Search results for "Combinatorial algorithms"
showing 3 items of 3 documents
Combinatorial Gray codes for classes of pattern avoiding permutations
2007
The past decade has seen a flurry of research into pattern avoiding permutations but little of it is concerned with their exhaustive generation. Many applications call for exhaustive generation of permutations subject to various constraints or imposing a particular generating order. In this paper we present generating algorithms and combinatorial Gray codes for several families of pattern avoiding permutations. Among the families under consideration are those counted by Catalan, Schr\"oder, Pell, even index Fibonacci numbers and the central binomial coefficients. Consequently, this provides Gray codes for $\s_n(\tau)$ for all $\tau\in \s_3$ and the obtained Gray codes have distances 4 and 5.
A combinatorial algorithm for the optimization of refraction seismics data inversion
1993
Abstract The problem of data inversion in refraction seismics can be split in two parts: data first must be preprocessed in order to determine the travel-time curve; this essentially is a geometrical problem, complicated, however, by its pattern recognition aspects. Once the geometrical problem is solved, the second part, the inversion proper, is straightforward, as the soil layering model can be calculated according to well-known algorithms. The more difficult part of the problem is the former, which implies a type of pattern recognition; because of this type of difficulty, the geometrical part of the problem usually is committed to the skill of a human operator. This paper describes an al…
CAMLearn : a semantic context-aware recommender system architecture : application on m-learning domain
2015
Given the rapid emergence of new mobile technologies and the growth of needs of a moving society in training, works are increasing to identify new relevant educational platforms to improve distant learning. The next step in distance learning is porting e-learning to mobile systems. This is called m-learning. So far, learning environment was either defined by an educational setting, or imposed by the educational content. In our approach, in m-learning, we change the paradigm where the system recommends content and adapts learning follow to learner's context.