Wyniki wyszukiwania - Biblioteka Nauki

1

Identification of models of order three applying step response moment method

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Halawa J. , Szustalewicz A.

Przegląd Elektrotechniczny

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2010

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tom R. 86, nr 6

236-238

EN

The paper presents a method of determining parameters of simplified model described by transfer function of order three. The function R(t) is a simple function of step response for the model under identification. Three moments of function R(t) suffice to calculate the parameters of simplified model.

PL

W pracy przedstawiono metodę wyznaczania parametrów modelu uproszczonego trzeciego rzędu na podstawie funkcji R(t), którą wyznacza się z odpowiedzi skokowej identyfikowanego obiektu. Trzy momenty funkcji R(t) służą do wyznaczenia parametrów modelu uproszczonego.

2

LARS regression in diagnosing mammograms: selection of variables for analysis

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Bartkowiak A. , Szustalewicz A.

Colloquium Biometricum

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2011

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tom 41

3

Watching steps of a grand tour implementation

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Bartkowiak A. , Szustalewicz A.

Machine Graphics and Vision

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1998

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tom Vol. 7, No. 3

655-680

EN

Bartkowiak and Szustalewicz, 1997 (B&Sz), have proposed an implementation of the grand tour algorithm designed specially to detect outliers in multivariate data. The algorithm work by performing a sequence of rotations and projections onto a specific 2D-plane (Π proj). This is equivalent to perform a series of rotations yielding transformed coordinates of the data: X(tr) = XA, with A being the rotation matrix, while X and X,sup>(tr) denote the data matrices before and after the rotation appropriately. A superimposed concentration ellipse indicates the outstanding points. We complement the paper of B&Sz by considering some details and variants of the implementation of the grand tour algorithm. In particular we watch the trajectories of the projected points. Our concern is the denseness of the watched projctions. We look at the trajectories of the projected point visible in the Π proj plane and the frequencies of thier appearing in various sectors of that plane. In the Appendix we present the derivation of the formula for the rotation matrix A employed in each step of the algorithm for obtaining the transformed data coordinates.

4

Distribution of amino-acids coding genetic information in yeast ORFs

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Bartkowiak A. , Szustalewicz A.

Metody Informatyki Stosowanej

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2008

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tom nr 3 (Tom 16)

33--39

EN

The genetic code of living organisms is inscribed into so called Open Reading Frames (ORFs) positioned in chromosomes. The code uses 20 amino-acids as building blocks of the inscribed information. We consider in details the 7th yeast chromosome containing together 593 ORFs and account how many times each of the 20 amino-acids appears in subsequent ORFs. It is found that the counts follow the negative binomial (NB) distribution with a surprisingly good fit. This is shown (i) graphically, (ii) applying (with some restrictions) the non-parametric Kolmogorov test, (iii) establishing critical levels by simulations.

5

Two non-conventional methods for visualization of multivariate two-group data

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Bartkowiak A. , Szustalewicz A.

Biocybernetics and Biomedical Engineering

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2000

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tom Vol. 20, no. 4

5-20

EN

We introduce two graphical methods which permit to visualize graphically multivariate data belonging to two groups, e.g. disease and control groups. The methods are: a display of two canonical variates, and dynamic projections by the grand tour. Both methods are exploratory: they help in visualization of multivariate data points belonging to two groups of data and learning what is the shape of the two groups. The proposed methods permit also to identify atypieal data points and outliers. The considerations are illustrated by a medical example concerned with patients suffering from ventilatory disorders and control patients in which ventilatory disorders were not stated.

PL

Opisujemy dwie metody graficzne, które pozwalają zobrazować dane podzielone na dwie grupy, np. na chorych i na grupę kontrolną. Są to: wykres dwóch zmiennych kanonicznych i metoda dynamicznych projekcji, nazywana grand tour. Obydwie metody są eksploratywne, tzn. pomagają w wizualizacji punktów należących do dwóch różnych grup oraz w rozpoznawaniu kształtów tych dwóch grup danych. Proponowane metody mogą być również przydatne przy znajdywaniu tzw. odstających obserwacji. Rozważania są ilustrowane danymi medycznymi, dotyczącymi pacjentów cierpiących na niewydolność układu wentylacyjnego i pacjentów kontrolnych, u których nie stwierdzono tej choroby.