TY  - JOUR
AU  - Blesić, Suzana
AU  - du Preez, D. Jean
AU  - Stratimirović, Đorđe
AU  - Ajtić, Jelena
AU  - Ramotsehoa, M. Cynthia
AU  - Allen, Martin W.
AU  - Wright, Caradee Y.
PY  - 2020
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2485
AB  - Studies of personal solar ultraviolet radiation (pUVR) exposure are important to identify populations at-risk of excess and insufficient exposure given the negative and positive health impacts, respectively, of time spent in the sun. Electronic UVR dosimeters measure personal solar UVR exposure at high frequency intervals generating large datasets. Sophisticated methods are needed to analyze these data. Previously, wavelet transform (WT) analysis was applied to high-frequency personal recordings collected by electronic UVR dosimeters. Those findings showed scaling behavior in the datasets that changed from uncorrelated to long-range correlated with increasing duration of time spent in the sun. We hypothesized that the WT slope would be influenced by the duration of time that a person spends in continuum outside. In this study, we address this hypothesis by using an experimental study approach. We aimed to corroborate this hypothesis and to characterize the extent and nature of influence time a person spends outside has on the shape of statistical functions that we used to analyze individual UVR exposure patterns. Detrended fluctuation analysis (DFA) was applied to personal sun exposure data. We analyzed sun exposure recordings from skiers (on snow) and hikers in Europe, golfers in New Zealand and outdoor workers in South Africa. Results confirmed validity of the DFA superposition rule for assessment of pUVR data and showed that pUVR scaling is determined by personal patterns of exposure on lower scales. We also showed that this dominance ends at the range of time scales comparable to the maximal duration of continuous exposure to solar UVR during the day; in this way the superposition rule can be used to quantify behavioral patterns, particularly accurate if it is determined on WT curves. These findings confirm a novel way in which large datasets of personal UVR data may be analyzed to inform messaging regarding safe sun exposure for human health.
PB  - Academic Press Inc Elsevier Science, San Diego
T2  - Environmental Research
T1  - Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis
VL  - 182
DO  - 10.1016/j.envres.2019.108976
ER  - 

@article{
author = "Blesić, Suzana and du Preez, D. Jean and Stratimirović, Đorđe and Ajtić, Jelena and Ramotsehoa, M. Cynthia and Allen, Martin W. and Wright, Caradee Y.",
year = "2020",
abstract = "Studies of personal solar ultraviolet radiation (pUVR) exposure are important to identify populations at-risk of excess and insufficient exposure given the negative and positive health impacts, respectively, of time spent in the sun. Electronic UVR dosimeters measure personal solar UVR exposure at high frequency intervals generating large datasets. Sophisticated methods are needed to analyze these data. Previously, wavelet transform (WT) analysis was applied to high-frequency personal recordings collected by electronic UVR dosimeters. Those findings showed scaling behavior in the datasets that changed from uncorrelated to long-range correlated with increasing duration of time spent in the sun. We hypothesized that the WT slope would be influenced by the duration of time that a person spends in continuum outside. In this study, we address this hypothesis by using an experimental study approach. We aimed to corroborate this hypothesis and to characterize the extent and nature of influence time a person spends outside has on the shape of statistical functions that we used to analyze individual UVR exposure patterns. Detrended fluctuation analysis (DFA) was applied to personal sun exposure data. We analyzed sun exposure recordings from skiers (on snow) and hikers in Europe, golfers in New Zealand and outdoor workers in South Africa. Results confirmed validity of the DFA superposition rule for assessment of pUVR data and showed that pUVR scaling is determined by personal patterns of exposure on lower scales. We also showed that this dominance ends at the range of time scales comparable to the maximal duration of continuous exposure to solar UVR during the day; in this way the superposition rule can be used to quantify behavioral patterns, particularly accurate if it is determined on WT curves. These findings confirm a novel way in which large datasets of personal UVR data may be analyzed to inform messaging regarding safe sun exposure for human health.",
publisher = "Academic Press Inc Elsevier Science, San Diego",
journal = "Environmental Research",
title = "Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis",
volume = "182",
doi = "10.1016/j.envres.2019.108976"
}

Blesić, S., du Preez, D. J., Stratimirović, Đ., Ajtić, J., Ramotsehoa, M. C., Allen, M. W.,& Wright, C. Y.. (2020). Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis. in Environmental Research
Academic Press Inc Elsevier Science, San Diego., 182.
https://doi.org/10.1016/j.envres.2019.108976

Blesić S, du Preez DJ, Stratimirović Đ, Ajtić J, Ramotsehoa MC, Allen MW, Wright CY. Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis. in Environmental Research. 2020;182.
doi:10.1016/j.envres.2019.108976 .

Blesić, Suzana, du Preez, D. Jean, Stratimirović, Đorđe, Ajtić, Jelena, Ramotsehoa, M. Cynthia, Allen, Martin W., Wright, Caradee Y., "Characterization of personal solar ultraviolet radiation exposure using detrended fluctuation analysis" in Environmental Research, 182 (2020),
https://doi.org/10.1016/j.envres.2019.108976 . .

TY  - JOUR
AU  - Stratimirović, Đorđe
AU  - Sarvan, Darko
AU  - Miljković, Vladimir
AU  - Blesić, Suzana
PY  - 2018
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2329
AB  - In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time- dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differ-entiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.
PB  - Elsevier Science Bv, Amsterdam
T2  - Communications in Nonlinear Science & Numerical Simulation
T1  - Analysis of cyclical behavior in time series of stock market returns
VL  - 54
SP  - 21
EP  - 33
DO  - 10.1016/j.cnsns.2017.05.009
ER  - 

@article{
author = "Stratimirović, Đorđe and Sarvan, Darko and Miljković, Vladimir and Blesić, Suzana",
year = "2018",
abstract = "In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time- dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differ-entiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Communications in Nonlinear Science & Numerical Simulation",
title = "Analysis of cyclical behavior in time series of stock market returns",
volume = "54",
pages = "21-33",
doi = "10.1016/j.cnsns.2017.05.009"
}

Stratimirović, Đ., Sarvan, D., Miljković, V.,& Blesić, S.. (2018). Analysis of cyclical behavior in time series of stock market returns. in Communications in Nonlinear Science & Numerical Simulation
Elsevier Science Bv, Amsterdam., 54, 21-33.
https://doi.org/10.1016/j.cnsns.2017.05.009

Stratimirović Đ, Sarvan D, Miljković V, Blesić S. Analysis of cyclical behavior in time series of stock market returns. in Communications in Nonlinear Science & Numerical Simulation. 2018;54:21-33.
doi:10.1016/j.cnsns.2017.05.009 .

Stratimirović, Đorđe, Sarvan, Darko, Miljković, Vladimir, Blesić, Suzana, "Analysis of cyclical behavior in time series of stock market returns" in Communications in Nonlinear Science & Numerical Simulation, 54 (2018):21-33,
https://doi.org/10.1016/j.cnsns.2017.05.009 . .

TY  - JOUR
AU  - Sarvan, Darko
AU  - Stratimirović, Đorđe
AU  - Blesić, Suzana
AU  - Đurđević, Vladimir
AU  - Miljković, Vladimir
AU  - Ajtić, Jelena
PY  - 2017
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2198
AB  - The dynamics of the beryllium-7 specific activity in surface air over 1987-2011 is analyzed using wavelet transform (WT) analysis and time -dependent detrended moving average (tdDMA) method, WT analysis gives four periodicities in the beryllium-7 specific activity: one month, three months, one year, and three years. These intervals are further used in tdDMA to calculate local autocorrelation exponents for precipitation, tropopause height and teleconnection indices. Our results show that these parameters share common periods with the beryllium-7 surface concentration. tdDMA method indicates that on the characteristic intervals of one year and shorter, the beryllium-7 specific activity is strongly autocorrelated. On the three-year interval, the beryllium-7 specific activity shows periods of anticorrelat ion, implying slow changes in its dynamics that become evident only over a prolonged period of time. A comparison of the Hurst exponents of all the variables on the one- and three-year intervals suggest some similarities in their dynamics. Overall, a good agreement in the behavior of the teleconnection indices and specific activity of beryllium-7 in surface air is noted.
PB  - Elsevier, Amsterdam
T2  - Physica A-Statistical Mechanics & its Applications
T1  - Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number
VL  - 469
SP  - 813
EP  - 823
DO  - 10.1016/j.physa.2016.11.040
ER  - 

@article{
author = "Sarvan, Darko and Stratimirović, Đorđe and Blesić, Suzana and Đurđević, Vladimir and Miljković, Vladimir and Ajtić, Jelena",
year = "2017",
abstract = "The dynamics of the beryllium-7 specific activity in surface air over 1987-2011 is analyzed using wavelet transform (WT) analysis and time -dependent detrended moving average (tdDMA) method, WT analysis gives four periodicities in the beryllium-7 specific activity: one month, three months, one year, and three years. These intervals are further used in tdDMA to calculate local autocorrelation exponents for precipitation, tropopause height and teleconnection indices. Our results show that these parameters share common periods with the beryllium-7 surface concentration. tdDMA method indicates that on the characteristic intervals of one year and shorter, the beryllium-7 specific activity is strongly autocorrelated. On the three-year interval, the beryllium-7 specific activity shows periods of anticorrelat ion, implying slow changes in its dynamics that become evident only over a prolonged period of time. A comparison of the Hurst exponents of all the variables on the one- and three-year intervals suggest some similarities in their dynamics. Overall, a good agreement in the behavior of the teleconnection indices and specific activity of beryllium-7 in surface air is noted.",
publisher = "Elsevier, Amsterdam",
journal = "Physica A-Statistical Mechanics & its Applications",
title = "Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number",
volume = "469",
pages = "813-823",
doi = "10.1016/j.physa.2016.11.040"
}

Sarvan, D., Stratimirović, Đ., Blesić, S., Đurđević, V., Miljković, V.,& Ajtić, J.. (2017). Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number. in Physica A-Statistical Mechanics & its Applications
Elsevier, Amsterdam., 469, 813-823.
https://doi.org/10.1016/j.physa.2016.11.040

Sarvan D, Stratimirović Đ, Blesić S, Đurđević V, Miljković V, Ajtić J. Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number. in Physica A-Statistical Mechanics & its Applications. 2017;469:813-823.
doi:10.1016/j.physa.2016.11.040 .

Sarvan, Darko, Stratimirović, Đorđe, Blesić, Suzana, Đurđević, Vladimir, Miljković, Vladimir, Ajtić, Jelena, "Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number" in Physica A-Statistical Mechanics & its Applications, 469 (2017):813-823,
https://doi.org/10.1016/j.physa.2016.11.040 . .