Stemming

Summary

In linguistic morphology and information retrieval, stemming is the process of reducing inflected (or sometimes derived) words to their word stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root. Algorithms for stemming have been studied in computer science since the 1960s. Many search engines treat words with the same stem as synonyms as a kind of query expansion, a process called conflation. A computer program or subroutine that stems word may be called a stemming program, stemming algorithm, or stemmer. Examples A stemmer for English operating on the stem cat should identify such strings as cats, catlike, and catty. A stemming algorithm might also reduce the words fishing, fished, and fisher to the stem fish. The stem need not be a word, for example the Porter algorithm reduces, argue, arg

Official source

https://en.wikipedia.org/wiki/Stemming

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Comparative study of environmental impacts of imported organic products and regional conventional products – Geneva's case

Florence Escalera

Nowadays, the consumer is worried by his health and by the environmental protection. Two interesting groups, among the others, can be distinguished : persons worried of eating organic products and persons who consume regional products. What about imported organic products? And what about local conventional products? Which environmental impacts have they? The objective of the work was to compare products stemming from the organic farming and imported in Geneva with products stemming from the regional conventional agriculture, where the region is Geneva. Studied products are apple, tomato, wheat and egg. The origin of these organic products is New-Zealand, Netherland, Canada and United Kingdom, respectively. Results show that each production process involves specific impacts. A unique conclusion for all fruits, all vegetables, all cereals or all animal products is not possible. However, for the precise cases studied, we can say that for all products results show that the imported organic products lead more environmental impacts than regional conventional products. For tomato and egg, a production improvement could invert the tendency. For apple and wheat, a transport reduction will decrease environmental impacts. These results lead to some interrogations : Is Local agriculture enough to feed its inhabitants? Is conventional agriculture sustainable?

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MATHICSE Technical Report : Explicit stabilized multirate method for stiff stochastic differential equations

Assyr Abdulle, Giacomo Rosilho De Souza

Stabilized explicit methods are particularly ecient for large systems of sti stochastic dif- ferential equations (SDEs) due to their extended stability domain. However, they loose their eciency when a severe stiness is induced by very few fast degrees of freedom, as the sti and nonsti terms are evaluated concurrently. Therefore, inspired by [A. Abdulle, M. J. Grote, and G. Rosilho de Souza, Preprint (2020), arXiv:2006.00744], we introduce a stochastic modi- ed equation whose stiness depends solely on the slow terms. By integrating this modied equation with a stabilized explicit scheme we devise a multirate method which overcomes the bottleneck caused by a few severely sti terms and recovers the eciency of stabilized schemes for large systems of nonlinear SDEs. The scheme is not based on any scale separation as- sumption of the SDE and therefore it is employable for problems stemming from the spatial discretization of stochastic parabolic partial dierential equations on locally rened grids. The multirate scheme has strong order 1=2, weak order 1 and its stability is proved on a model problem. Numerical experiments conrm the eciency and accuracy of the scheme.

EPFL2020

Explicit Stabilized Multirate Method For Stiff Stochastic Differential Equations

Assyr Abdulle, Giacomo Rosilho De Souza

Stabilized explicit methods are particularly efficient, for large systems of stiff stochastic differential equations (SDEs) due to their extended stability domain. However, they lose their efficiency when a severe stiffness is induced by very few "fast" degrees of freedom, as the stiff and nonstiff terms are evaluated concurrently. Therefore, inspired by [A. Abdulle, M. J. Grote, and G. Rosilho de Souza, Explicit stabilized multirate method for stiff differential equations, Math. Comp., in press, 2022], we introduce a stochastic modified equation whose stiffness depends solely on vi the "slow" terms. By integrating this modified equation with a stabilized explicit scheme, we devise a multirate method which overcomes the bottleneck caused by a few severely still terms and recovers the efficiency of stabilized schemes for large systems of nonlinear SDEs. The scheme is not based on any scale separation assumption of the SDE. Therefore, it is employable for problems stemming from the spatial discretization of stochastic parabolic partial differential equations on locally refined grids. The multirate scheme has strong Order 1/2, weak order 1, and its stability is proved on a model problem. Numerical experiments confirm the efficiency and accuracy of the scheme.

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