Skocz do pozycji: 1.

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

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Skocz do pozycji: 2.

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

/5

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Skocz do pozycji: 3.

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

/5

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Skocz do pozycji: 4.

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

/5

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Skocz do pozycji: 5.

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

/5

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Skocz do pozycji: 6.

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

/5

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Skocz do pozycji: 7.

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

/5

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Skocz do pozycji: 8.

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

/5

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Skocz do pozycji: 9.

Tytuł:

A Water Quality Evaluation of Integrated Mangrove Aquaculture System for Water Treatment in Super-Intensive White Leg Shrimp Pond

Autorzy:

Mahmudi, Mohammad
Musa, Muhammad
Bunga, Alamanda
Wati, Nur Azlina
Arsad, Sulastri
Lusiana, Evellin Dewi

Powiązania:

https://bibliotekanauki.pl/articles/2086395.pdf

Data publikacji:

2022

Wydawca:

Polskie Towarzystwo Inżynierii Ekologicznej

Tematy:

coastal ecosystem
eco-aquaculture
pollution index
principal component

Opis:

White leg shrimp (Litopenaeus vannamei) is known as a prime aquacultural commodity in Indonesia. However, the rapid growth of shrimp farming has resulted in widespread destruction of coastal ecosystems, including mangrove swamps. Intensification of shrimp culture has led to many other environmental problems. Integration of mangroves into aquaculture systems (IMAS) should be considered as a way to preserve the mangrove ecosystem as well as sustainability of the aquaculture business by treating the influent and effluent water. This study aimed to assess the benefits of integrating mangroves into shrimp aquaculture, in terms of water quality. The results showed that temperature, dissolved oxygen (DO), and nitrite levels in the water significantly differed between sample sites. PCA analysis indicates that total organic matter (TOM), nitrates, nitrites, and ammonia were the principal factors in the overall water quality of the ponds. The highest pollution index was found in the super-intensive shrimp ponds ('moderately polluted'), while the other sites, including the mangrove area, were categorized as 'lightly polluted'. These findings suggest that the presence of mangroves may improve the quality of aquaculture wastewater, but the pollution index may still not reach the 'good' category. It is therefore recommended that a wastewater treatment plant be installed to support the integrated aquaculture system.

Źródło:

Journal of Ecological Engineering; 2022, 23, 4; 287--296
2299-8993

Pojawia się w:

Journal of Ecological Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 10.

Tytuł:

Spectral Mapping Using Kernel Principal Components Regression for Voice Conversion

Autorzy:

Song, P.
Zhao, L.
Bao, Y.

Powiązania:

https://bibliotekanauki.pl/articles/177529.pdf

Data publikacji:

2013

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

spectral mapping
overfitting
oversmoothing
discontinuity
kernel principal component regression

Opis:

The Gaussian mixture model (GMM) method is popular and efficient for voice conversion (VC), but it is often subject to overfitting. In this paper, the principal component regression (PCR) method is adopted for the spectral mapping between source speech and target speech, and the numbers of principal components are adjusted properly to prevent the overfitting. Then, in order to better model the nonlinear relationships between the source speech and target speech, the kernel principal component regression (KPCR) method is also proposed. Moreover, a KPCR combined with GMM method is further proposed to improve the accuracy of conversion. In addition, the discontinuity and oversmoothing problems of the traditional GMM method are also addressed. On the one hand, in order to solve the discontinuity problem, the adaptive median filter is adopted to smooth the posterior probabilities. On the other hand, the two mixture components with higher posterior probabilities for each frame are chosen for VC to reduce the oversmoothing problem. Finally, the objective and subjective experiments are carried out, and the results demonstrate that the proposed approach shows greatly better performance than the GMM method. In the objective tests, the proposed method shows lower cepstral distances and higher identification rates than the GMM method. While in the subjective tests, the proposed method obtains higher scores of preference and perceptual quality.

Źródło:

Archives of Acoustics; 2013, 38, 1; 39-45
0137-5075

Pojawia się w:

Archives of Acoustics

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 11.

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

/5

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Skocz do pozycji: 12.

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

/5

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Skocz do pozycji: 13.

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

/5

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Skocz do pozycji: 14.

Tytuł:

Principal component data processing in radon metrology

Autorzy:

Machaj, B.
Urbański, P.

Powiązania:

https://bibliotekanauki.pl/articles/147140.pdf

Data publikacji:

2002

Wydawca:

Instytut Chemii i Techniki Jądrowej

Tematy:

principal component regression (PCR)
radon daughters measurement
radon measurement

Opis:

A gauge for the measurement of radon and radon daughters concentration was tested in a radon chamber. Count rate distribution in time at the output of radiation detectors was measured and registered. The count rate distribution in time was then processed employing Principal Component Analysis (PCA) and the Root Mean Square Error (RMSE) of the count rate was investigated. It was found that PCA processing removes great part of count rate random fluctuations originating from radiation statistics, which is resulting in a decrease of the count rate random error and in random error of concentration. The RMSE of radon daughters concentration is about 3 times lower when "raw" results are PCA processed. Such decrease of error, without PCA signal processing, would require 9 times higher air flow through the air filter on which the radon daughters are deposited. In case of the measurements of the radon concentration the drop of the error is 2-3 times higher in case of long counting time.

Źródło:

Nukleonika; 2002, 47, 1; 39-42
0029-5922
1508-5791

Pojawia się w:

Nukleonika

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 15.

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

/5

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Skocz do pozycji: 16.

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

/5

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Skocz do pozycji: 17.

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

/5

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Skocz do pozycji: 18.

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

/5

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Skocz do pozycji: 19.

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

/5

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Skocz do pozycji: 20.

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

/5

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Skocz do pozycji: 21.

Tytuł:

THE INS AND OUTS OF UNEMPLOYMENT IN POLISH VOIVODESHIPS

Autorzy:

Jaworski, Stanisław

Powiązania:

https://bibliotekanauki.pl/articles/453208.pdf

Data publikacji:

2014

Wydawca:

Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki

Tematy:

unemployment rate
Poisson process
smoothing
functional principal component data analysis

Opis:

This paper measures and compares the job-finding and separation transition rates of Polish voivodeships from 2005:Q1 to 2014:Q2. It uses readily accessible data of Local Data Bank in Poland: registered unemployment person by duration of unemployment and registered unemployment rate. The method of measurement stems from influential paper by Shimer on "Reassesing the Ins and Outs of Unemployment". The main sources of variability between the rates are investigated in terms of functional principal components.

Źródło:

Metody Ilościowe w Badaniach Ekonomicznych; 2014, 15, 2; 349-358
2082-792X

Pojawia się w:

Metody Ilościowe w Badaniach Ekonomicznych

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 22.

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

/5

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Skocz do pozycji: 23.

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

/5

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Skocz do pozycji: 24.

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

/5

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Skocz do pozycji: 25.

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

/5

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Skocz do pozycji: 26.

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

/5

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Skocz do pozycji: 27.

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

/5

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Skocz do pozycji: 28.

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

/5

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Skocz do pozycji: 29.

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

/5

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Skocz do pozycji: 30.

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

/5

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Skocz do pozycji: 31.

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

/5

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Skocz do pozycji: 32.

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

/5

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Skocz do pozycji: 33.

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

/5

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Skocz do pozycji: 34.

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

/5

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Skocz do pozycji: 35.

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

/5

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Skocz do pozycji: 36.

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

/5

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Skocz do pozycji: 37.

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

/5

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Skocz do pozycji: 38.

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

/5

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Skocz do pozycji: 39.

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

/5

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Skocz do pozycji: 40.

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

/5

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Skocz do pozycji: 41.

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

/5

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Skocz do pozycji: 42.

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

/5

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Skocz do pozycji: 43.

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

/5

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Skocz do pozycji: 44.

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

/5

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Skocz do pozycji: 45.

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

/5

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Skocz do pozycji: 46.

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

/5

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Skocz do pozycji: 47.

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

/5

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Skocz do pozycji: 48.

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

/5

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Skocz do pozycji: 49.

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

/5

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Skocz do pozycji: 50.

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

/5

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Skocz do pozycji: 51.

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

/5

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Skocz do pozycji: 52.

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

/5

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Skocz do pozycji: 53.

Tytuł:

Principal component and cluster analysis for determining diversification of bottom morphology based on bathymetric profiles from Brepollen (Hornsund, Spitsbergen)

Autorzy:

Moskalik, T.
Tegowski, J.
Grabowiecki, P.
Zulichowska, M.

Powiązania:

https://bibliotekanauki.pl/articles/47566.pdf

Data publikacji:

2014

Wydawca:

Polska Akademia Nauk. Instytut Oceanologii PAN

Tematy:

principal component
cluster analysis
bottom morphology
diversification
bathymetry
Hornsund
Spitsbergen
post-glacial region

Źródło:

Oceanologia; 2014, 56, 1
0078-3234

Pojawia się w:

Oceanologia

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 54.

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

/5

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Skocz do pozycji: 55.

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

/5

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Skocz do pozycji: 56.

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

/5

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Skocz do pozycji: 57.

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

/5

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Skocz do pozycji: 58.

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

/5

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Skocz do pozycji: 59.

Tytuł:

Wielocechowa analiza wyników doświadczeń wstępnych z żytem ozimym
Multivariate analysis of data from preliminary trials with winter rye

Autorzy:

Ukalski, Krzysztof
Śmiałowski, Tadeusz

Powiązania:

https://bibliotekanauki.pl/articles/2198126.pdf

Data publikacji:

2011-09-30

Wydawca:

Instytut Hodowli i Aklimatyzacji Roślin

Tematy:

analiza składowych głównych
formy mieszańcowe
formy populacyjne
plon ziarna
regresja składowych głównych
transformacja
żyto ozime
grain yield
hybrid forms
population forms
principal component analysis
principal component regression
transformation
winter rye

Opis:

Przedmiotem badań było 30 form żyta ozimego badanych w doświadczeniach wstępnych przez sześć Zakładów Hodowli Roślin oraz Zakład Roślin Zbożowych IHAR w Krakowie. Wyniki prezentowane w pracy dotyczą obiektów badanych w 2009 r. w 6 miejscowościach. Pod uwagę wzięto 10 cech: plon, MTZ, wysokość, odporność na wyleganie, przezimowanie, liczba dni do kłoszenia, liczba dni do dojrzałości, pylenie, odporność na mączniaka i rdzę brunatną. Celem pracy było: 1. zastosowanie analizy składowych głównych (PCA) na wartościach transformowanych dla cech wyrażonych w skali bonitacyjnej, 2. szczegółowe porównanie badanych form żyta przy użyciu regresji składowych głównych (PCR). Analiza składowych głównych PCA na wartościach poddanych transformacji wyjaśniła ponad 15% więcej zmienności całkowitej niż PCA na wartościach nietransformowanych dla trzech pierwszych składowych. Wyniki analizy PCR przedstawiono za pomocą wykresów przedstawiających zróżnicowanie badanych form żyta ozimego pod kątem wybranej cechy. Forma populacyjna HRSM 4 swoimi właściwościami zbliżona jest do form mieszańcowych.
The subjects of the study were 30 lines of winter rye examined in preliminary trials coordinated by the Plant Breeding and Acclimatization Institute, the Department of Cereals Crops in Cracow. The results presented in the paper concern objects examined in 6 locations in 2009. Ten traits were taken into account: grain yield, 1000 grains weight, plant height, lodging score, winter hardiness, no. of days to heading, no. of days to maturity, pollen fertility, powdery mildew score and brown rust score. The aim of the study was: firstly, the application of principal component analysis (PCA) on transformed values for traits formulated in valuation scale, secondly, detailed comparison of examined forms of winter rye using principal component regression (PCR). Principal component analysis PCA on values under transformation explained over 15% more total variation than PCA on non-transformed values for three first components. The results of PCR analysis are shown on graphs presenting diversity of examined forms of winter rye with consideration of particular traits. The population form HRSM 4 is similar, by its characteristics, to the hybrid lines.

Źródło:

Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin; 2011, 260/261; 251-262
0373-7837
2657-8913

Pojawia się w:

Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 60.

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

/5

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Skocz do pozycji: 61.

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

/5

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Skocz do pozycji: 62.

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

/5

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Skocz do pozycji: 63.

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

/5

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Skocz do pozycji: 64.

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

/5

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Skocz do pozycji: 65.

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

/5

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Skocz do pozycji: 66.

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

/5

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Skocz do pozycji: 67.

Tytuł:

PCA Based Components Selection Criteria for Computationally Efficient Physical Layer Key Generation (PLKG) System

Autorzy:

Sarsodia, Tapesh
Bhatt, Uma Rathore
Upadhyay, Raksha
Bhat, Vijay

Powiązania:

https://bibliotekanauki.pl/articles/27311925.pdf

Data publikacji:

2023

Wydawca:

Polska Akademia Nauk. Czasopisma i Monografie PAN

Tematy:

wireless networks
received signal strength
principal component analysis
physical layer key generation
Mean
Histfit

Opis:

Data security is one of the prime concerns in wireless networks. PLKG has been emerging as an attractive alternative to traditional cryptographic techniques. PLKG is more computationally efficient than cryptography. Moreover, PLKG using Principal component analysis (PCA) as pre-processing may further save computations. This paper proposes three mechanisms to select components of PCA which are based on Information content, Mean and Histfit. Bit Disagreement Rate (BDR) is compared for each mechanism. Histfit based method is found to be best. Since only two components are supposed to be processed for key generation, it is computationally efficient/ power efficient too.

Źródło:

International Journal of Electronics and Telecommunications; 2023, 69, 2; 361--369
2300-1933

Pojawia się w:

International Journal of Electronics and Telecommunications

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 68.

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

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Skocz do pozycji: 69.

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

/5

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Skocz do pozycji: 70.

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

/5

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Skocz do pozycji: 71.

Tytuł:

Wykorzystanie metody PCA i ICA do analizy sygnału EEG w kontekście usuwania zakłóceń
Use of PCA and ICA methods for analysis of EGG signal in context of removal of artefacts

Autorzy:

Paszkiel, S.

Powiązania:

https://bibliotekanauki.pl/articles/154789.pdf

Data publikacji:

2013

Wydawca:

Stowarzyszenie Inżynierów i Techników Mechaników Polskich

Tematy:

analiza artefaktów
analiza składowych głównych
analiza składowych niezależnych
EEG
analysis of artefacts
principal component analysis
independent component analysis

Opis:

W artykule przedstawiono metodę PCA (ang. Principal Component Analysis) oraz ICA (ang. Independent Component Analysis), jako narzędzia pomocne w procesie eliminacji artefaktów z sygnału elektroencefalograficznego. Proces rejestracji sygnału elektroencefalograficznego można zobrazować, jako BSS (ang. Blind Signals Separation). Dzięki temu możliwe jest dokonywanie estymacji nieznanych sygnałów źródłowych oraz ekstrakcji niepożądanych sygnałów zakłócających, w zakresie ich późniejszej eliminacji. W tym celu konieczne jest doskonalenie metod weryfikacji i eliminacji artefaktów z sygnału EEG. W artykule opisano możliwość zastosowania powyższych metod w zakresie sygnału EEG oraz zrealizowane zostało porównanie skuteczności ich działania.
: In the paper there are presented the Principal Component Analysis (PCA) and the Independent Component Analysis (ICA) as useful tools for elimination of artefacts in an electroencephalographic signal. The process of registration of the electroencephalographic signal can be described as BSS - Blind Signals Separation. It is possible to estimate unknown source signals and to extract intrusive disturbing signals in terms of their subsequent elimination. It is necessary to improve the methods of verification and elimination of artefacts from an EEG signal. The Brain Computer Interface (BCI) technology is presented briefly in the first part of the paper. EEG signal characteristics and its acqui-sition with the non-invasive method are described in the second part. Next, there is discussed the possibility of using the PCA and ICA methods in terms of analysis of an EEG signal. Comparison of the effectiveness of these methods is presented as well. A general profile of the EEG signal processing is shown in Fig. 1. An example of use of the infomax algorithm for a real EEG signal is depicted in Fig. 2. Fig. 3 shows an exemplary Event-Related Potential (ERP) of the EEG signal.

Źródło:

Pomiary Automatyka Kontrola; 2013, R. 59, nr 3, 3; 204-207
0032-4140

Pojawia się w:

Pomiary Automatyka Kontrola

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 72.

Tytuł:

Comparison of Selected Multiple Imputation Methods for Continuous Variables – Preliminary Simulation Study Results
Porównanie wybranych metod imputacji wielokrotnej dla zmiennych ilościowych – wstępne wyniki badań symulacyjnych

Autorzy:

Misztal, Małgorzata Aleksandra

Powiązania:

https://bibliotekanauki.pl/articles/656755.pdf

Data publikacji:

2018

Wydawca:

Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego

Tematy:

dane niekompletne
imputacja wielokrotna
analiza głównych składowych
missForest
incomplete data
multiple imputation
principal component analysis

Opis:

Problem występowania danych niekompletnych i ich wpływu na wyniki analiz statystycznych nie jest związany z żadną konkretną dziedziną nauki – pojawia się w ekonomii, socjologii, edukacji, naukach behawioralnych czy medycynie. W przypadku większości klasycznych metod statystycznych wymagana jest kompletna informacja o zmiennych charakteryzujących badane obiekty, a typowym podejściem do brakujących danych jest po prostu ich usunięcie. Prowadzi to jednak do niewiarygodnych i obciążonych wyników analiz i nie jest zalecane w literaturze przedmiotu. Rekomendowaną metodą postępowania z brakującymi danymi jest imputacja wielokrotna. W artykule rozważono kilka wybranych jej metod. Szczególną uwagę zwrócono na wykorzystanie analizy głównych składowych (PCA) jako metody imputacji. Celem pracy była ocena jakości imputacji opartej na PCA na tle dwóch innych technik uzupełniania braków danych: imputacji wielokrotnej za pomocą równań łańcuchowych (MICE) i metody missForest. Porównania metod imputacji dokonano, wykorzystując podejście symulacyjne i generując braki danych w 10 kompletnych zbiorach danych z repozytorium baz danych Uniwersytetu Kalifornijskiego w Irvine, z uwzględnieniem różnych mechanizmów generowania braków danych oraz różnych proporcji (10–50%) brakujących wartości. Do imputacji brakujących wartości zastosowano metodę równań łańcuchowych, metodę missForest oraz metodę opartą na głównych składowych (MIPCA). Znormalizowany pierwiastek kwadratowy błędu średniokwadratowego (NRMSE) wykorzystano jako miarę dokładności imputacji. Na podstawie przeprowadzonych analiz metoda missForest może być rekomendowana jako ta metoda wielokrotnej imputacji, która zapewnia najwyższą dokładność imputacji braków danych. Imputacja oparta na analizie głównych składowych (PCA) nie prowadzi do zadowalających wyników.
The problem of incomplete data and its implications for drawing valid conclusions from statistical analyses is not related to any particular scientific domain, it arises in economics, sociology, education, behavioural sciences or medicine. Almost all standard statistical methods presume that every object has information on every variable to be included in the analysis and the typical approach to missing data is simply to delete them. However, this leads to ineffective and biased analysis results and is not recommended in the literature. The state of the art technique for handling missing data is multiple imputation. In the paper, some selected multiple imputation methods were taken into account. Special attention was paid to using principal components analysis (PCA) as an imputation method. The goal of the study was to assess the quality of PCA‑based imputations as compared to two other multiple imputation techniques: multivariate imputation by chained equations (MICE) and missForest. The comparison was made by artificially simulating different proportions (10–50%) and mechanisms of missing data using 10 complete data sets from the UCI repository of machine learning databases. Then, missing values were imputed with the use of MICE, missForest and the PCA‑based method (MIPCA). The normalised root mean square error (NRMSE) was calculated as a measure of imputation accuracy. On the basis of the conducted analyses, missForest can be recommended as a multiple imputation method providing the lowest rates of imputation errors for all types of missingness. PCA‑based imputation does not perform well in terms of accuracy.

Źródło:

Acta Universitatis Lodziensis. Folia Oeconomica; 2018, 6, 339; 73-98
0208-6018
2353-7663

Pojawia się w:

Acta Universitatis Lodziensis. Folia Oeconomica

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 73.

Tytuł:

Assessment of soil quality in organic and non-organic paddy fields with technical irrigation system in Susukan

Autorzy:

Haryuni, H.
Wirawati, H.
Minardi, S.
Supriyadi, S.

Powiązania:

https://bibliotekanauki.pl/articles/971160.pdf

Data publikacji:

2020

Wydawca:

Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej

Tematy:

soil quality
paddy fields
principal component analysis
minimum data set (mds)
soil quality index (sqi)

Opis:

Soil quality is a measure of the condition of soil. The goal of sustainable agriculture is to maintain a non-negative trend in productivity while maintaining soil quality. Susukan is an area in Semarang, Central Java, Indonesia, which has developed organic farming to increase rice productiv- ity and quality. The main objective was to determine the sustainability of organic rice cropping sys- tems. The organic farming system at the research location has been conducted for 8 years. Appropri- ate agricultural management can maintain the quality of soil, environment and improve the health of plants, animals and humans. This research aims to know the soil quality and determine the minimum data set (MDS) in organic and non-organic paddy field with a technical irrigation system. Paddy soil samples were analyzed in the laboratory. The parameters are porosity, permeability, hydrogen potential (pH), cation exchange capacity (CEC), soil organic matter (SOC), total-N (nitrogen), car- bon/nitrogen (C/N) ratio, available-P (phosphorus), available-K (potassium), base saturation (BS), electric conductivity (EC), soil respiration (qCO2), redox potential (Eh) with 3 repetitions. The value of soil quality index (SQI) in the organic paddy field is 3.216 with bad soil quality criteria, while the non-organic paddy field is 0.147 with very bad criteria. The soil quality values are based on the key factors or MDS that is potential redox (EH), soil respiration (qCO2), potential hydrogen (pH), poros- ity, soil organic matter (SOC), total-N (nitrogen), C/N ratio, available-P (phosphorus).

Źródło:

Polish Journal of Soil Science; 2020, 53, 1
0079-2985

Pojawia się w:

Polish Journal of Soil Science

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 74.

Tytuł:

Soil quality assessment of the rainfed lowland ricefields under organic and conventional farming systems in Kaliwungu (Central Java)

Autorzy:

Supriyadi, Supriyadi
Rachmawati, Septiana
Herawati, Aktavia
Purwanto, Purwanto

Powiązania:

https://bibliotekanauki.pl/articles/762795.pdf

Data publikacji:

2018

Wydawca:

Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej

Tematy:

soil quality index (SQI), rainfed lowland rice, principal component analysis (PCA), minimum data set (MDS)

Opis:

Rainfed lowland rice is grown in land where the irrigation systems depend on rainwater. The use of chemical fertilizers in large quantities in order to improve production of rice will result in soil quality degradation. In order to improve the condition of the soil, a system of organic farming was provided. The aim of this study was to quantify soil quality in rainfed lowland ricefilds using soil quality indexes (SQI) and to compare SQIs of farming system under organic and conventional fertilization. The sample consists of seven sample points on soil fertilized organically and three sample points on soil which is managed in a conventional way, each taken from 5 subpoints at a depth of 0–30 cm and analyzed for 12 soil variables. The best representative soil quality variables forming a minimum data set (MDS) were selected using principal component analysis (PCA), and soil quality scores were obtained using both linear and non-linear scoring functions. The study results indicate that in case of organic farming system, the soil quality was better (SQI = 2.079) when compared to its quality in the conventional farming system (SQI = 1.397). The selected indicators used as the MDS are soil porosity, cation exchange capacity (CEC), soil organic carbon, C/N ratio, soil permeability, available-P (Av-P), and electrical conductivity (EC)

Źródło:

Polish Journal of Soil Science; 2018, 51, 2
0079-2985

Pojawia się w:

Polish Journal of Soil Science

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 75.

Tytuł:

Identification of changes of machine technical state on the basis of results of principle component analysis of a sequence of thermographic images
Identyfikacja zmian stanu obiektów technicznych na podstawie wyników analizy głównych składowych sekwencji zdjęć termograficznych

Autorzy:

Fidali, M.
Bzymek, A.

Powiązania:

https://bibliotekanauki.pl/articles/327752.pdf

Data publikacji:

2009

Wydawca:

Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN

Tematy:

diagnostyka
maszyna
termowizja
termografia
analiza głównych składowych
machine
diagnostics
thermovision
thermography
principal component analysis
PCA

Opis:

During continuous object observation with the use of a thermographic device, a sequence of thermographic images can be recorded in time function. On the basis of an acquired series of thermograms, determination of diagnostic signals and identification of changes of a machine technical state is possible. An approach presented in the paper concerns application of a Principal Component Analysis (PCA) method. In order to verify the method, an active diagnostic experiment, during which sequences of thermographic images were recorded and analyzed according to their components, was carried out. The obtained results showed that diagnostic signals provided by PCA could be used for identification of changes of a technical state as well as classification of the state with considerably high efficiency.
Podczas ciągłej obserwacji termowizyjnej obiektu technicznego rejestrowana jest sekwencja obrazów w czasie. Na podstawie zarejestrowanej sekwencji obrazów możliwe jest wyznaczenie sygnałów diagnostycznych pozwalających na identyfikację stanu technicznego obserwowanego obiektu. W artykule zaproponowano metodę diagnozowania maszyn na podstawie wyników analizy składowych głównych (PCA) sekwencji obrazów termowizyjnych. W celu weryfikacji metody przeprowadzono czynny eksperyment diagnostyczny, podczas którego rejestrowano sekwencje obrazów, które poddano analizie składowych. Uzyskane wyniki wykazały, że metoda składowych głównych pozwala na identyfikację zmian stanu technicznego oraz efektywną klasyfikację stanu technicznego maszyny.

Źródło:

Diagnostyka; 2009, 3(51); 45-48
1641-6414
2449-5220

Pojawia się w:

Diagnostyka

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 76.

Tytuł:

Assessment of soil quality in organic and non-organic paddy fields with technical irrigation system in Susukan

Autorzy:

Haryuni, Haryuni
Wirawati, Hesti
Minardi, Slamet
Supriyadi, Supriyadi

Powiązania:

https://bibliotekanauki.pl/articles/2088202.pdf

Data publikacji:

2020

Wydawca:

Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej

Tematy:

soil quality
paddy fields
principal component analysis
minimum data set (MDS)
soil quality index (SQI)

Opis:

Soil quality is a measure of the condition of soil. The goal of sustainable agriculture is to maintain a non-negative trend in productivity while maintaining soil quality. Susukan is an area in Semarang, Central Java, Indonesia, which has developed organic farming to increase rice productivity and quality. The main objective was to determine the sustainability of organic rice cropping systems. The organic farming system at the research location has been conducted for 8 years. Appropriate agricultural management can maintain the quality of soil, environment and improve the health of plants, animals and humans. This research aims to know the soil quality and determine the minimum data set (MDS) in organic and non-organic paddy field with a technical irrigation system. Paddy soil samples were analyzed in the laboratory. The parameters are porosity, permeability, hydrogen potential (pH), cation exchange capacity (CEC), soil organic matter (SOC), total-N (nitrogen), carbon/nitrogen (C/N) ratio, available-P (phosphorus), available-K (potassium), base saturation (BS), electric conductivity (EC), soil respiration (qCO2), redox potential (Eh) with 3 repetitions. The value of soil quality index (SQI) in the organic paddy field is 3.216 with bad soil quality criteria, while the non-organic paddy field is 0.147 with very bad criteria. The soil quality values are based on the key factors or MDS that is potential redox (EH), soil respiration (qCO2), potential hydrogen (pH), porosity, soil organic matter (SOC), total-N (nitrogen), C/N ratio, available-P (phosphorus).

Źródło:

Polish Journal of Soil Science; 2020, 53, 1; 81-95
0079-2985

Pojawia się w:

Polish Journal of Soil Science

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 77.

Tytuł:

Korelacje między wybranymi zanieczyszczeniami w ściekach deszczowych
Correlation between selected pollutants in rainfall wastewater

Autorzy:

Górska, K.
Szeląg, B.
Górski, J.
Bąk, Ł.

Powiązania:

https://bibliotekanauki.pl/articles/125912.pdf

Data publikacji:

2014

Wydawca:

Towarzystwo Chemii i Inżynierii Ekologicznej

Tematy:

ścieki deszczowe
metale ciężkie
analiza składowych głównych
biplot
rainfall wastewater
heavy metals
principal component analysis

Opis:

W ostatnim okresie coraz częściej zwraca się uwagę na fakt, że zanieczyszczenia ścieków deszczowych to nie tylko definiowane odpowiednimi przepisami zawiesiny ogólne i związki ropopochodne, ale też inne związki mające wpływ na środowisko gruntowe i wody odbiornika. Należą do nich m.in. metale ciężkie, chlorki, siarczany, biogeny, zanieczyszczenia mikrobiologiczne. Zróżnicowanie czynników wpływających na jakość ścieków deszczowych, związanych między innymi z zanieczyszczeniem powietrza atmosferycznego czy rodzajem pokrycia terenu oraz prowadzonej działalności człowieka, powoduje, że określenie typowego ich składu jest zadaniem bardzo trudnym, szczególnie jeśli mamy do czynienia z terenami zurbanizowanymi. W rezultacie duże zanieczyszczenie wód opadowych odprowadzanych z terenów miejskich wpływa zdecydowanie na okresowe pogorszenie stanu czystości wód oraz destabilizuje równowagę biologiczną w odbiorniku. W artykule przedstawiono wyniki badań stanu zanieczyszczenia ścieków deszczowych spływających systemem kanalizacyjnym z obszaru wybranej zlewni o typowo miejskim charakterze, zlokalizowanej w centrum Kielc. Do analiz wytypowano wezbrania z okresu letniego i zimowego, w czasie których pobrano za pomocą automatycznego samplera próby ścieków deszczowych i roztopowych. Oznaczono w nich stężenia metali ciężkich (Ni, Cu, Cr, Zn, Pb, Cd), chlorków oraz określono pH i temperaturę. Do oceny korelacji między analizowanymi wskaźnikami zanieczyszczeń zastosowano metodę składowych głównych, a na tej podstawie sporządzono biploty oraz wyznaczono współrzędne czynnikowe.
Recently, increasing attention has been paid to the fact that the rainfall wastewater pollution is defined not only by the suspended solids and oil derivatives, the admissible levels of which are given in regulations, but also by other compounds that affect the soil environment and the waters of the receiver. Those include, among others, heavy metals, chlorides, sulphates, biogenic substances, and microbiological pollutants. The quality of rainfall wastewater is influenced, among others by atmospheric air pollution, type of terrain coverage, and human activity. Diversity of factors that affect the quality of rainfall wastewater is enormous, which makes it extremely difficult to determine a typical composition of such wastewater, especially in urbanised areas. As a result, high pollution of rainfall waters running off from urban areas has a decisive impact on periodic deterioration of water purity and it disturbs the biological balance in the receiver. The paper presents the results of investigations on the pollution of rainfall wastewater running off, through a sewer system, from the area of selected catchment, typically urban in character, located in the centre of Kielce. The analysis was conducted for high water stages occurring in summer and winter periods. Samples of rainfall and spring thaw wastewater were collected using an automatic sampler. Heavy metals (Ni, Cu, Cr, Zn, Pb, Cd) and chloride concentrations, pH and temperature were determined for those samples. To assess the correlation between analysed pollution indexes, the Principal Component Analysis was used, on the basis of which biplots were made and factor coordinates were determined.

Źródło:

Proceedings of ECOpole; 2014, 8, 2; 497-504
1898-617X
2084-4557

Pojawia się w:

Proceedings of ECOpole

Dostawca treści:

Biblioteka Nauki

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Skocz do pozycji: 78.

Tytuł:

Chemical composition and nutritional value of maize grains from cultivars of different breeding and seed companies
Skład chemiczny oraz wartość pokarmowa ziarna kukurydzy odmian różnych firm hodowlano-nasiennych

Autorzy:

Szulc, P.
Podkówka, Z.
Bocianowski, J.
Krauklis, D.
Wilczewska, W.

Powiązania:

https://bibliotekanauki.pl/articles/337591.pdf

Data publikacji:

2018

Wydawca:

Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Maszyn Rolniczych

Tematy:

maize
grain
cultivars
nutritional value
principal component analysis
kukurydza
ziarno
odmiana
wartość odżywcza
analiza składników

Opis:

The study presents the results of field experiments aimed at assessing the level of yield, chemical composition and nutritive value of grain of 32 maize cultivars from different breeding and seed companies. The grain yield, grain chemical composition, fiber fraction content, grain nutritional value, thousand seed weight and grain density were determined to verify the adopted assumptions. The highest content of starch, total protein, fat and nitrogen-free extract compounds was found in the cultivars of the following companies: Limagrain, IGP, Saaten-Union and Maisadour, while the lowest in IGP, Maisadour, Limagrain and IGP, respectively. The energy value of 1 kg dry weight of maize grain for poultry ranged from 14.60 (Maisadour) to 15.22 MJ EM (IGP) and statistically significant differences in the concentration of metabolic energy for poultry was found only in the grain from these companies. Concentration of metabolic energy for pigs ranged from 15.79 (Limagrain) to 15.93 MJ (Saaten-Union) and statistically significant differences in the concentration of metabolic energy for pigs were recorded only in the grain from these companies. Grains from Saaten-Union had a higher concentration of net lactation energy than those from Limagrain and Maisadour. Crude protein, net energy of lactation, sugar, exhaust nitrogenless compounds, weight of one thousand seeds (WTS) and grain density influence on differentiation maize’s cultivars.
W pracy przedstawiono wyniki badań polowych, których celem była ocena poziomu plonowania, składu chemicznego oraz wartości pokarmowej ziarna 32 odmian kukurydzy różnych firm hodowlano-nasiennych. Celem weryfikacji przyjętych założeń określono plon ziarna, skład chemiczny ziarna, zawartość frakcji włókna, wartość pokarmową ziarna, masę tysiąca ziaren oraz gęstość ziarna. Największą zawartość skrobi, białka ogólnego, tłuszczu oraz związków bezazotowych wyciągowych stwierdzono w odmianach firm: Limagrain, IGP, Saaten-Union oraz Maisadour, natomiast najniższą odpowiednio w firmach IGP, Maisadour, Limagrain, IGP. Wartość energetyczna 1 kg suchej masy ziarna kukurydzy dla drobiu wahała się od 14,60 (Maisadour) do 15,22 MJ EM (IGP) i tylko w ziarnie pochodzącym z tych firm odnotowano różnice istotne statystycznie w koncentracji energii metabolicznej dla drobiu. Koncentracja energii metabolicznej dla świń wahała się od 15,79 (Limagrain) do 15,93 MJ (Saaten-Union) i tylko w ziarnie pochodzącym z tych firm odnotowano różnice istotne statystycznie w koncentracji energii metabolicznej dla świń. Ziarna z firmy Saaten-Union miały wyższą koncentrację energii netto laktacji niż z firmy Limagrain oraz Maisadour.

Źródło:

Journal of Research and Applications in Agricultural Engineering; 2018, 63, 4; 203-208
1642-686X
2719-423X

Pojawia się w:

Journal of Research and Applications in Agricultural Engineering

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 79.

Tytuł:

Application of Statistical Features and Multilayer Neural Network to Automatic Diagnosis of Arrhythmia by ECG Signals

Autorzy:

Slama, A. B.
Lentka, Ł.
Mouelhi, A.
Diouani, M. F.
Sayadi, M.
Smulko, J.

Powiązania:

https://bibliotekanauki.pl/articles/221289.pdf

Data publikacji:

2018

Wydawca:

Polska Akademia Nauk. Czytelnia Czasopism PAN

Tematy:

Multilayer Neural Network
arrhythmia diagnosis
ECG signal processing
Principal Component Analysis
Fisher’s Linear Discriminant

Opis:

Abnormal electrical activity of heart can produce a cardiac arrhythmia. The electrocardiogram (ECG) is a non-invasive technique which is used as a diagnostic tool for cardiac diseases. Non-stationarity and irregularity of heartbeat signal imposes many difficulties to clinicians (e.g., in the case of myocardial infarction arrhythmia). Fortunately, signal processing algorithms can expose hidden information within ECG signal contaminated by additive noise components. This paper explores a method of de-noising ECG signal by the discrete wavelet transform (DWT) and further detecting arrhythmia by estimated statistical parameters. Parameters of the de-noised ECG signals were used to form an input data vector determining whether the examined patient suffers from a cardiac arrhythmia or not. Input data were transformed using selected linear methods in order to reduce dimension of the input vector. A neural network was used to detect illness. Compared with the results of recent studies, the proposed method provides more accurate diagnosis based on the examined ECG signal data.

Źródło:

Metrology and Measurement Systems; 2018, 25, 1; 87-101
0860-8229

Pojawia się w:

Metrology and Measurement Systems

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 80.

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

/5

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Skocz do pozycji: 81.

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

/5

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Skocz do pozycji: 82.

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

/5

Artykuł

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Skocz do pozycji: 83.

Tytuł:

An efficient eigenspace updating scheme for high-dimensional systems

Autorzy:

Gangl, S.
Mongus, D.
Žalik, B.

Powiązania:

https://bibliotekanauki.pl/articles/330681.pdf

Data publikacji:

2014

Wydawca:

Uniwersytet Zielonogórski. Oficyna Wydawnicza

Tematy:

eigenspace updating
projection space
data compression
principal component analysis
przestrzeń rzutowa
kompresja danych
analiza składowych głównych

Opis:

Systems based on principal component analysis have developed from exploratory data analysis in the past to current data processing applications which encode and decode vectors of data using a changing projection space (eigenspace). Linear systems, which need to be solved to obtain a constantly updated eigenspace, have increased significantly in their dimensions during this evolution. The basic scheme used for updating the eigenspace, however, has remained basically the same: (re)computing the eigenspace whenever the error exceeds a predefined threshold. In this paper we propose a computationally efficient eigenspace updating scheme, which specifically supports high-dimensional systems from any domain. The key principle is a prior selection of the vectors used to update the eigenspace in combination with an optimized eigenspace computation. The presented theoretical analysis proves the superior reconstruction capability of the introduced scheme, and further provides an estimate of the achievable compression ratios.

Źródło:

International Journal of Applied Mathematics and Computer Science; 2014, 24, 1; 123-131
1641-876X
2083-8492

Pojawia się w:

International Journal of Applied Mathematics and Computer Science

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 84.

Tytuł:

Porównanie wybranych statystycznych metod analizy danych hydrogeochemicznych na przykładzie kenozoicznych poziomów wodonośnych w obszarze zlewni Gwdy
Comparison of selected statistical methods of hydrogeochemical data analysis exemplified by Cenozoic aquifers within the Gwda River basin

Autorzy:

Kotowski, T.

Powiązania:

https://bibliotekanauki.pl/articles/2062952.pdf

Data publikacji:

2011

Wydawca:

Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy

Tematy:

hydrogeochemia
analiza skupień
analiza składowych głównych
analiza czynnikowa
hydrogeochemistry
cluster analysis
principal component analysis
factor analysis

Opis:

W pracy zaprezentowano porównanie wybranych metod wnioskowania statystycznego, stosowanych w badaniach hydrogeochemicznych. Metody statystyczne zostały zastosowane w celu wstępnej identyfikacji procesów formowania składu chemicznego wód poziomów mioceńskiego i głębokiego plejstoceńskiego na obszarze zlewni Gwdy. W rezultacie przeprowadzonej analizy skupień otrzymano trzy grupy (skupienia) czynników kształtujących skład chemiczny wód podziemnych. W wyniku analizy składowych głównych i analizy czynnikowej wyróżniono zbiory dwóch czynników kształtujących skład chemiczny wód podziemnych. Wszystkie zastosowane metody okazały się wrażliwe na występowanie anomalii hydrogeochemicznych. Z tego względu, w przypadku analizy skupień i analizy składowych głównych, niemożliwe było dokonanie w pełni poprawnego opisu chemizmu wód podziemnych w obszarze badań. Najlepsze rezultaty osiągnięto przy zastosowaniu analizy czynnikowej. Wyniki analiz statystycznych odniesiono do rezultatów dodatkowych badań: składu izotopowego wody, stężeń siarczanów, trytu oraz badań mikrobiologicznych. Zastosowane metody statystyczne okazały się pomocne, jednakże interpretacja uzyskanych, szczególnie zróżnicowanych danych, jest utrudniona.
Comparison of selected methods of hydrogeochemical statistical analysis is presented in the paper. Statistical methods were applied to initially identify the formation processes of groundwater chemical composition within the Gwda river basin. As a result of a cluster analysis, three cluster sets of factors forming the chemical composition of the groundwater were distinguished. A set of two factors forming the chemical composition of the groundwater was distinguished as a result of a principal component analysis and a factor analysis. All the statistical methods used were found out to be susceptible upon hydrogeochemical anomalies. The observed susceptibility of the cluster analysis and the principal component analysis allowed a fully correct description of the formation of the groundwater chemical composition in the study area. The best results were achieved using the factor analysis, but this method is also susceptible upon the anomaly cases. The results of the statistical analysis were compared with the research results of additional factors such as the isotopic composition of water and concentrations of sulfates and tritium. The statistical methods appeared to be helpful. However, the interpretation of research results without the additional factors is intractable, especially in the case of hydrogeochemical anomalies.

Źródło:

Biuletyn Państwowego Instytutu Geologicznego; 2011, 447; 15--24
0867-6143

Pojawia się w:

Biuletyn Państwowego Instytutu Geologicznego

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 85.

Tytuł:

The influence of the principal component analysis of texture features on the classification quality of sponge tissue images
Wpływ analizy głównych składowych cech tekstury na jakość klasyfikacji obrazów tkanki gąbczastej

Autorzy:

Dzierżak, Róża

Powiązania:

https://bibliotekanauki.pl/articles/1841333.pdf

Data publikacji:

2020

Wydawca:

Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej

Tematy:

principal component analysis
classification
texture analysis
medical imaging
analiza głównych składowych
klasyfikacja
analiza tekstury
obrazowanie medyczne

Opis:

The aim of this article was to determine the effect of principal component analysis on the results of classification of spongy tissue images. Four hundred computed tomography images of the spine (L1 vertebra) were used for the analyses. The images were from fifty healthy patients and fifty patients diagnosed with osteoporosis. The obtained tissue image samples with a size of 50x50 pixels were subjected to texture analysis. As a result, feature descriptors based on a grey level histogram, gradient matrix, RL matrix, event matrix, autoregressive model and wavelet transform were obtained. The results obtained were ranked in importance from the most important to the least important. The first fifty features from the ranking were used for further experiments. The data were subjected to the principal component analysis, which resulted in a set of six new features. Subsequently, both sets (50 and 6 traits) were classified using five different methods: naive Bayesian classifier, multilayer perceptrons, Hoeffding Tree, 1-Nearest Neighbour and Random Forest. The best results were obtained for data on which principal components analysis was performed and classified using 1-Nearest Neighbour. Such an algorithm of procedure allowed to obtain a high value of TPR and PPV parameters, equal to 97.5%. In the case of other classifiers, the use of principal component analysis worsened the results by an average of 2%.
Celem niniejszego artykułu było określenie wpływu analizy głównych składowych na wyniki klasyfikacji obrazów tkanki gąbczastej. Do analiz wykorzystano czterysta obrazów tomografii komputerowej kręgosłupa (kręg L1). Obrazy pochodziły od pięćdziesięciu zdrowych pacjentów oraz pięćdziesięciu pacjentów ze zdiagnozowaną osteoporozą. Uzyskane próbki obrazowe tkanki o wymiarze 50x50 pikseli poddano analizie tekstury. W wyniku tego otrzymano deskryptory cech oparte na histogramie poziomów szarości, macierzy gradientu, macierzy RL, macierzy zdarzeń, modelu autoregresji i transformacie falkowej. Otrzymane wyniki ustawiono w rankingu ważności od najistotniejszej do najmniej ważnej. Pięćdziesiąt pierwszych cech z rankingu wykorzystano do dalszych eksperymentów. Dane zostały poddane analizie głównych składowych wskutek czego uzyskano zbiór sześciu nowych cech. Następnie oba zbiory (50 i 6 cech) zostały poddane klasyfikacji przy użyciu pięciu różnych metod: naiwnego klasyfikatora Bayesa, wielowarstwowych perceptronów, Hoeffding Tree, 1-Nearest Neighbour and Random Forest. Najlepsze wyniki uzyskano dla danych, na których przeprowadzono analizę głównych składowych i poddano klasyfikacji za pomocą 1-Nearest Neighbour. Taki algorytm postępowania pozwolił na uzyskanie wysokiej wartości parametrów TPR oraz PPV, równych 97,5%. W przypadku pozostałych klasyfikatorów zastosowanie analizy głównych składowych pogorszyło wyniki średnio o 2%.

Źródło:

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2020, 10, 3; 13-16
2083-0157
2391-6761

Pojawia się w:

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 86.

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

/5

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Skocz do pozycji: 87.

Tytuł:

Przenośny analizator diagnostyczny do wykrywania uszkodzeń stojana i wirnika w silnikach indukcyjnych
Portable Diagnostic Analyzer to Detection of the Stator and Rotor Faults in Induction Motors

Autorzy:

Pawlak, M.

Powiązania:

https://bibliotekanauki.pl/articles/1368211.pdf

Data publikacji:

2016

Wydawca:

Sieć Badawcza Łukasiewicz - Instytut Napędów i Maszyn Elektrycznych Komel

Tematy:

silnik indukcyjny
diagnostyka
analiza częstotliwościowa
analiza składowych głównych
induction motor
diagnostics
spectral analysis
principal component analysis

Opis:

This paper presents a novel design of a portable diagnostic analyzer, which is designed to fault detection of stator windings and the broken rotor bars in the induction motors of different power ratings. The measuring circuit of the system consists of two multi-range current clamps to measure the motor line current in two phases. Measurement signals are fed to the microprocessor-based recorder that transmits data samples to a portable computer using wireless communication technology - Bluetooth. In the role of the computer can be used any Android device (e.g. tablet), or ordinary notebook with Windows OS. Diagnostic software installed on a laptop computer analyzes the recorded signals of stator current, in terms of finding the diagnostic features characteristic of the stator and rotor faults. For this purpose, the current Park's vector modulus analysis and principal component analysis (PCA) were implemented.
W artykule przedstawiono nowatorską konstrukcję przenośnego analizatora diagnostycznego, który jest przeznaczony do wykrywania uszkodzeń uzwojeń stojana i wirnika w silnikach indukcyjnych o różnych mocach. Część pomiarową systemu stanowią dwa wielozakresowe przetworniki cęgowe, które mierzą prąd silnika w dwóch fazach. Sygnały pomiarowe doprowadzone są do mikroprocesorowego rejestratora, który przesyła próbki pomiarowe do komputera przenośnego, wykorzystując bezprzewodową technologię komunikacyjną - Bluetooth. W roli komputera można zastosować dowolne urządzenie z systemem Android (np. tablet), albo zwykły komputer przenośny (laptop) z systemem Windows. Oprogramowanie diagnostyczne zainstalowane na komputerze przenośnym analizuje zarejestrowane sygnały prądu stojana, pod kątem znalezienia diagnostycznych cech, charakterystycznych dla uszkodzeń stojana i wirnika. W tym celu zaimplementowano metody analizy częstotliwościowej wektora przestrzennego prądu stojana oraz metody analizy składowych głównych (PCA).

Źródło:

Maszyny Elektryczne: zeszyty problemowe; 2013, 3, 100/1; 177-182
0239-3646
2084-5618

Pojawia się w:

Maszyny Elektryczne: zeszyty problemowe

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 88.

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

/5

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Skocz do pozycji: 89.

Tytuł:

Classifying railway passenger stations for use transport planning – application to Bulgarian railway network
Classification des gares de chemin de fer de passagers concernant l’emploi de planification des transports –application pour le réseau de fer de la Bulgarie

Autorzy:

Stoilova, S.
Nikolova, R.

Powiązania:

https://bibliotekanauki.pl/articles/374397.pdf

Data publikacji:

2016

Wydawca:

Politechnika Śląska. Wydawnictwo Politechniki Śląskiej

Tematy:

principal component
cluster analysis
railway station
passengers
classification
główne składowe
analiza klasterów
stacja kolejowa
pasażerowie
klasyfikacja

Opis:

A methodology for the classification of railway passenger stations was developed in this study. Four groups of factors are defined to study the characteristics of the station: potential of the town, importance of the town, infrastructural factors, and characteristics of passengers. In the research we investigated 18 factors and studied 98 passenger stations of railway network in Bulgaria. The method of principal components has been applied for grouping the factors and cluster analysis has been applied to classify the stations. The factors have been classified into 4 components by the method of principal components. The stations have been classified into 6 groups using hierarchical cluster analysis. The methods, Average linkage between group and Within-groups linkage, and distance-type measures Euclidean distance and Squared Euclidean distance were compared to verify the results of cluster analysis. The grouping of the stations has been used for the determination of the stops for categories intercity passenger trains. The main groups of stations for servicing express trains are the first, second, third, fourth and fifth groups. In the sixth group are stations for servicing fast passenger trains. The methodology can be applied to the study of all stations and stops in the rail network.
Dans cette étude est élaborée la méthodologie de classification des gares de passagers. On a déterminé 4 groupes de facteurs pour l’étude des caractéristiques des gares: le potentiel de la ville, importance de la ville, facteurs infrastructurels et caractéristiques des passagers.18 facteurs sont étudiés au total. On a étudié 98 gares de passagers du réseau de fer de la Bulgarie. On a appliqué les méthodes des composantes générales pour le groupement des facteurs et une analyse de cluster pour le classement des gares. D’après la méthode des composantes générales les facteurs sont classifiés en 4 groupes. D’après la méthode de l’analyse hiérarchique les gares sont classifiées en 6 groupes. Les méthodes de liaison moyenne entre le groupe et les intra-groupes de liaison et la distance de type Euclidienne au carré ont été comparées à la verification des résultats de l’analyse de cluster. Le groupement des gares est utilize pour déterminer les arrêts des cathégories des trains de passagers interurbains. Les groups de gares essentiels concernant le service des trains express sont premier, deuxième, troisième, quatrième et cinquième groupe. Le sixième groupe comprend les gares pour le service des TGV. La méthodologie peut être appliquée pour l’étude de toutes les gares et stations dans le réseau de chemin de fer.

Źródło:

Transport Problems; 2016, 11, 2; 143-155
1896-0596
2300-861X

Pojawia się w:

Transport Problems

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 90.

Tytuł:

Intrusion detection system based on neural networks
System wykrywania włamań opartych na sieciach neuronowych

Autorzy:

Sachenko, A.
Komar, M.

Powiązania:

https://bibliotekanauki.pl/articles/322796.pdf

Data publikacji:

2014

Wydawca:

Politechnika Śląska. Wydawnictwo Politechniki Śląskiej

Tematy:

intrusion detection system
neural networks
principal component analysis
system wykrywania włamań
sieci neuronowe
analiza głównych składowych

Opis:

Designing the neural network detector of attacks using the vector quantization is considered in this paper. It's based on improved method for hierarchical classification of computer attacks and the information compression using the principal component analysis and combining the neural network detectors.
W artykule zaprezentowano podejście do projektowania detektora ataków komputerowych za pomocą sieci neuronowej i kwantyzacji wektorowej. Bazuje ono na ulepszonej metodzie hierarchicznej klasyfikacji ataków komputerowych i kompresji informacji za pomocą analizy głównych składowych i łączenia sieci neuronowych detektorów.

Źródło:

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2014, 68; 377-386
1641-3466

Pojawia się w:

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 91.

Tytuł:

Principal components of innovation performance in European Union countries
Główne składowe innowacyjności w krajach Unii Europejskiej

Autorzy:

Kleszcz, Agnieszka

Powiązania:

https://bibliotekanauki.pl/articles/1813754.pdf

Data publikacji:

2021-08-31

Wydawca:

Główny Urząd Statystyczny

Tematy:

innovation
European Innovation Scoreboard
EIS
principal component analysis
PCA
innowacje
Europejski Ranking Innowacyjności
analiza głównych składowych

Opis:

Innovation is one of the main determinants of economic development. Innovative activity is very complex, thus difficult to measure. The complexity of the phenomenon poses a great challenge for researchers to understand its determinants. The article focuses on the problem of innovation-related geographical disparities among European Union countries. Moreover, it analyses the principal components of innovation determined on the basis of the European Innovation Scoreboard (EIS) dimensions. The aim of the paper is to identify the principal components of the innovation index which differentiate countries by analysing the structure of the correlation between its components. All calculations were based on indicators included in the EIS 2020 Database, containing data from the years 2012–2019. A comparative analysis of the studied countries’ innovation performance was carried out, based on the principal component analysis (PCA) method, with the purpose of finding the uncorrelated principal components of innovation which differentiate the studied countries. The results were achieved by reducing a 10-dimensional data set to a 2-dimensional one, for a simpler interpretation. The first principal component (PC1) consisted of the human resources, attractive research systems, and finance and support dimensions (understood as academia and finance). The second principal component (PC2), involving the employment impacts and linkages dimensions, was interpreted as business-related. PC1 and PC2 jointly explained 68% of the observed variance, and similar results were obtained for the 27 detailed indicators outlined in the EIS. We can therefore assume that we have an accurate representation of the information contained in the EIS data, which allows for an alternative assessment and ranking of innovation performance. The proposed simplified index, described in a 2-dimensional space, based on PC1 and PC2, makes it possible to group countries in a new way, according to their level of innovation, which offers a wide range of application, e.g. PC1 captures geographic disparities in innovation corresponding to the division between the old and new EU member states.
Innowacyjność należy do głównych wyznaczników rozwoju gospodarczego. Działalność innowacyjna jest bardzo złożona, a przez to trudna do zmierzenia. Dużym wyzwaniem dla badaczy jest także poznanie uwarunkowań tego zjawiska. W artykule skupiono się na problemie zróżnicowania terytorialnego innowacyjności wśród krajów Unii Europejskiej, a także a Uniwersytet Jana Kochanowskiego w Kielcach, Wydział Nauk Ścisłych i Przyrodniczych, Instytut Geografii i Nauk o Środowisku, Polska / Jan Kochanowski University of Kielce, Faculty of Natural Sciences, Institute of Geography and Environmental Sciences, Poland. ORCID: https://orcid.org/0000-0002-0450-5247. E-mail: agakleszcz87@gmail.com. © Główny Urząd Statystyczny A. KLESZCZ Principal components of innovation performance in European Union countries 25 na analizie głównych składowych innowacyjności wyznaczonych przy wykorzystaniu wskaźników uwzględnianych w Europejskim Rankingu Innowacyjności (European Innovation Scoreboard – EIS). Celem badania omawianego w artykule jest identyfikacja głównych składowych innowacyjności różnicujących kraje na podstawie analizy struktury korelacji. Obliczenia oparto na wskaźnikach zawartych w bazie EIS 2020, obejmujących 2012–2019. Przeprowadzono analizę porównawczą krajów pod kątem wydajności innowacyjnej przy użyciu metody analizy głównych składowych (PCA), aby znaleźć nieskorelowane główne składowe innowacji różnicujące kraje. Wyniki uzyskano dzięki zredukowaniu 10-wymiarowego zestawu danych do zestawu 2-wymiarowego, łatwiejszego do interpretacji. Pozwoliło to wyróżnić pierwszą główną składową (PC1) zawierającą zasoby ludzkie, atrakcyjne systemy badawcze, finanse i wsparcie rozumiane jako środowisko akademickie i finanse. Druga główna składowa (PC2), obejmująca wpływ na zatrudnienie i sieć powiązań, jest interpretowana jako związana z biznesem. Składowe PC1 i PC2 wyjaśniły łącznie 68% wariancji; podobne wyniki uzyskano dla zestawu 27 szczegółowych wskaźników uwzględnianych w EIS. Można zatem uznać, że daje to dokładną reprezentację danych EIS, która zapewnia alternatywną ocenę i ranking wyników w zakresie innowacji. Zaproponowany uproszczony indeks innowacyjności, opisany w przestrzeni dwuwymiarowej, opierający się na PC1 i PC2, umożliwia nowy sposób grupowania krajów i może mieć szerokie zastosowanie, np. PC1 przedstawia geograficzne zróżnicowanie innowacji odpowiadające podziałowi na kraje członkowskie starej i nowej Unii.

Źródło:

Wiadomości Statystyczne. The Polish Statistician; 2021, 66, 8; 24-45
0043-518X

Pojawia się w:

Wiadomości Statystyczne. The Polish Statistician

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 92.

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

/5

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Skocz do pozycji: 93.

Tytuł:

The identification and analysis of the factors affecting energy consumer behaviour
Identyfikacja i analiza czynników wpływających na zachowanie konsumentów energii

Autorzy:

Trzęsiok, Joanna
Słupik, Sylwia

Powiązania:

https://bibliotekanauki.pl/articles/583891.pdf

Data publikacji:

2019

Wydawca:

Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu

Tematy:

energy consumption
energy consumer behaviour
principal component analysis
konsumpcja energii
zachowanie konsumentów energii
analiza głównych składowych

Opis:

The article aims to identify energy consumer behaviour, particularly in the area of energy saving. Trends in contemporary consumption, including energy consumption, reveal that an increasing number of consumers make purchase decisions in a conscious and rational manner. This is caused by the globalization and integration of markets, evolving lifestyles and social trends. Modern energy consumers are also concerned with their footprint on the natural environment. Using data, gathered in the survey, the authors conducted principal component analysis, selecting 12 new variables that represent the basic types of energy consumer behaviour focused around rational and sustainable energy consumption. The study also examined the factors that significantly influenced consumer attitudes and behaviour. The results showed that generally energy saving actions were not related to the income factor. Education, employment status and age also had a very limited influence on energy consumer attitudes.
Celem artykułu jest identyfikacja zachowań konsumentów energii, przede wszystkim pod względem ich działań dotyczących oszczędzania energii. Trendy współczesnej konsumpcji, w tym również dotyczącej energii, pokazują, że coraz więcej osób świadomie i racjonalnie podejmuje decyzje dotyczące zakupów. Wpływ na to mają zjawiska globalizacji i integracji rynków, zmiany stylu życia czy pewne trendy społeczne. Konsumenci energii coraz częściej kierują się też dobrem środowiska naturalnego. Wykorzystując dane będące wynikiem badania ankietowego, w artykule przeprowadzono analizę głównych składowych, wyłaniając 12 nowych zmiennych reprezentujących podstawowe typy zachowań użytkowników skoncentrowanych wokół racjonalnej i zrównoważonej konsumpcji energii. Zbadano też, jakie cechy istotnie wpływają na te postawy i zachowania. Okazało się, że działania mające na celu oszczędność energii nie są na ogół powiązane z czynnikiem dochodowym. Wykształcenie, status zawodowy czy wiek w niewielkim stopniu kształtują również postawy konsumentów energii.

Źródło:

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu; 2019, 63, 6; 113-126
1899-3192

Pojawia się w:

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 94.

Tytuł:

The impact of water quality on the availability of phytoplankton and growth of Litopenaeus vannamei

Autorzy:

Musa, Muhammad
Thoyibah, Auliarifka A.
Puspitaningtyas, Dyah A.
Arsad, Sulastri
Mahmudi, Mohammad
Lusiana, Evellin D.
Maftuch, Maftuch
Huda, Agus S.

Powiązania:

https://bibliotekanauki.pl/articles/2203547.pdf

Data publikacji:

2023

Wydawca:

Instytut Technologiczno-Przyrodniczy

Tematy:

algae
aquaculture
canonical correspondence analysis
CCA
dynamics of water quality
principal component analysis
PCA
vannamei shrimp

Opis:

This research analysed the availability of phytoplankton and the growth rate of Vannamei shrimp in relation to water quality changes. The research was carried out in February-March 2021 for a half cycle of shrimp cultivation in two ponds of the Brackish Water Fish Culture Probolinggo Laboratory in Probolinggo, East Java, Indonesia. The research used a descriptive method and included a survey. Sampling was made every two weeks for two months. Nine parameters were measured and ten shrimps were taken for a specific growth rate (SGR) measurement once per sampling. Data were analysed using the principal component analysis (PCA) and canonical correspondence analysis (CCA). Secondary data of water quality were added for the PCA. The results show that the phytoplankton found in the first pond consisted of Chlorophyta, Chrysophyta, and Cyanophyta, whereas the phytoplankton in the other pond included Chlorophyta, Chrysophyta, Cyanophyta, and Dinophyta. The abundance of phytoplankton ranged from 12-80∙103 cell∙cm-3, which indicated eutrophic waters. The PCA demonstrated that pH, nitrate, and total organic matter (TOM) significantly influenced phytoplankton abundance in the pond. In addition, water quality parameters, such as temperature, transparency, salinity, nitrite and phosphate levels, were tolerable in both ponds for the growth of shrimps. However, the level of pH was lower than the aquaculture quality standard, whereas those of nitrate, ammonia, and TOM were higher. The growth rate of Vannamei shrimp increased by 0.76–7.34%∙day-1.

Źródło:

Journal of Water and Land Development; 2023, 56; 127--135
1429-7426
2083-4535

Pojawia się w:

Journal of Water and Land Development

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 95.

Tytuł:

Wykorzystanie shift share analysis w opisie zmian struktury honorowych dawców krwi w Polsce
Use Shift Share Analysis of Changes in the Description of the Structure of Blood Donors in Poland

Autorzy:

Trzpiot, Grażyna
Szołtysek, Jacek
Ojrzyńska, Anna
Twaróg, Sebastian

Powiązania:

https://bibliotekanauki.pl/articles/587446.pdf

Data publikacji:

2013

Wydawca:

Uniwersytet Ekonomiczny w Katowicach

Tematy:

Analizy głównych komponentów
Badania empiryczne
Krwiodawstwo
Metody statystyczne
Blood donation
Empirical researches
Principal Component Analysis
Statistical methods

Opis:

The aim of this paper is to show and compare different levels of risk during a day and during a week on spot markets from the Polish Power Exchange (POLPX) and the European Energy Exchange (EEX). Based on Principal Component Analysis (PCA) the classification of contracts from the two power exchanges was made. The classification was made for linear rates of return of 24 contracts listed on the power exchanges from 01.2009 to 24.10.2012. Additionally, the 24 contracts were divided into seven groups dependent on the day of a week. Based on these data sets the classification of risk during a week was made.

Źródło:

Studia Ekonomiczne; 2013, 162; 85-98
2083-8611

Pojawia się w:

Studia Ekonomiczne

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 96.

Tytuł:

Zastosowanie fluorescencyjnej spektroskopii synchronicznej do oceny jakości próbek ziarna pszenicy i nasion rzepaku
Application of synchronous scanning fluorescence spectroscopy to analysis quality of wheat grain and rapeseed samples

Autorzy:

Tańska, M.
Konopka, I.
Smyk, B.
Konopka, S.

Powiązania:

https://bibliotekanauki.pl/articles/271121.pdf

Data publikacji:

2013

Wydawca:

Centralny Ośrodek Badawczo-Rozwojowy Aparatury Badawczej i Dydaktycznej, COBRABiD

Tematy:

pszenica
rzepak
fluorescencyjna spektroskopia synchroniczna
analiza składowych głównych
wheat
rapeseed
synchronous scanning fluorescence spectroscopy
principal component analysis

Opis:

Celem prezentowanych badań było określenie możliwości zastosowania synchronicznej fluorescencji do odróżniania próbek ziarna pszenicy oraz nasion rzepaku różniących się jakością. Ocenie poddano próbki ziarna/nasion „zdrowych" oraz eksperymentalnie uszkodzonych termicznie (przesuszenie) i hydrolityczno-mikrobiologicznie (przechowywanie w warunkach podwyższonej wilgotności). Jakość kontrolnych próbek ziarna pszenicy i nasion rzepaku oceniono za pomocą standardowych wyróżników technologicznych oraz za pomocą analizy zawartości wybranych związków bioaktywnych (kwasy fenolowe, toko- chromanole, chlorofile). Wszystkie próbki poddano analizie spektralnej wykorzystując rejestrację synchroniczną widm fluorescencji. Zastosowanie analizy składowych głównych (PCA) pozwoliło na wskazanie głównych obszarów spektralnych wskazujących na różne typy (jakość) analizowanych próbek. Zastosowane warianty uszkodzenia ziaren/nasion bardziej wpłynęły na próbki nasion rzepaku.
The aim of this study was to determine the possibility of using synchronous fluorescence to distinguish the wheat grain and rapeseed samples of different quality. We compared "healthy" grain/seed samples and experimentally damaged by heat (drying) and moisture-microbial deteriorated by storing at high moisture content. Quality of control samples was evaluated using standard methods according to Polish Standards. Additionally some selected bioactive compounds (phenolic acids, tocochromanols and chlorophylls) were also analyzed. All samples were subjected to spectral analyses using synchronous fluorescence spectroscopy. Application of principal component analysis (PCA) allowed us to identify the main areas indicating different spectral types (quality) of the analyzed samples. Utilized variants of the grains/seeds deterioration affected more significantly the rapeseed samples quality.

Źródło:

Aparatura Badawcza i Dydaktyczna; 2013, 18, 4; 355-363
2392-1765

Pojawia się w:

Aparatura Badawcza i Dydaktyczna

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 97.

Tytuł:

Observations of the aerosol particle number concentration in the marine boundary layer over the South-Eastern Baltic Sea

Autorzy:

Bycenkiene, S.
Ulevicius, V.
Prokopciuk, N.
Jasineviciene, D.

Powiązania:

https://bibliotekanauki.pl/articles/48185.pdf

Data publikacji:

2013

Wydawca:

Polska Akademia Nauk. Instytut Oceanologii PAN

Tematy:

principal component analysis
aerosol number concentration
wavelet transform
coastal site
marine boundary layer
environment pollution
Baltic region

Źródło:

Oceanologia; 2013, 55, 3
0078-3234

Pojawia się w:

Oceanologia

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 98.

Tytuł:

The relationship between morphological traits and seed yield of Iranian garden cress accession

Autorzy:

Rahimi, V.
Mohebodini, M.
Ghanbari, A.
Behnamian, M.
Azizinia, S.

Powiązania:

https://bibliotekanauki.pl/articles/12682952.pdf

Data publikacji:

2019

Wydawca:

Uniwersytet Przyrodniczy w Lublinie. Wydawnictwo Uniwersytetu Przyrodniczego w Lublinie

Tematy:

Iran
plant cultivation
cultivated plant
cress
Lepidium sativum
morphological trait
seed yield
plant research
principal component analysis

Opis:

In order to evaluate the relationship between traits affecting the seed yield of the garden cress, phenotypic correlations between seed yield and yield components were detected, direct and indirect effects of yield components on yield and its role in the description of diversity were estimated, and the experiment was conducted in a randomized complete block design with three replications in 2017. The ANOVA showed that the difference among accessions was significant for all traits. There was a significant phenotypic correlation between yield and most of the traits. The highest value of phenotypic correlation was obtained between seed yield and the ‘thousand seed weight’ (0.97). The regression analysis showed that the seed yield was highly influenced by the ‘thousand seed weight’, leaf height and the number of seeds per silique of the lateral branches and the main axis. These three traits constituted about 89% of changes in the total yield, while the ‘thousand seed weight’ was the most effective trait that entered the model and explained 51% of the variation. The path analysis of phenotypic correlation showed that the ‘thousand seed weight’ had the greatest direct effect on the yield (7.21). The ‘thousand seed weight’ had a positive indirect impact on other traits as well. As a result of the factor analysis, 3 independent factors explained about 79.33% of the yield variation. These factors consisted of the number of seeds per silique of the lateral branches, the number of seeds per silique of the main axis and the ‘thousand seed weight’.

Źródło:

Acta Scientiarum Polonorum. Hortorum Cultus; 2019, 18, 3; 137-145
1644-0692

Pojawia się w:

Acta Scientiarum Polonorum. Hortorum Cultus

Dostawca treści:

Biblioteka Nauki

/5

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Skocz do pozycji: 99.

Tytuł:

Forecasting short-term electric load using extreme learning machine with improved tree seed algorithm based on Lévy flight

Autorzy:

Chen, Xuan
Przystupa, Krzysztof
Ye, Zhiwei
Chen, Feng
Wang, Chunzhi
Liu, Jinhang
Gao, Rong
Wei, Ming
Kochan, Orest

Powiązania:

https://bibliotekanauki.pl/articles/2087016.pdf

Data publikacji:

2022

Wydawca:

Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN

Tematy:

short-term electric load forecast
extreme learning machine
Lévy flight
tree-seed algorithm
Kernel principal component analysis

Opis:

In recent years, forecasting has received increasing attention since it provides an important basis for the effective operation of power systems. In this paper, a hybrid method, composed of kernel principal component analysis (KPCA), tree seed algorithm based on Lévy flight (LTSA) and extreme learning machine (ELM), is proposed for short-term load forecasting. Specifically, the randomly generated weights and biases of ELM have a significant impact on the stability of prediction results. Therefore, in order to solve this problem, LTSA is utilized to obtain the optimal parameters before the prediction process is executed by ELM, which is called LTSA-ELM. Meanwhile, the input data is extracted by KPCA considering the sparseness of the electric load data and used as the input of LTSA-ELM model. The proposed method is tested on the data from European network on intelligent technologies (EUNITE) and experimental results demonstrate the superiority of the proposed approaches compared to the other methods involved in the paper.

Źródło:

Eksploatacja i Niezawodność; 2022, 24, 2; 153--162
1507-2711

Pojawia się w:

Eksploatacja i Niezawodność

Dostawca treści:

Biblioteka Nauki

/5

Artykuł

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Skocz do pozycji: 100.

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

/5

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