Wyniki wyszukiwania - BazTech

1

Nonparametric methods in the analysis of the quality of kernel of selected winter wheat cultivars

Ćwiklińska Magdalena, Hanusz Zofia, Soja Jakub, Polak Renata

Agricultural Engineering

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2021

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Vol. 25, No. 1

125--134

EN

The paper presents a statistical analysis of weight and diameter of kernel obtained for eight investigated winter wheat cultivars. Preliminary analyses of experimental results, such as compliance with a normal distribution, equality of variance for particular cultivars, and occurrence of outliers proved that there is no justification for the use of a traditional one-way analysis of variance for verification of hypotheses according to which weight and diameter of grains of the investigated winter wheat cultivars do not differ. A nonparametric Kruskal-Wallis test was used for verification of hypotheses which based on the experimental results enabled to reject both hypotheses. Further, simultaneous average weight and diameters of grain of the investigated cultivars were compared with the use of Nemenyi-Dunn test. The applied test enabled to conclude which cultivars had a significantly higher weight than the others. Analogous comparisons were carried out for the diameter of kernels of the investigated winter wheat cultivars.

PL

W pracy przedstawiono analizę statystyczną masy oraz średnicy ziarniaków uzyskanych dla ośmiu badanych odmian pszenicy ozimej. Wstępne analizy wyników eksperymentalnych, takie jak, zgodność z rozkładem normalnym, równość wariancji dla poszczególnych odmian oraz wystąpienie obserwacji odstających, wykazały brak podstaw do zastosowania klasycznej jednokierunkowej analizy wariancji do weryfikacji hipotez o braku zróżnicowania masy oraz średnicy ziarniaków badanych odmian pszenicy ozimej. Do weryfikacji hipotez wykorzystano nieparametryczny test Kruskala-Wallisa, który w oparciu o wyniki eksperymentalne pozwolił odrzucić obydwie hipotezy. W dalszej kolejności dokonano porównań jednoczesnych średnich mas i średnic ziarniaków badanych odmian stosując test Nemenyi-Dunna. Zastosowany test pozwolił stwierdzić, które odmiany charakteryzowały się masą istotnie wyższą od pozostałych. Analogiczne porównania przeprowadzono dla średnicy ziarniaków badanych odmian pszenicy ozimej.

2

Analysis of the spatial variability of the concentrations of Na+ and K+ ions in the groundwater sourced in Southern Poland

Kotowski T., Satora S.

Environment Protection Engineering

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2016

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Vol. 42, nr 2

5--18

EN

Differences in the spatial variability of Na+ and K+ ion concentrations in the groundwater sourced in Southern Poland have been analysed. The study was based on selected hydrogeological environments differing in the lithology and geometry of aquifer rock voids. The hydrogeochemical background for Na+ and K+ ions was determined for various hydrogeological environments as well. The hydroge-ochemical background ranges obtained do not deviate significantly from the background ranges for groundwater observed in other areas of Poland. The analyses conducted indicate the presence of anomalous concentrations of Na+ and K+ ions in all hydrogeological environments often accompanied with significantly elevated concentrations of Cl- and SO42– ions. Owing to the fact that the data analysed exhibit a distribution deviating considerably from a normal one, non-parametric methods of statistical inference were used. The results obtained indicate statistically significant differences between the variabilities of Na+ and K+ ion concentrations in various hydrogeological environments. The factors responsible for such differences are lithological variability and different groundwater circulation systems.

3

A parallel net of (1-NN, K-NN) classifiers for optical inspection of surface defects in ferrites

Jóźwik A., Chmielewski L., Skłodowski M., Cudny W.

Machine Graphics and Vision

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1998

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Vol. 7, No. 1/2

99-112

EN

The challenging task of optical inspection of surface defects in ferrite cores has been successfully approached with a set of methods. In this paper the attention is paid to the k Nearest Neighbours classifier developed for the system. A parallel net of two-decision classifiers is presented. The combination of the 1-NN and k-NN rules reduces the training time. A great part of computations is restricted to the class overlap area. The classification quality is significantly improved if a separate feature selection for each of the component classifiers is done. A dramatic improvement of classification speed obtained by reference patterns sets reduction for component classifiers is vital, as in the considered task the classifier is used for recognition of pixels. The proposed modifications of the classifier are of general usefulness for pattern recognition. The presented quality inspection system can be applied to various defect detection tasks.