Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "principal component analysis" wg kryterium: Wszystkie pola

  Lista filtrów
Wyrównaj
Wyświetlanie 1-100 z 204
Tytuł:
Principal Component Analysis versus Factor Analysis
Autorzy:
Gniazdowski, Zenon
Powiązania:
https://bibliotekanauki.pl/articles/1790041.pdf
Data publikacji:
2021-09
Wydawca:
Warszawska Wyższa Szkoła Informatyki
Tematy:
principal component analysis
factor analysis
number of principal components
number of factors
determining number of principal components
determining number of factors
Opis:
The article discusses selected problems related to both principal component analysis (PCA) and factor analysis (FA). In particular, both types of analysis were compared. A vector interpretation for both PCA and FA has also been proposed. The problem of determining the number of principal components in PCA and factors in FA was discussed in detail. A new criterion for determining the number of factors and principal components is discussed, which will allow to present most of the variance of each of the analyzed primary variables. An efficient algorithm for determining the number of factors in FA, which complies with this criterion, was also proposed. This algorithm was adapted to find the number of principal components in PCA. It was also proposed to modify the PCA algorithm using a new method of determining the number of principal components. The obtained results were discussed.
Źródło:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki; 2021, 15, 24; 35--88
1896-396X
2082-8349
Pojawia się w:
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Quantum image classification using principal component analysis
Autorzy:
Ostaszewski, M.
Sadowski, P.
Gawron, P.
Powiązania:
https://bibliotekanauki.pl/articles/375706.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
some quantum algorithms
quantum image processing
principal component analysis
Opis:
We present a novel quantum algorithm for the classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements. In order to apply the algorithm we present a new quantum representation of grayscale images.
Źródło:
Theoretical and Applied Informatics; 2015, 27, 1; 1-12
1896-5334
Pojawia się w:
Theoretical and Applied Informatics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A principal component analysis in concrete design
Autorzy:
Kobaka, Janusz
Katzer, Jacek
Powiązania:
https://bibliotekanauki.pl/articles/31342619.pdf
Data publikacji:
2022
Wydawca:
Politechnika Częstochowska
Tematy:
principal component analysis
PCA
concrete designing
concrete mix
analiza głównych składowych
projektowanie betonu
mieszanka betonowa
Opis:
Over the last 200 years, ordinary concrete has evolved from four basic ingredient materials (gravel, sand, cement, and water) to multicomponent complex composites. The number and variety of the additives, admixtures, non-conventional aggregates, fillers, and fibres currently used for concrete production have continued to grow rapidly. Regrettably, the methods for de-signing concrete mixes have not evolved at a similarly fast pace. Keeping the above facts in mind, the authors utilised a principal component analysis (PCA) to design modern concrete mixes. As an initial approach, 550 cast and tested concrete mixes were analysed. The main aim of the presented study was to prove the usefulness of the PCA methodology for the fast classification of concrete mix compositions. The acquired knowledge should be useful for the effective design of multicomponent modern concrete mixes.
Źródło:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym; 2022, 11; 203-219
2299-8535
2544-963X
Pojawia się w:
Budownictwo o Zoptymalizowanym Potencjale Energetycznym
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Processing of thermographic sequence using Principal Component Analysis
Autorzy:
Świta, R.
Suszyński, Z.
Powiązania:
https://bibliotekanauki.pl/articles/114604.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
filtering
correlation
PCA
segmentation
thermal sequences
Opis:
This paper describes application of the principal component analysis in relation to the thermal imaging contrast sequences, recorded with pulse excitation for three different objects. The aim of the study was to demonstrate that thermographic sequences contain an excessive number of data-distorting information about the characteristics of an object and that it is possible to reduce them. It has been shown that PCA can improve SNR, simplifies separation of areas with distinct features and allows determining their count, which is important, inter alia, with infrared image segmentation. The study shows examples of the results for a sequence of infrared registered for thin-layer-chromatography plate (SiO2 on glass) with separated analytes, the high power Si-eutectic-Mo thyristor structure with defects in eutectic, and the Al disk with cavities of different diameter and depth.
Źródło:
Measurement Automation Monitoring; 2015, 61, 6; 215-218
2450-2855
Pojawia się w:
Measurement Automation Monitoring
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Kernel Version of Functional Principal Component Analysis
Autorzy:
Górecki, Tomasz
Krzyśko, Mirosław
Powiązania:
https://bibliotekanauki.pl/articles/465977.pdf
Data publikacji:
2012
Wydawca:
Główny Urząd Statystyczny
Tematy:
PCA
FPCA
kernel version of FPCA
Opis:
In this paper a new construction of functional principal components (FPCA) is proposed, based on principal components for vector data. A kernel version of FPCA is also presented. The quality of the two described methods was tested on 20 different data sets.
Źródło:
Statistics in Transition new series; 2012, 13, 3; 559-668
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault detection and isolation with robust principal component analysis
Autorzy:
Tharrault, Y.
Mourot, G.
Ragot, J.
Maquin, D.
Powiązania:
https://bibliotekanauki.pl/articles/929927.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
analiza głównych składowych
odporność
detekcja uszkodzeń
lokalizacja uszkodzeń
principal component analysis
robustness
outliers
fault detection
fault isolation
structured residual vector
variable reconstruction
Opis:
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data set. Usually robust principal component analysis is applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. First, the objective was to find an accurate estimate of the covariance matrix of the data so that a PCA model might be developed that could then be used for fault detection and isolation. A very simple estimate derived from a one-step weighted variance-covariance estimate is used (Ruiz-Gazen, 1996). This is a 'local' matrix of variance which tends to emphasize the contribution of close observations in comparison with distant observations (outliers). Second, structured residuals are used for multiple fault detection and isolation. These structured residuals are based on the reconstruction principle, and the existence condition of such residuals is used to determine the detectable faults and the isolable faults. The proposed scheme avoids the combinatorial explosion of faulty scenarios related to multiple faults to be considered. Then, this procedure for outliers detection and isolation is successfully applied to an example with multiple faults.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 429-442
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Chatter detection using principal component analysis in cold rolling mill
Autorzy:
Usmani, N. I.
Kumar, S.
Velisatti, S.
Tiwari, P. K.
Mishra, S. K.
Patnaik, U. S.
Powiązania:
https://bibliotekanauki.pl/articles/329460.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
chatter
principal component analysis
PCA
cold rolling
vibration
drgania samowzbudne
analiza składowych głównych
walcowanie na zimno
drgania
Opis:
Most cold rolling mills are prone to chatter problem. Chatter marks are often observed on the strip surface in cold rolling mill leading to downgrade and rejection of rolled material. Chatter impact product quality as well as productivity of mill. In absence of online chatter detection no corrective action can be taken immediately and whole campaign gets affected. Most conventional approach for online chatter detection is by using vibration measurement of mill stands in time & frequency domain. Present work proposes two approaches to detect chatter in cold rolling mill using a statistical technique called Principal Component Analysis (PCA). In this paper two methods are used for chatter detection. First method applies PCA on Fast Fourier Transform (FFT) to differentiate between chatter and non-chatter condition. Second method applies PCA on statistical parameters calculated from raw vibration data to detect chatter.
Źródło:
Diagnostyka; 2018, 19, 1; 73-81
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Supervised Kernel Principal Component Analysis by Most Expressive Feature Reordering
Autorzy:
Ślot, K.
Adamiak, K.
Duch, P.
Żurek, D.
Powiązania:
https://bibliotekanauki.pl/articles/308598.pdf
Data publikacji:
2015
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
feature selection
kernel methods
pattern classification
Opis:
The presented paper is concerned with feature space derivation through feature selection. The selection is performed on results of kernel Principal Component Analysis (kPCA) of input data samples. Several criteria that drive feature selection process are introduced and their performance is assessed and compared against the reference approach, which is a combination of kPCA and most expressive feature reordering based on the Fisher linear discriminant criterion. It has been shown that some of the proposed modifications result in generating feature spaces with noticeably better (at the level of approximately 4%) class discrimination properties.
Źródło:
Journal of Telecommunications and Information Technology; 2015, 2; 3-10
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza czynnikowa zdjęć wielospektralnych
Principal component analysis of multispectral images
Autorzy:
Czapski, P.
Kotlarz, J.
Kubiak, K.
Tkaczyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/213759.pdf
Data publikacji:
2014
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Lotnictwa
Tematy:
PCA
metody statystyczne
bioróżnorodność
krzywe blasku
redukcja danych
statistical methods
biodiversity
light curves
data reduction
Opis:
Analiza zdjęć wielospektralnych sprowadza się często do modelowania matematycznego opartego o wielowymiarowe przestrzenie metryczne, w których umieszcza się pozyskane za pomocą sensorów dane. Tego typu bardzo intuicyjne, łatwe do zaaplikowania w algorytmice analizy obrazu postępowanie może skutkować zupełnie niepotrzebnym wzrostem niezbędnej do analiz zdjęć mocy obliczeniowej. Jedną z ogólnie przyjętych grup metod analizy zbiorów danych tego typu są metody analizy czynnikowej. Wpracy tej prezentujemy dwie z nich: Principal Component Analysis (PCA) oraz Simplex Shrink-Wrapping (SSW). Użyte jednocześnie obniżają znacząco wymiar zadanej przestrzeni metrycznej pozwalając odnaleźć w danych wielospektralnych charakterystyczne składowe, czyli przeprowadzić cały proces detekcji fotografowanych obiektów. W roku 2014 w Pracowni Przetwarzania Danych Instytutu Lotnictwa oraz Zakładzie Ochrony Lasu Instytutu Badawczego Leśnictwa metodykę tą równie skutecznie przyjęto dla analizy dwóch niezwykle różnych serii zdjęć wielospektralnych: detekcji głównych składowych powierzchni Marsa (na podstawie zdjęć wielospektralnych pozyskanych w ramach misji EPOXI, NASA) oraz oszacowania bioróżnorodności jednej z leśnych powierzchni badawczych projektu HESOFF.
Mostly, analysis of multispectral images employs mathematical modeling based on multidimensional metric spaces that includes collected by the sensors data. Such an intuitive approach easily applicable to image analysis applications can result in unnecessary computing power increase required by this analysis. One of the groups of generally accepted methods of analysis of data sets are factor analysis methods. Two such factor analysis methods are presented in this paper, i.e. Principal Component Analysis (PCA ) and Simplex Shrink - Wrapping (SSW). If they are used together dimensions of a metric space can be reduced significantly allowing characteristic components to be found in multispectral data, i.e. to carry out the whole detection process of investigated images. In 2014 such methodology was adopted by Data Processing Department of the Institute of Aviation and Division of Forest Protection of Forest Research Institute for the analysis of the two very different series of multispectral images: detection of major components of the Mars surface (based on multispectral images obtained from the epoxy mission, NASA) and biodiversity estimation of one of the investigated in the HESOFF project forest complexes.
Źródło:
Prace Instytutu Lotnictwa; 2014, 1 (234) March 2014; 143-150
0509-6669
2300-5408
Pojawia się w:
Prace Instytutu Lotnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wavelength-sensitive-function-based spectral reconstruction using segmented principal component analysis
Autorzy:
Wu, G.
Shen, X.
Liu, Z.
Zhang, J.
Powiązania:
https://bibliotekanauki.pl/articles/174199.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
spectral reconstruction
wavelength-sensitive function
segmented principal component analysis
Opis:
Spectral images provide richer information than colorimetric images. A high-dimensional spectral data presents a challenge for efficient spectral reconstruction. In conventional reconstruction methods it is very difficult to obtain good spectral and colorimetric accuracy simultaneously. In this paper, a segmented principal component analysis (SPCA) method and a weighted segmented principal component analysis (wSPCA) method are proposed for efficient reconstruction of spectral color information. The methods require, firstly, partitioning the complete spectrum of wavelengths into two subgroups, considering the sensitivity of human visual system. Then the classical principal component analysis (PCA) carried out each subgroup of data separately. The results indicated that the spectral and colorimetric accuracy of the SPCA and wSPCA outperformed the PCA and weighted PCA, and wSPCA clearly retained more color visual information.
Źródło:
Optica Applicata; 2016, 46, 3; 365-374
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal Component Analysis and Cluster Analysis In Multivariate Assessment of Water Quality
Autorzy:
Jankowska, J.
Radzka, E.
Rymuza, K.
Powiązania:
https://bibliotekanauki.pl/articles/124319.pdf
Data publikacji:
2017
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
principal component analysis
water quality
cluster analysis
Opis:
This paper deals with the use of multivariate methods in drinking water analysis. During a five-year project, from 2008 to 2012, selected chemical parameters in 11 water supply networks of the Siedlce County were studied. Throughout that period drinking water was of satisfactory quality, with only iron and manganese ions exceeding the limits (21 times and 12 times, respectively). In accordance with the results of cluster analysis, all water networks were put into three groups of different water quality. A high concentration of chlorides, sulphates, and manganese and a low concentration of copper and sodium was found in the water of Group 1 supply networks. The water in Group 2 had a high concentration of copper and sodium, and a low concentration of iron and sulphates. The water from Group 3 had a low concentration of chlorides and manganese, but a high concentration of fluorides. Using principal component analysis and cluster analysis, multivariate correlation between the studied parameters was determined, helping to put water supply networks into groups according to similar water quality.
Źródło:
Journal of Ecological Engineering; 2017, 18, 2; 92-96
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wavelets and principal component analysis method for vibration monitoring of rotating machinery
Autorzy:
Bendjama, H.
Boucherit, M. S.
Powiązania:
https://bibliotekanauki.pl/articles/949212.pdf
Data publikacji:
2016
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
vibration
fault diagnosis
wavelet analysis
principal component analysis, squared
prediction error
Opis:
Fault diagnosis is playing today a crucial role in industrial systems. To improve reliability, safety and efficiency advanced monitoring methods have become increasingly important for many systems. The vibration analysis method is essential in improving condition monitoring and fault diagnosis of rotating machinery. Effective utilization of vibration signals depends upon effectiveness of applied signal processing techniques. In this paper, fault diagnosis is performed using a combination between Wavelet Transform (WT) and Principal Component Analysis (PCA). The WT is employed to decompose the vibration signal of measurements data in different frequency bands. The obtained decomposition levels are used as the input to the PCA method for fault identification using, respectively, the Q-statistic, also called Squared Prediction Error (SPE) and the Q-contribution. Clearly, useful information about the fault can be contained in some levels of wavelet decomposition. For this purpose, the Q-contribution is used as an evaluation criterion to select the optimal level, which contains the maximum information.Associated to spectral analysis and envelope analysis, it allows clear visualization of fault frequencies. The objective of this method is to obtain the information contained in the measured data. The monitoring results using real sensor measurements from a pilot scale are presented and discussed.
Źródło:
Journal of Theoretical and Applied Mechanics; 2016, 54, 2; 659-670
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Magnitude Modelling of HRTF Using Principal Component Analysis Applied to Complex Values
Autorzy:
Ramos, O. A.
Tommasini, F. C.
Powiązania:
https://bibliotekanauki.pl/articles/177682.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
head related transfer functions
HRTF
principal components analysis
PCA
binaural audition
auditory perception
Opis:
Principal components analysis (PCA) is frequently used for modelling the magnitude of the head- related transfer functions (HRTFs). Assuming that the HRTFs are minimum phase systems, the phase is obtained from the Hilbert transform of the log-magnitude. In recent years, the PCA applied to HRTFs is also used to model individual HRTFs relating the PCA weights with anthropometric measurements of the head, torso and pinnae. The HRTF log-magnitude is the most used format of input data to the PCA, but it has been shown that if the input data is HRTF linear magnitude, the cumulative variance converges faster, and the mean square error (MSE) is smaller. This study demonstrates that PCA applied directly on HRTF complex values is even better than the two formats mentioned above, that is, the MSE is the smallest and the cumulative variance converges faster after the 8th principal component. Different objective experiments around all the median plane put in evidence the differences which, although small, seem to be perceptually detectable. To elucidate this point, psychoacoustic discrimination tests are done between measured and reconstructed HRTFs from the three types of input data mentioned, in the median plane between −45◦ and +90◦.
Źródło:
Archives of Acoustics; 2014, 39, 4; 477-482
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Parametric estimation of water retention using mGMDH method and principal component analysis
Autorzy:
Neyshaburi, M.R.
Bayat, H.
Rastgou, M.
Mohammadi, K.
Gregory, A.S.
Nariman-Zadeh, N.
Powiązania:
https://bibliotekanauki.pl/articles/905465.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Opis:
Performing a primary analysis, such as principal component analysis (PCA) may increase accuracy and reliability of developed pedotransfer functions (PTFs). This study focuses on the usefulness of the soil penetration resistance (PR) and principal components (PCs) as new inputs along with the others to develop the PTFs for estimating the soil water retention curve (SWRC) using a multi-objective group method of data handling (mGMDH). The Brooks and Corey (1964) SWRC model was used to give a description of the water retention curves and its parameters were determined from experimental SWRC data. To select eight PCs, PCA was applied to all measured or calculated variables. Penetration resistance, organic matter (OM), aggregates mean weight diameter (MWD), saturated hydraulic conductivity (Ks), macro porosity (Mp), micro porosity (Mip) and eight selected PCs were used as predictors to estimate the Brooks and Corey model parameters by mGMDH. Using PR or OM, Ks and MWD, improved the estimation of SWRC in some cases. Using the predicted PR can be useful in the estimation of SWRC. Using either the MP and Mip or the eight PCs significantly improved the PTFs accuracy and reliability. It would be very useful to apply PCA on the original variables as a primary analysis to develop parametric PTFs.
Źródło:
Polish Journal of Soil Science; 2016, 49, 1
0079-2985
Pojawia się w:
Polish Journal of Soil Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using principal component analysis and canonical discriminant analysis for multibeam seafloor characterisation data
Autorzy:
Łubniewski, Z.
Stepnowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/331872.pdf
Data publikacji:
2012
Wydawca:
Polskie Towarzystwo Akustyczne
Opis:
The paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification is performed by utilisation of several statistical methods applied for analysis of a set of seafloor descriptors derived from multibeam data. In the paper, the use of Principal Component Analysis (PCA), as well as Canonical Discriminant Analysis (CDA) for reduction of the seafloor parameter space dimension is presented along with the obtained results. In addition, the use of the open source World Wind Java SDK tool for implementation of imaging and mapping of seafloor multibeam data, integrated with other elements of a scene and overlaid on rich background data, is also shown.
Źródło:
Hydroacoustics; 2012, 15; 123-130
1642-1817
Pojawia się w:
Hydroacoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On a generalization of the principal component analysis
O uogólnieniu analizy głównych składowych
Autorzy:
Jajuga, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/906716.pdf
Data publikacji:
1987
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 1987, 68
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Land clayey deposits compressibility investigation using principal component analysis and multiple regression tools
Autorzy:
Berrah, Yacine
Chegrouche, Aymen
Brahmi, Serhane
Boumezbeur, Abderrahmane
Powiązania:
https://bibliotekanauki.pl/articles/2201674.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
Tematy:
compressibility index
geotechnical parameters
principal component analysis
PCA
multiple regression models
indeks ściśliwości
parametry geotechniczne
analiza głównych składowych
regresja wielokrotna
Opis:
The settlement and compressibility magnitude of the major clayey and marly sediments in Tebessa area (N-E of Algeria) depends on several geotechnical parameters such as compression Cc and recompression Cs indices. The aim of this study was to investigate the parameters related to soil compressibility through tools of statistical analysis, which save time in comparison to multiply repeated laboratory tests. The study also adopted the principal component analysis (PCA) method to eliminate a number of uncorrelated variables that have no influence on the compressibility magnitude, or their impact is insignificant. The highest mean correlation coefficients were obtained for different contributing parameters. Multiple regression analysis has been performed to obtain the best fit model of the output Cc parameter taking into account the best correlation by adding parameters as regressors to reach the highest coefficient of regression R2 . The final obtained model of the present case study gives the best fit model with R2 of 0.92 which is a better value compared to different published models in the literature (R2 of 0.7 as maximum). The chosen input parameters using PCA combined with multiple regression analysis allow identifying the most important input parameters that noticeably affect the soil compression index, and provide with the best model for estimating the Cc index.
Źródło:
Geomatics, Landmanagement and Landscape; 2022, 4; 95--107
2300-1496
Pojawia się w:
Geomatics, Landmanagement and Landscape
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Classification of the indoor environment of a mobile robot using principal component analysis
Autorzy:
Yaqub, T.
Katupitya, J.
Powiązania:
https://bibliotekanauki.pl/articles/384275.pdf
Data publikacji:
2008
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
mobile robot environment
PCA
classification
feature extraction
training data
bootstrap method
Opis:
Large indoor environments of a mobile robot usually consist of different types of areas connected together. The structure of a corridor differs from a room, a main hall or laboratory. A method for online classification of these areas using a laser scanner is presented in this paper. This classification can reduce the search space of localization module to a great extent making the navigation system efficient. The intention was to make the classification of a sensor observation in a fast and real-time fashion and immediately on its arrival in the sensor frame. Our approach combines both the feature based and statistical approaches. We extract some vital features of lines and corners with attributes such as average length of lines and distance between corners from the raw laser data and classify the observation based on these features. Bootstrap method is used to get a robust correlation of features from training data and finally Principal Component Analysis (PCA) is used to model the environment. In PCA, the underlying assumption is that data is coming from a multivariate normal distribution. The use of bootstrap method makes it possible to use the observations data set which set, which is not necessarily normally distributed. This technique lifts up the normality assumption and reduces the computational cost further as compared to the PCA techniques based on raw sensor data and can be easily implemented in moderately complex indoor environment. The knowledge of the environment can also be up-dated in an adaptive fashion. Results of experimentation in a simulated hospital building under varying environmental conditions using a real-time robotic software Player/Stage are shown.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 2; 44-53
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal Component Analysis of Egg Quality Characteristics of Isa Brown Layer Chickens in Nigeria
Autorzy:
Ukwu, H. O.
Abari, P. O.
Kuusu, D. J.
Powiązania:
https://bibliotekanauki.pl/articles/1178566.pdf
Data publikacji:
2017
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Correlation
Egg
Isa brown
Principal component
Quality
Opis:
This study was designed to provide an objective description of egg quality of Isa brown layer chickens in Nigeria. 104 eggs were used for the study. The eggs were initially weighed individually using a sensitive electronic weighing balance with accuracy of 0.001g. Data were collected on egg weight, egg length, egg width, oblong circumference, egg shell weight, yolk height, albumen height, albumen length, Haugh unit, albumen index and egg shell thickness. Data were subjected to principal component analysis. Egg quality traits had three principal components (factors) that contributed 85.805% of the total variability of the original eleven egg characteristics tested. The three principal components had Eigen values of 4.73 (PC1), 3.656 (PC2) and 1.069 (PC3). The first factor (PC1) accounted for 42.84% of the total variance, the second factor (PC2) accounted for 33.24% of the total variance, while the third factor (PC3) accounted for 9.72% of the total variance. The moderate to large communalities (0.583 – 0.944) observed indicate that a large number of variance has been accounted for by the factor solution. The present principal component analysis provided a means for objective description of the interdependence in the original eleven egg quality characteristics of Isa Brown layer chickens.
Źródło:
World Scientific News; 2017, 70, 2; 304-311
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of principal component analysis for optimization of a system operation assessment criteria set
Autorzy:
Muślewski, Ł.
Knopik, L.
Powiązania:
https://bibliotekanauki.pl/articles/247903.pdf
Data publikacji:
2013
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
quality
criteria
transport system
analysis
canonical correlations
optimization
Opis:
The analysis of results of experimental tests and a literature survey of the issue reveal that the subject matter connected with determination of the optimal number of a given transportation system operation assessment criteria has a direct influence on the result of the considered assessment. The analysis was made within the research on operation quality of a selected transportation system. In order to optimize the analysed system assessment criteria, a theoretical description has been made and an example of canonical correlations application has been presented. Analysis of canonical correlations involves determination of linear combination parameters of the studied sets so that the obtained correlation coefficient will have maximal value. In the successive step, the next pair of linear combination are not correlated with the combinations determined in the first step. The determined correlations can measure the power of relation between two sets of variables and are useful in the process of choosing significant criteria for a given research object operation quality assessment.
Źródło:
Journal of KONES; 2013, 20, 4; 307-312
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of principal component analysis for optimization of a system operation assessment criteria set
Autorzy:
Muślewski, Ł.
Knopik, L.
Powiązania:
https://bibliotekanauki.pl/articles/242963.pdf
Data publikacji:
2012
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
quality
criteria
transport system
analysis of main components
optimization
Opis:
The analysis of results of experimental tests and a literature survey on the issue reveal that the subject matter connected with determination of the optimal number of a given transportation system operation assessment criteria has a direct influence on the result of the considered assessment. Whole study has been made on the basis of the analysis of data obtained from tests performed in a real municipal transportation system, providing transport tasks in a 400 thousand urban agglomeration. On the basis of the tests, there was determined a set of sixteen criteria for the system operation assessment, depending on preferences of drivers, passengers, workers of the system providing vehicles with serviceability and the last group of results is a final assessment. The research involved tests of significance for correlation coefficients between the assessment criteria. The method of main factors involving analysis of a linear transformation of existing vector of variables X into Y has been used to study the task dimensioning. Proper values, providing basis for determination of a new space correspond to coordinates of the newly created vector Y. On this basis, the dimension of the criteria and their significance space has been concluded. The determined criteria have been accepted for the development of a resultant model for assessment of a transportation system operation quality.
Źródło:
Journal of KONES; 2012, 19, 4; 481-486
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The application of principal component analysis (pca) for the study of the spanish tourist demand
Autorzy:
González, María Jesús González
Pascual, María-Eva Vallejo
Powiązania:
https://bibliotekanauki.pl/articles/1051397.pdf
Data publikacji:
2018-12-30
Wydawca:
Uniwersytet im. Adama Mickiewicza w Poznaniu
Tematy:
Spain
autonomous communities
tourist demand
principal component analysis
Opis:
The objective of this study is the characterisation of the Spanish autonomous communities as tourist destinations for Spanish trips, based on the activities carried out, using the principal component method. The Spanish tourist is not only motivated by the sun and beach. This paper aims to clarify how Spanish people consider other tourist destinations. We contrast how frequently other types of tourism are valued when choosing their destination within the Spanish geography. Inland tourism, sports tourism, entertainment as well as gastronomy are becoming increasingly important.
Źródło:
Quaestiones Geographicae; 2018, 37, 4; 43-52
0137-477X
2081-6383
Pojawia się w:
Quaestiones Geographicae
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forcing variables in simulation of transpiration of water stressed plants determined by principal component analysis
Autorzy:
Durigon, A.
de Jong van Lier, Q.
Metselaar, K.
Powiązania:
https://bibliotekanauki.pl/articles/24101.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Opis:
To date, measuring plant transpiration at canopy scale is laborious and its estimation by numerical modelling can be used to assess high time frequency data. When using the model by Jacobs (1994) to simulate transpiration of water stressed plants it needs to be reparametrized. We compare the importance of model variables affecting simulated transpiration of water stressed plants. A systematic literature review was performed to recover existing parameterizations to be tested in the model. Data from a field experiment with common bean under full and deficit irrigation were used to correlate estimations to forcing variables applying principal component analysis. New parameterizations resulted in a moderate reduction of prediction errors and in an increase in model performance. Ags model was sensitive to changes in the mesophyll conductance and leaf angle distribution parameterizations, allowing model improvement. Simulated transpiration could be separated in temporal components. Daily, afternoon depression and long-term components for the fully irrigated treatment were more related to atmospheric forcing variables (specific humidity deficit between stomata and air, relative air humidity and canopy temperature). Daily and afternoon depression components for the deficit-irrigated treatment were related to both atmospheric and soil dryness, and long-term component was related to soil dryness.
Źródło:
International Agrophysics; 2016, 30, 4
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Data compression by Principal Component Analysis (PCA) in modelling of soil density parameters based on soil granulation
Autorzy:
Sulewska, M. J.
Zabielska-Adamska, K.
Powiązania:
https://bibliotekanauki.pl/articles/2060294.pdf
Data publikacji:
2015
Wydawca:
Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy
Tematy:
Artificial Neural Networks
principal component analysis
compaction parameters
minimum and maximum dry density of solid particles
graining parameters
Opis:
The parameter for the density specification of naturally compacted non-cohesive soils and soils in embankments of hydraulic structures is the density index (ID). The parameter used to control the quality of compaction of cohesive and non-cohesive soils artificially thickened, embedded in a variety of embankments is the degree of compaction (IS). In order to determine the parameters of density (ID or IS), compaction parameters ( or should be examined in a laboratory, which often is a long and difficult procedure to carry out. Therefore, there is a need for methods of improving and shortening the test of compaction parameters based on the development and application of useful correlations. Since compaction parameters are dependent on the soil granulation, a method based on regression and artificial neural networks was applied to develop required correlations. Due to the large number of input variables of neural networks in relation to the number of case studies, a PCA method was used to reduce the number of input variables, which resulted in reduction in the size of neural networks.
Źródło:
Geological Quarterly; 2015, 59, 2; 400--407
1641-7291
Pojawia się w:
Geological Quarterly
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An application of Hilbert-Huang transform and principal component analysis for diagnostics of cylindrical plunge grinding process
Autorzy:
Lajmert, P.
Powiązania:
https://bibliotekanauki.pl/articles/100119.pdf
Data publikacji:
2010
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
diagnostics
plunge grinding
Hilbert-Huang transform
Opis:
This paper presents a sensor based diagnostic system for a cylindrical plunge grinding process which ensures a reliable process state and tool wear identification. A new signal processing technique, i.e. Hilbert-Huang transform (HHT) was evaluated for this purpose based on the vibration and acoustic emission signal measurements. Numerical and experimental studies have demonstrated that the process state and tool wear may be effectivel detected through a statistical analysis of the time-dependent amplitudes and instantaneous frequencies resulting from the HHT. A principal component analysis was used to diagnose different grinding process states.
Źródło:
Journal of Machine Engineering; 2010, 10, 1; 39-49
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Porównanie liniowych metod PCA (Principal Component Analysis) i LDA (Linear Discriminant Analysis) zastosowanych do klasyfikacji matryc wzbudzeniowo-emisyjnych wybranych grup substancji biologicznych
Comparison of Principal Component Analysis and Linear Discriminant Analysis applied to classification of excitation-emission matrices of the selected biological material
Autorzy:
Leśkiewicz, M.
Kaliszewski, M.
Mierczyk, Z.
Włodarski, M.
Powiązania:
https://bibliotekanauki.pl/articles/211300.pdf
Data publikacji:
2016
Wydawca:
Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
Tematy:
analiza cech
spektroskopia fluorescencyjna
klasyfikacja substancji biologicznych
Feature Analysis
Fluorescence Spectroscopy
Biological Material Classification
Opis:
W pracy porównano właściwości dwóch liniowych metod (PCA i LDA) pozwalających na redukcję wymiarów w trakcie analizy cech oraz zbadano wydajność tych dwóch algorytmów w procesie klasyfikacji wybranego materiału biologicznego na podstawie jego wzbudzeniowo-emisyjnych matryc fluorescencyjnych. Stwierdzono, że metoda LDA redukuje liczbę wymiarów (znaczących zmiennych) bardziej efektywnie niż metoda PCA. Za pomocą algorytmu LDA udało się uzyskać względnie dobre rozróżnienie badanego materiału biologicznego.
Quality of two linear methods (PCA and LDA) applied to reduce dimensionality of feature analysis is compared and efficiency of their algorithms in classification of the selected biological materials according to their excitation-emission fluorescence matrices is examined. It has been found that LDA method reduces the dimensions (or a number of significant variables) more effectively than PCA method. Arelatively good discrimination within the examined biological material has been obtained with the use of LDA algorithm.
Źródło:
Biuletyn Wojskowej Akademii Technicznej; 2016, 65, 1; 15-31
1234-5865
Pojawia się w:
Biuletyn Wojskowej Akademii Technicznej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-parameter data visualization by means of principal component analysis (PCA) in qualitative evaluation of various coal types
Autorzy:
Niedoba, T.
Powiązania:
https://bibliotekanauki.pl/articles/109595.pdf
Data publikacji:
2014
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
principal component analysis
PCA
multi-parameter data visualization
coal
identification of data
covariance matrix
pattern recognition
Opis:
Multi-parameter data visualization methods are a modern tool allowing to classify some analyzed objects. When it comes to grained materials, e.g. coal, many characteristics have an influence on the material quality. Besides the most obvious features like particle size, particle density or ash contents, coal has many other qualities which show significant differences between the studied types of material. The paper presents the possibility of applying visualization techniques for coal type identification and determination of significant differences between various types of coal. The Principal Component Analysis was applied to achieve this purpose. Three types of coal 31, 34.2 and 35 (according to Polish classification of coal types) were investigated, which were initially screened on sieves and subsequently divided into density fractions. Next, each size-density fraction was analyzed chemically to obtain other characteristics. It was pointed out that the applied methodology allowed to identify certain coal types efficiently, which makes it useful as a qualitative criterion for grained materials. However, it was impossible to provide such identification based on contrastive comparisons of all three types of coal. The presented methodology is a new way of analyzing data concerning widely understood mineral processing.
Źródło:
Physicochemical Problems of Mineral Processing; 2014, 50, 2; 575-589
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal Component Analysis in the Study of Structure of the Best Polish Decathlon Competitors from the Period between 1985–2015
Autorzy:
Dziadek, Bartosz
Iskra, Janusz
Przednowek, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/1030587.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Szczeciński. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego
Tematy:
decathlon
principal component analysis
sport career
Opis:
The modern decathlon is a sport consisting of ten different events held over two days, played by men. Depending on the complexity of combined events, variety of events (runs, throws, jumps), the multi-stage, time-consuming and difficult training process the sport is considered as one of the most difficult. The analysis of careers of the best decathlon participants and applying advanced data-mining methods can help define the patterns occurring between each decathlon event and the final result. The research material encompasses career data of the 25 top competitors from Poland in years 1985–2015. Principal component analysis (PCA) was used in the research in order to designate new uncorrelated variables (components), representing input data across a new plane. Data analysis involved appointment of correlations between the events, determining the number of main components taken into account in further studies, analysis of the weight of each variable in formation of main components as well as visualisation and interpretation of results in the new plane described by the determined main components. Through the implementation of PCA method in the process of analysis it was possible to designate over 69% of compound data volatility with the use of the first three components. The first component, comprised of seven variables, displays the largest share in the total variability. The study of the relationship between variables in the new plane displayed strong correlations between sprint events (100 m, 110 m hurdles) and long jump and pole vault. No correlations between the 1500 m run and other events were found.
Źródło:
Central European Journal of Sport Sciences and Medicine; 2018, 23, 3; 77-87
2300-9705
2353-2807
Pojawia się w:
Central European Journal of Sport Sciences and Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Specyficzna identyfikacja emiterów radarowych bazująca na analizie składowych głównych
Specific radar emitter identification based on principal component analysis
Autorzy:
Kawalec, A.
Owczarek, R.
Rapacki, T.
Wnuczek, S.
Powiązania:
https://bibliotekanauki.pl/articles/210693.pdf
Data publikacji:
2006
Wydawca:
Wojskowa Akademia Techniczna im. Jarosława Dąbrowskiego
Tematy:
walka elektroniczna
klasyfikacja cech sygnałów radarowych
specyficzna identyfikacja emiterów
przekształcenie Karhunena-Loeve'a
warfare electronic
radar signal feature classification
specific emitter identification
Karhunen-Loeve expansion
Opis:
W artykule została przedstawiona problematyka związana z identyfikacją emiterów radarowych należących do tego samego typu i klasy. Jest to specyficzny rodzaj identyfikacji (SEI, ang. Specific Emitter Identification), polegający na rozróżnianiu poszczególnych egzemplarzy tego samego typu radaru. Klasyczna identyfikacja sygnałów bazująca na analizie statystycznej podstawowych parametrów mierzalnych sygnału nie spełnia wymagań stawianych przed SEI. Przedstawiona w artykule metoda identyfikacji opiera się na przekształceniu Karhunena-Loeve'a (KL), która należy do metod analizy składowych głównych (PCA, ang. Principal Component Analysis).
One of the most difficult tasks in the radar signal processing is optimal features extraction and classification. The multifunction radar systems cannot be classified and precisely recognized by most of new and modern Electronic Support Measure and Electronic Intelligence Devices in the real time. In most cases, the modern ESM/ELINT systems cannot recognize the different devices of the same type or class. New method of the radar identification with a high quality of recognizing is the Specific Emitter Identification (SEI). The main task is to find non-intentional modulations in the receiving signals. This paper provides an overview of the new methods of measurement emitter signal features parameters and their transformation. This paper presents some aspects of radar signal features processing using Karhunen-Loeve's expansion as a feature selection and classification transform.
Źródło:
Biuletyn Wojskowej Akademii Technicznej; 2006, 55, 1; 41-54
1234-5865
Pojawia się w:
Biuletyn Wojskowej Akademii Technicznej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machining Investigations of Squeeze Cast TiB2/Al 7075 Composites through EDM: Regression Modelling and Weighted Principal Component Analysis
Autorzy:
Pradhan, Rahul Chandra
Das, Diptikanta
Sahoo, Barada Prasanna
Rout, Chiranjeeb
Panda, Akash
Barla, Evangelin
Powiązania:
https://bibliotekanauki.pl/articles/27324484.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
Al 7075
TiB2
metal matrix composite
electrical discharge machining
weighted principal component analysis
Opis:
2 wt.% TiB2 (mean particle size: 400 nm) reinforced Al 7075 metal matrix composites (MMCs) fabricated through mechanical stirring and ultrasonic agitation integrated squeeze casting process were subjected to electrical discharge machining (EDM) after determining the physical and mechanical properties. EDM was conducted with Cu electrode tools to investigate influence of machining factors, i.e. peak current (IP), pulse on time (TON) and gap voltage (VG) on the tool wear rate (TWR), material removal rate (MRR) and average surface roughness (ASR) of the machined surfaces. All the three responses increased on increasing IP and TON, but reduced on increasing VG. The machined surfaces were studied through scanning electron microscope (SEM). Significance of the EDM parameters on the individual responses were studied using analysis of variance (ANOVA) and regression models for the responses were developed using response surface method (RSM). The responses under consideration were optimized simultaneously using Taguchi embedded weighted principal component analysis (WPCA), which resulted the parametric combination of 4A (current), 100 μs (pulse duration) and 75V (voltage) was the optimal setting for the multi-criteria decision problem. Finally, the result of optimization was validated by conducting some confirmatory experiments.
Źródło:
Archives of Metallurgy and Materials; 2023, 68, 2; 551--562
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Unemployment rate for various countries since 2005 to 2012: comparison of its level and pace using functional principal component analysis
Autorzy:
Jaworski, Stanisław
Furmańczyk, Konrad
Powiązania:
https://bibliotekanauki.pl/articles/453714.pdf
Data publikacji:
2012
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:
B-splines basis system
functional principal component analysis,
unemployment rate
Opis:
We apply the functional principal component analysis to compare the unemployment rate in euro area, Japan and USA since 2005 to 2012. For preprocessing analysis we used B-splines system with roughness penalty for smoothing the data. The analysis enables to reveal the most important type of variation in unemployment rate and its pace's in examined countries.
Źródło:
Metody Ilościowe w Badaniach Ekonomicznych; 2012, 13, 2; 40-47
2082-792X
Pojawia się w:
Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza nieliniowych składowych głównych dla danych czasowo‑przestrzennych geograficznie ważonych
Nonlinear Principal Component Analysis for Geographically Weighted Temporal‑spatial Data
Autorzy:
Krzyśko, Mirosław
Łukaszonek, Wojciech
Ratajczak, Waldemar
Wołyński, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/658130.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
nieliniowa analiza składowych głównych
dane geograficznie ważone
dane czasowo‑przestrzenne
nonlinear principal component analysis
geographically weighted data
temporal‑spatial data
Opis:
Schölkopf, Smola and Müller (1998) have proposed a nonlinear principal component analysis (NPCA) for fixed vector data. In this paper, we propose an extension of the aforementioned analysis to temporal‑spatial data and weighted temporal‑spatial data. To illustrate the proposed theory, data describing the condition of state of higher education in 16 Polish voivodships in the years 2002–2016 are used.
Schölkopf, Smola i Müller (1998) zaproponowali analizę nieliniowych składowych głównych (NPCA) dla ustalonych danych wektorowych. Niniejszy artykuł zawiera rozszerzenie tej metody na dane czasowo‑przestrzenne oraz czasowo‑przestrzenne geograficznie ważone. Każdy obiekt jest scharakteryzowany za pomocą macierzy Xi, rozmiaru T × p, zawierającej wartości p cech zaobserwowanych w T momentach czasowych, i = 1, …, n. Macierze te są przekształcane nieliniowo do przestrzeni Hilberta i budowana jest scentrowana macierz jądrowa. Ostatecznie macierz ta jest podstawą konstrukcji nieliniowych składowych głównych. W przypadku danych geograficznie ważonych macierz Xizostaje zastąpiona macierzą wiXi, gdzie wijest dodatnią wagą geograficzną związaną z i‑tym miejscem obserwacji, i = 1, …, n. Teoria zilustrowana jest przykładem dotyczącym stanu szkolnictwa wyższego w 16 polskich województwach, notowanego w latach 2002–2016.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2018, 4, 337; 169-181
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Interpolation of soil infiltration in furrow irrigation: Comparison of kriging, inverse distance weighting, multilayer perceptron and principal component analysis methods
Autorzy:
Alipour, N.
Nasseri, A.
Mohammbdi, T.A.
Pazira, E.
Powiązania:
https://bibliotekanauki.pl/articles/971544.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
artificial neural network
geostatistical analysis
irrigation
soil infiltration
Opis:
Study on soil infiltration rate as part of water cycle is essential for managing water resources and designing irrigation systems. The present study was conducted with the aim to compare Kriging, inverse distance weighting (IDW), multilayer perceptron (MLP) and principal component analysis (PCA) methods in the interpolation of soil infiltration in furrow irrigation, and determine the best interpolation method. To conduct infiltration tests, furrows were made on the farm in four triad groups. Infiltration through the blocked furrows method was measured 10, 20, 30, 40, 50, 60, 90, 120, 150, 160, 180 and 210 min after irrigation at a 10-meter distance in each furrow. Data were analyzed by GS+ and Neuro Solutions (NS) software packages. In this study, the maximum error (ME), mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), relative error (RE) and correlation coefficient (r) were used to compare the interpolation methods. The results of analysis of variance (ANOVA) indicated that differences in methods based on RMSE, MBE, MAE and ME indices were not significant; however, this difference was significant based on r and RE indices. According to the ANOVA results, it can be said that the PCA method with a r of 0.69 and RE of 31%, was predicted with a higher accuracy as compared to other methods.
Źródło:
Polish Journal of Soil Science; 2019, 52, 1; 59-74
0079-2985
Pojawia się w:
Polish Journal of Soil Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation of dimensions of farmer attitudes in principal component analysis (PCA)
Ocena wymiarów postaw rolników w analizie głównych składowych (PCA)
Autorzy:
Domagalska-Grędys, M.
Powiązania:
https://bibliotekanauki.pl/articles/1790269.pdf
Data publikacji:
2020
Wydawca:
The Polish Association of Agricultural and Agribusiness Economists
Tematy:
relations and attitudes of farmers implementing biodiversity processes
social capital
bond
relationship opportunism
PCA
relacje i postawy rolników realizujących procesy bioróżnorodności
kapitał
społeczny
więź
oportunizm relacji
Opis:
The aim of the article was to identify leading relationship attitudes among farmers keeping animals of conservative breeds. The practical justification for the adopted analyses was to identify factors that foster desirable relations (attitudes) in agriculture based on ties. The research was conducted among 145 farms using an interview questionnaire in the poviats of three voivodships (Malopolskie, Podkarpackie, Lubelskie), where operations with livestock conservation breeds occurred. Collective selection was deliberate, meeting the criteria for the use of the extended diversity of breeds of farmed animals in 3 categories (cows, sheep and pigs). On the basis of the PCA test and analysis, 2 types of attitudes were selected: bonded and opportunistic. In the implemented accounts represented by farms according to three species of animals of conservative breeds, the opportunistic attitude was more prevalent than the prison attitude. The opportunism of pig and cattle breeders was particularly valued. In addition, the distribution of attitudes in groups was analysed, among others, due to the characteristics of farmers (age, sex, education and professional experience) and the presence of a successor on the farm. What was confirmed, among others, was the impact of a lack of professional experience of farmers on pro-bonding attitudes. In addition, in the groups, the distribution of attitudes was analysed, among others, according to the characteristics of farmers (age, gender, education, professional experience) and the presence of a successor on the farm. The influence of the lack of professional experience of farmers on relationship-oriented attitudes was confirmed. The younger generation of farmers may be more effective in implementing programmes of genetic biodiversity of farm animals. Small-scale farms, developed by better-educated farmers, with short work experience in agriculture and less experience in keeping animals of conservative breeds, prove to be developmental. The obtained results are illustrative of purposely selected objects, with restrictions, they can be related to the population of all Polish farms keeping animals of conservative breeds.
Celem artykułu jest identyfikacja wiodących postaw relacyjnych wśród rolników utrzymujących zwierzęta ras zachowawczych. Uzasadnieniem praktycznym przyjętych analiz było wskazanie czynników, sprzyjających pożądanym relacjom (postawom) w rolnictwie opartym na więzi. Badania przeprowadzono w 145 gospodarstwach z wykorzystaniem kwestionariusza wywiadu w powiatach trzech województw (małopolskiego, podkarpackiego i lubelskiego), w których występowały gospodarstwa z rasami zachowawczymi zwierząt gospodarskich. Dobór gospodarstw był celowy, spełniający kryterium zapewnienia największego zróżnicowania ras zwierząt hodowlanych 3 gatunków (krów, owiec i świń). Na podstawie testu i analizy PCA wyłoniono 2 typy postaw, tj. typ więzi i typ oportunistyczny. W realizowanych relacjach rolników reprezentujących gospodarstwa według trzech gatunków zwierząt ras zachowawczych, mocniej zaznaczyła się postawa oportunistyczna niż więziowa. Szczególnie wysoko cenili oportunizm hodowcy świń i bydła. Dodatkowo w grupach przeanalizowano rozkłady postaw, m.in. ze względu na cechy rolników (wiek, płeć, wykształcenie, doświadczenie zawodowe) i obecność następcy w gospodarstwie. Potwierdzono m.in. wpływ braku doświadczeń zawodowych rolników na postawy prowięziowe. Młodsze pokolenie rolników jest bardziej efektywne w realizacji programów bioróżnorodności genetycznej zwierząt gospodarskich. Rozwojowe okazały się mniejsze powierzchniowo gospodarstwa, prowadzone przez lepiej wykształconych rolników, o krótkim stażu pracy w rolnictwie i mniejszych doświadczeniach w utrzymywaniu zwierząt ras zachowawczych. Uzyskane wyniki są poglądowe dla dobranych celowo obiektów, z ograniczeniami można je odnosić do populacji wszystkich polskich gospodarstw utrzymujących zwierzęta ras zachowawczych.
Źródło:
Annals of The Polish Association of Agricultural and Agribusiness Economists; 2020, 22, 1; 66-76
2657-781X
2657-7828
Pojawia się w:
Annals of The Polish Association of Agricultural and Agribusiness Economists
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The quality of public finance in the light of fiscal governance concept: implications for the European Union countries
Autorzy:
Kargol-Wasiluk, Aneta
Wildowicz-Giegiel, Anna
Powiązania:
https://bibliotekanauki.pl/articles/22446543.pdf
Data publikacji:
2018
Wydawca:
Instytut Badań Gospodarczych
Tematy:
public finance
quality
fiscal governance
principal component analysis
Opis:
Research background: The research area on the quality of public finance (QPF) appears to be intellectually attractive. In the light of the challenges of the 21st century, public finance should be characterized by adequate quality, ensuring effective implementation of the economic functions of government. The problem of QPF is increasingly more frequent in the face of a deteriorating fiscal situation of most countries in Europe and around the world. Hence, it is worth considering which factors determine the quality of public finance. Purpose of the article: This article aims to show the possibility of assessing the quality of public finance in the light of fiscal governance concept.  The identification of the key components of QPF seems to be useful from the point of view of empirical research, and can be implemented to assess the quality of public finance in the EU?28. Methods: Descriptive analysis along with principal component analysis (PCA) was implemented to indicate dimensions of QPF. Findings & Value added: The quality of public finance consists of a well-designed fiscal rules (numerical and non-numerical) and institutions, as well as structural reforms. The obtained results allow to characterize the quality of public finance through the prism of six identified principal components. They have a mixed character, two of them are partly or totally related to the institutional aspects of public finance, which proves their importance in the process of improving the quality of public finance. Improving the quality of public finance remains a key challenge for policy makers in the EU. The growing impact of globalization and the aging population also cause the need to improve the qualitative aspects of fiscal policy. The study contributes to the literature on public finance, particularly in the empirical dimension through broadening the knowledge on institutional factors which can be used to measure QPF index. The results of research have certainly enriched the existing knowledge on the phenomenon of QPF and the ways of its measurement.
Źródło:
Equilibrium. Quarterly Journal of Economics and Economic Policy; 2018, 13, 3; 411-426
1689-765X
2353-3293
Pojawia się w:
Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The use of some morphological traits for the assessment of genetic diversity in spinach (Spinacia oleracea L.) landraces
Autorzy:
Ebadi-Segheloo, Asghar
Asadi-Gharneh, Hossein ali
Mohebodini, Mehdi
Janmohammadi, Mohsen
Nouraein, Mojtaba
Sabaghnia, Naser
Powiązania:
https://bibliotekanauki.pl/articles/2199739.pdf
Data publikacji:
2014-06-19
Wydawca:
Instytut Hodowli i Aklimatyzacji Roślin
Tematy:
breeding
cluster analysis
diversity
landraces
principal component analysis
Opis:
Investigation of native accessions of spinach (Spinacia oleracea L.) would be aid in the development of new genetically improved varieties, so in this research 121 spinach landraces, collected from the various spinach growing areas of Iran, were evaluated to determine their diversity using several agro-morphological traits. High coefficients of variation (CV) were recorded in fresh yield, leaf area and dry yield. Using principal component (PC) analysis, the first three PCs with eigenvalues more than 0.9 contributed 80.56% of the variability among accessions. The first PC was related to leaf yield performance (fresh and dry yields, leaf numbers at flowering and lateral branches) while the PC2 was related to leaf characteristic (leaf width, petiole length, petiole diameter and leaf area). The third PC was related to seed characteristic (seed yield and 1000-seed weight) and was named as seed property component. The 121 spinach landraces were grouped into six clusters using cluster analysis. Each cluster had some specific characteristics of its own and the clusters I and II were clearly separated from clusters III and V and also from clusters IV and VI. The studied accessions are an important resource for the generation of a core collection of spinach in the world. The results of present research will support tasks of conservation and utilization of landraces in spinach breeding programs.
Źródło:
Plant Breeding and Seed Science; 2014, 69; 69-80
1429-3862
2083-599X
Pojawia się w:
Plant Breeding and Seed Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessing domestic factors determining water consumption in a semi-arid area (Sedrata City) using artificial neural networks and principal component analysis
Autorzy:
Zeroual, Menal
Hani, Azzedine
Boustila, Amir
Powiązania:
https://bibliotekanauki.pl/articles/1844342.pdf
Data publikacji:
2021
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
artificial neural networks
domestic water use determinants
household water consumption
principal component analysis
semi-arid area
Opis:
The growing demand for fresh water and its scarcity are the major problems encountered in semi-arid cities. Two different techniques have been used to assess the main determinants of domestic water in the Sedrata City, North-East Algeria: principal component analysis (PCA) and artificial neural networks (ANNs). To create the ANNs models based on the PCA, twelve explanatory variables are initially investigated, of which nine are socio-economic parameters and three physical characteristics of building units. Two optimum ANNs models have been selected where correlation coefficients equal to 0.99 in training, testing and validation phases. In addition, results demonstrate that the combination of socio-economic parameters with physical characteristics of building units enhances the assessment of household water consumption.
Źródło:
Journal of Water and Land Development; 2021, 49; 219-228
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India
Autorzy:
Kathwas, Amar Kumar
Patel, Nilanchal
Powiązania:
https://bibliotekanauki.pl/articles/2088182.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
geomorphological feature
soil erosion
USLE
principal component analysis
Opis:
Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms.
Źródło:
Polish Journal of Soil Science; 2021, 54, 1; 1-24
0079-2985
Pojawia się w:
Polish Journal of Soil Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Taxonomic position of Pinus ceciliae (Pinaceae) endemic for Balearic Islands as revealed on needle characteristics
Autorzy:
Boratynska, K.
Tomaszewski, D.
Montserrat, J.M.
Marek, S.
Boratynski, A.
Powiązania:
https://bibliotekanauki.pl/articles/2077667.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Instytut Dendrologii PAN
Tematy:
biometry
discrimination analysis
Pinus halepensis
Principal Component Analysis
Opis:
The Cecilian pine (Pinus ceciliae) is endemic to Balearic islands (Spain). It is a small taxon, some- times treated as synonym of Aleppo pine (P. halepensis), to which is closely related, differing mainly with dense crown shape and upright branches. The other characteristics, which differ between P. ceciliae and P. halepensis concern the cone scale and needle length only. We examined biometrically needles of Cecilian pine from Mallorca (5 tress) and Menorca (9 trees) islands, and compared them to Aleppo pine populations rep- resented by 30 trees from each island. Each tree was represented by 5 needles, and they were studied with respect to 17 morphological and anatomical characteristics. We detected that needles of the Cecilian pine were smaller, but only when compared to the Aleppo pine from the same island. In general, this difference was also observed in the number of resin canals, number of stomata and stomatal rows. Interestingly, the proportions of the needle dimensions pattern were similar in both taxa. In conclusion we stated the results support the taxonomic rank of Cecilian pine as a variety, Pinus halepensis var. ceciliae (Llorens & L.Llorens) L.Llorens, Fl. Països Catalans, 1: 197 (1984)
Źródło:
Dendrobiology; 2019, 82; 8-16
1641-1307
Pojawia się w:
Dendrobiology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Klasyczna i neuronowa analiza głównych składowych na przykładzie zadania kompresji obrazu
Classical and neural network-based principal component analysis for image compression
Autorzy:
Bartecki, K.
Powiązania:
https://bibliotekanauki.pl/articles/154740.pdf
Data publikacji:
2013
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
analiza składników głównych
sztuczna sieć neuronowa
kompresja danych
principal component analysis
artificial neural network
data compression
Opis:
W artykule omówiono zastosowanie analizy składników głównych (PCA) w zadaniu kompresji stratnej sygnału na przykładzie kompresji obrazu. Zadanie zrealizowano z wykorzystaniem klasycznej metody PCA oraz dwóch rodzajów sieci neuronowych: jednokierunkowej, dwuwarstwowej sieci z uczeniem nadzorowanym i jednowarstwowej sieci z uczeniem nienadzorowanym. W każdym z przypadków przeanalizowano wpływ struktury modelu PCA na wartości współczynnika kompresji oraz średniokwadratowego błędu kompresji.
In the paper, lossy data compression techniques based on the principal component analysis (PCA) are considered on the example of image compression. The presented task is performed using the classical PCA method based on the eigen-decomposition of the image covari-ance matrix as well as two different kinds of artificial neural networks. The first neural structure used is a two-layer feed-forward network with supervised learning shown in Fig.1, while the second one is a single-layered network with unsupervised Hebbian learning. In each case considered, the effect of the PCA model structure on the data compression ratio and the mean square reconstruction error is analysed. The compression results for a Hebbian neural network with K=4 PCA units are presented in Figs. 2, 3 and 4. They show that only 4 eigenvectors are able to capture the main features of the processed image, giving as a result high value of the data compression ratio. However, the reconstructed image quality is not sufficient from a practical point of view. Therefore, selection of the appropriate value for K should take into account the tradeoff between a sufficiently high value for the compression ratio and a reasonably low value for the image reconstruction error. The summary results for both classical and neural PCA compression approaches obtained for different number of eigenvectors (neurons) are compared in Fig. 5. The author concludes that a positive aspect of using neural networks as a tool for extracting principal components from the image data is that they do not require calculating the correlation matrix explicitly, as in the case of the classical PCA-based approach.
Źródło:
Pomiary Automatyka Kontrola; 2013, R. 59, nr 1, 1; 34-37
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-trait evaluation of value for cultivation and use of early maturing edible potato cultivars registered in Poland
Autorzy:
Rymuza, K.
Powiązania:
https://bibliotekanauki.pl/articles/123780.pdf
Data publikacji:
2015
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
edible potato
potato cultivar
principal component analysis
cluster analysis
Opis:
The work presents an analysis of diversity and comparison of value for cultivation and use of early maturing potato cultivars registered with the Polish National Register of Cultivars. The comparison was based on 17 yield and appearance traits and quality attributes of tubers as well as their resistance to diseases. The analysis employed the following multi-dimensional statistical methods: principal component analysis and cluster analysis. The principal component analysis revealed that over 70% of the total variation was associated with the first 6 principal components. Cluster analysis yielded 4 groups of genotypes. The first group consisted of the cultivars which produced tubers with the most shallow eyes, the best flavour and the least severe darkening of raw flesh. The cultivars in the second group produced high yields and were low in starch, dry matter and glycoalkaloids. The tubers of cultivars which were classified into the third group had the highest starch, dry matter and vitamin C contents. However, they produced the lowest yields and were quite susceptible to most diseases. The fourth group was made up of high-yielding cultivars which tended to accumulate glycoalkaloids but were most resistant to hollow heart in tubers.
Źródło:
Journal of Ecological Engineering; 2015, 16, 1; 50-56
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza porównawcza efektywności metod redukcji zmiennych - analiza składowych głównych i analiza czynnikowa
Comparative Analysis of Effectiveness of the Methods for Reduction of Variables - Principal Component Analysis and Factor Analysis
Autorzy:
Czopek, Anna
Powiązania:
https://bibliotekanauki.pl/articles/589975.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Analiza czynnikowa
Analiza porównawcza
Analizy głównych komponentów
Comparative analysis
Factor analysis
Principal Component Analysis
Opis:
Principal component analysis and factor analysis are the two most popular methods that allow to bring a large number of studied variables to a much smaller number of mutually independent principal components or factors. New variables (principal components or factors) retain a relatively large part of the information contained in the original variables, while each of them is a carrier of other substantive content. Both of these methods of reduction of the variables are often used, because too many pending attributes increases the range of the difficulty of interpretation. The main reason of undertaking the project is an attempt to show, that the abovementioned methods, although they are very similar, cannot be indentified. Despite the fact, that in both cases eigenvalues are calculated, factor loadings, etc., but still there are differences in the way of action, about which it must be remembered. So the usage of these names the variables are unacceptable. The article consists of three parts. The first and second chapter are devoted, respectively, to the analysis of the principal components and factor analysis, where a short characterization of these methods had been made. In the third chapter, on the basis of an empirical example, we compared the effectiveness of the principal components analysis and factor analysis.
Źródło:
Studia Ekonomiczne; 2013, 132; 7-23
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessment of Sustainable Development Using Cluster Analysis and Principal Component Analysis
Ocena zrównoważonego rozwoju za pomocą analizy skupień i analizy głównych składników
Autorzy:
Drastichová, Magdaléna
Filzmoser, Peter
Powiązania:
https://bibliotekanauki.pl/articles/371108.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Komitet Człowiek i Środowisko PAN
Tematy:
European Union (EU)
Hierarchical Cluster Analysis (HCA)
Principal Component Analysis (PCA)
Sustainable Development (SD)
Sustainable Development Goals (SDGs)
JEL Classification
Q01
Q50
Q51
Q54
Q56
Unia Europejska
hierarchiczna analiza skupień
analiza głównych wskaźników
rozwój zrównoważony
cele zrównoważonego rozwoju
Opis:
The European Union (EU) Sustainable Development Goals (SDG) indicator set replaced the EU Sustainable Development Strategy (SDS) in 2017. The selected indicators of this set were chosen for the analysis to classify the sample of the 28 EU countries along with Norway according to their performance in sustainability. In the selection of indicators, priority was given to the indicators reflecting the social dimension of SD, along with important representatives of the economic, ecological and institutional dimensions of SD generally. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) were applied to the data of 12 indicators in the period 2012- 2016. By means of the HCA, four clusters were created in each year of the period 2012-2016 using the indicator values of particular years and then using all the indicator values in all the monitored years for the general assignment of countries to particular clusters. According to changes in the assignment to particular clusters over the years, the sustainability of development and the path of SD in the examined countries are assessed. As regards the core countries of each cluster, cluster 1 includes the most developed EU countries and is thus evaluated as the best performing cluster. Cluster 2 including the least developed EU countries is evaluated as the worst performing cluster. Cluster 3 predominantly includes the transitive economies and it is evaluated as the second best performing cluster according to the indicators applied. Cluster 4 containing the Southern countries is assessed as the second worst performing cluster. From the shifts of countries that occurred between the years, the shift of Ireland from cluster 3 to cluster 1 in 2013 must be emphasised as the move towards higher sustainability. The shift of Slovakia and Hungary from cluster 2 to cluster 3 in 2013 is also evaluated as progress towards higher sustainability.
W Unii Europejskiej w 2017 r. Cele zrównoważonego rozwoju zastąpiły dotychczasową Strategię zrównoważonego rozwoju. W tej pracy wybrane wskaźniki odnoszące się do nowych Celów zrównoważonego rozwoju stanowią podstawę klasyfikacji 28 krajów Wspólnoty oraz Norwegii. Wśród tych wskaźników priorytetowo potraktowano te odnoszące się do wymiaru społecznego zrównoważonego rozwoju, uzupełniając dyskusję o podstawowe wskaźniki ekonomiczne, ekologiczne i instytucjonalne. Przeanalizowano okres obejmujący lata 2012-2016. Wobec wybranych 12 wskaźników zastosowano hierarchiczną analizę skupień i analizę głównych składników. Utworzono cztery klastry w ramach każdego roku z analizowanego okresu, określając wartości wskaźników dla poszczególnych lat, a następnie określenie wszystkich wartości wskaźników dla wszystkich monitorowanych lat umożliwiło przypisanie krajów do poszczególnych klastrów. Określenie zmian w przypisaniu do poszczególnych klastrów na przestrzeni lat umożliwiło ocenę zrównoważoności rozwoju i określenie ścieżki zrównoważonego rozwoju badanych krajów. Jeśli chodzi o główne kraje każdego klastra, to klaster 1 obejmuje najbardziej rozwinięte kraje UE i dlatego jest oceniany jako klaster, który osiąga najlepsze wyniki. Klaster 2 uwzględnia najsłabiej rozwinięte kraje i oceniony jest jako ten, który osiąga najgorsze wyniki. Klaster 3 obejmuje głównie gospodarki znajdujące się w okresie przejściowym i jest oceniany jako drugi osiągający najlepsze wyniki. Klaster 4 obejmuje kraje Południa i jest oceniany jako drugi osiągający najgorsze wyniki. Uwzględniając zmiany jakie zaszły w okresie kolejnych lat, należy podkreślić przesunięcie Irlandii z klastra 3 do klastra 1 w 2013 r., co oznacza ruch w kierunku większej zrównoważoności. Tak samo należy ocenić przejście w tym samym roku Słowacji i Węgier z klastra 2 do klastra 3.
Źródło:
Problemy Ekorozwoju; 2019, 14, 2; 7-24
1895-6912
Pojawia się w:
Problemy Ekorozwoju
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of principal component analysis for the assessment of spring wheat characteristics
Wykorzystanie metody analizy składowych głównych do oceny cech pszenicy jarej
Autorzy:
Rymuza, K.
Turska, E.
Wielogorska, G.
Bombik, A.
Powiązania:
https://bibliotekanauki.pl/articles/47062.pdf
Data publikacji:
2012
Wydawca:
Politechnika Bydgoska im. Jana i Jędrzeja Śniadeckich. Wydawnictwo PB
Opis:
In the studies, the analysis of the diversification of spring wheat characteristics was carried out depending on the growth system. Field experiment was carried out in years 2004-2006 at the Agricultural Experimental Station in Zawady, which is part of the Siedlce University of Natural Sciences and Humanities. The obtained correlation coefficients prove that the relation between wheat characteristics depends on the growth system. The applied method of principal component analysis (PCA) allowed a complex assessment of the relations between the characteristics. It also made it possible to reduce the original seven characteristics to three new variables, which carried over 75% of the information of the input data obtained from the direct sowing and almost 80% for the conventional tillage. The greatest discriminatory power, which diversified the studied plants, was shown by the mass of 1000 grains and grain yield.
W badaniach dokonano analizy zróżnicowania cech pszenicy jarej w zależności od systemu uprawy. Doświadczenie polowe przeprowadzono w latach 2004- -2006 w Rolniczej Stacji Doświadczalnej Zawady, należącej do Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach. Uzyskane wartości współczynników korelacji dowodzą, że współzależność pomiędzy cechami pszenicy zależy od systemu uprawy. Zastosowana metoda analizy składowych głównych (PCA) pozwoliła na kompleksową ocenę współzależności cech. Umożliwiła jednocześnie zredukowanie siedmiu pierwotnych cech do trzech nowych zmiennych, które przenosiły ponad 75% informacji danych wejściowych uzyskanych dla siewu bezpośredniego i prawie 80% dla uprawy tradycyjnej. Najsilniejszą moc dyskryminacyjną, różnicującą badane obiekty, wykazały masa tysiąca ziaren i plon ziarna.
Źródło:
Acta Scientiarum Polonorum. Agricultura; 2012, 11, 1
1644-0625
Pojawia się w:
Acta Scientiarum Polonorum. Agricultura
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Association between dietary patterns and cardiovascular risk factors in a selected population of Lower Silesia (PURE Study Poland)
Autorzy:
Czekajlo, A.
Różańska, D.
Zatońska, K.
Szuba, A.
Regulska-Ilow, B.
Powiązania:
https://bibliotekanauki.pl/articles/2081935.pdf
Data publikacji:
2018
Wydawca:
Instytut Medycyny Wsi
Tematy:
risk factors
cardiovascular diseases
principal component analysis
dietary patterns
Opis:
Introduction. Dietary pattern analysis is used to describe the dietary habits of a selected population. In many studies, dietary patterns (DPs) have been associated with risk factors for cardiovascular disease (CVD). The aim of the study was to assess the association between dietary patterns identified in the population of Lower Silesia, Poland, with anthropometric and biochemical risk factors for CVD. Materials and method. The study group included 2,025 participants of the Prospective Urban Rural Epidemiological (PURE) Study. Dietary intake was evaluated based on data from the Food Frequency Questionnaire (FFQ). Dietary patterns were derived using principal component analysis (PCA). The relationship between DPs and body mass index (BMI), waist circumference, waist-hip ratio, blood pressure, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides and fasting glucose level, was assessed. Results. Three dietary patterns identified in the study explained 35.6% of total variance. The ‘fruit, vegetables & dairy’ DP, characterized by a high intake of vegetables, fruits, nuts, seeds, raisins, milk and low-fat dairy, was associated with improved lipid profile and anthropometric measures, lower diastolic blood pressure and lower fasting glucose concentration. ‘Traditional’ and ‘fat & sugar’ DPs were unfavourably associated with most of the risk factors for CVD presented in this study. Conclusions. Dietary patterns identified in this study were differently related to selected anthropometric and biochemical risk factors for CVD. ‘Fruit, vegetables & dairy’ DP was favourably associated with the biochemical and anthropometric CVD risk factors, and was characterized by higher nutritional value in comparison with ‘traditional’ and ‘fat & sugar’ DPs.
Źródło:
Annals of Agricultural and Environmental Medicine; 2018, 25, 4; 635-641
1232-1966
Pojawia się w:
Annals of Agricultural and Environmental Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal Stock Portfolio – Application of Multivariate Statistical Analysis
Optymalny portfel akcji – zastosowanie wielowymiarowej analizy statystycznej
Autorzy:
Konarzewska, Iwona
Powiązania:
https://bibliotekanauki.pl/articles/904809.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
optimal portfolio models
principal component analysis of rates of return
Opis:
Investigating relationship between risk of the Markowitz optimal portfolio and the strength of interdependence for the set of rates of return for portfolio components we state (Konarzewska, 2008, 2012) that the risk measured as variance/standard deviation is slightly sensitive on small disturbance in data set when the series of data are strongly interrelated. What more, portfolio risk rises as the strength of interdependence declines. We have found that if strong linear relationship is present among series, it is important to control the direction between the portfolio weights vector and the eigenvector corresponding to maximal eigenvalue of the correlation/covariance matrix – the ideal situation being orthogonality of the two vectors. These results can be utilized in: the algorithm for pre-selection of investment portfolio components, construction of the optimal investment portfolio models. Both propositions utilize eigenvalue decomposition of the rates of return correlation or covariance matrix. Theoretical results are illustrated by empirical examples for medium-sized firms being components of mWIG40 index on Stock Exchange in Warsaw. We compare optimal portfolios obtained for Markowitz and PCA – aided models.
W artykule przedstawiamy wybrane wyniki teoretyczne na temat konstrukcji optymalnego portfela akcji z wykorzystaniem informacji dostepnej w wyniku przeprowadzenia analizy głównych składowych macierzy kowariancji czy też macierzy korelacji stóp zwrotu z akcji. Wyniki teoretyczne prowadzą do konstrukcji modeli optymalizacyjnych uwzględniajacych redukcję przestrzeni danych do określonej liczby głównych składowych, co udaje się skutecznie przeprowadzić w warunkach silnych związków o charakterze liniowym między szeregami stóp zwrotu z akcji. W pracy prezentujemy wyniki analiz dla modeli Markowitza oraz modeli opartych o analizę głównych składowych na przykładzie sektora średnich spółek na GPW w Warszawie w latach 2009-2011. Badanie empiryczne pokazuje różnice wyników optymalizacji oraz ryzyka portfeli w przypadkach, kiedy korzystamy z macierzy kowariancji albo korelacji.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2013, 286
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Physicochemical characterization of synclinal spring water of Taoura, region of Souk Ahras – North East Algeria
Autorzy:
Bouhafs, Fatma
Laraba, Abdelaziz
Powiązania:
https://bibliotekanauki.pl/articles/1841971.pdf
Data publikacji:
2021
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
chemistry
principal component analysis
PCA
pollution
springs
Taoura
water quality
Opis:
The springs of the Taoura region flow from a syncline shaped structure. All resources in the region were mobilized as a result of increased demand. However, the development of anthropic activities and population growth in the area pose risk for groundwater. Analytical results obtained from a series of samplings in November 2017–April 2018, express the quality of water suitable for the irrigation of agricultural land. The highest values are recorded in April 2018 at 20.5 to 21.6°C and pH of 8.0 to 8.2. The study recorded high electrical conductivity from 1390 to 1495 μS∙cm–1 and TDS from 1270 to 1500 mg∙dm–3 in November 2017, which shows important mineralization that characterizes spring water. Physical parameters were measured in situ using a HORIBA multi-parameter probe. Chemical analyses were carried out using NFT 90-005 titration, and nitrogen parameters by DIN 38405-D92 spectrophotometry. Maximum levels of nitrates and phosphates were recorded at 228 and 18.4 mg∙dm–3 respectively. The principal component analysis (PCA) showed a good correlation of the November 2017 period with mineralization parameters. Moreover, there is a strong correlation between the wet period and pollution factors. The two methods of analysis has allowed to distinguish three groups of geochemical water types: a bicarbonate calcium group typical for waters having transited in carbonate horizons. A second chloride calcium group shows basic exchange between water and clay levels, and the third chloride bicarbonate calcium group reveals an enrichment in calcium and chloride, which reflects water circulation with an exchange of the carbonated and evaporitic sedimentary rock matrix.
Źródło:
Journal of Water and Land Development; 2021, 50; 27-37
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A game theoretical study of generalised trust and reciprocation in Poland. [Part] 2, A description of the study group
Autorzy:
Markowska-Przybyła, U.
Ramsey, D. M.
Powiązania:
https://bibliotekanauki.pl/articles/406286.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
Bayesian networks
principal component analysis
social survey
experimental game theory
Opis:
The first article describing this project presented the three games that the participants played: the Ultimatum Game, the Trust Game and the Public Goods Game. This article describes the study group on the basis of a questionnaire regarding where they study and come from, their social contacts, interest in current issues, views on inequality and outlook on life. A description of the migratory decisions of students is given. In particular, two exploratory methods are used to investigate the data’s structure: Bayesian networks and principal component analysis. Bayesian networks are used to illustrate the associations between categorical variables. Principal component analysis is designed to describe latent variables which reflect the associations between numerical variables. We present the results of this analysis and discuss the advantages and disadvantages of these two methods.
Źródło:
Operations Research and Decisions; 2015, 25, 2; 51-73
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal component analysis in assessment of relations to some pelleted feed characteristics
Statystyczna analiza składowych głównych w ocenie zależności wybranych cech paszy granulowanej
Autorzy:
Rynkiewicz, M.
Snieg, M.
Powiązania:
https://bibliotekanauki.pl/articles/45178.pdf
Data publikacji:
2015
Wydawca:
Zachodniopomorski Uniwersytet Technologiczny w Szczecinie. Wydawnictwo Uczelniane ZUT w Szczecinie
Źródło:
Acta Scientiarum Polonorum. Zootechnica; 2015, 14, 3
1644-0714
Pojawia się w:
Acta Scientiarum Polonorum. Zootechnica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Electronic noses for monitoring benzene occupational exposure in biological samples of Egyptian workers
Autorzy:
Mohamed, Ehab I.
Khalil, Gihane I.
Abdel-Mageed, Samir M.
Bayoumi, Amani M.
Ramadan, Heba S.
Kotb, Metwally A.
Powiązania:
https://bibliotekanauki.pl/articles/2179801.pdf
Data publikacji:
2013-03-01
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
phenol
muconic acid
exhaled air
blood
urine
principal component analysis
Opis:
Objectives: Benzene is commonly emitted in several industries, leading to widespread environmental and occupational exposure hazards. While less toxic solvents have been substituted for benzene, it is still a component of petroleum products and is a trace impurity in industrial products resulting in continued higher occupational exposures in industrial settings in developing countries. Materials and Methods: We investigated the potential use of an electronic nose (e-nose) to monitor the headspace volatiles in biological samples from benzene-exposed Egyptian workers and non-exposed controls. The study population comprised 150 non-smoking male workers exposed to benzene and an equal number of matching non-exposed controls. We determined biomarkers of benzene used to estimate exposure and risk including: benzene in exhaled air and blood; and its urinary metabolites such as phenol and muconic acid using gas chromatography technique and a portable e-nose. Results: The average benzene concentration measured in the ambient air of the workplace of all studied industrial settings in Alexandria, Egypt; was 97.56±88.12 μg/m³ (range: 4.69–260.86 μg/m³). Levels of phenol and muconic acid were signifi cantly (p < 0.001) higher in both blood and urine of benzene-exposed workers as compared to non-exposed controls. Conclusions: The e-nose technology has successfully classifi ed and distinguished benzene-exposed workers from non-exposed controls for all measured samples of blood, urine and the exhaled air with a very high degree of precision. Thus, it will be a very useful tool for the low-cost mass screening and early detection of health hazards associated with the exposure to benzene in the industry.
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2013, 26, 1; 165-172
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Alarms management by supervisory control and data acquisition system for wind turbines
Autorzy:
Ramirez, Isaac Segovia
Mohammadi-Ivatloob, Behnam
Márqueza, Fausto Pedro García
Powiązania:
https://bibliotekanauki.pl/articles/1841786.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
alarm management
maintenance management
principal component analysis
SCADA
wind turbines
Opis:
Wind energy is one of the most relevant renewable energy. A proper wind turbine maintenance management is required to ensure continuous operation and optimized maintenance costs. Larger wind turbines are being installed and they require new monitoring systems to ensure optimization, reliability and availability. Advanced analytics are employed to analyze the data and reduce false alarms, avoiding unplanned downtimes and increasing costs. Supervisory control and data acquisition system determines the condition of the wind turbine providing large dataset with different signals and alarms. This paper presents a new approach combining statistical analysis and advanced algorithm for signal processing, fault detection and diagnosis. Principal component analysis and artificial neural networks are employed to evaluate the signals and detect the alarm activation pattern. The dataset has been reduced by 93% and the performance of the neural network is incremented by 1000% in comparison with the performance of original dataset without filtering process.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 1; 110-116
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Differences between technological and textural parameters of meat from farmed and wildlife red deer (Cervus elaphus) determined by PCA method
Różnice pomiędzy parametrami technologicznymi i teksturalnymi mięsa jeleni (Cervus elaphus) hodowlanych i dziko żyjących określone metodą składowych głównych
Autorzy:
Kral, M.
Snirc, M.
Tremlova, B.
Powiązania:
https://bibliotekanauki.pl/articles/825883.pdf
Data publikacji:
2018
Wydawca:
Polskie Towarzystwo Technologów Żywności
Tematy:
farmed deer
wildlife animal
red deer
Cervus elaphus
meat
difference
technological parameter
texture parameter
determination
PCA method zob.principal component analysis
principal component analysis
Źródło:
Żywność Nauka Technologia Jakość; 2018, 25, 3
1425-6959
Pojawia się w:
Żywność Nauka Technologia Jakość
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of Principal Component Analysis and Cluster Analysis for Differentiation of Traditionally-Manufactured Vinegars Based on Phenolic and Volatile Profiles, and Antioxidant Activity
Autorzy:
Karadag, Ayse
Bozkurt, Fatih
Bekiroglu, Hatice
Sagdic, Osman
Powiązania:
https://bibliotekanauki.pl/articles/1363303.pdf
Data publikacji:
2020
Wydawca:
Instytut Rozrodu Zwierząt i Badań Żywności Polskiej Akademii Nauk w Olsztynie
Tematy:
vinegar
Antioxidant
phenolics
volatiles
OXITEST
PCA
Opis:
This study aimed to characterize twelve vinegar samples produced by the traditional method with the use of whole fruits and without any preservatives in terms of their physicochemical properties, total phenolic content (TPC), total flavonoid content (TFC), phenolic compound profiles, antioxidant activity (DPPH• scavenging activity, FRAP, CUPRAC), and volatile compositions, as well as their abilities to delay oxidation in mayonnaise. Types of raw material significantly affected all of the above parameters (p<0.05). Gallic acid, protocatechuic acid, and caffeic acid were detected as the major phenolic acids in all vinegar samples. Among, flavonoids, rutin, and kaempferol were also identified. The major volatiles belonged to acetic acid esters and alcohol groups, and isoamyl acetate was determined in all vinegar samples at changing ratios. The high positive correlation coefficient (r>0.70) was determined between DPPH• scavenging activity of vinegars and induction period of accelerating oxidation based on the OXITEST of mayonnaises produced with these vinegars. Vinegar types significantly affected the oxidative stability of mayonnaise (p<0.05). Furthermore, it was demonstrated that vinegar samples could be clearly discriminated by principal component and cluster analyses. This study suggests that fruit type should be considered as a crucial factor in the production of vinegars affecting not only sensory properties but also their physicochemical and bioactive properties.
Źródło:
Polish Journal of Food and Nutrition Sciences; 2020, 70, 4; 347-360
1230-0322
2083-6007
Pojawia się w:
Polish Journal of Food and Nutrition Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for detecting cross-inhibition effects in the environmental biocatalytic processes
Autorzy:
Herke, Z.
Maskow, T.
Nemeth, Z.I.
Powiązania:
https://bibliotekanauki.pl/articles/80851.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
biocatalysis
microorganism
enzyme
bioremediation
inhibition
modelling
regression analysis
principal component analysis
Źródło:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology; 2015, 96, 4
0860-7796
Pojawia się w:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Factors of the development of organic farming in Poland at the voivodship level
Autorzy:
Nowak, Ewa
Jadczyszyn, Jan
Powiązania:
https://bibliotekanauki.pl/articles/2148092.pdf
Data publikacji:
2020-12-30
Wydawca:
Instytut Uprawy Nawożenia i Gleboznawstwa – Państwowy Instytut Badawczy
Tematy:
organic farming
Rural Development Program
Principal component analysis – PCA
voivodships
Polska
Opis:
The purpose of the research based on the data from the Report on the state of organic farming in Poland in 2015–2016 and environmental conditions, was to determine the impact of natural and economic factors and subsidies from EU programs on the level of organic production and to better understand the diver-sity of the spatial structure of organic farming within the system of provinces (voivodships). Nineteen structural, socio-economic and financial features, and 3 environmental features that charac-terize the quality of agricultural production and forms of nature protection for 16 voivodships, were used as assessment criteria.Principal component analysis allowed the basic factors of diver-sification to be discovered of the set of voivodships contained in the hidden structure defined by the features adopted for analysis. Homogeneous groups – organic farming types by voivodships were distinguished using the k-means method.The comparative analysis allowed the connections between the structure of organic farming and its place in voivodships to be highlighted in connection with support for organic farming, the number of producers of organic agricultural products, production of feed on arable land, production of cereals and vegetables. The location of organic farms is related to the occurrence of Natura 2000 areas. The first type includes two voivodships, Zachodnio-pomorskie and Warmińsko-Mazurskie – with the highest level of development of organic farming. In the second type, the fol-lowing voivodships were concentrated: Lubelskie, Łódzkie, Ma-zowieckie, Podlaskie and Świętokrzyskie, with a high level of or-ganic farming, where farms smaller in area, that focus on fruit and vegetable production are the predominant type. In the third type, the following voivodships were located in the region of western Poland: Pomorskie and Wielkopolskie with a medium level of organic farming and very diverse in characteristics, including the largest and smaller organic farms with a low level of fruit and vegetable production. The fourth type includes the Małopolskie and Podkarpackie voivodships with a very small farm area and a small number of producers. In the fifth type with the least developed organic farming with a small number of producers and low fruit and vegetable production, three voivodships focused on the average farm area: Śląskie, Opolskie and Kujawsko-Pomorskie.
Źródło:
Polish Journal of Agronomy; 2020, 43; 43-46
2081-2787
Pojawia się w:
Polish Journal of Agronomy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Trace elements in scalp hair of leukaemia patients
Autorzy:
Khuder, A.
Bakir, M. A.
Hasan, R.
Mohammad, A.
Habil, K.
Powiązania:
https://bibliotekanauki.pl/articles/971518.pdf
Data publikacji:
2014
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
leukaemia
principal component analysis
scalp hair
U-test
X-ray fluorescence
Opis:
The aim of this study was to determine the concentration of Fe, Ni, Cu, Zn and Pb in scalp hair of leukaemia patients and healthy volunteers, using the optimised XRF method. Leukaemia hair samples were classifi ed corresponding to type, growth and age of the participants. The results showed that the studied trace elements (TEs) in both of leukaemia and control groups were positively skewed. In comparison with the control group, lower Fe, Cu, Zn and Pb and higher of Ni medians were found in all studied leukaemia patients. The median rank obtained by Mann–Whitney U-test revealed insignifi cant differences between the leukaemia patients subgroups and the controls. An exact probability (α < 0.05) associated with the U-test showed signifi cant differences between medians in leukaemia patients and controls groups for Pb (lymphatic/control, acute/control), Cu (lymphatic/control, chronic/control), Ni (lymphatic/control, chronic/control) and Fe (chronic/control). Very strong positive and negative correlations (r > 0.70) in the scalp hair of control group were observed between Ni/Fe-Ni, Cu/Fe-Cu, Zn/Fe-Zn, Pb/Fe-Pb, Cu/Ni-Zn/Ni, Cu/Ni-Pb/Ni, Zn/Ni-Pb/Ni, Zn/Fe-Zn/Cu, Pb/Ni-Ni and Ni/Fe-Pb/Ni, whereas only very strong positive ratios in the scalp hair of leukaemia patients group were observed between Ni/Fe-Ni, Cu/Fe-Cu, Zn/Fe-Zn and Pb/Fe-Pb, all correlations were signifi cant at p < 0.05. Other strong and signifi cant correlations were also observed in scalp hair of both groups. Signifi cant differences between grouping of studied TEs in all classifi ed leukaemia groups and controls were found using principal component analysis (PCA). The results of PCA confi rmed that the type and the growth of leukaemia factors were more important in element loading than the age factor.
Źródło:
Nukleonika; 2014, 59, 3; 111-120
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault diagnosis of rotating machines using vibration and bearing temperature measurements
Autorzy:
Nembhard, A. D.
Sinha, J. K.
Pinkerton, A. J.
Elbhbah, K.
Powiązania:
https://bibliotekanauki.pl/articles/328481.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
vibration monitoring
condition monitoring
rotating machinery
fault diagnosis
principal component analysis
Opis:
Acquisition and subsequent processing of vibration data for fault diagnosis of rotating machinery with multiple bearings, such as Turbo-generator (TG) sets, can be quite involved, as data are usually required in three mutually perpendicular directions for reliable diagnosis. Consequently, the task of diagnosing faults on such systems may be daunting for even an experienced analyst. Hence, the current study aims to develop a simplified fault diagnosis (FD) method that uses just a single vibration and a single temperature sensor on each bearing. Initial trials on an experimental rotating rig indicate that supplementing vibration data with temperature measurements gave improved FD when compared with FD using vibration data alone. Observations made from the initial trials are presented in this paper.
Źródło:
Diagnostyka; 2013, 14, 3; 45-51
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of evaluation algorithm for port logistics park based on PCA-SVM model
Autorzy:
Hu, B.
Powiązania:
https://bibliotekanauki.pl/articles/260528.pdf
Data publikacji:
2018
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
port logistics demand
support vector machine
principal component analysis
economic hinterland
Opis:
To predict the logistics needs of the port, an evaluation algorithm for the port logistics park based on the PCASVM model was proposed. First, a quantitative indicator set for port logistics demand analysis was established. Then, based on the grey correlation analysis method, the specific indicator set of port logistics demand analysis was selected. The advantages of both principal component analysis and support vector machine algorithms were combined. The PCA-SVM model was constructed as a predictive model of the port logistics demand scale. The empirical analysis was conducted. Finally, from the perspective of the structure, demand, flow pattern and scale of port logistics demand, the future logistics demand of Shenzhen port was analysed. Through sensitivity analysis, the main influencing factors were found out, and the future development proposals of Shenzhen port were put forward. The results showed that the port throughput of Shenzhen City in 2016 was 21,328,200 tons. Compared with the previous year, it decreased by about 1.74 %. In summary, the PCA-SVM model accurately predicts the logistics needs of the port.
Źródło:
Polish Maritime Research; 2018, S 3; 29-35
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multivariate and Geostatistical Analyses of Groundwater Quality for Acid Rock Drainage at Waste Rock and Tailings Storage Site
Autorzy:
Adadzi, Patrick
Allwright, Amy
Fourie, Francois
Powiązania:
https://bibliotekanauki.pl/articles/2202307.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
acid rock drainage
groundwater
correlation matrix
principal component analysis
geostatistical analysis
Opis:
A multi-disciplinary approach is indispensable for adequate acid rock drainage (ARD), mineral leaching impact, and groundwater management. Groundwater is a valuable resource, and it is critical to protect as well as mitigate the effects of pollution such as ARD in the mining environment. Mine waste storage facilities (waste rocks and tailings) are potential ARD sources capable of degrading groundwater reserves. This research investigated and reported the application of a case study of multivariate statistical and spatial variability of selected parameters associated with ARD in groundwater around WRD and TSF at mine sites. Water quality analysis data of seventy water samples from 10 boreholes located at the WRD and TSF mine were utilised in this study. The correlation matrix and principal components analysis was applied to the data set to determine the associated variability in groundwater in relation to ARD. Geostatistical analysis was used to produce contour maps to ARD principal components of the study site, using ordinary kriging of the best fit models. The application of multivariate statistical and geospatial analysis in groundwater quality assessment with coupled soil and groundwater modelling of flow and transport at waste rock dump and tailings storage sites provides an essential tool for exploratory data analysis, and spatial extent determination of the relationship between various data sets significant to acid rock drainage.
Źródło:
Journal of Ecological Engineering; 2022, 23, 12; 203--216
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting of subjective comfort in tram using ordinal logistic regression and manifold learning
Autorzy:
Pietraszek, J.
Grzegożek, W.
Szczygieł, J.
Powiązania:
https://bibliotekanauki.pl/articles/246634.pdf
Data publikacji:
2012
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
rail transport
vibrations
ordinal logistic regression
principal component analysis
manifold learning
Opis:
Comfort in a vehicle has a very important role to play as one of the most important dynamic performance characteristics of rail vehicles. It is the factor of ever-increasing importance, even creating a specialized branch of engineering associated with relation between human limitations and designing of machines: human–factors engineering. The vibration is known to be a major factor that affects and deteriorates ride comfort. For evaluating ride comfort in rail vehicles, there have been developed methods resulting in the creation of many standards and multiple criteria used and even standardized in different countries. One of the authors, J. Szczygieł designed and performed a passive experiment to collect data describing physical conditions of ride and associated subjective assessments of comfort. Panel of fourteen people during the tram ride made synchronous subjective assessments of comfort, assessing it on a discrete ordinal scale of 0 to 5, using electronic panels connected to the computer. At the same time computer through sensors recorded values of acceleration in three perpendicular axes. It made possible to correlate the fuzzy subjective evaluations with objective physical measurements. Because of the discrete type of fuzzy ratings of comfort, natural way of modelling is the ordinal logistic regression. The classic form of the ordinal logistic regression assumes that in the space of explanatory factors there are parallel activation hyper-planes slightly disturbed by unknown or uncontrolled noise factors. In fact, the assumption of linearity is a very strong idealization and leads to considerable misclassifications. The original space of explanatory factors is 11-dimensional with ten continuous dimensions and one discrete. Then the multivariate method, principal component analysis (PCA), was used to identify principal components, which are responsible most to the variability of the studied set. The scree plot was used to identify the number of significant PCA factors. The use of PCA revealed that the area occupied by the data set is approximately 6-dimensional. However, the dimensionality reduction of explanatory variables set did not lead to better forecasting accuracy. A more subtle analysis involving discretization techniques showed that activation hyperplanes are highly curved in the six-dimensional area identified by PCA but their dimensionality is much lower. The details of the procedure are described in the article. The article conclusion is that is necessary to introduce curvilinear coordinate system embedded into the shapes of activation hyper-planes to obtain better classification.
Źródło:
Journal of KONES; 2012, 19, 2; 403-409
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Elucidation of tidal spatial-temporal variation of physico-chemical and nutrient parameters of estuarine water at South Gujarat
Autorzy:
Desai, Nisheeth C.
Kukadiya, Nipul B.
Mehta1, Jignasu P.
Godhani, Dinesh R.
Lakhmapurkar, Jayendra
Dave, Bharti P.
Powiązania:
https://bibliotekanauki.pl/articles/1030123.pdf
Data publikacji:
2020
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Estuary water
Nutrients
Physico-chemical parameters
Principal component analysis
Tidal variation
Opis:
In the present study, the four estuaries were selected from the South Gujarat region to appraise the impact of industrial pollution in the estuarine water samples. The study focused on the tidal variation of nutrients, which disclosed that concentrations of NO2–N, NO3–N, NH4–N, TN, and reactive silicates were higher in low-tide whereas pH, salinity, and dissolved oxygen were higher in high-tide water samples. The results of high BOD and low DO expose the anthropogenic inputs in these estuaries during the low-tide. The results of physico-chemical and nutrients parameters of water showed that the pollution level is strongly influenced by tidal and seasonal changes. Pearson’s correlation matrix and principal component analysis (PCA) are applied to a hydrological and hydrographical dataset for finding the spatial-temporal variation during the tidal difference. This study suggested that there is an impact of industrial pollution and anthropogenic inputs on the estuarine water of the study area.
Źródło:
World Scientific News; 2020, 143; 79-102
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of modern methods for increasing and managing the financial prosperity of businesses in the context of performance: a case study of the tourism sector in Slovakia
Autorzy:
Onuferová, Erika
Čabinová, Veronika
Dzurov Vargová, Tünde
Powiązania:
https://bibliotekanauki.pl/articles/19233492.pdf
Data publikacji:
2020
Wydawca:
Instytut Badań Gospodarczych
Tematy:
business performance
modern methods
performance benchmarking
travel agencies
Principal Component Analysis
Opis:
Research background: In the context of constantly changing business environment, the financial sector is focusing on new trends in financial management systems. Nowadays, there is a need to achieve long-term financial growth, so financial managers try to develop new models for managing and improving the financial performance of businesses in economic practice. Purpose of the article: This article aims to determine the financial performance of travel agencies by applying modern business performance evaluation methods in order to create a performance portfolio (ranking) for the years 2013-2017, subsequently to reveal the concordance rate of order of the selected business entities by comparing applied financial methods in the context of performance benchmarking. The research question is as follows: Does the multidimensional PCA method in the form of the performance portfolio of travel agencies provide similar financial results compared to the EVA indicator? Methods: For measuring the financial performance of businesses, the method of Principal Component Analysis (PCA) and the indicator Economic Value Added (EVA) were chosen. Spearman's rank-order correlation was applied in order to reveal the concordance rate of the analyzed travel agencies. Findings & Value added: The results indicate that by applying the PCA method, 6 key performance factors can be identified. Moreover, the findings revealed that the assessment of travel agencies using the PCA method and EVA indicator did not lead to the same financial results. Individual financial methods identified a different number of strong-performing and inefficient business entities. In this backdrop, we concluded that the business performance measurement based on the PCA method is not a suitable alternative to measuring performance using the EVA indicator.
Źródło:
Oeconomia Copernicana; 2020, 11, 1; 95-116
2083-1277
Pojawia się w:
Oeconomia Copernicana
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Interrelationship and Determining Factors of Water Quality Dynamics in Whiteleg Shrimp Ponds in Tropical Eco-Green Aquaculture System
Autorzy:
Musa, Muhammad
Mahmudi, Mohammad
Arsad, Sulastri
Lusiana, Evellin Dewi
Sunadji
Wardana, Wisnu Angga
Ompusunggu, Magdalena Florensia
Damayanti, Dhea Novita
Powiązania:
https://bibliotekanauki.pl/articles/2202326.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
aquaculture wastewater
intensive system
Litopenaeus vannamei
mangrove
PCA
principal component analysis
Opis:
Whiteleg shrimp (Litopenaeus vannamei) farming is a major activity in the coastal areas of many tropical countries. To meet the demand in this market, the culture system has expanded using intensive technology, which has resulted in the emission of effluents that threaten the surrounding aquatic ecosystem. Therefore, proper aquaculture management is needed to ensure both economic and ecological benefits. This led to the emergence of eco-green aquaculture. Water quality monitoring is a critical part of aquaculture management and when performed regularly, it yields a large and complex dataset. In this study, the authors aimed to analyse the dynamics of water quality characteristics and the relationships between these variables in whiteleg shrimp ponds in a tropical eco-green aquaculture system from 2020 to 2022. Since the data includes nine parameters and is quite complex, the principal component analysis (PCA) approach was used. This method enables to identify the factors that determine water quality, which will help ensure effective and efficient aquaculture management. Consequently, the water quality variables in the studied area were reduced to five dimensions and salinity, ammonia, and pH were found to be the key factors responsible for the changes in water quality characteristics. Hence, these variables should be the focus of farming management systems.
Źródło:
Journal of Ecological Engineering; 2023, 24, 1; 19--27
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adult Participation in Evening Secondary Schools: The Findings of Empirical Research in the Greek Islands
Autorzy:
Papadimitriou, Achilleas
Powiązania:
https://bibliotekanauki.pl/articles/28409259.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Dolnośląski DSW. Wydawnictwo Naukowe DSW
Tematy:
adult participation
evening schools
Greek islands
quantitative research
principal component analysis
Opis:
The study of adult participation in education and the examination of the factors that influence their final decision is one of the most critical issues in the field. This article summarises the findings of empirical research on adult engagement in evening schools in Greece, with an emphasis on evening schools in the Greek islands. Evening schools started in Greece around 60 years ago. These schools, now part of the secondary education system, are primarily aimed towards those who work during the day (mostly adults). Their goal is to provide the opportunity for adults who, for some reason, interrupted their studies in Gymnasium (lower secondary/middle school) or Lyceum (upper secondary/high school) to complete it. There has never been a study on residents of Greek islands who participate in educational programmes of this nature. The presented research investigates factors that impact adult participation in all evening schools administratively situated in Greek islands. Between February and May 2022, 268 adult students participated in the study by completing a survey questionnaire that was quantitatively evaluated using SPSSs. The sample comes from all the islands where evening Lyceums operate. To determine the elements that influence participation, the data was submitted to component analysis using the Principal Component Analysis (PCA) approach. Four of the discovered factors are deemed critical (self-assessment, attitudes towards education, educational perspective and expectations), while others seem somewhat relevant and have a role.
Źródło:
Teraźniejszość – Człowiek – Edukacja; 2023, 25, 1(93); 9-32
1505-8808
2450-3428
Pojawia się w:
Teraźniejszość – Człowiek – Edukacja
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie analizy glownych skladowych do opisu konsumenckiej struktury jakosci jablek
The application of principal component analysis to characterize a consumer structure of apple quality
Autorzy:
Czernyszewicz, E
Powiązania:
https://bibliotekanauki.pl/articles/826536.pdf
Data publikacji:
2008
Wydawca:
Polskie Towarzystwo Technologów Żywności
Tematy:
Polska
owoce
jablka
spozycie zywnosci
jakosc
wyrozniki jakosci
przechowywanie
jedrnosc miazszu
soczystosc
smakowitosc
cechy odmianowe
konsumenci
preferencje konsumentow
Opis:
W pracy przedstawiono preferencje konsumentów lubelskich w zakresie cech wpływających na jakość jabłek. Do opisu preferencji zastosowano metodę analizy głównych składowych. Stwierdzono, że preferencje dotyczą głównie dwóch grup cech obejmujących charakterystyki związane z wyglądem zewnętrznym oraz przechowywaniem owoców, a ponadto z cechami odmianowymi, takim jak: smak oraz jędrność i soczystość miąższu. Analiza pozwoliła również zidentyfikować różnice w preferencjach kobiet i mężczyzn. Stwierdzono, że wielkość jabłek i odmiana różnicują preferencje kobiet i mężczyzn w niewielkim stopniu.
In the paper, the preferences were presented of consumers in a city of Lublin regarding properties impacting the quality of apples. A ‘PCA’ method (Principal Component Analysis) was used to describe the preferences studied. It was found that those preferences mainly referred to two groups of properties connected with the external appearance of the fruit and the method of storing them; moreover, they also covered the characteristics of cultivars, such as: taste, firmness, and juiciness of parenchyma. With this Analysis applied, it was also possible to identify differences in the preferences of women and men. It was found that the size of apples and their cultivar only insignificantly differentiated the preferences of women and men.
Źródło:
Żywność Nauka Technologia Jakość; 2008, 15, 2; 119-127
1425-6959
Pojawia się w:
Żywność Nauka Technologia Jakość
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An identification source of variation on the water quality pattern in the Malacca River basin using chemometric approach
Autorzy:
Hua, A. K.
Powiązania:
https://bibliotekanauki.pl/articles/204612.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hierarchical cluster analysis
discriminant analysis
principal component analysis
multiple linear
regression analysis
Opis:
The Malacca River basin experienced river water pollution which caused a major deterioration to the ecosystems and environmental health. This study is carried out to assess the water quality data and identify the pattern of water pollution sources in the study area, and also to develop a predictive performance of water quality in the Malacca River basin. A chemometric approach using a combination of HCA, DA, PCA, and MLR, was applied into twenty water quality variables from nine sampling stations that were collected from January until December of 2015 in the river basin. HCA pointed out three clusters, namely Cluster 1 (C1) with low pollution source, Cluster 2 (C2) with moderate pollution source, and Cluster 3 (C3) with high pollution source. In the DA analysis, the results showed 21 variables, 12 variables, and 9 variables for standard mode, forward stepwise mode, and backward stepwise mode, respectively. Meanwhile, the PCA indicated that the main source of pollutants is detected from residential, industrial, commercial, agricultural, animal livestock, as well as forest land. Among the three models developed from MLR analysis, C3 with a high pollution source is detected to be the most suitable model to be used for the prediction of Water Quality Index in the Malacca River basin. This study proposed for an effective river water quality management by having new water quality monitoring network to be designed for more practical use in order to reduce time and effort, as well as cost saving purposes.
Źródło:
Archives of Environmental Protection; 2018, 44, 4; 111-122
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Music Recommendation System
Autorzy:
Hoffmann, P.
Kaczmarek, A.
Spaleniak, P.
Kostek, B.
Powiązania:
https://bibliotekanauki.pl/articles/308747.pdf
Data publikacji:
2014
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
feature vectors
music classification
music information retrieval
music parametrization
principal component analysis
Opis:
The paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music files. They are assigned to 22 classes corresponding to different music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments are shown for the variety of feature vectors. Also, a music recommendation system is presented along with its main user interfaces.
Źródło:
Journal of Telecommunications and Information Technology; 2014, 2; 59-69
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A comparative analysis of the principal component method and parallel analysis in working with official statistical data
Autorzy:
Holubova, Halyna
Powiązania:
https://bibliotekanauki.pl/articles/10559806.pdf
Data publikacji:
2023-02-24
Wydawca:
Główny Urząd Statystyczny
Tematy:
principal components
principal component analysis
factor analysis
Kaiser criterion
рarallel analysis
simulation
Opis:
The dynamic development of the digitized society generates large-scale information data flows. Therefore, data need to be compressed in a way allowing its content to remain complete and informative. In order for the above to be achieved, it is advisable to use the principal component method whose main task is to reduce the dimension of multidimensional space with a minimal loss of information. The article describes the basic conceptual approaches to the definition of principle components. Moreover, the methodological principles of selecting the main components are presented. Among the many ways to select principle components, the easiest way is selecting the first k-number of components with the largest eigenvalues or to determine the percentage of the total variance explained by each component. Many statistical data packages often use the Kaiser method for this purpose. However, this method fails to take into account the fact that when dealing with random data (noise), it is possible to identify components with eigenvalues greater than one, or in other words, to select redundant components. We conclude that when selecting the main components, the classical mechanisms should be used with caution. The Parallel analysis method uses multiple data simulations to overcome the problem of random errors. This method assumes that the components of real data must have greater eigenvalues than the parallel components derived from simulated data which have the same sample size and design, variance and number of variables. A comparative analysis of the eigenvalues was performed by means of two methods: the Kaiser criterion and the parallel Horn analysis on the example of several data sets. The study shows that the method of parallel analysis produces more valid results with actual data sets. We believe that the main advantage of Parallel analysis is its ability to model the process of selecting the required number of main components by determining the point at which they cannot be distinguished from those generated by simulated noise.
Źródło:
Statistics in Transition new series; 2023, 24, 1; 199-212
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting Yield Curves in an Adaptive Framework
Autorzy:
Chen, Ying
Li, Bo
Powiązania:
https://bibliotekanauki.pl/articles/483285.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
interest rates
functional principal component analysis
local parametric model
Nelson-Siegel model
Opis:
Forecasting yield curves with regime switches is important in academia and financial industry. As the number of interest rate maturities increases, it poses difficulties in estimating parameters due to the curse of dimensionality. To deal with such a feature, factor models have been developed. However, the existing approaches are restrictive and largely based on the stationarity assumption of the factors. This inaccuracy creates non-ignorable financial risks, especially when the market is volatile. In this paper, a new methodology is proposed to adaptively forecast yield curves. Specifically, functional principal component analysis (FPCA) is used to extract factors capable of representing the features of yield curves. The local AR(1) model with time-dependent parameters is used to forecast each factor. Simulation and empirical studies reveal the superiority of this method over its natural competitor, the dynamic Nelson-Siegel (DNS) model. For the yield curves of the U.S. and China, the adaptive method provides more accurate 6- and 12-month ahead forecasts.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2011, 3, 4; 237-259
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the potential for using selected PCA-based methods to analyze the crime rate in Poland
Autorzy:
Misztal, Małgorzata
Powiązania:
https://bibliotekanauki.pl/articles/424843.pdf
Data publikacji:
2019
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
crime
criminal offence
multivariate exploratory data analysis
principal component analysis
factorial maps
Opis:
The aim of the paper is to assess the potential for using some selected PCA-based methods to analyze the spatial diversity of crime in Poland during 2000-2017. Classical principal components analysis (PCA) deals with two-way matrices, usually taking into account objects and variables. In the case of data analyzed in the study, apart from two dimensions (objects – voivodships, variables – criminal offences), there is also the dimension of time, so the dataset can be seen as data cube: objects × variables × time. Therefore, this type of data requires the use of methods handling three-way data structures. In the paper the variability of some selected categories of criminal offences in time (2000- -2017) and space (according to voivodships) is analyzed using the between-class and the within-class principal component analysis. The advantage of these methods is, among others, the possibility of the graphical presentation of the results in two-dimensional space with the use of factorial maps.
Źródło:
Econometrics. Ekonometria. Advances in Applied Data Analytics; 2019, 23, 2; 15-32
1507-3866
Pojawia się w:
Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stylistyka ceramiki grupy wschodniej kultury amfor kulistych – ujęcie strukturalne
Pottery style of the eastern group of the Globular Amphora culture – structural analysis
Autorzy:
Sieradzka, Elżbieta
Powiązania:
https://bibliotekanauki.pl/articles/567563.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Rzeszowski. Instytut Archeologii Uniwersytetu Rzeszowskiego. Muzeum Okręgowe w Rzeszowie
Tematy:
Globular Amphora culture
pottery style
statistical analysis
principal component analysis
network analysis
Opis:
In the classical approach presented by Marzena Szmyt, statistical analysis of the ceramic style of the eastern group of Globular Amphora Culture was based on detailed classification of ornaments and their co-occurrence within grave inventories. This paper introduces an alternative proposition, focusing on structural analysis of decoration of vessels. Additionally, in order to show the distribution of stylistic features among the graves, some elements of the network analysis were implemented.
Źródło:
Materiały i Sprawozdania Rzeszowskiego Ośrodka Archeologicznego; 2017, 38; 13-26
0137-5725
Pojawia się w:
Materiały i Sprawozdania Rzeszowskiego Ośrodka Archeologicznego
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecast of prices and volatility on the day ahead market
Autorzy:
Ganczarek-Gamrot, Alicja
Powiązania:
https://bibliotekanauki.pl/articles/425278.pdf
Data publikacji:
2013
Wydawca:
Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:
principal component analysis (PCA)
SARIMA model
DCC model
Value-at- -Risk
portfolio
Opis:
The subject of this paper is the forecast of prices and volatility on the Day Ahead Market (DAM). The analysis was made for two portfolios of four contracts from 30.03.2009 to 28.10.2011 for two fixings on DAM. Four out of 24 contracts noted on DAM were chosen by PCA. Prices were forecast by the SARIMA models incorporating autocorrelation and seasonality. Value-at-Risk calculated through the DCC model was used to forecast volatility. These models describe well the prices and volatility on the DAM and may be used for forecasting purposes. Prices on fixing 2 are characterized by higher volatility than prices on fixing 1.
Źródło:
Econometrics. Ekonometria. Advances in Applied Data Analytics; 2013, 1(39); 111-120
1507-3866
Pojawia się w:
Econometrics. Ekonometria. Advances in Applied Data Analytics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using chemometrics to identify water quality in Daya Bay, China
Autorzy:
Wu, M.-L.
Wang, Y.-S.
Sun, C.-C.
Wang, H.
Lou, Z.-P.
Dong, J.-D.
Powiązania:
https://bibliotekanauki.pl/articles/49096.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
robust principal component analysis
water quality
chemometrics
China
cluster analysis
Daya Bay
Opis:
In this paper, chemometric approaches based on cluster analysis, classical and robust principal component analysis were employed to identify water quality in Daya Bay (DYB), China. The results show that these approaches divided water quality in DYB into two groups: stations S3, S8, S10 and S11 belong to cluster A, which lie in Dapeng Cove, Aotou Harbor and the north-eastern part of DYB, where water quality is related mainly to anthropogenic activities. The other stations belong to cluster B, which lie in the southern, central and eastern parts of DYB, where the quality is related mainly to water exchange with the South China Sea. Cluster analysis yields good results as a first exploratory method for evaluating spatial difference, but it fails to demonstrate the relationship between variables and environmental quality on the one hand and the untreated data on the other. However, with the aid of suitable chemometric approaches, the relationship between samples or variables can be investigated. Classical and robust principal component analysis can provide a visual aid for identifying the water environment in DYB, and then extracting specific information about relationships between variables and spatial variation trends in water quality.
Źródło:
Oceanologia; 2009, 51, 2; 217-232
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent Prediction Model of the Thermal and Moisture Comfort of the Skin-Tight Garment
Autorzy:
Cheng, Pengpeng
Wang, Jianping
Zeng, Xianyi
Bruniaux, Pascal
Chen, Daoling
Powiązania:
https://bibliotekanauki.pl/articles/2056304.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Tematy:
sportswear tights
thermal comfort
moisture comfort
principal component analysis
intelligent prediction model
Opis:
In order to improve the efficiency and accuracy of predicting the thermal and moisture comfort of skin-tight clothing (also called skin-tight underwear), principal component analysis (PCA) is used to reduce the dimensions of related variables and eliminate the multicollinearity relationship among variables. Then, the optimized variables are used as the input parameters of the coupled intelligent model of the genetic algorithm (GA) and back propagation (BP) neural network, and the thermal and moisture comfort of different tights (tight tops and tight trousers) under different sports conditions is analysed. At the same time, in order to verify the superiority of the genetic algorithm and BP neural network intelligent model, the prediction results of GA-BP, PCA-BP and BP are compared with this model. The results show that principal component analysis (PCA) improves the accuracy and adaptability of the GA-BP neural network in predicting thermal and humidity comfort. The forecasting effect of the PCA-GA-BP neural network is obviously better than that of the GA-BP, PCA-BP, BP model, which can accurately predict the thermal and moisture comfort of tight-fitting sportswear. The model has better forecasting accuracy and a simpler structure.
Źródło:
Fibres & Textiles in Eastern Europe; 2022, 1 (151); 50--58
1230-3666
2300-7354
Pojawia się w:
Fibres & Textiles in Eastern Europe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wielocechowa analiza różnorodności fenotypowej mieszańców ziemniaka uzyskanych z krzyżowań tetraploid × diploid
Multivariate analysis of phenotypic diversity in the tetraploid × diploid hybrid progenies of potatoes
Autorzy:
Domański, Leszek
Mańkowski, Dariusz R.
Flis, Bogdan
Jakuczun, Henryka
Zimnoch-Guzowska, Ewa
Powiązania:
https://bibliotekanauki.pl/articles/2198318.pdf
Data publikacji:
2012-06-28
Wydawca:
Instytut Hodowli i Aklimatyzacji Roślin
Tematy:
analiza składowych głównych
zmienność wielocechowa
ziemniak
multivariable variation
potato
principal component analysis
Opis:
Osiemdziesiąt rodów ziemniaka uzyskanych z czterech interploidalnych krzyżowań 4x-2x zostało ocenione na 12 cech użytkowych, w tym morfologii bulw, w Instytucie Hodowli i Aklimatyzacji Roślin, Oddział Młochów w latach 2008–2009. Celem badań była ocena genotypowej różnorodności wśród rodów ziemniaka i uzyskanie wglądu w strukturę wielocechowej zmienności. Analiza składowych głównych (PCA) wyodrębniła pięć składowych głównych, które wyjaśniały 78,4% łącznej wariancji wśród rodów ziemniaka. Wykazana przez analizę PCA genotypowa różnorodność potomstwa 4x-2x daje szansę na wyselekcjonowanie wartościowych tetraploidalnych rodów zarówno na jadalny, jak i przetwórczy kierunek użytkowania. Spośród wyodrębnionych pięciu składowych głównych pierwsze trzy były najważniejsze. Pierwsza składowa (29,9% zmienności) była głównie skorelowana z regularnością kształtu, głębokością oczek i ciemnieniem enzymatycznym. Druga składowa, tłumacząca 16% łącznej zmienności była dodatnio skorelowana z plonem bulw, średnią masą bulwy i spłaszczeniem bulw. Trzecia składowa, wyjaśniająca 13,2% łącznej zmienności była pozytywnie skorelowana z zawartością skrobi i barwą chipsów.
Eighty potato clones derived from interploid crosses 4x-2x were evaluated for 12 tuber morphological and agronomic traits at the Plant Breeding and Acclimatization Institute — National Research Institute, Research Center Młochów during 2008–2009. The objective of the research was to assess the genotypic diversity among potato clones and to gain insight into the structure of multivariable variation. The principal component analysis (PCA) distinguished five principle components which explained 78.4% of the total variance among potato clones. The demonstrated genotypic diversity of 4x-2x progenies gives the chance for selecting valuable tetraploid clones for both table and processing use. Out of five PCs, the first three were the most important. The first PC (29.9% of total variance) was mostly correlated with shape regularity, depth of eyes and enzymatic browning. The second PC, that explained 16.2% of the total variance, was positively correlated with tuber yield, mean tuber weight and tuber flatness. The third PC explaining 13.2% of the total variance was positively correlated with starch content and chip colour.
Źródło:
Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin; 2012, 264; 189-194
0373-7837
2657-8913
Pojawia się w:
Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Multivariate Technique to Develop Hybrid Water Quality Index of the Bengawan Solo River, Indonesia
Autorzy:
Lusiana, Evellin Dewi
Mahmudi, Mohammad
Hutahaean, Sarah Mega
Darmawan, Arief
Buwono, Nanik Retno
Arsad, Sulastri
Musa, Muhammad
Powiązania:
https://bibliotekanauki.pl/articles/2026733.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
principal component analysis
WQI
water quality index
variable selection
water quality assessment
Opis:
Surface water resource, such as river, is constantly contaminated by domestic and industrial pollutants. In order to properly manage the water resource, a composite index for water quality assessment, such as water quality index (WQI), has been designed to monitor and evaluate the properties of surface water. However, this index is quite subjective in terms of determination of relative weights. A principal component analysis (PCA) can be used to reduce the dimension and subjectivity of water quality variables. The purpose of this study was to implement the use of hybrid PCA and WQI methods to assess and monitor the water quality of the Bengawan Solo River, which is located in Java Island, Indonesia. The result suggested that COD, BOD, TSS, TDS, nitrate, nitrite, and ammonia were the main factors that determine water quality of the Bengawan Solo River. Furthermore, it was revealed that most samples from the river showed water quality status as slightly polluted. In addition to this, the seasonal variation of the PCWI values indicated a significant increase of water pollution in the Bengawan Solo River per year.
Źródło:
Journal of Ecological Engineering; 2022, 23, 2; 123-131
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Major, minor, and trace elements in whole blood of patients with different leukemia patterns
Autorzy:
Khuder, A.
Bakir, M. A.
Solaiman, A.
Issa, H.
Habil, K.
Mohammad, A.
Powiązania:
https://bibliotekanauki.pl/articles/146612.pdf
Data publikacji:
2012
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
leukemia
principal component analysis
Student's t test
whole blood
X-ray fluorescence
Opis:
The elemental sensitivity method for X-ray fluorescence analysis was applied to determine S, Cl, K, Ca, Fe, Cu, Zn, Br, and Rb in the whole blood of leukemia patients and healthy volunteers. Leukemia samples were classified according to type, growth, and age of participants. Student’s t-test results showed that, the mean concentration of the studied elements was significantly lower in leukemia patients than that in controls. Strong mutual correlations (r greather than 0.50) in the whole blood of leukemia patients were observed between S-Ca, K-Fe, K-Ca, Fe-Zn, K-Zn, K-Rb, Fe-Rb, Zn-Rb, S-Cl, S-K, Ca-Fe, Cl-Ca, and Ca-Rb; whereas, S-K, S-Ca, S-Cl, Cl-K, Cl-Ca, Fe-Zn, Zn-Rb, Fe-Rb, K-Fe, and Zn-Br exhibited strong relationships (r greather than 0.50) in the whole blood of controls, all were significant at p less than 0.05. Significant differences between grouping of studied elements in the control group and all classified leukemia groups, except younger age-group, were obtained using principal component analysis. The study indicated appreciably different patterns of element distribution and mutual relationships in the whole blood of leukemia patients in comparison with controls.
Źródło:
Nukleonika; 2012, 57, 3; 389-399
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Predicting motor oil condition using artificial neural networks and principal component analysis
Prognozowanie stanu oleju silnikowego za pomocą sztucznych sieci neuronowych i analizy składowych głównych
Autorzy:
Rodrigues, Joao
Costa, Ines
Farinha, J. Torres
Mendes, Mateus
Margalho, Luis
Powiązania:
https://bibliotekanauki.pl/articles/1841873.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
condition monitoring
oil analysis
multivariate analysis
predictive maintenance
monitorowanie stanu
analiza oleju
analiza wielowymiarowa
konserwacja predykcyjna
Opis:
The safety and performance of engines such as Diesel, gas or even wind turbines depends on the quality and condition of the lubricant oil. Assessment of engine oil condition is done based on more than twenty variables that have, individually, variations that depend on the engines’ behaviour, type and other factors. The present paper describes a model to automatically classify the oil condition, using Artificial Neural Networks and Principal Component Analysis. The study was done using data obtained from two passenger bus companies in a country of Southern Europe. The results show the importance of each variable monitored for determining the ideal time to change oil. In many cases, it may be possible to enlarge intervals between maintenance interventions, while in other cases the oil passed the ideal change point.
Bezpieczeństwo i wydajność silników takich, jak silniki Diesla czy gazowe, a nawet turbiny wiatrowe, zależą od jakości i stanu oleju smarowego. Stanu oleju silnikowego ocenia się na podstawie ponad dwudziestu zmiennych, z których każda ulega wahaniom w zależności od typu i zachowania silnika oraz innych czynników. W niniejszym artykule opisano model, który pozwala na automatyczną klasyfikację stanu oleju, z wykorzystaniem sztucznych sieci neuronowych i analizy składowych głównych. Badania przeprowadzono na podstawie danych uzyskanych od dwóch przewoźników pasażerskich działających na terenie jednego z krajów położonych na południu Europy. Wyniki pokazują, że każda z monitorowanych zmiennych ma znaczenie dla określenia idealnego czasu na wymianę oleju. Podczas gdy w wielu przypadkach w badanych przedsiębiorstwach możliwe było zwiększenie odstępów czasowych między działaniami konserwacyjnymi, w innych, idealny moment wymiany oleju został przekroczony.
Źródło:
Eksploatacja i Niezawodność; 2020, 22, 3; 440-448
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Biometric watermarking for security enhancement in digital images
Autorzy:
Wójtowicz, W.
Powiązania:
https://bibliotekanauki.pl/articles/115437.pdf
Data publikacji:
2013
Wydawca:
Fundacja na Rzecz Młodych Naukowców
Tematy:
images security
watermarking technique
discrete wavelet transform (DWT)
biometrics
principal component analysis (PCA)
Opis:
In this paper some preliminary investigation on combination of watermarking technique with biometric data to increase security of digital images in case of medical images is proposed. Performance of watermarking algorithm, based on discrete wavelet transform (DWT) decomposition, that incorporates biometric watermark is elaborated. The frequency domain were chosen as it is proven, that this domain provides better robustness against attacks and leads to less perceptibility of an embedded watermark. To assure confidentiality of patient data their hand geometry features are embedded instead of patient’s name. Proposed system is evaluated by measuring the similarity between embedded and extracted biometric codes.
Źródło:
Challenges of Modern Technology; 2013, 4, 4; 7-11
2082-2863
2353-4419
Pojawia się w:
Challenges of Modern Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Slovak Creativity Index – A PCA Based Approach
Autorzy:
Hudec, Oto
Klasová, Slávka
Powiązania:
https://bibliotekanauki.pl/articles/623791.pdf
Data publikacji:
2016-07-07
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Slovak creativity index
urbanisation
principal component analysis
R11
C21
A13
Opis:
The article aims at transferring the European Creativity Index (ECI) assessment from the country to regional comparison basis, focusing on the case of Slovakia. The newly created Slovak Creativity Index (SCI) has the power to assess the creativity potential found in the Slovak regions. The Principal Component Analysis has been chosen as an advanced method for establishing a well-designed overall Index and six sub-indices to show differences and variability according to all dimensions of the creative potential. The research also explains several relations between creative performance of the regions by several factors such as urbanisation, cultural environment, human capital and tolerance.
Źródło:
European Spatial Research and Policy; 2016, 23, 1
1231-1952
1896-1525
Pojawia się w:
European Spatial Research and Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The North Sea Bicycle Race ECG project : time-domain analysis
Autorzy:
Długosz, D.
Eftestøl, T.
Królak, A.
Wiktorski, T.
Ørn, S.
Powiązania:
https://bibliotekanauki.pl/articles/384850.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
ECG
principal Component Analysis
silhouette analysis
clustering
EKG
analiza głównych składowych
grupowanie
klastering
Opis:
Analysis of electrocardiogram and heart rate provides useful information about health condition of a patient. The North Sea Bicycle Race is an annual cycling competition in Norway. Examination of ECG recordings collected from participants of this race may allow defining and evaluating the relationship between physical endurance exercises and heart electrophysiology. Parameters reflecting potentially alarming deviations are to be identified in this study. This paper presents results of a time-domain analysis of ECG data collected in 2014, implementing K-Means clustering. A double stage analysis strategy, aimed at producing hierarchical clusters, is proposed. The first phase allows rough separation of data. Second stage is applied to reveal internal structure of the majority clusters. In both steps, discrepancies driving the separation could stem from three sources. Firstly, they could be signs of abnormalities in electrical activity of the heart. Secondly, they may allow discriminating between natural groups of participants – according to sex, age, physical fitness. Finally, some deviations could result from faults in data extraction, therefore serving in evaluation of the parameters. The clusters were defined predominantly by combinations of features: heartbeat signals correlation, P-wave shape, and RR intervals; none of the features alone was discriminative for all the clusters.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 1; 23-32
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Convergence Analysis for Principal Component Flows
Autorzy:
Yoshizawa, S.
Helmke, U.
Starkov, K.
Powiązania:
https://bibliotekanauki.pl/articles/908317.pdf
Data publikacji:
2001
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
badanie zbieżności
sieć neuronowa
principal component analysis
neural networks
gradient flows
phase portrait
Hessians
Opis:
A common framework for analyzing the global convergence of several flows for principal component analysis is developed. It is shown that flows proposed by Brockett, Oja, Xu and others are all gradient flows and the global convergence of these flows to single equilibrium points is established. The signature of the Hessian at each critical point is determined.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2001, 11, 1; 223-236
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
PCA-based approximation of a class of distributed parameter systems: classical vs. neural network approach
Autorzy:
Bartecki, K.
Powiązania:
https://bibliotekanauki.pl/articles/201641.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
distributed parameter system
principal component analysis
artificial neural network
supervised learning
unsupervised learning
Opis:
In this article, an approximation of the spatiotemporal response of a distributed parameter system (DPS) with the use of the principal component analysis (PCA) is considered. Based on a data obtained by the numerical solution of a set of partial differential equations, a PCA-based approximation procedure is performed. It consists in the projection of the original data into the subspace spanned by the eigenvectors of the data covariance matrix, corresponding to its highest eigenvalues. The presented approach is carried out using both the classical PCA method as well as two different neural network structures: two-layer feed-forward network with supervised learning (FF-PCA) and single-layer network with unsupervised, generalized Hebbian learning rule (GHA-PCA). In each case considered, the effect of the approximation model structure represented by the number of eigenvectors (or, in the neural case, units in the network projection layer) on the mean square approximation error of the spatiotemporal response and on the data compression ratio is analysed. As shown in the paper, the best approximation quality is obtained for the classical PCA method as well as for the FF-PCA neural approach. On the other hand, an adaptive learning method for the GHA-PCA network allows to use it in e.g. an on-line identification scheme.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 651-660
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessment of the influence of soil properties on 137Cs accumulation in Of horizon in forest soils
Autorzy:
Ziembik, Z.
Dołhańczuk-Śródka, A.
Wacławek, M.
Powiązania:
https://bibliotekanauki.pl/articles/148398.pdf
Data publikacji:
2010
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
137Cs
forest soil
physicochemical parameters
cluster analysis (CA)
principal component analysis (PCA)
Opis:
The work focuses on assessment of soil physicochemical parameters influence on 137Cs accumulation in Of soil horizon. Besides organic matter content and pH, the parameters related to sorption properties and mobile ions concentration were considered. The data were transformed using Box-Cox formula. To find mutual relationships between variables cluster analysis (CA) and principal components analysis (PCA) were used. It was found that the transformed physicochemical parameters in Of horizon are more or less related with each other but no linear or nearly linear relationships between 137Cs activity and physicochemical parameters were found.
Źródło:
Nukleonika; 2010, 55, 2; 205-212
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multivariate diversity of Polish winter triticale cultivars for spike and other traits.
Autorzy:
Kociuba, Wanda
Mądry, Wiesław
Kramek, Aneta
Ukalski, Krzysztof
Studnicki, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/2199592.pdf
Data publikacji:
2010-12-01
Wydawca:
Instytut Hodowli i Aklimatyzacji Roślin
Tematy:
canonical variate analysis
cluster analysis
cultivars
principal component analysis
spike traits
winter triticale
Opis:
The objective of the present study was to determine the extent and pattern of genotypic diversity for six spike quantitative characters and two other traits in 36 winter triticale cultivars released in Poland, to classify the cultivars into similarity groups (clusters) and to identify those traits, among the studied ones, which mostly discriminated distinguished groups of cultivars. The 36 cultivars, released in the period from 1982 to 1999, were evaluated across three years 2002-2004 at the Experimental Field Station in Czesławice near Nałęczów, Poland. The experiments were carried out on the brown soil with loess subsoil. In each year the one-replicated experimental design was used with 2 m2 plots, rows 20 cm apart, and dense sowing using about 2 cm spacing of seeds. Analyses of variance for each trait data according to the random model (both cultivars and years were assumed to be random factors) were done. To classify and characterize genotypic diversity of the cultivars for the eight traits, the pattern analysis was used. It involved both cluster analysis using Ward’s procedure with a measure of the multivariate similarity among cultivars being Squared Euclidean Distance and canonical variate analysis (CVA) on the basis of cultivar BLUPs for the original traits. Quite different groups of cultivars for the studied traits were found, specially one group was substantially distanced to the others. As it was shown by CVA, spike length and number of spikelets per spike as negatively correlated with number of grains per spikelet in the studied set of the cultivars relatively largest contributed to overall differentiation of the distinguished eight groups and then, these traits best discriminated among the eight cultivar groups in the term of Mahalanobis distance for the considered traits. The 1000 grain weight and grain protein content much less contributed to overall discrimination of the cultivar groups than the previous four traits. The most important agronomic traits characterizing productivity of the spike grain weight and its two components, e.g. number of grains per spikelet and number of grains per spike had least discriminating power for the groups of cultivars. Grain yield per unit area of cereals is a result of spike grain yield and the number of spikes per unit area. In these studies of winter triticale cultivar diversity only grain spike yield and its components were included. Thus, the presented study are a primary evaluating of phenotypic diversity in the cultivars. The further study on the cultivar diversity evaluation for grain yield per unit area and its components is necessary...  
Źródło:
Plant Breeding and Seed Science; 2010, 62; 31-42
1429-3862
2083-599X
Pojawia się w:
Plant Breeding and Seed Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of Multivariate Statistical Analysis of Hydrochemical Data for the Identification of the Geochemical Processes in the Tirana-Fushe Kuqe Alluvial Aquifer, North-Western Albania
Autorzy:
Raço, Endri
Beqiraj, Arjan
Cenameri, Sabina
Jahja, Aurela
Powiązania:
https://bibliotekanauki.pl/articles/2173334.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
Tirana-Fushe Kuqe aquifer
groundwater
multivariate analysis
principal component analysis
hierarchical cluster analysis
Opis:
During the research, 71 groundwater samples were collected over a 300 km2 area of Tirana-Fushe Kuqe alluvial aquifer extension (central-western Albania) and subsequently analyzed for 11 parameters (pH, K+, Na+, Ca2+, Mg2+, HCO3-, Cl-, SO42-, NO3-, TH and TDS). Both geochemical conventional (Piper and Chadha diagrams) methods of groundwater classification and multivariate statistical (principal components analysis – PCA and hierarchical cluster analysis – HCA) methods were applied to the dataset to evidence the geochemical processes controlling groundwater geochemistry evaluation through the aquifer. The conventional geochemical methods revealed four (G1–G4) hydrochemical groups where the dominant group is G2 the samples of which are from unconfined to semiconfined recharge zone and the majority of them have Ca-Mg-HCO3 groundwater. Group G3 includes the samples from the confined coastal aquifer having Na-Cl groundwater. Group G1 includes three groundwater samples of Ca-Mg-SO4 from the central part of the aquifer, while group G4, the samples of which are spatially located between G3 and G2 zones, has Na-HCO3 groundwater. The first four components of the PCA account for 85.35% of the total variance. Component PC1 is characterized by very high positive loadings of TH, Ca2+, and Mg2+, suggesting the importance of dissolution processes in the aquifer recharge zone. Component PC2 is characterized by very high positive loadings in Na+, K+, and Cl-and moderate to high loadings of TDS, revealing the involvement of seawater intrusion and diffusion from clay layers. On the basis of their variable loadings, the first two components are defined as the “hardness” and “salinity”, respectively. The HCA produced four geochemically distinct clusters, C1–C4. The samples of cluster C1 are from the coastal confined aquifer and their groundwater belongs to the Na-Cl type. The samples from cluster C2 are located in the south and east recharge areas and most of them have Ca–Mg–HCO3 groundwater, while the samples from cluster C3, which are located in the northeastern recharge zone, have Mg-Ca–HCO3 groundwater. Finally, cluster C4 includes two groundwater subgroups having Na-Cl-HCO3 and Na-Mg-Cl-HCO3 groundwater in the vicinity of cluster C1 as well as Na-HCO3-Cl and Na-Mg-HCO3-Cl groundwater next to cluster C2 and C3.
Źródło:
Journal of Ecological Engineering; 2022, 23, 8; 327--340
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Multivariate Statistical Methods to the Hydrochemical Study of Groundwater Quality in the Sahel Watershed, Algeria
Autorzy:
Hakim, Djafer Khodja
Amina, Aichour
Amina, Rezig
Djouhra, Baloul
Ahmed, Ferhati
Powiązania:
https://bibliotekanauki.pl/articles/2173331.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
hydrochemical analysis
water quality
groundwater
principal component analysis
hierarchical cluster analysis
Sahel watershed
Opis:
The quality of groundwater is characterized by several numbers of physical and chemical parameters, which determine the use of water (water supply, irrigation, industry). This search paper is a contribution made to know the hydrochemical characteristics of groundwater in the Sahel sub-catchment which belongs to the large Soummam North basin of Algeria. Different multivariate statistical techniques were used such as principal component analysis (PCA), Hierarchical Cluster Analysis (HCA) and Diagram Analysis. These analyses are exercised to a dataset formed from 37 boreholes with 12 chemical variables over the entire surface of the watershed. The samples were collected in 2016. The 37 boreholes are one of the main water resources that supply the wilaya of Bouira with drinking water and irrigation. The analysis of water quality using different methods (ACP, HCA and Diagram) resulted in two chemical kinds: (Chloride, calcium sulfate and magnesium), and (Bicarbonate calcium and magnesium). The results have shown that 74% of the boreholes were contaminated, the rest of boreholes were characterized by a good quality and they have not suffered any contamination and can be consumed without any risk.
Źródło:
Journal of Ecological Engineering; 2022, 23, 8; 341--349
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal component analysis of older people registered as unemployed in public employment offices
Analiza głównych składowych populacji osób starszych zarejestrowanych w powiatowych urzędach pracy jako bezrobotni
Autorzy:
Bolesta, Karolina
Powiązania:
https://bibliotekanauki.pl/articles/2176597.pdf
Data publikacji:
2023-01-31
Wydawca:
Główny Urząd Statystyczny
Tematy:
pensioners
disability pensioners
retirement age
pre-retirement benefit
unemployed
professional deactivation
principal component analysis
PCA
Kaiser-Meyer-Olkin measure
Bartlett's test of sphericity
emeryci
renciści
wiek emerytalny
świadczenie przedemerytalne
bezrobotni
dezaktywizacja zawodowa
analiza głównych składowych
współczynnik Kaisera-Meyera-Olkina
test sferyczności Bartletta
Opis:
The determinants of registering as an unemployed person in the public employment office may be of both a socio-demographic and legal character. Although every individual has their own motivation to register as unemployed, it is still possible to analyse the phenomenon on a group level. The purpose of this study is to show the similarities and differences of older people registering as unemployed and to identify the factors that were key to professional deactivation. The research is based on data from the Polish Central Analytical and Reporting System concerning 1,276,555 people born in the years 1940–1965, who were at least once registered as unemployed in a public employment office. The study uses principal component analysis (PCA) to identify the factors which influence to the largest extent the decision to deactivate professionally. The Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett’s test of sphericity proved the feasibility of the PCA. The number of principal components was determined on the basis of Kaiser’s criterion. The varimax factor rotation was applied to simplify the relation between the variables and to enhance the interpretation of the obtained results. The analysis included five groups: pensioners, disability pensioners, people who reached retirement age, people who received pre-retirement benefits and the total population. For each group three to four components were identified which combined different variables. Education and occupation in the last place of work formed the only common component for the five groups which influences the most critical decisions in the labour market. This component demonstrates the level of competence and may determine the moment of professional deactivation. The research shows that economic mechanisms are more important than legal conditions in all the analysed groups.
Czynniki decydujące o zarejestrowaniu się w urzędzie pracy jako osoba bezrobotna mogą mieć charakter społeczno-demograficzny lub prawny. Podjęcie takiej decyzji jest kwestią indywidualną, niemniej jednak można przeanalizować to zjawisko na poziomie grupy. Celem badania omawianego w artykule jest wykazanie podobieństw i różnic osób rejestrujących się jako bezrobotni oraz identyfikacja czynników, które mają największe znaczenie dla dezaktywizacji zawodowej. W badaniu wykorzystano dane z Centralnego Systemu AnalitycznoRaportowego dotyczące 1 276 555 osób urodzonych pomiędzy 1940 r. a 1965 r., które co najmniej raz były zarejestrowane w powiatowym urzędzie pracy jako bezrobotni. W celu identyfikacji komponentów najsilniej wpływających na decyzję o dezaktywizacji zawodowej przeprowadzono analizę głównych składowych (ang. principal component analysis – PCA). Wyniki pomiaru adekwatności Kaisera-Meyera-Olkina oraz testu sferyczności Bartletta potwierdziły słuszność zastosowania tej analizy. Na podstawie kryterium Kaisera określono liczbę głównych składowych. Przeprowadzono rotację czynników varimax, aby uprościć relację między zmiennymi i lepiej zinterpretować uzyskane wyniki. Analiza dotyczyła pięciu grup: emerytów, rencistów, osób, które osiągnęły wiek emerytalny, osób, które pobierały świadczenie przedemerytalne, oraz całej populacji. Dla każdego zbioru danych zidentyfikowano od trzech do czterech składowych łączących różne zmienne. We wszystkich grupach stwierdzono jeden wspólny komponent – łączący wykształcenie i zawód wykonywany w ostatnim miejscu pracy – który wpływa na podejmowanie kluczowych decyzji na rynku pracy. Obrazuje on kompetencje pracowników i może determinować moment dezaktywizacji zawodowej. Wyniki badania wskazują na większe znaczenie mechanizmu ekonomicznego niż uwarunkowań prawnych we wszystkich analizowanych grupach.
Źródło:
Wiadomości Statystyczne. The Polish Statistician; 2023, 68, 1; 23-38
0043-518X
Pojawia się w:
Wiadomości Statystyczne. The Polish Statistician
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Electronic nose with polymer-composite sensors for monitoring fungal deterioration of stored rapeseed
Autorzy:
Gancarz, Marek
Wawrzyniak, Jolanta
Gawrysiak-Witulska, Marzena
Wiącek, Dariusz
Nawrocka, Agnieszka
Rusinek, Robert
Powiązania:
https://bibliotekanauki.pl/articles/973040.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
principal component analysis
e-nose
rapeseed
ergosterol
colony forming units
volatile organic compounds
Opis:
Investigations were performed to examine the possibility of using an electronic nose to monitor development of fungal microflora during the first eighteen days of rapeseed storage. The Cyranose 320 device manufactured by Sensigent was used to analyse volatile organic compounds. Each sample of infected material was divided into three parts and the degree of spoilage was measured in three ways: analysis of colony forming units, determination of ergosterol content, and measurement of volatile organic compounds with the e-nose. Principal component analysis was performed on the generated patterns of signals and six groups of different spoilage levels were isolated. An analysis of sensorgrams for a few sensors with a strong signal for each group of rapeseed spoilage was performed. The ratio of the association time to the steady state was calculated. This ratio was different for the low level and the highest level of ergosterol and colony forming units. The results have shown that the e-nose can be a useful tool for quick estimation of the degree of rapeseed spoilage.
Źródło:
International Agrophysics; 2017, 31, 3
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Selection of optimal coal blends in terms of ash fusion temperatures using Support Vector Machine (SVM) classifier - a case study for Polish coals
Autorzy:
Żogała, Alina
Rzychoń, Maciej
Łączny, Jacek M.
Róg, Leokadia
Powiązania:
https://bibliotekanauki.pl/articles/110177.pdf
Data publikacji:
2019
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
coal blends
ash fusion temperature
support vector machine
principal component analysis
machine learning
Opis:
One of the most important criteria for selecting coal for a given technology are the ash Fusion temperatures (AFTs). An effective way to regulate the AFTs so that they meet the criteria for a given industrial application is to form blends of different coals. The values of the AFTs in the blends are nonadditive, therefore they can't be calculated using the weighted average of the blend components. On the other hand, direct determination of ATFs values requires many additional time-consuming and expensive laboratory tests. Therefore, it is important to develop a solution that, in addition to the effective prediction of the values of AFTs, will also enable optimal selection of components of the blend in terms of its key parameters. The aim of the work was to develop an algorithm for the selection of the optimal coal blends in terms of AFTs for given industrial applications. This algorithm uses nonlinear classifying model which was built using machine learning method, support vector machine (SVM). To carry out the training samples of Polish hard coals from different mines of the Upper Silesian Coal Basin were used. The accuracy of the developed model is 92.3%. The results indicate the effectiveness of the proposed solution, which can find practical application in the form of an expert system used in the coal industry. The paper presents the concept of developed IT tool which has been tested for a selected case.
Źródło:
Physicochemical Problems of Mineral Processing; 2019, 55, 5; 1311-1322
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Główne składowe rozwoju inteligentnego Polski
Principal components of the smart development of Poland
Autorzy:
Rozmus, Dorota
Trzęsiok, Joanna
Powiązania:
https://bibliotekanauki.pl/articles/542528.pdf
Data publikacji:
2018-05-28
Wydawca:
Główny Urząd Statystyczny
Tematy:
polityka spójności
rozwój inteligentny
metoda głównych składowych
cohesion policy
smart development
principal component analysis
Opis:
W systemie STRATEG, utworzonym przez GUS na potrzeby monitorowania polityki spójności, zgromadzono ponad 300 wskaźników do pomiaru rozwoju inteligentnego. Z uwagi na dużą liczbę zmiennych zasadne wydaje się zbadanie możliwości konstrukcji wskaźników syntetycznych jak najlepiej reprezentujących zmienne pierwotne. Celem badania, które przeprowadzono na podstawie danych z baz STRATEG i BDL za 2015 r., jest wskazanie — dzięki zastosowaniu analizy czynnikowej — głównych składowych rozwoju inteligentnego w Polsce, informujących o najważniejszych obszarach charakteryzowanych przez wskaźniki rozwoju inteligentnego. W efekcie uzyskano siedem głównych składowych, łącznie wyjaśniających ponad 94% wariancji pierwotnego zbioru wskaźników, dla których zaproponowano merytoryczną interpretację.
The STRATEG system created by Statistics Poland for monitoring cohesion policy, contains more than 300 indicators for measuring smart development. Due to a large number of variables, it seems appropriate to examine the possibility of constructing synthetic indicators that best represent the primary variables. The aim of this study, which was conducted on the basis of data for 2015 from the STRATEG and BDL databases, is to identify, owing to the use of factor analysis, the main components of smart development in Poland, informing about the most important areas characterised by the indicators of smart development. As a result 7 main components were obtained, which together account for more than 94% of variance from the original set of indicators and for which a substantive interpretation was proposed.
Źródło:
Wiadomości Statystyczne. The Polish Statistician; 2018, 63, 5; 25-36
0043-518X
Pojawia się w:
Wiadomości Statystyczne. The Polish Statistician
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Image Based Rendering to improvement of face recognition using Principal Component Analysis
Zastosowanie metody Image Based Rendering do poprawy rozpoznawania twarzy metodą analizy komponentów głównych
Autorzy:
Okarma, K.
Miętus, A.
Powiązania:
https://bibliotekanauki.pl/articles/153384.pdf
Data publikacji:
2010
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
Image Based Rendering
analiza komponentów głównych
rozpoznawanie twarzy
image-based rendering
principal component analysis
face recognition
Opis:
In the paper the application of Image Based Rendering as a supplementary method useful for PCA-based face recognition is discussed. Presented results are based on the synthetic images of human faces' side views obtained from 3D models and 300 faces taken from FERET database. Application of Image Based Rendering allows the use of en face images rendered as the output based on two side views so the recognition accuracy can be improved.
W artykule omówiono zastosowanie metody Image Based Rendering (IBR) jako techniki uzupełniającej, użytecznej przy rozpoznawaniu twarzy opartym na analizie komponentów głównych (PCA). Typowym zastosowaniem metody IBR jest szybka synteza obrazu o jakości porównywalnej z obrazem referencyjnym na podstawie informacji uzyskiwanych z rzeczywistej kamery zlokalizowanej w innym położeniu niż wirtualna kamera docelowa. Niezbędnym elementem do celów takiej syntezy jest również znajomość mapy głębokości obrazu referencyjnego. Uzyskiwane w taki sposób obrazy mogą być szczególnie użyteczne przy konieczności ich porównania ze wzorcami znajdującymi się w bazie, co jest typowe dla metod klasyfikacji i rozpoznawania wzorców, w tym obrazów. Przedstawione wyniki uzyskane zostały na podstawie syntetycznych obrazów twarzy obserwowanych z boku oraz 300 twarzy uzyskanych z bazy FERET. Jako reprezentatywna technika rozpoznawania twarzy, umożliwiająca dodatkowe wykorzystanie metody IBR, wybrana została metoda PCA, dla której uzyskano zauważalną poprawę skuteczności rozpoznawania twarzy z użyciem proponowanej metody. Zastosowanie metody IBR pozwala wykorzystać frontalne obrazy twarzy wyrenderowane nawet na podstawie obrazu z jednej kamery referencyjnej, co podnosi skuteczność rozpoznawania twarzy. Wykorzystanie obrazów z dwóch kamer bocznych wymaga precyzyjnego pasowania oraz kompensacji wpływu oświetlenia.
Źródło:
Pomiary Automatyka Kontrola; 2010, R. 56, nr 12, 12; 1495-1497
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparison of the beef prices in selected countries of the European Union
Autorzy:
Jaworski, Stanisław
Powiązania:
https://bibliotekanauki.pl/articles/453098.pdf
Data publikacji:
2012
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:
B-splines basis system
functional principal component analysis
functional analysis of variance
permutation tests
Opis:
Functional data analysis is used to examine beef price differences in selected countries of the European Union from 2006 to 2011. The prices are modeled as functional observations. The analysis is conducted in three steps relating to three kinds of functional data analysis. First the observations are smoothed with roughness penalty. Then functional principal analysis is applied. Finally functional analysis of variance is used to reveal significant difference between two given groups of countries.
Źródło:
Metody Ilościowe w Badaniach Ekonomicznych; 2012, 13, 2; 31-39
2082-792X
Pojawia się w:
Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wielowymiarowa analiza czynników sukcesu projektów IT
Multidimensional Analysis of Factors of IT Project Success
Autorzy:
Gładysz, Barbara
Frączkowski, Kazimierz
Powiązania:
https://bibliotekanauki.pl/articles/589729.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Analiza składowych głównych
Czynniki sukcesu
Projekt IT
Principal component analysis
Project IT
Success factors
Opis:
Dzięki postępowi technologicznemu, który nastąpił w ostatnich latach, znacznie wzrosła liczba projektów informatycznych. Projekty te często okazywały się skomplikowanymi przedsięwzięciami obarczonymi wysokim ryzykiem. Właściwe zarządzanie projektem może wpłynąć na harmonogram, budżet i jakość projektu, a tym samym przyczynić się do sukcesu projektu. W artykule dokonano wielowymiarowej analizy czynników sukcesu projektu. Badania zostały przeprowadzone na podstawie danych ankietowych.
Due to technological advances in recent years, the number of IT projects has significantly increased. Such projects are often complicated and associated with high risk. Appropriate project management has a positive influence on the budget, quality and achieving deadlines, and in this way can lead to the success of a project. This paper presents and multi-criterion analysis of factors involved in the success/failure of a project. This research was carried out on the basis of data from a questionnaire.
Źródło:
Studia Ekonomiczne; 2015, 248; 80-89
2083-8611
Pojawia się w:
Studia Ekonomiczne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Principal component analysis of chlorophyll content in tobacco, bean and petunia plants exposed to different tropospheric ozone concentrations
Analiza składowych głównych zawartości chlorofilu w roślinach tytoniu, fasoli i petunii eksponowanych na stanowiskach o różnych stężeniach ozonu troposferycznego
Autorzy:
Borowiak, K.
Zbierska, J.
Budka, A.
Kayzer, D.
Powiązania:
https://bibliotekanauki.pl/articles/396114.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
tropospheric ozone
sensitive
resistance
chlorophyll
principal component analysis (PCA)
ozon troposferyczny
wrażliwość
odporność
chlorofil
Opis:
Three plant species were assessed in this study - ozone-sensitive and -resistant tobacco, ozone-sensitive petunia and bean. Plants were exposed to ambient air conditions for several weeks in two sites differing in tropospheric ozone concentrations in the growing season of 2009. Every week chlorophyll contents were analysed. Cumulative ozone effects on the chlorophyll content in relation to other meteorological parameters were evaluated using principal component analysis, while the relation between certain days of measurements of the plants were analysed using multivariate analysis of variance. Results revealed variability between plant species response. However, some similarities were noted. Positive relations of all chlorophyll forms to cumulative ozone concentration (AOT 40) were found for all the plant species that were examined. The chlorophyll b/a ratio revealed an opposite position to ozone concentration only in the ozone-resistant tobacco cultivar. In all the plant species the highest average chlorophyll content was noted after the 7th day of the experiment. Afterwards, the plants usually revealed various responses. Ozone-sensitive tobacco revealed decrease of chlorophyll content, and after few weeks of decline again an increase was observed. Probably, due to the accommodation for the stress factor. While during first three weeks relatively high levels of chlorophyll contents were noted in ozone-resistant tobacco. Petunia revealed a slow decrease of chlorophyll content and the lowest values at the end of the experiment. A comparison between the plant species revealed the highest level of chlorophyll contents in ozone-resistant tobacco.
W zaprezentowanych badaniach wykorzystano trzy gatunki roślin - tytoń szlachetny (odmiana wrażliwa oraz odporna na ozon), odmiany wrażliwe petunii oraz fasoli. Rośliny eksponowano na dwóch stanowiskach różniących się stężeniem ozonu troposferycznego w sezonie wegetacyjnym 2009 roku. Co tydzień wykonywano pomiary zawartości chlorofilu wybranych roślin. Powiązanie kumulatywnych stężeń ozonu względem zawartości chlorofilu oraz wybranych parametrów meteorologicznych wykonano za pomocą analizy składowych głównych, natomiast do porównania reakcji roślin w poszczególnych dniach ekspozycji wykorzystano wielowymiarową analizę wariancji. Badania wykazały zróżnicowanie pomiędzy gatunkami w reakcji na obecność ozonu troposferycznego. Zauważyć jednak można pewne tendencje. Stwierdzono pozytywną zależność pomiędzy zawartością wszystkich form chlorofilu dla wszystkich badanych gatunków i kumulatywnym stężeniem ozonu (AOT 40). Wskaźnik chlorofilu b/a wykazał odwrotną tendencję względem AOT 40 jedynie dla odmiany odpornej na ozon tytoniu. Wszystkie gatunki wykazały najwyższy poziom chlorofilu w 7 dniu ekspozycji, a w następnych dniach odpowiedź roślin była zróżnicowana. Odmiana wrażliwa tytoniu wykazała zmniejszenie zawartości chlorofilu, a po kilku tygodniach ponownie wzrost, co może sugerować adaptację do warunków stresowych. Odmiana odporna tytoniu ekspozycji. Petunia wykazała stopniowy spadek zawartości chlorofilu w ciągu trwania eksperymentu. Porównanie odpowiedzi wybranych gatunków wykazało najwyższe poziomy chlorofilu u odmiany odpornej tytoniu.
Źródło:
Civil and Environmental Engineering Reports; 2014, 12; 5-16
2080-5187
2450-8594
Pojawia się w:
Civil and Environmental Engineering Reports
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mierzenie ryzyka stóp procentowych: przypadek rynku międzybankowego w Polsce
Interest rate risk measurement: the Polish interbank market case
Autorzy:
Olsza, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/422739.pdf
Data publikacji:
2012
Wydawca:
Główny Urząd Statystyczny
Tematy:
zabezpieczenie
analiza głównych składowych
ryzyko stóp procentowych
hedging
principal component analysis
interest rate risk
Opis:
W artykule przedstawiony został przykład zastosowania różnych podejść do pomiaru ryzyka stóp procentowych. Analizy empiryczne zaprezentowane w artykule przeprowadzono z wykorzystaniem danych z polskiego rynku międzybankowego za okres od 5 września 2000 roku do 19 listopada 2010 roku. Zaprezentowano narzędzia pomiaru ryzyka stóp procentowych, bazujące na wartościach wektorów własnych odpowiadających poszczególnym głównym składowym. Miary te, poprzez nadanie stosownej interpretacji ekonomicznej poszczególnych głównych składowych, mogą mieć także zastosowanie w analizie wrażliwości portfela instrumentów dłużnych na określone ruchy krzywej terminowej stóp procentowych. W artykule omówiono także kwestię odpowiedniego doboru oraz możliwego wpływu zakresu wykorzystywanych danych rynkowych na wartości oraz stabilność oszacowań wektorów własnych uzyskiwanych z użyciem analizy głównych składowych. W celu sprawdzenia efektywności pomiaru ryzyka stopy procentowej z wykorzystaniem analizy głównych składowych dokonano pomiaru skuteczności trzech różnych strategii zabezpieczających, pierwszej utworzonej na podstawie wskazań miar wrażliwości analizowanego portfela na zmiany poszczególnych głównych składowych, drugiej bazującej na miarach duracji efektywnej, wypukłości efektywnej oraz BPV oraz przy założeniu braku zabezpieczenia. Uzyskane wyniki nie wykazały znaczących różnic w stopniu zabezpieczenia portfela w przypadku strategii zabezpieczających wykorzystujących główne składowe oraz miary duracji efektywnej, wypukłości efektywnej oraz BPV.
The article presents an example of the application of different approaches to the measurement of interest rate risk. Empirical analysis described in the article was carried out using data from the Polish interbank market for the period from September 5th, 2000 to November 19th, 2010. Interest rate risk measurement techniques using principal component analysis (PCA) are presented in the article. These techniques, by giving appropriate economic interpretation of each principal component, can also be used in the sensitivity analysis of the portfolio of debt securities to specific interest rate curve movements. The article also discusses the issue of the appropriate selection of scope and range of market data used in the analysis and its possible impact on values and stability of eigenvectors obtained using PCA. Three different hedging strategies were tested in order to check the effectiveness of interest rate risk measurement using PCA, the first based on PCA, the other based on the measures of effective duration, effective convexity, and BPV, the last considered strategy assumed no hedging at all. The results showed no significant differences in the degree of portfolio value protection in case of hedging strategy using PCA and the one based on the measures of effective duration, effective convexity, and BPV.
Źródło:
Przegląd Statystyczny; 2012, 59, 4; 434-454
0033-2372
Pojawia się w:
Przegląd Statystyczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation and selection process of suppliers through analytical framework: an emprical evidence of evaluation tool
Autorzy:
Imeri, S.
Shahzad, K.
Takala, J.
Liu, Y
Sillanpää, I.
Ali, T.
Powiązania:
https://bibliotekanauki.pl/articles/407383.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
supplier evaluation
supplier performance management
supplier selection model
principal component analysis
supply chain management
Opis:
The supplier selection process is very important to companies as selecting the right suppliers that fit companies strategy needs brings drastic savings. Therefore, this paper seeks to address the key area of supplies evaluation from the supplier review perspective. The purpose was to identify the most important criteria for suppliers’ evaluation and develop evaluation tool based on surveyed criteria. The research was conducted through structured questionnaire and the sample focused on small to medium sized companies (SMEs) in Greece. In total eighty companies participated in the survey answering the full questionnaire which consisted of questions whether these companies utilize some suppliers’ evaluation criteria and what criteria if any is applied. The main statistical instrument used in the study is Principal Component Analysis (PCA). Thus, the research has shown that the main criteria are: the attitude of the vendor towards the customer, supplier delivery time, product quality and price. Conclusions are made on the suitability and usefulness of suppliers’ evaluation criteria and in way they are applied in enterprises.
Źródło:
Management and Production Engineering Review; 2015, 6, 3; 10-20
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multifactorial components analysis of the renewable energy sector in the OECD countries and managerial implications
Analiza komponentów wielofunkcyjnych sektora energii odnawialnej w krajach OECD i implikacje kierownicze
Autorzy:
Androniceanu, Ane-Mari
Georgescu, Irina
Dobrin, Cosmin
Dragulanescu, Irina Virginia
Powiązania:
https://bibliotekanauki.pl/articles/2021559.pdf
Data publikacji:
2020
Wydawca:
Politechnika Częstochowska
Tematy:
renewable energy
principal component analysis
government policy
energia odnawialna
analiza głównych komponentów
polityka rządu
Opis:
New technologies and new market realities determine the global energy industry to redesign their business models in all significant areas. We based our research on the components of renewable energy within the OECD countries and used thirteen indicators in order to find out both the relations and the impact of main sectorial indicators and the global indicators of the OECD countries to their economic and social development. The main goal of our research is to discover the main correlations between the renewable energies and the economic development of the OECD countries. We used databases of the OECD, Our World in Data, International Energy Agency (IEA) and International Renewable Energy Agency (IRENA), available for years 2017 and 2018. We apply Principal Component Analysis (PCA) and retain three principal components explaining 76.098% of the total variance. The main findings of the PCA application are; (1) factor 1 is dominated by the main renewable energy sources: traditional biofuels, hydropower, solar, wind and other renewables, as well as energy products, energy exports, energy capacity and energy generation; (2) factor 2 is dominated positively by energy imports and negatively by primary energy supply and GDP per capita; (3) factor 3 measures electricity generation. The results are addressed to the OECD member states, but also to other categories of states. Our results clearly show that if the OECD states are developing coherent renewable energy policies as part of an integrated smart energy system. The results show a direct link between investments in renewable energy and macroeconomic indicators of the considered states and main implications to the management.
Nowe technologie i nowe realia rynkowe determinują globalny przemysł energetyczny do przeprojektowania modeli biznesowych we wszystkich istotnych obszarach. Nasze badania oparliśmy na składnikach energii odnawialnej w krajach OECD i wykorzystaliśmy trzynaście wskaźników, aby poznać zarówno relacje, jak i wpływ głównych wskaźników sektorowych oraz wskaźników globalnych krajów OECD na ich rozwój gospodarczy i społeczny. Głównym celem naszych badań jest odkrycie głównych korelacji między energią odnawialną a rozwojem gospodarczym krajów OECD. Korzystaliśmy z baz danych OECD, Our World in Data, Międzynarodowej Agencji Energii (IEA) i Międzynarodowej Agencji Energii Odnawialnej (IRENA), dostępnych za lata 2017 i 2018. Stosujemy analizę głównych komponentów (PCA) i zatrzymujemy trzy główne komponenty wyjaśniające 76,098% całkowitej wariancji. Główne ustalenia wniosku o PCA są następujące; (1) czynnik 1 jest zdominowany przez główne odnawialne źródła energii: tradycyjne biopaliwa, energię wodną, słoneczną, wiatrową i inne odnawialne źródła energii, a także produkty energetyczne, eksport energii, moc i wytwarzanie energii; (2) czynnik 2 jest zdominowany pozytywnie przez import energii, a negatywnie przez podaż energii pierwotnej i PKB na mieszkańca; (3) współczynnik 3 mierzy wytwarzanie energii elektrycznej. Wyniki skierowane są do krajów członkowskich OECD, ale także do innych kategorii państw. Nasze wyniki jasno pokazują, że państwa OECD opracowują spójną politykę w zakresie energii odnawialnej w ramach zintegrowanego inteligentnego systemu energetycznego. Wyniki wskazują na bezpośredni związek między inwestycjami w energię odnawialną a wskaźnikami makroekonomicznymi rozważanych krajów i głównymi implikacjami dla zarządzania.
Źródło:
Polish Journal of Management Studies; 2020, 22, 2; 36-49
2081-7452
Pojawia się w:
Polish Journal of Management Studies
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-100 z 204

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies