) higher productivity among

, and at larger size scales, the best possible communities gradually “blend in ” with the rest of the network and thus become less “community-like.” This behavior is not explained, even at a qualitative level, by any of the commonly-used network generation models. Moreover, this behavior is exactly the opposite

are similar to the conclusion category and (b) the degree to which the premise categories are similar to members of the lowest level category that includes both the premise and the conclusion categories. A model based on this hypothesis accounts for 13 qualitative phenomena and the quantitative results

-based Kalman filtering algorithm. We compare the performance of the two approaches by analyzing their theoretical convergence rates, by conducting quantitative experiments with images of a flat poster, and by conducting qualitative experiments with images of a realistic outdoor-scene model. The results show

from evolu-tionary economics and technology studies. This results in a multi-level perspective on TT where two views of the evolution are combined: (i) evolution as a process of variation, selection and retention, (ii) evolution as a process of unfolding and re-configuration. The perspective

Abstract: High Power Laboratory is designed for high currents tests and it found within a modernisation process through: purchasing of new equipment, electrical apparatus and electromechanical equipment in order to realise a new installation endowed with equipment having superior characteristics and by rehabilitation of the existent buildings according to European Union norms.

A framework for the qualitative representation of positional information in a two-dimensional space is presented. Qualitative representations use discrete quantity spaces, where a particular distinction is introduced only if it is relevant to the context being modeled. This allows us to build a

Advances in networking technologies will soon make it possible to use the global information infrastructure in a qualitatively different way—as a computational resource as well as an information resource. This idea for an integrated computation and information resource called the Computational

This article presents: (i) a multi-scale representation of grey-level shape called the scale-space primal sketch, which makes explicit both features in scale-space and the relations between structures at different scales, (ii) a methodology for extracting significant blob-like image structures from

Spatial reasoning is essential for many AI applications. In most existing systems the representation is primarily numerical, so the information that can be handled is limited to precise quantitative data. However, for many purposes the ability to manipulate high-level qualitative spatial