National Repository of Grey Literature 45 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Sort Program for Real Keys with Linear Time Complexity
Jiřina, Marcel
In this report we present a program for sorting data structures with sorting keys as real numbers, i.e. of type "real" or "float". The basis of the program is a modification of the countingsort algorithm for reals (instead of integers). It uses a comparision-type sorting for small part of data set given. The time complexity of this part of program can be bounded by linear function of n and thus, the total time complexity is also O(n) for n data items.
Use of biological feedback during training of postural regulation
Papáček, Roman ; Mužík, Jan (advisor) ; Jiřina, Marcel (referee)
The thesis focuses on the study of the impact of visual stimuli from virtual reality scenes and on influencing and training postural stability in patients after brain damage. It endeavours to inform comprehensively about the substantial facts related to this topic and widen the possibilities of an objective evaluation of postural stability and this eliminate the risk of a subjective mistake made by a physiotherapist. In the course of the work I have used a number of virtual reality scenes through which I measured and evaluated both static and dynamic labour of the tested people with their own centre of mass. The process of positioning was scanned by Wii Balance Board and the data were recorded with the help of a specially designed computer application "Rehabilitation in virtual reality". It was necessary to create two groups of people tested. A group of healthy probands of 50 in number and a group of patients comprising 3 members. In one part, the recorded data represented the figures of centre deflection (in millimetres), and in the other part, the number of points gained during the measuring. The results of both parts were then processed into well-arranged tables which also involve the basic statistic quantities, and they are presented in the form of graphs. In the conclusion, the thesis verifies...
The Distribution Mapping Functions
Jiřina, Marcel
The target of this study is to make clear the difference of the distribution mapping function introduced in 2003 and the classical notion of point processes theory, the counting function N, Ripley’s K-function, and other two distance functions, F and G-functions. We summarize here necessary starting points from the point process theory using the famous work by Baddeley, a two-volume book of Daley and Vere-Jones and short paper by Dixon. When dealing with the distribution mapping function we use up-to-date formulations used in various papers since 2003.
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Influence of Metric on Classification Error of Distance-Based Classifiers
Jiřina, Marcel
Five types of classifiers that use sample distances for class estimation of an unknown sample was tested. Each classifier was tested with fifteen different metrics on 24 classification tasks from the UCI Machine Learning Repository. The metrics were compared and the best of them was found for each classifier. Surprisingly, the best metrics for all five types of classifiers is the Hassanat metrics. Classifiers were also compared and ranked according to their classification ability. Wilcoxon Test and Friedman Aligned test were used for statistical evaluation.
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Volatility of selected separators/classifiers wrt. data sets from field of particle physics
Jiřina, Marcel ; Hakl, František
We study the volatility, i.e. influence of random changes in data sets to overall separation/classification behavior of separators/classifiers. This is motivated by the fact, that simulated data and true data from ATLAS experiment may differ, and a question arises what if separators or cuts are optimized for simulated data, and then used for true data from the experiment. This behavior was studied using simulated data modified by artificial distortions of known size. We found that even slight change in data sets causes a little worse result than supposed but, surprisingly, even relatively large distortions give then nearly the same results. Only truly great variations cause degradation of separation quality of separator/classifier as well as of the cuts method.
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1 Jiřina, Martin
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