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EN
Context: In software engineering, snowball sampling has been used as a supplementary and primary search strategy. The current guidelines recommend using Google Scholar (GS) for snowball sampling. However, the use of GS presents several challenges when using it as a source for citations and references. Objective: To compare the effectiveness and usefulness of two leading citation databases (GS and Scopus) for use in snowball sampling search. Method: We relied on a published study that has used snowball sampling as a search strategy and GS as the citation source. We used its primary studies to compute precision and recall for Scopus. Results: In this particular case, Scopus was highly effective with 95% recall and had better precision of 5.1% compared to GS’s 2.8%. Moreover, Scopus found nine additional relevant papers. On average, one would read approximately 15 extra papers in GS than Scopus to identify one additional relevant paper. Furthermore, Scopus supports batch downloading of both citations and papers’ references, has better quality metadata, and does better source filtering. Conclusion: This study suggests that Scopus seems to be more effective and useful for snowball sampling than GS for systematic secondary studies attempting to identify peer-reviewed literature.
2
Content available remote Solving Sequential Planning Problems via Constraint Satisfaction
EN
Planning problems deal with finding a sequence of actions that transfer the initial state of the world into a desired state. Frequently such problems are solved by dedicated algorithms but there exist planners based on translating the planning problem into a different formalism such as constraint satisfaction or Boolean satisfiability and using a general solver for this formalism. The paper describes how to enhance existing constraintmodels of sequential planning problems by using techniques such as symmetry breaking (dominance rules), singleton consistency, nogoods, lifting, or techniques motivated by the partial-order planning.
PL
Krawędziowa liczba przeszukiwawcza grafu informuje nas ilu mobilnych agentów, przykładowo jednostek policji, jest niezbędnych do przechwycenia poruszającego się z dowolnie dużą prędkością uciekiniera w danym grafie. Podczas praktycznych zastosowań modelu w systemach bezpieczeństwa rzadko jednak spotyka się jednostki poruszające się z nieograniczoną prędkością. W pracy tej pokazujemy, że agenci mogą wykorzystać fakt ograniczonej prędkości uciekiniera w celu poprawienia strategii jego przechwytywania. Zaproponowany zostaje dyskretny w czasie model analizy przechwytywania obiektów poruszających się w grafie z ograniczoną prędkością.
EN
Edge search number of a graph is a value, that provides us with information as to how many mobile agents, for instance police units, are required to capture an arbitrary fast evader in a given graph. In practical application of this model in security systems units, that do not have any boundary on their speed, are rarely met. In this paper we show, that agents may use the fact of evaders bounded speed in order to improve their search strategy. We present a discrete-time model which may be used to analyze interception of objects moving with bounded speed.
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