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1
Content available remote

Distinction between voluntary cough sound and speech in volunteers by spectral and complexity analysis

100%
Martinek J., Tatar M., Javorka M.
Journal of Physiology and Pharmacology. Supplement
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2008
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tom 59
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nr 6
433-440
2

Application of cIassification trees in statistical analysis of ewe prolificacy

84%
Piwczynski D.
Roczniki Naukowe Polskiego Towarzystwa Zootechnicznego
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2009
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tom 05
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nr 2
3

Podział zasobu nieruchomości wspólnot mieszkaniowych z wykorzystaniem drzewa klasyfikacyjnego

84%
Muczynski A.
Acta Scientiarum Polonorum. Administratio Locorum
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2010
|
tom 09
|
nr 4
4
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Analysis of selected accommodation conditions at agritourism farms based on the method of classification trees

67%
Cichowska J., Klimek A.
Infrastruktura i Ekologia Terenów Wiejskich
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2011
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nr 12
A comparative analysis, using the classification tree method, of typically agritourism and agriculturally inactive farms has been conducted in this paper. An interview questionnaire, carried out on 78 farms, has been applied as a research tool.According to the research, typically agritourism farms evaluated the quality of their own services more positively. However, these factors did not influence the improvement of offer standards. Perhaps they had to invest more often in the development of farms rather than focus on improving the sanitary and hygiene infrastructure. The residential buildings may have not been adapted to undergo redevelopment in that respect. Agriculturally inactive households rarely broadened their knowledge in order to improve accommodation conditions. They had higher standards regardless of the level of hosts' qualifications. Presumably, hosts who focus mainly on agritourism are more likely to improve accommodation conditions. They basically do not have to pay expenses that would be incurred by agricultural activity. The application of the classification tree method has allowed to observe that high self-evaluation of services provided does not always have to result in better sanitary equipment of rooms or possession of living rooms. The method has made it possible to present the examined factors in a simple graphical manner, thus allowing to notice differences between typically agritourism farms and agriculturally inactive farms.
5

Reliable automation of bat call identification for eastern New South Wales, Australia, using classification trees and AnaScheme software

67%
Adams M. D., Law B. S., Gibson M. S.
Acta Chiropterologica
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2010
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tom 12
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nr 1
Accurate and efficient identification of bat (Microchiroptera) echolocation calls has been hampered by poor knowledge of the intraspecific variability in calls (including regional variation), a lack of call parameters for use in separating species and the amount of time required to manually identify individual calls or call sequences. We constructed and tested automated bat call identification keys for three regions in New South Wales, Australia, using over 4,000 reference calls in ≈300 call sequences per region. We used the program AnaScheme to extract time, frequency and shape parameters from calls recorded with the Anabat system. Classification trees were built to separate species using these parameters and provided the decision rules for construction of the keys. An ‘Unknown’ category was included in the keys for sequences that could not be confidently identified to species. The reliability of the keys was tested automatically with AnaScheme, using independent sets of reference call sequences, and keys were refined before further testing on additional test sequences. Regional keys contained 18–19 species or included species groups. We report rates of sequence misidentification (accuracy) and correct identification (detection) relative to all sequences (including ‘unknowns’) used to test each version of a key. Refined versions of the keys were accurate, with total misidentification rates of 0.5–5.3% for the three regions. Additionally, total correct identifications for regions were 56–75% (> 50% for most species), an overall high rate of detection. When ‘unknowns’ were ignored, as is common in many published studies, correct identification for regions increased to 91–99%, rates which compare favourably to the most successful classifiers tested to date. The future use of AnaScheme for automated bat call identification is promising, especially for the large-scale temporal and spatial acoustic sampling to which Anabat is particularly suited.
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