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Tytuł:
Burzliwa dyspersja ciecz-ciecz w mieszalniku statycznym typu Kenics
Turbulent liquid-liquid dispersion in Kenics static mixer
Autorzy:
Kiziukevich, D.
Podgórska, W.
Powiązania:
https://bibliotekanauki.pl/articles/2073326.pdf
Data publikacji:
2018
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
CFD
Kenics
krople
model Eulerian
model Mixture
droplets
Mixture model
Two-fluid model
Opis:
Przeprowadzomo symulacje numeryczne CFD z wykorzystaniem modeli przepływów wielofazowych Mixture i Eulerian w celu wyznaczenia pola przepływu, rozkładu ułamka objętościowego fazy rozproszonej i własności burzliwości w mieszalniku statycznym typu Kenics. Zbadano czułość obu modeli na wielkość kropel. Oba modele przewidują podobne wartości szybkości dyssypacji energii dla różnych rozmiarów kropel. Model Eulerian przewiduje kilkanaście procent wyższe wartości szybkości dyssypacji energii. Na podstawie wyznaczonej szybkości dyssypacji energii określono rozmiary kropel uzyskiwanych w mieszalniku.
CFD numerical simulations using Mixture and Two-fluid models of multiphase flows were performed to determine flow field, distribution of dispersed phase volume fraction, and turbulence properties in Kenics static mixer. Sensitivity of both models to drop size was investigated. Both models predict similar values of energy dissipation rate for droplets of different size. Two-fluid model predicts over 10% larger values of energy dissipation rate. Calculated values of energy dissipation rate were used to predict sizes of drops produced in the mixer.
Źródło:
Inżynieria i Aparatura Chemiczna; 2018, 3; 63--64
0368-0827
Pojawia się w:
Inżynieria i Aparatura Chemiczna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Poczucie śląskości wśród Ślązaków – analiza empiryczna z wykorzystaniem modeli klas ukrytych
A sense of being Silesian – an empirical analysis with the use of latent class models
Autorzy:
Genge, Ewa
Powiązania:
https://bibliotekanauki.pl/articles/425295.pdf
Data publikacji:
2013
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
latent class analysis
mixture model
model-based clustering
categorical data
Opis:
The paper focuses on latent class models and their application for quantitative data. Latent class modeling is one of multivariate analysis techniques of the contingency table and can be viewed as a special case of model-based clustering, for multivariate discrete data. It is assumed that each observation comes from one of the numbers of subpopulations, with its own probability distribution. We used latent class analysis for grouping and detecting homogeneity of Silesian people using poLCA package of R. We analyzed data collected by the Department of Social Pedagogy, University of Silesia in Katowice.
Źródło:
Econometrics. Ekonometria. Advances in Applied Data Analytics; 2013, 4(42); 48-59
1507-3866
Pojawia się w:
Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Speech emotion recognition under white noise
Autorzy:
Huang, C.
Chen, G.
Yu, H.
Bao, Y.
Zhao, L.
Powiązania:
https://bibliotekanauki.pl/articles/177301.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
speech emotion recognition
speech enhancement
emotion model
Gaussian mixture model
Opis:
Speaker‘s emotional states are recognized from speech signal with Additive white Gaussian noise (AWGN). The influence of white noise on a typical emotion recogniztion system is studied. The emotion classifier is implemented with Gaussian mixture model (GMM). A Chinese speech emotion database is used for training and testing, which includes nine emotion classes (e.g. happiness, sadness, anger, surprise, fear, anxiety, hesitation, confidence and neutral state). Two speech enhancement algorithms are introduced for improved emotion classification. In the experiments, the Gaussian mixture model is trained on the clean speech data, while tested under AWGN with various signal to noise ratios (SNRs). The emotion class model and the dimension space model are both adopted for the evaluation of the emotion recognition system. Regarding the emotion class model, the nine emotion classes are classified. Considering the dimension space model, the arousal dimension and the valence dimension are classified into positive regions or negative regions. The experimental results show that the speech enhancement algorithms constantly improve the performance of our emotion recognition system under various SNRs, and the positive emotions are more likely to be miss-classified as negative emotions under white noise environment.
Źródło:
Archives of Acoustics; 2013, 38, 4; 457-463
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automated tracking and real time following of moving person for robotics applications
Autorzy:
Patoliya, Jignesh J.
Mewada, Hiren K.
Powiązania:
https://bibliotekanauki.pl/articles/384835.pdf
Data publikacji:
2019
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
visual tracking
robot operating system
identity retention
Gaussian Mixture Model
Opis:
Presently the interaction of robots with human plays an important role in various social applications. Reliable tracking is an important aspect for the social robots where robots need to follow the moving person. This paper proposes the implementation of automated tracking and real time following algorithm for robotic automation. Occlusion and identity retention are the major challenges in the tracking process. Hence, a feature set based identity retention algorithm is used and integrated with robot operating system. The tracking algorithm is implemented using robot operating system in Linux and using OpenCV. The tracking algorithm achieved 85% accuracy and 72.30% precision. Further analysis of tracking algorithm corresponds to the integration of ROS and OpenCV is presented. The analysis of tracking algorithm concludes that ROS linking required 0.64% more time in comparison with simple OpenCV code based tracking algorithm.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 4; 31-37
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Small Area Estimation Under a Mixture Model
Autorzy:
Chandra, Hukum
Bathla, HVL
Sud, U.C.
Powiązania:
https://bibliotekanauki.pl/articles/465788.pdf
Data publikacji:
2010
Wydawca:
Główny Urząd Statystyczny
Tematy:
Linear mixed model
Small area estimation
EBLUP
Zero-inflated data
mixture model
Opis:
Small area estimation (SAE) under a linear mixed model may not be efficient if data contain substantial proportion of zeros than would be expected under standard model assumptions (hereafter zero-inflated data). We discuss the SAE for zero-inflated data under a mixture model (Fletcher et al., 2005 and Karlberg, 2000) that account for excess zeros in the data. Our results from simulation studies show that mixture model based approach for SAE works well and produces an efficient set of small area estimates. An application to real survey data from the National Sample Survey Organisation of India demonstrates the satisfactory performance of the approach.
Źródło:
Statistics in Transition new series; 2010, 11, 3; 76-89
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fitting a Gaussian mixture model through the Gini index
Autorzy:
López-Lobato, Adriana Laura
Avendaño-Garrido, Martha Lorena
Powiązania:
https://bibliotekanauki.pl/articles/2055144.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
Gini index problem
Gaussian mixture model
clustering
indeks Giniego
model mieszaniny Gaussa
grupowanie
Opis:
A linear combination of Gaussian components is known as a Gaussian mixture model. It is widely used in data mining and pattern recognition. In this paper, we propose a method to estimate the parameters of the density function given by a Gaussian mixture model. Our proposal is based on the Gini index, a methodology to measure the inequality degree between two probability distributions, and consists in minimizing the Gini index between an empirical distribution for the data and a Gaussian mixture model. We will show several simulated examples and real data examples, observing some of the properties of the proposed method.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 487--500
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
GEE Estimators in Mixture Model with Varying Concentrations
Estymatory GEE w modelu mieszanym ze zmiennymi współczynnikami koncentracji
Autorzy:
Doronin, Oleksii
Maiboroda, Rostislav
Powiązania:
https://bibliotekanauki.pl/articles/654526.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
model mieszany
estymacja semiparametryczna
GEE (metoda uogólnionych równań estymujących)
mixture model
semiparametric estimation
GEE
Opis:
W pracy omówiono semiparametryczny model mieszany, w którym pewne współczynniki są parametryzowane za pomocą wspólnego parametru euklidesowego, natomiast inne są zupełnie nieznane. Wprowadzono metodę estymacji parametrów opartą na podejściu GEE (uogólnionych równań estymujących)  oraz adaptacyjnym podejściu GEE. Proponowane estymatory zostały przeanalizowane w badaniu symulacyjnym.
We discuss semiparametric mixture model where some components are parametrized with common Euclidean parameter and others are fully unknown. We introduce GEE approach and adaptive GEE-based approach for parameter estimation. Proposed estimators are tested on simulated sample.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2015, 3, 314
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Small Area Estimation for Skewed Data in the Presence of Zeroes
Autorzy:
Karlberg, Forough
Powiązania:
https://bibliotekanauki.pl/articles/466079.pdf
Data publikacji:
2015
Wydawca:
Główny Urząd Statystyczny
Tematy:
small area estimation
representative outliers
zero-valued observations lognormal-logistic mixture model
Opis:
Skewed distributions with representative outliers pose a problem in many surveys. Various small area prediction approaches for skewed data based on transformation models have been proposed. However, in certain applications of those predictors, the fact that the survey data also contain a non-negligible number of zero-valued observations is sometimes dealt with rather crudely, for instance by arbitrarily adding a constant to each value (to allow zeroes to be considered as “positive observations, only smaller”, instead of acknowledging their qualitatively different nature). On the other hand, while a lognormal-logistic model has been proposed (to incorporate skewed distributions as well as zeroes), that model does not include any hierarchical aspects, and is therefore not explicitly adapted to small area prediction. In this paper, we consolidate the two approaches by extending one of the already established log-transformation mixed small area prediction models to incorporate a logistic component. This allows for the simultaneous, systematic treatment of domain effects, outliers and zero-valued observations in a single framework. We benchmark the resulting model-based predictors (against relevant alternatives) in applications to simulated data as well as empirical data from the Australian Agricultural and Grazing Industries Survey.
Źródło:
Statistics in Transition new series; 2015, 16, 4; 541-562
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Presenting a technique for registering images and range data using a topological representation of a path within an environment
Autorzy:
Ferreira, F.
Davim, L.
Rocha, R.
Dias, J.
Santos, V.
Powiązania:
https://bibliotekanauki.pl/articles/385035.pdf
Data publikacji:
2007
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
sensor feature integration
binary data
Bernoulli mixture model
dimensionality reduction
robot localisation
change detection
Opis:
This article presents a novel method to the utilize topological representation of a path, thatpath that is created from sequences of images from digital cameras and sensor data from range sensors. A topological representation of the environment is created by leading the robot around the environment during a familiarisation phaseLeading the robot around the environment during a familiarisation phase creates a topological representation of the environment. While moving down the same path, the robot is able to localise itself within the topological representation that is has been previously created. The principal contribution to the state of the art is that, by using a topological representation of the environment, individual 3D data sets acquired from a set of range sensors need not be registered in a single, [Global] Coordinate Reference System. Instead, 3D point clouds for small sections of the environment are indexed to a sequence of multi-sensor views, of images and range data. Such a registration procedure can be useful in the construction of 3D representations of large environments and in the detection of changes that might occur within these environments.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2007, 1, 3; 47-56
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An improved ant colony optimization algorithm and its application to text-independent speaker verification system
Autorzy:
Aghdam, M. H.
Powiązania:
https://bibliotekanauki.pl/articles/91678.pdf
Data publikacji:
2012
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
ant colony
optimization
ant colony optimization
ACO
security
automatic speaker verification
ASV
feature space
Gaussian mixture model universal background model
GMM-UBM
Opis:
With the growing trend toward remote security verification procedures for telephone banking, biometric security measures and similar applications, automatic speaker verification (ASV) has received a lot of attention in recent years. The complexity of ASV system and its verification time depends on the number of feature vectors, their dimensionality, the complexity of the speaker models and the number of speakers. In this paper, we concentrate on optimizing dimensionality of feature space by selecting relevant features. At present there are several methods for feature selection in ASV systems. To improve performance of ASV system we present another method that is based on ant colony optimization (ACO) algorithm. After feature selection phase, feature vectors are applied to a Gaussian mixture model universal background model (GMM-UBM) which is a text-independent speaker verification model. The performance of proposed algorithm is compared to the performance of genetic algorithm on the task of feature selection in TIMIT corpora. The results of experiments indicate that with the optimized feature set, the performance of the ASV system is improved. Moreover, the speed of verification is significantly increased since by use of ACO, number of features is reduced over 80% which consequently decrease the complexity of our ASV system.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 4; 301-315
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Preprocessing large datasets using Gaussian mixture modelling to improve prediction accuracy of truck productivity at mine sites
Autorzy:
Fan, Chengkai
Zhang, Na
Jiang, Bei
Liu, Wei Victor
Powiązania:
https://bibliotekanauki.pl/articles/2203342.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
kopalnia
samochód ciężarowy
piasek roponośny
oil sands mining
mine truck productivity
Gaussian mixture model
latent variable
prediction accuracy
relative importance
Opis:
The historical datasets at operating mine sites are usually large. Directly applying large datasets to build prediction models may lead to inaccurate results. To overcome the real-world challenges, this study aimed to handle these large datasets using Gaussian mixture modelling (GMM) for developing a novel and accurate prediction model of truck productivity. A large dataset of truck haulage collected at operating mine sites was clustered by GMM into three latent classes before the prediction model was built. The labels of these latent classes generated a latent variable. Two multiple linear regression (MLR) models were then constructed, including the ordinary-MLR (O-MLR) and the hybrid GMM-MLR models. The GMM-MLR model incorporated the observed input variables and a latent variable in the form of interaction terms. The O-MLR model was the baseline model and did not involve the latent variable. The GMM-MLR model performed considerably better than the O-MLR model in predicting truck productivity. The interaction terms quantitatively measured the differences in how the observed input variables affected truck productivity in three classes (high, medium, and low truck productivity). The haul distance was the most crucial input variable in the GMM-MLR model. This study provides new insights into handling massive amounts of data in truck haulage datasets and a more accurate prediction model for truck productivity.
Źródło:
Archives of Mining Sciences; 2022, 67, 4; 661--680
0860-7001
Pojawia się w:
Archives of Mining Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wyniki badań skuteczności rozdzielania mieszaniny w tryjerze obiegowym ze stożkową powierzchnią roboczą. Etap I. Separator z powierzchnią roboczą obracającą się wokół osi własnej
Results of the research on efficiency of mixture separation in a circulating trieur with conical working surface. Stage I. Separator with working surface rotating about its own axis
Autorzy:
Jadwisieńczak, K.
Choszcz, D.
Konopka, S.
Powiązania:
https://bibliotekanauki.pl/articles/291560.pdf
Data publikacji:
2009
Wydawca:
Polskie Towarzystwo Inżynierii Rolniczej
Tematy:
tryjer obiegowy
stożkowa powierzchnia robocza
mieszanina modelowa
circulating trieur
conical working surface
model mixture
Opis:
Praca dotyczy oceny skuteczności rozdzielania dwuskładnikowej (modelowej) mieszaniny składającej się z cząstek długich (ziaren żyta) i krótkich (nasion gorczycy) w nowym separatorze z powierzchnią roboczą w postaci ściętego stożka z wgłębieniami. Podano stochastyczne modele opisujące wpływ podstawowych czynników konstrukcyjnych i eksploatacyjnych separatora na skuteczność rozdzielania mieszaniny.
The work concerns assessment of efficiency in separation of binary (model) mixture consisting of long particles (rye seeds) and short particles (mustard seeds) in a new separator with working surface in form of bevelled cone with pits. The paper specifies stochastic models describing the impact of basic constructional and operating factors in the separator on mixture separation efficiency.
Źródło:
Inżynieria Rolnicza; 2009, R. 13, nr 6, 6; 117-124
1429-7264
Pojawia się w:
Inżynieria Rolnicza
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid texture and gradient modeling for dynamic background subtraction identification systemin tobacco plant using 5G data service
Autorzy:
Gowda Thirthe, M.T.
Chandrika, J.
Powiązania:
https://bibliotekanauki.pl/articles/38699145.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
background subtraction
local binary pattern
tobacco plant
texture
Gaussian mixture model
illumination change
plant disease identification system
usuwanie tła
lokalny wzorzec binarny
tytoń
tekstura
model mieszaniny Gaussa
zmiana oświetlenia
system identyfikacji chorób roślin
Opis:
Background: Detecting the plants as objects of interest in any vision-based input sequence is highly complex due to nonlinear background objects such as rocks, shadows,etc. Therefore, it is a difficult task and an emerging one with the development of precision agriculture systems. The nonlinear variations of pixel intensity with illuminationand other causes such as blurs and poor video quality also make the object detection taskchallenging. To detect the object of interest, background subtraction (BS) is widely usedin many plant disease identification systems, and its detection rate largely depends on thenumber of features used to suppress and isolate the foreground region and its sensitivitytoward image nonlinearity. Methodology: A hybrid invariant texture and color gradient-based approach is proposed to model the background for dynamic BS, and its performance is validated byvarious real-time video captures covering different kinds of complex backgrounds and various illumination changes. Based on the experimental results, a simple multimodal featureattribute, which includes several invariant texture measures and color attributes, yieldsfinite precision accuracy compared with other state-of-art detection methods. Experimental evaluation of two datasets shows that the new model achieves superior performanceover existing results in spectral-domain disease identification model. 5G assistance: After successful identification of tobacco plant and its analysis, the finalresults are stored in a cloud-assisted server as a database that allows all kinds of 5G servicessuch as IoT and edge computing terminals for data access with valid authentication fordetailed analysis and references.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 41-54
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modele struktury grubości w dwu- i wielopiętrowych drzewostanach z udziałem jodły Abies alba Mill. i buka Fagus sylvatica L.
Models of diameter structure in two- and multi-storied stands with fir Abies alba Mill. and beech Fagus sylvatica L.
Autorzy:
Pach, M.
Podlaski, R.
Powiązania:
https://bibliotekanauki.pl/articles/989729.pdf
Data publikacji:
2015
Wydawca:
Polskie Towarzystwo Leśne
Tematy:
lesnictwo
drzewostany mieszane
struktura grubosci
drzewostany dwupietrowe
drzewostany wielopietrowe
jodla pospolita
Abies Alba
buk zwyczajny
Fagus sylvatica
rozklad piersnic
rozklad Weibulla
rozklad mieszany
tree diameter modelling
forest complex structure
weibull mixture model
Opis:
The objectives of the study were (1) to determine the models of diameter at breast height (dbh) distributions in two− and multi−storied mixed stands with fir Abies alba Mill. and beech Fagus sylvatica L. as well as (2) to assess the usefulness of single Weibull distribution and two−component mixture of Weibull distribution to approximation of empirical dbh distributions for distinguished models of dbh structures. In the Świętokrzyskie Mountains, 21 sample plots ranging in size from 0.2 to 0.4 ha were established. To identify the models of dbh distributions, in two− and multi−storied stands with similar empirical dbh distributions, the hierarchical cluster analysis (HCA) with the Jaccard's measure and the Ward's minimum variance agglomeration method were used. To approximate dbh distributions, the single Weibull distribution and the two−component mixture of Weibull distribution were employed. In two− and multi−storied mixed stands with fir and beech, with the mean age between 50 and 70 at the dbh, four models of dbh distributions were determined (fig. 1). Two of them were decreasing, strongly asymmetric (OS and OJ models; fig. 2) and the other two were increasing in the initial phase and decreasing in the final, having two maximums (DM1 and DM2 models; fig. 3). In the stands with the complex structure mixed distribution should be used to approximate empirical data. The analysis revealed high suitability and versatility of Weibull distribution both as single form and two−component mixture.
Źródło:
Sylwan; 2015, 159, 08; 632-638
0039-7660
Pojawia się w:
Sylwan
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimation of regression parameters of two dimensional probability distribution mixtures
Estymacja parametrów regresji mieszanki dwuwymiarowych rozkładów prawdopodobieństwa
Autorzy:
Sitek, Grzegorz
Powiązania:
https://bibliotekanauki.pl/articles/592694.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
EM algorithm
Least squares method for an implicite interdependence
Mixture regression model
Algorytm EM
Metoda najmniejszych kwadratów dla zależności niejawnych
Mieszanki regresji
Opis:
We use two methods of estimation parameters in a mixture regression: maximum likelihood (MLE) and the least squares method for an implicit interdependence. The most popular method for maximum likelihood esti-mation of the parameter vector is the EM algorithm. The least squares method for an implicit interdependence is based solving systems of nonlinear equations. Most frequently used method in the estimation of parameters mixtures regression is the method of maximum likelihood. The article presents the possibility of using a different the least squares method for an implicit interdependence and compare it with the maximum likelihood method. We compare accuracy of two methods of estimation by simulation using bias: root mean square error and bootstrapping standard errors of estimation.
Do estymacji parametrów mieszanek regresji stosujemy dwie metody: metodę największej wiarygodności oraz metodę najmniejszych kwadratów dla zależności niejawnych. Najbardziej popularną metodą polegającą na maksymalizacji funkcji wiarygodności jest algorytm EM. Metoda najmniejszych kwadratów dla zależności niejawnych polega na rozwiązaniu układu równań nieliniowych. Najczęściej stosowaną metodą estymacji parametrów mieszanek regresji jest metoda największej wiarygodności. W artykule pokazano możliwość zastosowania innej metody najmniejszych kwadratów dla zależności niejawnych. Obie metody porównujemy symulacyjnie, używając obciążenia estymatora, pierwiastka błędu średniokwadratowego estymatora oraz bootstrapowe błędy standardowe.
Źródło:
Studia Ekonomiczne; 2016, 304; 30-46
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
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