Search results

1

A theoretical model for the collective motion of proteins by means of principal component analysis

100%

Kamberaj H.

Open Physics

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2011

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vol. 9

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issue 1

96-109

EN

A coarse grained model in the frame work of principal component analysis is presented. We used a bath of harmonic oscillators approach, based on classical mechanics, to derive the generalized Langevin equations of motion for the collective coordinates. The dynamics of the protein collective coordinates derived from molecular dynamics simulations have been studied for the Bovine Pancreatic Trypsin Inhibitor. We analyzed the stability of the method by studying structural fluctuations of the Ca atoms obtained from a 20 ns molecular dynamics simulation. Subsequently, the dynamics of the collective coordinates of protein were characterized by calculating the dynamical friction coefficient and diffusion coefficients along with time-dependent correlation functions of collective coordinates. A dual diffusion behavior was observed with a fast relaxation time of short diffusion regime 0.2–0.4 ps and slow relaxation time of long diffusion about 1–2 ps. In addition, we observed a power law decay of dynamical friction coefficient with exponent for the first five collective coordinates varying from −0.746 to −0.938 for the real part and from −0.528 to −0.665 for its magnitude. It was found that only the first ten collective coordinates are responsible for configuration transitions occurring on time scale longer than 50 ps.

2

An LMI approach to checking stability of 2D positive systems

100%

Twardy M.

|

2007

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vol. 55

|

issue 4

3

Projective filtering of time-aligned beats for foetal ECG extraction

100%

Kotas M.

|

2007

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vol. 55

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issue 4

4

Principal Component Analysis in the Study of Structure of the Best Polish Decathlon Competitors from the Period between 1985–2015

100%

Dziadek B., Iskra J., Przednowek K.

Central European Journal of Sport Sciences and Medicine

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2018

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vol. 23

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issue 3

77-87

EN

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.

5

Quantum image classification using principal component analysis

100%

Ostaszewski M., Sadowski P., Gawron P., Ostaszewski M., Sadowski P., Gawron P.

Theoretical and Applied Informatics

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2015

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vol. 27

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issue 1

6

A Predication Analysis of the Factors Influencing Minimum Ignition Temperature of Coal Dust Cloud Based on Principal Component Analysis and Support Vector Machine

88%

Zhao D., Qi H., Pan J., Zhao D., Qi H., Pan J.

Archives of Mining Sciences

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2019

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vol. 64

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issue 2

7

Trace elements in scalp hair of leukaemia patients

88%

Khuder A., Bakir M. A., Hasan R., Mohammad A., Habil K.

Nukleonika

|

2014

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vol. 59

|

issue 3

111-120

EN

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.

8

Hybrid GRA-PCA and modified weighted TOPSIS coupled with Taguchi for multi-response process parameter optimization in turning AISI 1040 steel

75%

Nazma S. M., Dhar N. R., Nazma S. M., Dhar N. R.

Archive of Mechanical Engineering

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2021

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vol. 68

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issue 1

9

Assessing domestic factors determining water consumption in a semi-arid area (Sedrata City) using artificial neural networks and principal component analysis

75%

Zeroual M., Hani A., Boustila A., Zeroual M., Hani A., Boustila A.

Journal of Water and Land Development

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2021

|

issue 49

10

Multivariate statistical characterization of groundwater quality in Fesdis, East of Algeria

75%

Khelif S., Boudoukha A.

Journal of Water and Land Development

|

2018

|

issue 37

Refine search results

A theoretical model for the collective motion of proteins by means of principal component analysis

An LMI approach to checking stability of 2D positive systems

Projective filtering of time-aligned beats for foetal ECG extraction

Principal Component Analysis in the Study of Structure of the Best Polish Decathlon Competitors from the Period between 1985–2015

Quantum image classification using principal component analysis

A Predication Analysis of the Factors Influencing Minimum Ignition Temperature of Coal Dust Cloud Based on Principal Component Analysis and Support Vector Machine

Trace elements in scalp hair of leukaemia patients

Hybrid GRA-PCA and modified weighted TOPSIS coupled with Taguchi for multi-response process parameter optimization in turning AISI 1040 steel

Assessing domestic factors determining water consumption in a semi-arid area (Sedrata City) using artificial neural networks and principal component analysis

Multivariate statistical characterization of groundwater quality in Fesdis, East of Algeria