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1

Urban Ecological Quality Assessment Based on Remote Sensing Data in African Context – A Case Study of Tangier City (Morocco, NW Africa)

Tahiri Mounia, Bahi Hicham, Bouramtane Tarik, Malah Anass, Sabri Anas, Mohsine Ismail, Kacimi Ilias

Ecological Engineering & Environmental Technology

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2023

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Vol. 24, iss. 9

204--217

EN

Climate change, combined with rapid urbanization, can face many challenges in achieving urban ecological sustainability, especially in developing countries. Due to the lack of valuable data, measuring the negative impact of this urban environmental damage, particularly in African cities, is however difficult to investigate. In this context, this research proposes an efficient index, including environmental, societal, and topographic indicators, extracted from remote sensing data, to evaluate the spatial ecological vulnerability of Tangier city in Morocco. This composite index, called the Urban Ecological Quality Index (UEQI), was developed for 2002, 2013, and 2023 in the spring season, using the Principal Component Analysis (PCA) as a multivariate statistical technique. Furthermore, the spatial autocorrelation analysis of the UEQI was performed to study the correlation between the index values and its surroundings, using Global Moran’s I and Local Moran’s I test statistics. The results show that on the one hand, zones located in the center of the city kept poor ecological quality in the three studied years, where the lack of green spaces and the high population density are the main reasons for this bad state. On the other hand, climate variability, such as precipitation change, directly affects the ecological quality of Tangier city. In fact, from 2002 to 2013, due to Morocco’s increased precipitation during this decade, the UEQI improved in 36%, unchanged in 50%, and degraded in 14% of the study area. However, from 2013 to 2023, with more than 52% degraded UEQI, the ecological quality of the city was affected by drought periods, which have been more frequent and intense in this decade, especially in green areas and agricultural land.

2

Applying grain-size and compositional data analysis for interpretation of the Quaternary oxbow lake sedimentation processes: eastern Great Hungarian Plain

Eltijani Abdelrhim, Molnár Dávid, Makó László, Geiger János, Sümegi Pál

Studia Quaternaria

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2022

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Vol. 39, Nr 2

83--93

EN

Grain size distribution is one of the paleoenvironmental proxies that provide insight statistical distribution of size fractions within the sediments. Multivariate statistics have been used to investigate the depositional process from the grain size distribution. Still, the direct application of the standard multivariate methods is not straightforward and can yield misleading interpretations due to the compositional nature of the raw grain size data. This paper is a methodological framework for grain size data characterization through the centered log ratio transformation and euclidean data, coupled with principal component analysis, cluster analysis, and linear discriminant analysis to examine Quaternary sediments from Tovises bed in the southeast Great Hungarian Plain. These approaches provide statistically significant and sedimentologically interpretable results for both datasets. However, the details by which they supplemented the conceptual model were significantly different, and this discrepancy resulted in a different temporal model of the depositional history.

3

Assessment of Surface Water Quality in the Hau Giang Province Using GIS and Statistical Approaches

Thuan Nguyen Cong

Journal of Ecological Engineering

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2022

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Vol. 23, nr 9

265--276

EN

The study aimed to assess the surface water quality in the Hau Giang province in 2021 at 44 locations (with a frequency of 5 times per year) using Principal Component Analysis (PCA), Cluster Analysis (CA) and GIS. Surface water quality was compared with the national technical regulation on surface water quality (QCVN 08-MT:2015/BTNMT, column A1) and Water Quality Index (WQI). The results showed that the surface water quality parameters of total suspended solids, organic matters, nutrients, coliform, and Fe far exceeded the allowable limits, while the Cl-, color, and CN- parameters were within the allowable limits of QCVN 08-MT:2015/BTNMT, column A1. The values of WQI showed that the water quality of the Hau Giang province ranged from poor to excellent. The water quality at the Vam Cai Dau and Hau River areas could only be exploited for water supply, but appropriate treatment is needed. CA divided the monitoring months into three distinct clusters and reduced the sampling sites from 44 to 33 locations, reducing 25% of monitoring cost per year. PCA revealed three main factors which could explain 69.0% of the variation in water quality. The water pollution sources were mainly industrial and agricultural discharges, domestic and urban activities, transportation activities, salinity, hydrological conditions and water runoff. The current findings provide useful information which support local environmental managers and water supply companies for safe and sustainable.

4

Evaluation of water treatment plants quality in Basrah Province, by factor and cluster analysis

Al Saad Zainb A.A., Hamdan Ahmed N.A.

Journal of Water and Land Development

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2020

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no. 46

10--19

EN

The Shatt Al Arab River (SAAR) is a major source of raw water for most water treatment plants (WTP’s) located along with it in Basrah province. This study aims to determine the effects of different variables on water quality of the SAAR, using multivariate statistical analysis. Seventeen variables were measured in nine WTP’s during 2017, these sites are Al Hussain (1), Awaissan (2), Al Abass (3), Al Garma (4), Mhaigran (5), Al Asmaee (6), Al Jubaila (7), Al Baradia (8), Al Lebani (9). The dataset is treated using principal component analysis (PCA) / factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of contamination and the suitability of water for drinking and irrigation. Three factors are responsible for the data structure representing 88.86% of the total variance in the dataset. CA shows three different groups of similarity between the sampling stations, in which station 5 (Mhaigran) is more contaminated than others, while station 3 (Al Abass) and 6 (Al Asmaee) are less contaminated. Electrical conductivity (EC) and sodium adsorption ratio (SAR) are plotted on Richard diagram. It is shown that the samples of water of Mhaigran are located in the class of C4-S3 of very high salinity and sodium, water samples of Al Abass station, are located in the class of C3-S1 of high salinity and low sodium, and others are located in the class of C4-S2 of high salinity and medium sodium. Generally, the results of most water quality parameters reveal that SAAR is not within the permissible levels of drinking and irrigation.

5

Anthropogenic and Climatic Causality of Changes in the Hydrological Regime of the Dnieper River

Pichura Vitalii Ivanovich, Potravka Larisa Aleksandrovna, Skrypchuk Petro Mikhalovich, Stratichuk Natalia Vladimirovna

Journal of Ecological Engineering

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2020

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Vol. 21, nr 4

1--10

EN

The intensive use of water resources and the transformation of natural landscapes under the influence of human economic activity have led to changes in the natural water balance of river drainage basins. The negative processes thereof are intensified by climatic changes that have significantly disturbed the hydrological regime, determined by changes in water content and river flow dynamics. The retrospective study and prediction of the flow of the Dnieper River was carried out using multivariate statistics and adaptive methods of nonlinear time series analysis. The anomalous features were identified and the main periods of changes in the water regime of the river for 190 years (1818–2008) were determined using the standard root-mean-square deviation and wavelet analysis. As a result of non-linear prediction, it was determined that if the tendency of anthropogenic and climatic formation of the water regime of the Dnieper River sustains, there is a 90% probability of insignificant but steady trend and cyclical reduction of the average annual flow by 1.6 m3/s per year to 1120 ± 270 m3/s by 2040. The results of the detailed retrospective analysis for 190 years and the prediction of the probability of changes in the flow of the Dnieper river confirm the previous conclusions of many scientists regarding the significant transformation of the ecosystem of the transboundary river and provide new knowledge regarding the main stages of formation of the water regime and the probability of further regulation of the flow of the Dnieper river if the current conditions of the negative impact of economic activities are maintained in the transboundary basin.

6

Application of chemometric methods in analysis of environmental data

Chevallier A., Jakubowska M.

Analit

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2018

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Nr 6

84--53

7

Detection of potential areas of changing climatic conditions at a regional scale until 2100 for Saxony, Germany

Kronenberg R., Franke J., Bernhofer C., Körner P.

Meteorology Hydrology and Water Management. Research and Operational Applications

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2015

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Vol. 3, Iss. 2

17--26

EN

Two different approaches are applied for the investigation of possible changes within the climate regime – as an important component of vulnerability – on a regional scale for Saxony, Germany. Therefore data were applied from the output of the statistical climate models WETTREG2010 and WEREX-V for a projected period until 2100. In the first step, rain gauge-based precipitation regions with similar statistics have been classified. The results show that stable regions are mainly located in the Ore Mountains, while regions of higher uncertainty in terms of a climate signal exist particularly between the lowlands and mountains. In the second step, station-based data on precipitation, temperature and climatic water balance were interpolated by the regionalisation service RaKliDa. Model runs which lay closest to the observed data for the period 1968 to 2007 were identified. Therefore, regions of similar climates were classified and compared by means of a Taylor diagram. The derived patterns of the observed data are in good agreement with formerly defined climate regions. In the final step, anomalies of 10 yearlong averages from 2021 until 2090 were calculated and then spatially classified. The classification revealed four complex regions of changing climate conditions. The derived patterns show large differences in the spatial distribution of future precipitation and climatic water balance changes. In contrast, temperature anomalies are almost independent of these patterns and nearly equally distributed.

8

Classification methods for high-dimensional genetic data

Kalina J.

Biocybernetics and Biomedical Engineering

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2014

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Vol. 34, no. 1

10--18

EN

Standard methods of multivariate statistics fail in the analysis of high-dimensional data. This paper gives an overview of recent classification methods proposed for the analysis of high-dimensional data, especially in the context of molecular genetics. We discuss methods of both biostatistics and data mining based on various background, explain their principles, and compare their advantages and limitations. We also include dimension reduction methods tailor-made for classification analysis and also such classification methods which reduce the dimension of the computation intrinsically. A common feature of numerous classification methods is the shrinkage estimation principle, which has obtained a recent intensive attention in high-dimensional applications.

9

Assessment of water physico-chemical characteristics and statistical evaluation of Narmada Estuarine Region, Gujarat, India

Nirmal Kumar I. J., Basil G., Nirmal Kumar R., Sajish P. R., Shailendra V.

Journal of Water and Land Development

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2012

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no. 16 [I-VI]

43-48

EN

Investigations on physicochemical parameters (temperature, pH, salinity, dissolved oxygen), including dissolved nutrients (PO4-P, NO3-N, SiO4-Si) and chlorophyll-a were carried out in the water off the mouth of the Narmada estuary from July 2008 to June 2009. The multivariate statistics and principal component analysis applied to the datasets, indicated two factors during the whole study period influencing variability in the water to the extent of 72%. Principal axis factoring and alpha factoring have been used to observe the mode of association of parameters and their interrelationships, for evaluating water quality. The results indicated the addition of phosphates and silicates to the coastal water by the Narmada estuary from natural sources during study period. The study indicated that the Narmada estuary adds sufficiently well-oxygenated, nutrient-rich water to the coastal region.

PL

Analizę parametrów fizyczno-chemicznych (temperatura, pH, zasolenie, tlen rozpuszczony), stężenia pierwiastków biogennych (PO4-P, NO3-N, SiO4-Si) i chlorofilu prowadzono w wodach estuarium Narmada od lipca 2008 do czerwca 2009. Statystyka wielowymiarowa i analiza głównych składowych, zastosowana do zbioru wyników, wskazała dwa czynniki, które w 72% odpowiadały za zmienność składu chemicznego wody w całym okresie badań. Do oceny jakości wody zastosowano analizę czynnikową celem określenia powiązań między parametrami i ich wzajemnych zależności. Wyniki pokazały, że w okresie badawczym estuarium Narmada dostarczało do wód przybrzeżnych fosforany i krzemiany pochodzące z naturalnych źródeł. Przeprowadzone badania dowodzą, że estuarium Narmada zasila strefę brzegową w dobrze natlenione i bogate w pierwiastki biogenne wody.

10

Spectrophotometric study of interaction between selected bile acids and cyclodextrins

Zarzycki P. K., Baran M. J., Harasimiuk F. B.

Pomiary Automatyka Kontrola

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2010

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R. 56, nr 4

355-359

EN

The main goal of present work was to explore the host-guest complex formation between selected bile acids (dehydrocholic, cholic, deoxycholic, taurodeoxycholic, glycodeoxycholic, glycocholic and chenodeoxycholic acid) and cyclodextrins (ß-cyclodextrin and its hydroxypropyl derivative) at sub-ambient and elevated temperature, using as a probe the phenolphthalein-cyclodextrin inclusion complex detected via UV-Vis spectrophotometry. In order to explore the general trends in the complexation ability of the bile acids by macrocycles investigated, the quantitative data set containing ?AU values was analyzed by principal component analysis.

PL

W pracy przedstawiono wyniki badań nad oddziaływaniem wybranych kwasów żółciowych (kwas dehydrocholowy, cholowy, deoksycholowy, taurodeoksycholowy, glikodeoksycholowy, glikocholowy oraz chenodeo-ksycholowy; rys. 1) z substancjami makrocyklicznymi (ß-cyklodekstryna i jej hydroksypropylowa pochodna) w różnych temperaturach (0 oraz 30oC), wykorzystując jako detektor kompleks inkluzyjny makrocykli z fenoloftaleiną (rys. 2 i 3). Z punktu widzenia chemii analitycznej i diagnostyki medycznej kwasy żółciowe są grupą związków trudnych w detekcji i analizie ilościowej. Zastosowanie kompleksów supramolekularnych typu gość-gospodarz, w których skład wchodzi substancja barwna np. fenoloftaleina, umożliwia zastosowanie spektroftometrii do detekcji kwasów żółciowych oraz badań ich oddziaływania ze związkami makrocyklicznymi. Jest to istotne z punktu widzenia zastosowań praktycznych np. analizy kwasów żółciowych w materiałach biologicznych rozdzielanych metodami chromatograficznymi. W prezentowanej pracy dane eksperymentalne (?AU) uzyskane za pomocą spektrofotometrii UV-Vis (rys. 4) były analizowane metodą PCA (Principal Component Analysis; rys. 5). Wyniki analizy wskazują na kluczową rolę temperatury oraz podstawnika przy węglu C12 szkieletu sterydów na siłę oddziaływania badanych kwasów żółciowych z cyklodekstrynami (rys. 6). Zaobserwowano, iż w warunkach mikrochromatografii planarnej jest bardzo trudno rozdzielić parę kwasów chenodeoksycholowy/ deoksycholowy (rys. 7). Uzyskane wyniki wskazują na możliwość poprawy rozdzielania chromatograficznego wybranych par kwasów zółciowych przy zastosowaniu faz ruchomych modyfikowanych cyklodekstrynami (rys. 8).

11

New Modelling and Process Optimisation Approach for the False-Twist Texturing of Polyester

Silva E. A., Paiva A. P., Balestrassi P. P., Silva C. E. S.

Fibres & Textiles in Eastern Europe

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2009

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Vol. 17, no. 6 (77)

57--62

EN

After the wave of ISO 9000 certification, a large number of enterprises started to accumulate a great amount of data regarding their processes. False-twist texturing plants used these data to set up a process and improve their operations. This article shows that data mining, partial least squares modelling and genetic algorithm optimization can provide further use for these data to benefit the company in many areas, such as setting up adequate process parameters without requiring an expert to do so, providing the customer with the requirements that will fulfill his needs, simplifying machine changes, and reducing lot changes. The results show that the model and optimization structure put together can find multiple solutions for machine parameters by providing the multiple product properties or quality levels desired. The prediction of yarn properties, such as linear density (Dtex), elongation, tenacity and boiled water shrinkage were made with R2 between 0.80 and 0.99.

PL

Wprowadzanie norm ISO spowodowało, że duża ilość firm zaczęła gromadzić obszerne dane dotyczące stosowanych procesów produkcyjnych. Przedsiębiorstwa realizujące procesy teksturowania fałszywym skrętem wykorzystywały zgromadzone dane dla ustalenia warunków procesu i udoskonalenia jego przebiegu. W artykule wykazano, że analiza danych, odpowiednie modelowanie oraz optymalizacja z wykorzystaniem algorytmów genetycznych może prowadzić do dalszych udoskonaleń procesu. Wynikiem tego mogą być rozliczne korzyści przedsiębiorstwa polegające na możliwości ustawienia odpowiednich parametrów procesu technologicznego bez potrzeby przeprowadzania dodatkowych doświadczeń oraz udostępnienia klientowi zestawu parametrów spełniających jego wymagania. Dzięki temu można również uzyskać uproszczenie wymiany maszyn oraz zmniejszenie ilość partii próbnych. Wyniki wykazały, że model opracowany wspólnie ze strukturą optymalizacji może doprowadzić do znalezienia wielu zestawów parametrów potrzebnych dla uzyskania określonych asortymentów produkcji oraz wymaganej jakości. Przewidywanie takich parametrów włókien jak gęstość liniowa, wytrzymałość liniowa, wydłużenie przy zerwaniu i skurcz we wrzącej wodzie można było określić przy współczynniku R2 w granicach od 0.80 do 0.99.

12

Lake water quality assessment by multivariate statystical analysis

Simeonov V., Zachariadis G., Voutsa D., Stratis J., Anthemidis A., Samara C., Tsakovski S., Kouimtzis T., Simenova P., Andreev G.

Chemia i Inżynieria Ekologiczna

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2004

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Vol. 11, nr 6

471--488

EN

The present study deals with the multivariate statistical assessment of the water quality of several lakes located in Northern Greece. A two-year monitoring of different chemical and physicochemical parameters of the lake water was performed for the lakes Koronia, Volvi, Doirani, Megali Prespa and Mikri Prespa. The application of cluster and principal components analysis as well as apportioning modelling on absolute principal components scores has shown that if the whole data set is proceeded six latent factors prove to be responsible for the data structure and they form a specific pattern or the region where the lakes are located: the lake water quality is affected by natural, sediment, waste inlets (domestic and industrial), oxidation and toxic factors. Further, specific patterns of similar type were constructed for each lake with respect to the sampling period and to the relationships between the chemical and physicochemical parameters. Again, latent factors responsible for the data structure of each lake are identified. Finally, the contribution of each identified source to the chemical concentration was determined both for the whole dataset and for each lake in consideration.

PL

Przy użyciu statystyki wielu zmiennych oceniono jakość wody kilku jezior w północnej Grecji. W ciągu dwu lat monitorowano parametry chemiczne i fizykochemiczne wody z jezior: Koronia, Volvi, Doirani, Megali Prespa i Mikri Prespa. Stosowano zarówno analizę klasterową (grupową) oraz składowych głównych, jak również modelowanie z wykorzystaniem wartości absolutnych składowych (komponentów) głównych. Wyniki tych analiz dla całego zbioru danych pokazują, że ich struktura jest określona przez sześć czynników ukrytych, które tworzą obraz specyficzny dla danej lokalizacji jezior. Jakość wody jeziornej określają: czynniki naturalne, osady denne, zrzuty odpadów (komunalnych i przemysłowych) oraz substancje utleniające i toksyczne. Dla każdego jeziora skonstruowano charakterystyczne specyfikacje (podobnego typu), biorąc pod uwagę okres próbkowania oraz zależności między parametrami chemicznymi i fizykochemicznymi. Określono czynniki ukryte odpowiedzialne za strukturę danych opisujących każde jezioro. Określono wpływ każdego ze źródeł na skład chemiczny zarówno dla wszystkich danych, jak i oddzielnie dla każdego rozpatrywanego jeziora.

13

Environmetric assessment of pollutant concentrations effects on forest ecosystems

Antonova D., Antonov L., Petrov V., Simeonov V., Tsakovski S., Braun S., Flueckiger W.

Chemia i Inżynieria Ekologiczna

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2004

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Vol. 11, nr 6

439--448

EN

The present communication deals with the application of cluster and principal components analysis to a data set collected by monitoring wet precipitation at three different sampling sites. The idea is to identify latent factors responsible for the data structure at each site and, thus, to get information on their effects on the forest ecosystems. It has been found that a significant separation between the sites is achieved based on the analytical results and the identified factors correspond to acidic, mineral and crustal effects on the forest ecosystem.

PL

Przedstawiono wyniki zastosowania chemometrycznej analizy klasterów (grup) oraz analizy składowych głównych dla danych monitoringu ciekłego opadu atmosferycznego z trzech różnych miejsc. Celem była identyfikacja czynników ukrytych, odpowiedzialnych za strukturę danych z każdego miejsca pobierania próbek. W rezultacie otrzymano informacje o wpływie tych czynników na ekosystemy leśne. Zarówno doświadczalne dane analityczne, jak i zidentyfikowane 3 czynniki ukryte (kwasowy, mineralny i fazy krystalicznej) wskazują na znaczące różnice między badanymi ekosystemami leśnymi.

14

Environmetric Study of the Water Quality of the Struma River Basin, Bulgaria. Part II. Multivariate Statistical Modeling of the Water Quality Parameters

Nikolov N., Mihailov G., Simeonov V., Mirinchev G.

Chemia i Inżynieria Ekologiczna

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2002

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Vol. 9, nr 12

1531-1539

EN

The present paper is the last part of a study concerning the water quality of Struma river and its tributaries in Bulgarian territory. Monitoring data for a long period of observation were treated by the use of various multivariate statistical approaches (cluster analysis, principal components analysis, apportioning modelling) in order to collect new type of information about the data set. It has been found that the sampling sites form four types of similarity groups according to their location along the river stream - urban, rural, inlet and background. It makes possible to organize in a better way the monitoring procedure. Further, four latent factors were found responsible for the data structure - anthropogenic, water hardness, biological and acidic. These factors explain over 75% of the total variance of the system. Finally, an apportioning procedure was carried out to indicate to what extent each source (latent factor) contributes to the formation of the chemical variables responsible for the water quality.

PL

Praca ta stanowi ostatnią część badań dotyczących jakości wody rzeki Struma i jej dopływów na terytorium Bułgarii. Gromadzone przez długi czas dane monitoringowe zostały poddane statystycznej analizie za pomocą wariancji wielokrotnej (analizy klasterów, analizy głównych komponentów, rozdzielnego modelowania) w celu zebrania nowych informacji o zgromadzonych wynikach. Stwierdzono, że miejsca pobrania próbek można podzielić na cztery, charakteryzujące się podobieństwem, grupy oraz ze względu na ich lokalizację wzdłuż biegu rzeki, a mianowicie: miejską rolniczą, w pobliżu ujść i tło. Podział ten umożliwia lepsze zorganizowanie procedury monitoringowej. Stwierdzono, że za strukturę badanych danych były odpowiedzialne cztery ukryte czynniki: antropogeniczny, twardość wody, biologiczny i kwasowość. Czynniki te wyjaśniają ponad 75% całkowitej wariancji badanego systemu. Procedura rozdzielnego modelowania pokazała, w jakim stopniu każde ze źródeł (ukryte czynniki) miało wkład w powstałe zmiany chemiczne odpowiedzialne za jakość wody.

15

Environmetric approaches to estima te pollution impacts on a coastal area by sediment and river water studies

Simeonov V., Simeonova P.

Chemia i Inżynieria Ekologiczna

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2001

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Vol. 8, nr 12

1257-1267

EN

An effort is done to demonstrate the opportunities of same environmetric methods like regression analysis, cluster analysis and principal components analysis. Their role for data modeling is stressed and the basic theoretical principles are given. The application of the multivariate statistical methods is illustrated by two major examples: - Assessment of metal pollution based on multivariate statistical modeling of "hot spot" sediments from the Black Sea - Trend study of Kamchia River water quality. In the first part of the study the environmetric approach makes it possible to separate three zones o the marine environment with different level of pollution (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible pollution sources and separates natural from anthropogenic factors, the latter originating from contamination by chemical, oil refinery and steel-work enterprises. In the second part of the study nine sampling sites along Kamchia River were considered as sources for water quality monitoring data. Trends for all determinants are calculated by the use of linear regression analysis and special attention is paid to a specific coastal site. Then five latent factors were extracted from the monitoring data set in order to gain information about same structural characteristics of the set.

PL

Pokazano możliwości jakie stwrzają metody enwironmetryczne: analiza klasterów i analiza głównych składników. Nacisk położono na ich rolę w opracowywaniu danych pomiarowych; podano również ich główne założenia. Zastosowanie statystycznej metody multiwariancji zostało zilustrowane dwoma przykładami: - ocena zanieczyszczenia metalami osadów dennych z Morza Czarnego; - badaniami nad jakości wód rzeki Kamchia. Podejście environmetryczne umożliwiło rozróżnienie trzech stref środowiska morskiego o różnym poziomie zanieczyszczenia (zatoki: Bourgas i Warna oraz strefa buforowa jeziora). Ponadto, wyznaczenie czterech niejawnych czynników daje ścisłą interpretację możliwych źródeł zanieczyszczenia oraz oddziela czynniki naturalne od antropogennych - pochodzących od zanieczyszczeń chemikaliami, ropą naftową z rafinerii i zakładów metalurgicznych. Ponadto, rozważano dziewięć miejsc pobierania próbek wzdłuż rzeki Kamchia jako źródła danych do oceny jakości wody. Zastosowano tu analizę regresji liniowej; specjalną uwagę zwrócono na obszar wybrzeża. Dane monitoringowe opracowano enwironmetrycznie uzyskując informacje o ich strukturze.