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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Dynamic properties of trees
 Němeček, Viktor ; Mareš, Martin (advisor) ; Mička, Ondřej (referee)
In this thesis we compared some variants of binary search trees that approach dynamic optimality: Tango trees, Multisplay trees, and Splay trees. We empirically tested the behavior of these three types of trees, as well as Red-Black trees. We measured the amount of visited nodes per operation and running time on real hardware. We proved that Tango trees and Multisplay trees are in most cases less efficient than Splay trees and Red-Black trees. Cache-related effects played a surprisingly large part in the behavior of Red-Black tree and Splay tree. 1
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Perceptual learning and Ideal Bayesian obsever in visual search task
 Němeček, Viktor ; Děchtěrenko, Filip (advisor) ; Pilát, Martin (referee)
Searching for objects in a complex environment is an activity we do many times each day. Najemnik and Geisler (2005; 2008; 2009) showed in their work that people do not perform optimally, and devised multiple ideal observer models for one particular visual search task. In this thesis we tried to show that if people get feedback from one of the ideal observer models, they learn to solve the task better during a given amount of trials than they would without the feedback. We were unable to prove any nontrivial result with statistical significance due to a small sample size, but the data suggests that the feedback indeed has a positive effect on the learning, and that the continuation of the research is justified. An iOS application necessary for the experiment was created as a part of the thesis. Aside from the experiment itself, one can also use it to play a visual search testing game. 1
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See also: similar author names
2 Němeček, Vojtěch
7 Němeček, Vratislav
5 Němeček, Václav
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