Let G be a quasirandom graph on n vertices, and let W be a random walk on G of length αn. Must the set of edges traversed by W form a quasirandom graph? This question was asked by Böttcher, Hladký, Piguet and Taraz. Our aim in this paper is to give a positive answer to this question. We also prove a similar result for random embeddings of trees.

We present our approach and result for the MediaEval 2017 AcousticBrainz Content-based music genre recognition task. Experimental results show that the best results come from random forest with partial feature selection.

This article is devoted to a new iterative construction of hierarchical classifiers in SimpleCLI for the detection of phishing websites. Our new construction of hierarchical systems creates ensembles of ensembles in SimpleCLI by iteratively linking a top-level ensemble to another middle-level ensemble instead of a base classifier so that the top-level ensemble can generate a large multilevel sy...

As people living near forests in many parts of the world receive recognition of resource-management rights, questions arise about where forest boundaries should be set and who should legitimately receive these rights. Drawing on research conducted among forest-dwelling Kenyah communities in Kalimantan, Indonesia, during 1995 to 1998, I show that the realization of resource rights must be unders...

Increasing trees have been introduced by Bergeron, Flajolet and Salvy [1]. This kind of notion covers several well knows classes of random trees like binary search trees, recursive trees, and plane oriented (or heap ordered) trees. We consider the height of increasing trees and prove for several classes of trees (including the above mentioned ones) that the height satisfies EHn ∼ γ logn (for so...

Forest types mapping, is one of the most necessary elements in the forest management and silviculture treatments. Traditional methods such as field surveys are almost time-consuming and cost-intensive. Improvements in remote sensing data sources and classification –estimation methods are preparing new opportunities for obtaining more accurate forest biophysical attributes maps. This research co...

Classical methods for classification of pixels in multispectral images include supervised classifiers such as the maximum-likelihood classifier, neural network classifiers, fuzzy neural networks, support vector machines, and decision trees. Recently, there has been an increase of interest in ensemble learning – a method that generates many classifiers and aggregates their results. Breiman propo...