TY  - CONF
AU  - Stanković, Slavka
AU  - Perošević, Ana
AU  - Jović, Mihajlo
AU  - Onjia, Antonije
PY  - 2016
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/7115
AB  - Uzorci morske vode, morske trava (Posidonia oceanica) i školjki (Mythus galloprovincialis) prikupljeni na priobalnom području Boke Kotorske, Crna Gora, sa sedam lokacija, i analizirani kako bi se utvrdio kvalitet morske vode u odnosu na sledeće
elemenate: Fe, Zn, Ni, Cd, Co. Cu, Kao, Pb. I Hg. Svi uzorci su uzeti istovremeno u periodu od deset različitih sezona. Na osnovu analize biološkog koncentracionog faktora (BCF) vezanih za školjke i makroalge može se pratiti sezonsko zagađenje morske vode i
istovremena P. oceanica i M. galloprovincialis mogu se koristiti kao dobri indikatori sezonskog zagađenja morske vode.
AB  - Sea water, sea grass (Posidonia oceanica) and mussels (Mytilus galloprovincialis) samples were collected from the costal area of Boka Kotorska Bay, Montenegro, from seven locations and analyzed in order to determine the sea water quality related to the next elements: Fe, Zn, Ni, Cd, Co. Cu, As, Pb, and Hg. All samples were taken in the period of ten different seasons. Based on the analysis of biological concentration factor ( BC for shellfish and seaweed can be traced seasonal pollution of sea water and simultaneously came to the conclusion that P. oceanica and M. galloprovincialis can be a good indicators of the seasonal pollution of sca water.
PB  - Beograd : Srpsko društvo za zaštitu voda
C3  - Voda 2016 : zbornik radova 45. godišnje konferencije o aktuelnim problemima korišćenja i zaštite voda, Zlatibor, 15.-17. jun 2016
T1  - Sezonsko određivanje kvaliteta morske vode korišćenjem školjke i makroalge kao bioindikatora
T1  - Seasonal determination of sea water quality using mussels and macroalgae as bioindicators
EP  - 412
SP  - 405
UR  - https://hdl.handle.net/21.15107/rcub_technorep_7115
ER  - 

@conference{
author = "Stanković, Slavka and Perošević, Ana and Jović, Mihajlo and Onjia, Antonije",
year = "2016",
abstract = "Uzorci morske vode, morske trava (Posidonia oceanica) i školjki (Mythus galloprovincialis) prikupljeni na priobalnom području Boke Kotorske, Crna Gora, sa sedam lokacija, i analizirani kako bi se utvrdio kvalitet morske vode u odnosu na sledeće
elemenate: Fe, Zn, Ni, Cd, Co. Cu, Kao, Pb. I Hg. Svi uzorci su uzeti istovremeno u periodu od deset različitih sezona. Na osnovu analize biološkog koncentracionog faktora (BCF) vezanih za školjke i makroalge može se pratiti sezonsko zagađenje morske vode i
istovremena P. oceanica i M. galloprovincialis mogu se koristiti kao dobri indikatori sezonskog zagađenja morske vode., Sea water, sea grass (Posidonia oceanica) and mussels (Mytilus galloprovincialis) samples were collected from the costal area of Boka Kotorska Bay, Montenegro, from seven locations and analyzed in order to determine the sea water quality related to the next elements: Fe, Zn, Ni, Cd, Co. Cu, As, Pb, and Hg. All samples were taken in the period of ten different seasons. Based on the analysis of biological concentration factor ( BC for shellfish and seaweed can be traced seasonal pollution of sea water and simultaneously came to the conclusion that P. oceanica and M. galloprovincialis can be a good indicators of the seasonal pollution of sca water.",
publisher = "Beograd : Srpsko društvo za zaštitu voda",
journal = "Voda 2016 : zbornik radova 45. godišnje konferencije o aktuelnim problemima korišćenja i zaštite voda, Zlatibor, 15.-17. jun 2016",
title = "Sezonsko određivanje kvaliteta morske vode korišćenjem školjke i makroalge kao bioindikatora, Seasonal determination of sea water quality using mussels and macroalgae as bioindicators",
pages = "412-405",
url = "https://hdl.handle.net/21.15107/rcub_technorep_7115"
}

Stanković, S., Perošević, A., Jović, M.,& Onjia, A.. (2016). Sezonsko određivanje kvaliteta morske vode korišćenjem školjke i makroalge kao bioindikatora. in Voda 2016 : zbornik radova 45. godišnje konferencije o aktuelnim problemima korišćenja i zaštite voda, Zlatibor, 15.-17. jun 2016
Beograd : Srpsko društvo za zaštitu voda., 405-412.
https://hdl.handle.net/21.15107/rcub_technorep_7115

Stanković S, Perošević A, Jović M, Onjia A. Sezonsko određivanje kvaliteta morske vode korišćenjem školjke i makroalge kao bioindikatora. in Voda 2016 : zbornik radova 45. godišnje konferencije o aktuelnim problemima korišćenja i zaštite voda, Zlatibor, 15.-17. jun 2016. 2016;:405-412.
https://hdl.handle.net/21.15107/rcub_technorep_7115 .

Stanković, Slavka, Perošević, Ana, Jović, Mihajlo, Onjia, Antonije, "Sezonsko određivanje kvaliteta morske vode korišćenjem školjke i makroalge kao bioindikatora" in Voda 2016 : zbornik radova 45. godišnje konferencije o aktuelnim problemima korišćenja i zaštite voda, Zlatibor, 15.-17. jun 2016 (2016):405-412,
https://hdl.handle.net/21.15107/rcub_technorep_7115 .

TY  - JOUR
AU  - Ben Issa, Nureddin
AU  - Marinković, Aleksandar
AU  - Rajaković, Ljubinka V.
PY  - 2012
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/2086
AB  - A simple and efficient method for the separation and determination of dimethylarsenate DMAs(V) was developed in this work. Two resins, a strong base anion exchange (SBAE) resin and iron-oxide coated hybrid (HY) resin were tested. By simple adjustment of the pH value of water to 7.00, DMAs(V) passed through the HY column without any changes, while all other arsenic species (inorganic arsenic and monomethylarsonate, MMAs(V)) were quantitatively bonded on the HY resin. The resin capacity was calculated according to the breakthrough point in a fixed bed flow system. At pH 7.00, the HY resin bonded more than 4150 μg g-1 of As(III), 3500 μg g-1 of As(V) and 1500 μg g-1 of MMAs(V). Arsenic adsorption behavior in the presence of impurities showed tolerance with the respect to potential interference of anions commonly found in natural water. DMAs(V) was determined in the effluent by inductively coupled plasma mass spectrometry (ICP-MS). The detection limit was 0.03 μg L-1 and the relative standard deviation (RSD) was between 1.1-7.5 %. The proposed method was established by application of standard procedures, i.e., using an external standard, certified reference material and by the standard addition method.
AB  - U radu je prikazan jednostavan i efikasan metod za razdvajanje i određivanje dimetilarsenata, DMAs(V). Za izdvajanja DMAs(V) korišćena je hibridna smola modifikovana gvožđe-oksidom (HY). Za određivanje koncentracija arsena primenjena je metoda masene spektrometrije sa indukovano spregnutom plazmom (ICP-MS). Kvantitativno odvajanje DMAs(V) od svih vrsta arsena prisutnih u prirodnim vodam ostvareno je primenom HY smole uz kontrolu pH vrednosti. Pri pH vrednosti vode od 7,00 sve vrste arsena u vodi se kvantitativno vezuju za HY smolu izuzev DMAs(V). Kapacitet HY smole je izračunat na osnovu određivanja tačke proboja u protočnom sistemu, HY smola veže više od 4150 μg g-1 As(III), 3500 μg g-1 As(V) i 1500 μg g-1 MMAs(V). Kapacitet smole je visok i postojan i u prisustvu jona koji su prirodni sastojci vode. U efluentu je određena koncentracija DMAs(V) primenom ICP-MS. Predloženi metod je uspostavljen i potvrđen primenom standardnih analitičkih postupaka, analizom sertifikovanog referentnog materijala i analizom uzoraka uz primenu spoljašnjeg standarda i standardnog dodatka. Granica određivanja bila je 0,03 μg L-1, a relativna standardna devijacija (RSD) u opsegu između 1,1-7,50 %.
PB  - Serbian Chemical Society, Belgrade
T2  - Journal of the Serbian Chemical Society
T1  - Separation and determination of dimethylarsenate in natural waters
T1  - Razdvajanje i određivanje dimetilarsenata u prirodnim vodama
EP  - 788
IS  - 6
SP  - 775
VL  - 77
UR  - https://hdl.handle.net/21.15107/rcub_technorep_2086
ER  - 

@article{
author = "Ben Issa, Nureddin and Marinković, Aleksandar and Rajaković, Ljubinka V.",
year = "2012",
abstract = "A simple and efficient method for the separation and determination of dimethylarsenate DMAs(V) was developed in this work. Two resins, a strong base anion exchange (SBAE) resin and iron-oxide coated hybrid (HY) resin were tested. By simple adjustment of the pH value of water to 7.00, DMAs(V) passed through the HY column without any changes, while all other arsenic species (inorganic arsenic and monomethylarsonate, MMAs(V)) were quantitatively bonded on the HY resin. The resin capacity was calculated according to the breakthrough point in a fixed bed flow system. At pH 7.00, the HY resin bonded more than 4150 μg g-1 of As(III), 3500 μg g-1 of As(V) and 1500 μg g-1 of MMAs(V). Arsenic adsorption behavior in the presence of impurities showed tolerance with the respect to potential interference of anions commonly found in natural water. DMAs(V) was determined in the effluent by inductively coupled plasma mass spectrometry (ICP-MS). The detection limit was 0.03 μg L-1 and the relative standard deviation (RSD) was between 1.1-7.5 %. The proposed method was established by application of standard procedures, i.e., using an external standard, certified reference material and by the standard addition method., U radu je prikazan jednostavan i efikasan metod za razdvajanje i određivanje dimetilarsenata, DMAs(V). Za izdvajanja DMAs(V) korišćena je hibridna smola modifikovana gvožđe-oksidom (HY). Za određivanje koncentracija arsena primenjena je metoda masene spektrometrije sa indukovano spregnutom plazmom (ICP-MS). Kvantitativno odvajanje DMAs(V) od svih vrsta arsena prisutnih u prirodnim vodam ostvareno je primenom HY smole uz kontrolu pH vrednosti. Pri pH vrednosti vode od 7,00 sve vrste arsena u vodi se kvantitativno vezuju za HY smolu izuzev DMAs(V). Kapacitet HY smole je izračunat na osnovu određivanja tačke proboja u protočnom sistemu, HY smola veže više od 4150 μg g-1 As(III), 3500 μg g-1 As(V) i 1500 μg g-1 MMAs(V). Kapacitet smole je visok i postojan i u prisustvu jona koji su prirodni sastojci vode. U efluentu je određena koncentracija DMAs(V) primenom ICP-MS. Predloženi metod je uspostavljen i potvrđen primenom standardnih analitičkih postupaka, analizom sertifikovanog referentnog materijala i analizom uzoraka uz primenu spoljašnjeg standarda i standardnog dodatka. Granica određivanja bila je 0,03 μg L-1, a relativna standardna devijacija (RSD) u opsegu između 1,1-7,50 %.",
publisher = "Serbian Chemical Society, Belgrade",
journal = "Journal of the Serbian Chemical Society",
title = "Separation and determination of dimethylarsenate in natural waters, Razdvajanje i određivanje dimetilarsenata u prirodnim vodama",
pages = "788-775",
number = "6",
volume = "77",
url = "https://hdl.handle.net/21.15107/rcub_technorep_2086"
}

Ben Issa, N., Marinković, A.,& Rajaković, L. V.. (2012). Separation and determination of dimethylarsenate in natural waters. in Journal of the Serbian Chemical Society
Serbian Chemical Society, Belgrade., 77(6), 775-788.
https://hdl.handle.net/21.15107/rcub_technorep_2086

Ben Issa N, Marinković A, Rajaković LV. Separation and determination of dimethylarsenate in natural waters. in Journal of the Serbian Chemical Society. 2012;77(6):775-788.
https://hdl.handle.net/21.15107/rcub_technorep_2086 .

Ben Issa, Nureddin, Marinković, Aleksandar, Rajaković, Ljubinka V., "Separation and determination of dimethylarsenate in natural waters" in Journal of the Serbian Chemical Society, 77, no. 6 (2012):775-788,
https://hdl.handle.net/21.15107/rcub_technorep_2086 .

TY  - JOUR
AU  - Sredović, I.
AU  - Rajaković, Lj.
PY  - 2010
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/5610
AB  - Corrosion effects in thermal power plants and environmental impact cause an increase in demand for fluorine analysis in coal. Solid sample decomposition, organic and inorganic fluorine compounds, volatility of fluorine species are problems which deserve a special attention. The aim of this work was to optimize the pyrohydrolytic (Phy) determination of fluorine content in the lignite coal. The parameters of pyrohydrolysis were evaluated and optimized by two statistical methods: Plackett-Burman (PB) design and response surface methodology (RSM). The content of fluorine in the absorption solution was measured by fluoride ion-selective electrode. The limit of detection of the proposed method was 20μgg-1, with good recovery (95%) and relative standard deviation less than 5%. With such benefits as simplicity, precision, accuracy and economy, this method is highly suitable for routine analysis of coal.
PB  - Elsevier
T2  - Journal of Hazardous Materials
T1  - Pyrohydrolytic determination of fluorine in coal: A chemometric approach
EP  - 451
IS  - 1-3
SP  - 445
VL  - 177
DO  - 10.1016/j.jhazmat.2009.12.053
ER  - 

@article{
author = "Sredović, I. and Rajaković, Lj.",
year = "2010",
abstract = "Corrosion effects in thermal power plants and environmental impact cause an increase in demand for fluorine analysis in coal. Solid sample decomposition, organic and inorganic fluorine compounds, volatility of fluorine species are problems which deserve a special attention. The aim of this work was to optimize the pyrohydrolytic (Phy) determination of fluorine content in the lignite coal. The parameters of pyrohydrolysis were evaluated and optimized by two statistical methods: Plackett-Burman (PB) design and response surface methodology (RSM). The content of fluorine in the absorption solution was measured by fluoride ion-selective electrode. The limit of detection of the proposed method was 20μgg-1, with good recovery (95%) and relative standard deviation less than 5%. With such benefits as simplicity, precision, accuracy and economy, this method is highly suitable for routine analysis of coal.",
publisher = "Elsevier",
journal = "Journal of Hazardous Materials",
title = "Pyrohydrolytic determination of fluorine in coal: A chemometric approach",
pages = "451-445",
number = "1-3",
volume = "177",
doi = "10.1016/j.jhazmat.2009.12.053"
}

Sredović, I.,& Rajaković, Lj.. (2010). Pyrohydrolytic determination of fluorine in coal: A chemometric approach. in Journal of Hazardous Materials
Elsevier., 177(1-3), 445-451.
https://doi.org/10.1016/j.jhazmat.2009.12.053

Sredović I, Rajaković L. Pyrohydrolytic determination of fluorine in coal: A chemometric approach. in Journal of Hazardous Materials. 2010;177(1-3):445-451.
doi:10.1016/j.jhazmat.2009.12.053 .

Sredović, I., Rajaković, Lj., "Pyrohydrolytic determination of fluorine in coal: A chemometric approach" in Journal of Hazardous Materials, 177, no. 1-3 (2010):445-451,
https://doi.org/10.1016/j.jhazmat.2009.12.053 . .

TY  - JOUR
AU  - Ražić, Slavica
AU  - Onjia, Antonije
PY  - 2010
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1715
AB  - Chemical analysis in conjunction with multivariate data evaluation methods was used to study elemental profiles and geographical origin of wines from central Balkan countries (Serbia Montenegro and Macedonia) Nine elements (Na K Mg Ca Fe Mn Zn Cu and Pb) chosen as chemical descriptors were analyzed in 41 commercial wine samples Unsupervised pattern recognition methods principal component analysis (PCA) and factor analysis identified the main factors controlling the data variability while the application of hierarchical cluster analysis (HCA) highlighted a differentiation between sample groups belonging to different variable inputs Three PCs were shown to be the most significant together accounting for 70 8% of the total variance Supervised pattern recognition methods linear discriminant analysis (LDA) k nearest neighbor (kNN) soft independent modeling of class analogy (SIMCA) and artificial neural network (ANN) applied to the classification of wine samples demonstrated different recognition and prediction abilities The recognition rate for LDA was 97 6% and the percentage of classification obtained by kNN SIMCA and ANN was 100% However the LDA method produced the best prediction rate of 83 3% whereas kNN SIMCA and ANN gave much lower percentages of correctly classified samples at 72 2 61 1 and 55 6% respectively Trace elements seem to be suitable descriptors for wine samples studied by classification methods since their concentrations comprising both natural and other sources of influence are attributed to grapegrowing and winemaking sites Comparison of pattern recognition methods reveals the difference in their classification power
PB  - Amer Soc Enology Viticulture, Davis
T2  - American Journal of Enology and Viticulture
T1  - Trace Element Analysis and Pattern Recognition Techniques in Classification of Wine from Central Balkan Countries
EP  - 511
IS  - 4
SP  - 506
VL  - 61
DO  - 10.5344/ajev.2010.10002
ER  - 

@article{
author = "Ražić, Slavica and Onjia, Antonije",
year = "2010",
abstract = "Chemical analysis in conjunction with multivariate data evaluation methods was used to study elemental profiles and geographical origin of wines from central Balkan countries (Serbia Montenegro and Macedonia) Nine elements (Na K Mg Ca Fe Mn Zn Cu and Pb) chosen as chemical descriptors were analyzed in 41 commercial wine samples Unsupervised pattern recognition methods principal component analysis (PCA) and factor analysis identified the main factors controlling the data variability while the application of hierarchical cluster analysis (HCA) highlighted a differentiation between sample groups belonging to different variable inputs Three PCs were shown to be the most significant together accounting for 70 8% of the total variance Supervised pattern recognition methods linear discriminant analysis (LDA) k nearest neighbor (kNN) soft independent modeling of class analogy (SIMCA) and artificial neural network (ANN) applied to the classification of wine samples demonstrated different recognition and prediction abilities The recognition rate for LDA was 97 6% and the percentage of classification obtained by kNN SIMCA and ANN was 100% However the LDA method produced the best prediction rate of 83 3% whereas kNN SIMCA and ANN gave much lower percentages of correctly classified samples at 72 2 61 1 and 55 6% respectively Trace elements seem to be suitable descriptors for wine samples studied by classification methods since their concentrations comprising both natural and other sources of influence are attributed to grapegrowing and winemaking sites Comparison of pattern recognition methods reveals the difference in their classification power",
publisher = "Amer Soc Enology Viticulture, Davis",
journal = "American Journal of Enology and Viticulture",
title = "Trace Element Analysis and Pattern Recognition Techniques in Classification of Wine from Central Balkan Countries",
pages = "511-506",
number = "4",
volume = "61",
doi = "10.5344/ajev.2010.10002"
}

Ražić, S.,& Onjia, A.. (2010). Trace Element Analysis and Pattern Recognition Techniques in Classification of Wine from Central Balkan Countries. in American Journal of Enology and Viticulture
Amer Soc Enology Viticulture, Davis., 61(4), 506-511.
https://doi.org/10.5344/ajev.2010.10002

Ražić S, Onjia A. Trace Element Analysis and Pattern Recognition Techniques in Classification of Wine from Central Balkan Countries. in American Journal of Enology and Viticulture. 2010;61(4):506-511.
doi:10.5344/ajev.2010.10002 .

Ražić, Slavica, Onjia, Antonije, "Trace Element Analysis and Pattern Recognition Techniques in Classification of Wine from Central Balkan Countries" in American Journal of Enology and Viticulture, 61, no. 4 (2010):506-511,
https://doi.org/10.5344/ajev.2010.10002 . .

TY  - JOUR
AU  - Nastasović, Aleksandra
AU  - Sandić, Zvjezdana P.
AU  - Suručić, Ljiljana T.
AU  - Maksin, Danijela
AU  - Jakovljević, Dragica
AU  - Onjia, Antonije
PY  - 2009
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1416
AB  - Two samples of macroporous crosslinked poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate), poly(GMA-co-EGDMA), with different porosity parameters were synthesized by suspension copolymerization and functionalized with ethylene diamine and diethylene triamine. The kinetics of Cr(VI) sorption by amino-functionalized poly(GMA-co-EGDMA) was investigated under non-competitive conditions. Competitive kinetics was studied from following multicomponent solutions: Cu(II) and Cr(VI); Cu(II), Co(II), Cd(II) and Ni(II): Cr(VI), Cu(II), Co(II) and Cd(II) solutions. Two kinetic models (the pseudo-first and pseudo-second-order) were used to determine the best-fit equation for the metals sorption by poly(GMA-co-EGDMA)-en and poly(GMA-co-EGDMA)-deta.
PB  - Elsevier, Amsterdam
T2  - Journal of Hazardous Materials
T1  - Kinetics of hexavalent chromium sorption on amino-functionalized macroporous glycidyl methacrylate copolymer
EP  - 159
IS  - 1-3
SP  - 153
VL  - 171
DO  - 10.1016/j.jhazmat.2009.05.116
ER  - 

@article{
author = "Nastasović, Aleksandra and Sandić, Zvjezdana P. and Suručić, Ljiljana T. and Maksin, Danijela and Jakovljević, Dragica and Onjia, Antonije",
year = "2009",
abstract = "Two samples of macroporous crosslinked poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate), poly(GMA-co-EGDMA), with different porosity parameters were synthesized by suspension copolymerization and functionalized with ethylene diamine and diethylene triamine. The kinetics of Cr(VI) sorption by amino-functionalized poly(GMA-co-EGDMA) was investigated under non-competitive conditions. Competitive kinetics was studied from following multicomponent solutions: Cu(II) and Cr(VI); Cu(II), Co(II), Cd(II) and Ni(II): Cr(VI), Cu(II), Co(II) and Cd(II) solutions. Two kinetic models (the pseudo-first and pseudo-second-order) were used to determine the best-fit equation for the metals sorption by poly(GMA-co-EGDMA)-en and poly(GMA-co-EGDMA)-deta.",
publisher = "Elsevier, Amsterdam",
journal = "Journal of Hazardous Materials",
title = "Kinetics of hexavalent chromium sorption on amino-functionalized macroporous glycidyl methacrylate copolymer",
pages = "159-153",
number = "1-3",
volume = "171",
doi = "10.1016/j.jhazmat.2009.05.116"
}

Nastasović, A., Sandić, Z. P., Suručić, L. T., Maksin, D., Jakovljević, D.,& Onjia, A.. (2009). Kinetics of hexavalent chromium sorption on amino-functionalized macroporous glycidyl methacrylate copolymer. in Journal of Hazardous Materials
Elsevier, Amsterdam., 171(1-3), 153-159.
https://doi.org/10.1016/j.jhazmat.2009.05.116

Nastasović A, Sandić ZP, Suručić LT, Maksin D, Jakovljević D, Onjia A. Kinetics of hexavalent chromium sorption on amino-functionalized macroporous glycidyl methacrylate copolymer. in Journal of Hazardous Materials. 2009;171(1-3):153-159.
doi:10.1016/j.jhazmat.2009.05.116 .

Nastasović, Aleksandra, Sandić, Zvjezdana P., Suručić, Ljiljana T., Maksin, Danijela, Jakovljević, Dragica, Onjia, Antonije, "Kinetics of hexavalent chromium sorption on amino-functionalized macroporous glycidyl methacrylate copolymer" in Journal of Hazardous Materials, 171, no. 1-3 (2009):153-159,
https://doi.org/10.1016/j.jhazmat.2009.05.116 . .

TY  - CONF
AU  - Dragović, Snežana
AU  - Momčilović, Milan
AU  - Onjia, Antonije
PY  - 2008
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/7185
AB  - Some of the most commonly occuring problems in radioecological and environmental
radioactivitiy studies when applying traditional statistical models are multivariate and
multiscale structures of data. Spatial data analysis of radioactively contaminated areas are
particularly complex for many reasons: uncertainty of the source term, high spatial and
temporal variability of pollution patterns, spatial and temporal nonstationarity and
multivariate nature of the phenomenon with linearly and nonlinearly correlated variables.
There are only few studies on employing the multivariate approach to describe the correlation
between locations and radioactive contamination (Kanevski, 1996; Kanevski, 1997).
In this work the feasibility of using multivariate analysis techniques, principal component
analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft
independent modelling of class analogy (SIMCA) and artificial neural networks (ANN), to
predict soils and bioindicators origin based on their radionuclide content was examined.
PB  - Østerås : Norwegian Radiation Protection Authority
C3  - Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway
T1  - Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations
EP  - 110
SP  - 107
UR  - https://hdl.handle.net/21.15107/rcub_technorep_7185
ER  - 

@conference{
author = "Dragović, Snežana and Momčilović, Milan and Onjia, Antonije",
year = "2008",
abstract = "Some of the most commonly occuring problems in radioecological and environmental
radioactivitiy studies when applying traditional statistical models are multivariate and
multiscale structures of data. Spatial data analysis of radioactively contaminated areas are
particularly complex for many reasons: uncertainty of the source term, high spatial and
temporal variability of pollution patterns, spatial and temporal nonstationarity and
multivariate nature of the phenomenon with linearly and nonlinearly correlated variables.
There are only few studies on employing the multivariate approach to describe the correlation
between locations and radioactive contamination (Kanevski, 1996; Kanevski, 1997).
In this work the feasibility of using multivariate analysis techniques, principal component
analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft
independent modelling of class analogy (SIMCA) and artificial neural networks (ANN), to
predict soils and bioindicators origin based on their radionuclide content was examined.",
publisher = "Østerås : Norwegian Radiation Protection Authority",
journal = "Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway",
title = "Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations",
pages = "110-107",
url = "https://hdl.handle.net/21.15107/rcub_technorep_7185"
}

Dragović, S., Momčilović, M.,& Onjia, A.. (2008). Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations. in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway
Østerås : Norwegian Radiation Protection Authority., 107-110.
https://hdl.handle.net/21.15107/rcub_technorep_7185

Dragović S, Momčilović M, Onjia A. Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations. in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway. 2008;:107-110.
https://hdl.handle.net/21.15107/rcub_technorep_7185 .

Dragović, Snežana, Momčilović, Milan, Onjia, Antonije, "Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations" in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway (2008):107-110,
https://hdl.handle.net/21.15107/rcub_technorep_7185 .

TY  - JOUR
AU  - Sremac, Snežana
AU  - Popović, Aleksandar R.
AU  - Todorović, Žaklina
AU  - Čokeša, Đuro
AU  - Onjia, Antonije
PY  - 2008
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1347
AB  - An interpretative strategy (factorial design experimentation + total resolution analysis + chromatogram simulation) was employed to optimize the separation of 16 polycyclic aromatic hydrocarbons (PAHs) (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(k)fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, indeno(1,2,3-c,d)pyrene, dibenzo(a,h)anthracene, benzo(g,h,i)perylene) in temperature-programmed gas chromatography (GC). Also, the retention behavior of PAHs in the same GC system was studied by a feed-forward artificial neural network (ANN). GC separation was investigated as a function of one (linear temperature ramp) or two (linear temperature ramp+the final hold temperature) variables. The applied interpretative approach resulted in rather good agreement between the measured and the predicted retention times for PAHs in both one and two variable modeling. The ANN model, strongly affected by the number of input experiments, was shown to be less effective for one variable used, but quite successful when two input variables were used. All PAHs, including difficult to separate peak pairs (benzo(k)fluoranthene/benzo(b)fluoranthene and indeno(1,2,3-c,d)pyrene/dibenzo(a,h)anthracene), were separated in a standard (5% phenyl-95% climethylpolysiloxane) capillary column at an optimum temperature ramp of 8.0 degrees C/min and final hold temperature in the range of 260-320 degrees C.
PB  - Elsevier, Amsterdam
T2  - Talanta
T1  - Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons
EP  - 71
IS  - 1
SP  - 66
VL  - 76
DO  - 10.1016/j.talanta.2008.02.004
ER  - 

@article{
author = "Sremac, Snežana and Popović, Aleksandar R. and Todorović, Žaklina and Čokeša, Đuro and Onjia, Antonije",
year = "2008",
abstract = "An interpretative strategy (factorial design experimentation + total resolution analysis + chromatogram simulation) was employed to optimize the separation of 16 polycyclic aromatic hydrocarbons (PAHs) (naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo(a)anthracene, benzo(k)fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, indeno(1,2,3-c,d)pyrene, dibenzo(a,h)anthracene, benzo(g,h,i)perylene) in temperature-programmed gas chromatography (GC). Also, the retention behavior of PAHs in the same GC system was studied by a feed-forward artificial neural network (ANN). GC separation was investigated as a function of one (linear temperature ramp) or two (linear temperature ramp+the final hold temperature) variables. The applied interpretative approach resulted in rather good agreement between the measured and the predicted retention times for PAHs in both one and two variable modeling. The ANN model, strongly affected by the number of input experiments, was shown to be less effective for one variable used, but quite successful when two input variables were used. All PAHs, including difficult to separate peak pairs (benzo(k)fluoranthene/benzo(b)fluoranthene and indeno(1,2,3-c,d)pyrene/dibenzo(a,h)anthracene), were separated in a standard (5% phenyl-95% climethylpolysiloxane) capillary column at an optimum temperature ramp of 8.0 degrees C/min and final hold temperature in the range of 260-320 degrees C.",
publisher = "Elsevier, Amsterdam",
journal = "Talanta",
title = "Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons",
pages = "71-66",
number = "1",
volume = "76",
doi = "10.1016/j.talanta.2008.02.004"
}

Sremac, S., Popović, A. R., Todorović, Ž., Čokeša, Đ.,& Onjia, A.. (2008). Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons. in Talanta
Elsevier, Amsterdam., 76(1), 66-71.
https://doi.org/10.1016/j.talanta.2008.02.004

Sremac S, Popović AR, Todorović Ž, Čokeša Đ, Onjia A. Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons. in Talanta. 2008;76(1):66-71.
doi:10.1016/j.talanta.2008.02.004 .

Sremac, Snežana, Popović, Aleksandar R., Todorović, Žaklina, Čokeša, Đuro, Onjia, Antonije, "Interpretative optimization and artificial neural network modeling of the gas chromatographic separation of polycyclic aromatic hydrocarbons" in Talanta, 76, no. 1 (2008):66-71,
https://doi.org/10.1016/j.talanta.2008.02.004 . .

TY  - JOUR
AU  - Nastasović, Aleksandra
AU  - Onjia, Antonije
PY  - 2008
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1234
AB  - Inverse gas chromatography (IGC) is an attractive technique for polymer characterization due to possible simultaneous determination of various physicochemical properties of polymer systems merely from retention times of selected sorbates. The technique is especially advantageous to polymers that cannot be characterized by conventional methods. In this review, the utilization of the method for glass transition determination of homopolymers, copolymers and polymer blends is described. Advantages and drawbacks of the IGC method over traditionally used methods for glass transition temperature determination is discussed, along with the most important parameters that influence the precision and accuracy of the glass transition temperature (T-g) measurements.
PB  - Elsevier, Amsterdam
T2  - Journal of Chromatography A
T1  - Determination of glass temperature of polymers by inverse gas chromatography
EP  - 15
IS  - 1-2
SP  - 1
VL  - 1195
DO  - 10.1016/j.chroma.2008.05.009
ER  - 

@article{
author = "Nastasović, Aleksandra and Onjia, Antonije",
year = "2008",
abstract = "Inverse gas chromatography (IGC) is an attractive technique for polymer characterization due to possible simultaneous determination of various physicochemical properties of polymer systems merely from retention times of selected sorbates. The technique is especially advantageous to polymers that cannot be characterized by conventional methods. In this review, the utilization of the method for glass transition determination of homopolymers, copolymers and polymer blends is described. Advantages and drawbacks of the IGC method over traditionally used methods for glass transition temperature determination is discussed, along with the most important parameters that influence the precision and accuracy of the glass transition temperature (T-g) measurements.",
publisher = "Elsevier, Amsterdam",
journal = "Journal of Chromatography A",
title = "Determination of glass temperature of polymers by inverse gas chromatography",
pages = "15-1",
number = "1-2",
volume = "1195",
doi = "10.1016/j.chroma.2008.05.009"
}

Nastasović, A.,& Onjia, A.. (2008). Determination of glass temperature of polymers by inverse gas chromatography. in Journal of Chromatography A
Elsevier, Amsterdam., 1195(1-2), 1-15.
https://doi.org/10.1016/j.chroma.2008.05.009

Nastasović A, Onjia A. Determination of glass temperature of polymers by inverse gas chromatography. in Journal of Chromatography A. 2008;1195(1-2):1-15.
doi:10.1016/j.chroma.2008.05.009 .

Nastasović, Aleksandra, Onjia, Antonije, "Determination of glass temperature of polymers by inverse gas chromatography" in Journal of Chromatography A, 1195, no. 1-2 (2008):1-15,
https://doi.org/10.1016/j.chroma.2008.05.009 . .

TY  - JOUR
AU  - Dragović, Snežana
AU  - Janković Mandić, Ljiljana
AU  - Momčilović, Milan
AU  - Onjia, Antonije
PY  - 2007
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/7231
AB  - Background: Terrestrial radiation emitted from naturally occurring radionuclides, such as 40K and radionuclides from the 238U
and 232Th series and their decay products represent the main external source of irradiation to the human body. The purpose
of this study was to provide a preliminary assessment of the doses from terrestrial exposure of population in Serbia and to
estimate a potential radiation hazard for population inhabiting investigated areas.
Methods: The gamma dose rates, external hazard indexes, and annual effective doses due to terrestrial naturally occurring radionuclides
(
238U, 232Th and 40K) were calculated based on their activities in soil samples in Serbia as determined by gamma-ray spectrometry.
Results: The total absorbed gamma dose rate due to these radionuclides varied from 16.9 to 125 nGy h-1, with a mean of 62.8
nGy h-1. Assuming a 20% occupancy factor, the corresponding annual effective dose varied from 2.07 to 15.4×10-5 Sv with
the mean value of 7.7×10-5 Sv, i.e. annual effective dose was in range of the world wide average values.
Conclusion: According to the values of external hazard index obtained in this study (mean Hex = 0.35), the radiation hazard
was insignificant for the population living in investigated areas.
PB  - Institute of Oncology
T2  - Archive of Oncology
T1  - Population doses from terrestrial gamma exposure in Serbia
EP  - 80
IS  - 3-4
SP  - 78
VL  - 15
UR  - https://hdl.handle.net/21.15107/rcub_technorep_7231
ER  - 

@article{
author = "Dragović, Snežana and Janković Mandić, Ljiljana and Momčilović, Milan and Onjia, Antonije",
year = "2007",
abstract = "Background: Terrestrial radiation emitted from naturally occurring radionuclides, such as 40K and radionuclides from the 238U
and 232Th series and their decay products represent the main external source of irradiation to the human body. The purpose
of this study was to provide a preliminary assessment of the doses from terrestrial exposure of population in Serbia and to
estimate a potential radiation hazard for population inhabiting investigated areas.
Methods: The gamma dose rates, external hazard indexes, and annual effective doses due to terrestrial naturally occurring radionuclides
(
238U, 232Th and 40K) were calculated based on their activities in soil samples in Serbia as determined by gamma-ray spectrometry.
Results: The total absorbed gamma dose rate due to these radionuclides varied from 16.9 to 125 nGy h-1, with a mean of 62.8
nGy h-1. Assuming a 20% occupancy factor, the corresponding annual effective dose varied from 2.07 to 15.4×10-5 Sv with
the mean value of 7.7×10-5 Sv, i.e. annual effective dose was in range of the world wide average values.
Conclusion: According to the values of external hazard index obtained in this study (mean Hex = 0.35), the radiation hazard
was insignificant for the population living in investigated areas.",
publisher = "Institute of Oncology",
journal = "Archive of Oncology",
title = "Population doses from terrestrial gamma exposure in Serbia",
pages = "80-78",
number = "3-4",
volume = "15",
url = "https://hdl.handle.net/21.15107/rcub_technorep_7231"
}

Dragović, S., Janković Mandić, L., Momčilović, M.,& Onjia, A.. (2007). Population doses from terrestrial gamma exposure in Serbia. in Archive of Oncology
Institute of Oncology., 15(3-4), 78-80.
https://hdl.handle.net/21.15107/rcub_technorep_7231

Dragović S, Janković Mandić L, Momčilović M, Onjia A. Population doses from terrestrial gamma exposure in Serbia. in Archive of Oncology. 2007;15(3-4):78-80.
https://hdl.handle.net/21.15107/rcub_technorep_7231 .

Dragović, Snežana, Janković Mandić, Ljiljana, Momčilović, Milan, Onjia, Antonije, "Population doses from terrestrial gamma exposure in Serbia" in Archive of Oncology, 15, no. 3-4 (2007):78-80,
https://hdl.handle.net/21.15107/rcub_technorep_7231 .

TY  - CHAP
AU  - Dragović, Snežana
AU  - Onjia, Antonije
PY  - 2007
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/6542
AB  - Pattern recognition methods provide powerful tools for the analysis and interpretation of large environmental data sets generated within environmental monitoring programmes. Most of these data sets consist of trace elements and/or trace organic pollutants patterns. Only a few studies have been done on employing the pattern recognition methods to describe the correlation between locations and radioactive contamination. This multivariate approach has been used predominantly for the identification of radioactive isotopes, quantitative gamma-ray spectrometry analysis and for optimization of gamma-ray spectrometric measurements. Spatial data analysis based on radioactive contamination of diverse regions is complex for many reasons. These include the uncertainty of the source term, high spatial and temporal variability of pollution patterns, spatial and temporal non-stationary and the multivariate nature of the phenomenon with linearly and non-linearly correlated variables. Our studies show that the geographic origin can be recognized with minimum effort if the relevant constituents are analyzed and the results are included in data analysis algorithms. Five common pattern-recognition techniques, artificial neural networks (ANN), principal component analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbors (kNN) and soft independent modeling of class analogy (SIMCA) were employed to classify soil and bioindicator samples (mosses and lichens) according to their geographical origin, based on their content of radionuclides from different sources (members of the natural uranium and thorium decay chains, cesium isotopes originating from the Chernobyl power plant accident and cosmogenic beryllium), determined by gamma-ray spectrometry. The ability of the ANN to extract hidden features from the input signals was found to be particularly useful for this kind of monitoring, when the data sets with complex correlation structures had to be analyzed, or when data sets contained series of many highly inter correlated variables.
PB  - Nova Science Publishers
T2  - Pattern Recognition in Nanoscience, Environmental Engineering and Archeology
T1  - Pattern Recognition Methods in Environmental Radioactivity Studies
EP  - 157
IS  - 5
SP  - 123
UR  - https://hdl.handle.net/21.15107/rcub_technorep_6542
ER  - 

@inbook{
author = "Dragović, Snežana and Onjia, Antonije",
year = "2007",
abstract = "Pattern recognition methods provide powerful tools for the analysis and interpretation of large environmental data sets generated within environmental monitoring programmes. Most of these data sets consist of trace elements and/or trace organic pollutants patterns. Only a few studies have been done on employing the pattern recognition methods to describe the correlation between locations and radioactive contamination. This multivariate approach has been used predominantly for the identification of radioactive isotopes, quantitative gamma-ray spectrometry analysis and for optimization of gamma-ray spectrometric measurements. Spatial data analysis based on radioactive contamination of diverse regions is complex for many reasons. These include the uncertainty of the source term, high spatial and temporal variability of pollution patterns, spatial and temporal non-stationary and the multivariate nature of the phenomenon with linearly and non-linearly correlated variables. Our studies show that the geographic origin can be recognized with minimum effort if the relevant constituents are analyzed and the results are included in data analysis algorithms. Five common pattern-recognition techniques, artificial neural networks (ANN), principal component analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbors (kNN) and soft independent modeling of class analogy (SIMCA) were employed to classify soil and bioindicator samples (mosses and lichens) according to their geographical origin, based on their content of radionuclides from different sources (members of the natural uranium and thorium decay chains, cesium isotopes originating from the Chernobyl power plant accident and cosmogenic beryllium), determined by gamma-ray spectrometry. The ability of the ANN to extract hidden features from the input signals was found to be particularly useful for this kind of monitoring, when the data sets with complex correlation structures had to be analyzed, or when data sets contained series of many highly inter correlated variables.",
publisher = "Nova Science Publishers",
journal = "Pattern Recognition in Nanoscience, Environmental Engineering and Archeology",
booktitle = "Pattern Recognition Methods in Environmental Radioactivity Studies",
pages = "157-123",
number = "5",
url = "https://hdl.handle.net/21.15107/rcub_technorep_6542"
}

Dragović, S.,& Onjia, A.. (2007). Pattern Recognition Methods in Environmental Radioactivity Studies. in Pattern Recognition in Nanoscience, Environmental Engineering and Archeology
Nova Science Publishers.(5), 123-157.
https://hdl.handle.net/21.15107/rcub_technorep_6542

Dragović S, Onjia A. Pattern Recognition Methods in Environmental Radioactivity Studies. in Pattern Recognition in Nanoscience, Environmental Engineering and Archeology. 2007;(5):123-157.
https://hdl.handle.net/21.15107/rcub_technorep_6542 .

Dragović, Snežana, Onjia, Antonije, "Pattern Recognition Methods in Environmental Radioactivity Studies" in Pattern Recognition in Nanoscience, Environmental Engineering and Archeology, no. 5 (2007):123-157,
https://hdl.handle.net/21.15107/rcub_technorep_6542 .

TY  - JOUR
AU  - Dragović, Snežana D.
AU  - Onjia, Antonije
PY  - 2007
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1182
AB  - The artificial neural network (ANN) data analysis method was used to recognize and classify soils of an unknown geographic origin. A total of 103 soil samples were differentiated into classes according to the regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232, and Be-7) activities detected by gamma-ray spectrometry were then used as inputs to ANN. Five different training algorithms with different numbers of samples in training sets were tested and compared in order to find the one with the minimum root mean square error (RMSE). The best predictive power for the classification of soils from the fifteen regions was achieved using a network with seven hidden layer nodes and 2500 training epochs using the online back-propagation randomized training algorithm. With the optimized ANN, most soil samples not included in the ANN training data set were correctly classified at an average rate of 92%.
PB  - Maik Nauka/Interperiodica/Springer, New York
T2  - Russian Journal of Physical Chemistry A
T1  - Artificial neural network data analysis for classification of soils based on their radionuclide content
EP  - 1481
IS  - 9
SP  - 1477
VL  - 81
DO  - 10.1134/S0036024407090257
ER  - 

@article{
author = "Dragović, Snežana D. and Onjia, Antonije",
year = "2007",
abstract = "The artificial neural network (ANN) data analysis method was used to recognize and classify soils of an unknown geographic origin. A total of 103 soil samples were differentiated into classes according to the regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232, and Be-7) activities detected by gamma-ray spectrometry were then used as inputs to ANN. Five different training algorithms with different numbers of samples in training sets were tested and compared in order to find the one with the minimum root mean square error (RMSE). The best predictive power for the classification of soils from the fifteen regions was achieved using a network with seven hidden layer nodes and 2500 training epochs using the online back-propagation randomized training algorithm. With the optimized ANN, most soil samples not included in the ANN training data set were correctly classified at an average rate of 92%.",
publisher = "Maik Nauka/Interperiodica/Springer, New York",
journal = "Russian Journal of Physical Chemistry A",
title = "Artificial neural network data analysis for classification of soils based on their radionuclide content",
pages = "1481-1477",
number = "9",
volume = "81",
doi = "10.1134/S0036024407090257"
}

Dragović, S. D.,& Onjia, A.. (2007). Artificial neural network data analysis for classification of soils based on their radionuclide content. in Russian Journal of Physical Chemistry A
Maik Nauka/Interperiodica/Springer, New York., 81(9), 1477-1481.
https://doi.org/10.1134/S0036024407090257

Dragović SD, Onjia A. Artificial neural network data analysis for classification of soils based on their radionuclide content. in Russian Journal of Physical Chemistry A. 2007;81(9):1477-1481.
doi:10.1134/S0036024407090257 .

Dragović, Snežana D., Onjia, Antonije, "Artificial neural network data analysis for classification of soils based on their radionuclide content" in Russian Journal of Physical Chemistry A, 81, no. 9 (2007):1477-1481,
https://doi.org/10.1134/S0036024407090257 . .

TY  - JOUR
AU  - Dragović, Snežana
AU  - Onjia, Antonije
PY  - 2007
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1121
AB  - Multivariate data analysis methods were used to recognize and classify soils of unknown geographic origin. A total of 103 soil samples were differentiated into classes, according to regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232 and Be-7) activities detected by gamma-ray spectrometry were then used as the inputs in different pattern recognition methods. For the classification of soil samples using eight selected radionuclides, the prediction ability of linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) were 82.8%, 88.6%, 60.0% and 92.1%, respectively.
PB  - Pergamon-Elsevier Science Ltd, Oxford
T2  - Applied Radiation and Isotopes
T1  - Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods
EP  - 224
IS  - 2
SP  - 218
VL  - 65
DO  - 10.1016/j.apradiso.2006.07.005
ER  - 

@article{
author = "Dragović, Snežana and Onjia, Antonije",
year = "2007",
abstract = "Multivariate data analysis methods were used to recognize and classify soils of unknown geographic origin. A total of 103 soil samples were differentiated into classes, according to regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232 and Be-7) activities detected by gamma-ray spectrometry were then used as the inputs in different pattern recognition methods. For the classification of soil samples using eight selected radionuclides, the prediction ability of linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) were 82.8%, 88.6%, 60.0% and 92.1%, respectively.",
publisher = "Pergamon-Elsevier Science Ltd, Oxford",
journal = "Applied Radiation and Isotopes",
title = "Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods",
pages = "224-218",
number = "2",
volume = "65",
doi = "10.1016/j.apradiso.2006.07.005"
}

Dragović, S.,& Onjia, A.. (2007). Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods. in Applied Radiation and Isotopes
Pergamon-Elsevier Science Ltd, Oxford., 65(2), 218-224.
https://doi.org/10.1016/j.apradiso.2006.07.005

Dragović S, Onjia A. Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods. in Applied Radiation and Isotopes. 2007;65(2):218-224.
doi:10.1016/j.apradiso.2006.07.005 .

Dragović, Snežana, Onjia, Antonije, "Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods" in Applied Radiation and Isotopes, 65, no. 2 (2007):218-224,
https://doi.org/10.1016/j.apradiso.2006.07.005 . .

TY  - JOUR
AU  - Dragović, Snežana D.
AU  - Onjia, Antonije
AU  - Dragović, Ranko M.
AU  - Bacić, Goran
PY  - 2007
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1095
AB  - Mosses and lichens have an important role in biomonitoring. The objective of this study is to develop a neural network model to classify these plants according to geographical origin. A three-layer feed-forward neural network was used. The activities of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) detected in plant samples by gamma-ray spectrometry were used as inputs for neural network. Five different training algorithms with different number of samples in training sets were tested and compared, in order to find the one with the minimum root mean square error. The best predictive power for the classification of plants from 12 regions was achieved using a network with 5 hidden layer nodes and 3,000 training epochs, using the online back-propagation randomized training algorithm. Implementation of this model to experimental data resulted in satisfactory classification of moss and lichen samples in terms of their geographical origin. The average classification rate obtained in this study was (90.7 +/- 4.8)%.
PB  - Springer, Dordrecht
T2  - Environmental Monitoring and Assessment
T1  - Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis
EP  - 253
IS  - 1-3
SP  - 245
VL  - 130
DO  - 10.1007/s10661-006-9393-4
ER  - 

@article{
author = "Dragović, Snežana D. and Onjia, Antonije and Dragović, Ranko M. and Bacić, Goran",
year = "2007",
abstract = "Mosses and lichens have an important role in biomonitoring. The objective of this study is to develop a neural network model to classify these plants according to geographical origin. A three-layer feed-forward neural network was used. The activities of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) detected in plant samples by gamma-ray spectrometry were used as inputs for neural network. Five different training algorithms with different number of samples in training sets were tested and compared, in order to find the one with the minimum root mean square error. The best predictive power for the classification of plants from 12 regions was achieved using a network with 5 hidden layer nodes and 3,000 training epochs, using the online back-propagation randomized training algorithm. Implementation of this model to experimental data resulted in satisfactory classification of moss and lichen samples in terms of their geographical origin. The average classification rate obtained in this study was (90.7 +/- 4.8)%.",
publisher = "Springer, Dordrecht",
journal = "Environmental Monitoring and Assessment",
title = "Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis",
pages = "253-245",
number = "1-3",
volume = "130",
doi = "10.1007/s10661-006-9393-4"
}

Dragović, S. D., Onjia, A., Dragović, R. M.,& Bacić, G.. (2007). Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis. in Environmental Monitoring and Assessment
Springer, Dordrecht., 130(1-3), 245-253.
https://doi.org/10.1007/s10661-006-9393-4

Dragović SD, Onjia A, Dragović RM, Bacić G. Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis. in Environmental Monitoring and Assessment. 2007;130(1-3):245-253.
doi:10.1007/s10661-006-9393-4 .

Dragović, Snežana D., Onjia, Antonije, Dragović, Ranko M., Bacić, Goran, "Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis" in Environmental Monitoring and Assessment, 130, no. 1-3 (2007):245-253,
https://doi.org/10.1007/s10661-006-9393-4 . .

TY  - JOUR
AU  - Vasiljević, Tatjana
AU  - Spasojević, J.
AU  - Baćić, M.
AU  - Onjia, Antonije
AU  - Laušević, Mila
PY  - 2006
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/927
AB  - In this work the effect of the activated carbon cloth surface acidity and pH of the solution on phenols adsorption has been studied. Two phenols, widely different in the terms of their pKa values (phenol and 2,4-dinitrophenol), have been chosen as the model compounds. It has been shown that phenol adsorption was favored by low pH values of solution and high point of zero charge values of activated carbon cloths. The adsorption of 2,4-dinitrophenol was promoted at very low pH values of solution and it was less influenced by activated carbon cloth surface acidity.
PB  - Taylor & Francis Inc, Philadelphia
T2  - Separation Science and Technology
T1  - Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH
EP  - 1075
IS  - 6
SP  - 1061
VL  - 41
DO  - 10.1080/01496390600588853
ER  - 

@article{
author = "Vasiljević, Tatjana and Spasojević, J. and Baćić, M. and Onjia, Antonije and Laušević, Mila",
year = "2006",
abstract = "In this work the effect of the activated carbon cloth surface acidity and pH of the solution on phenols adsorption has been studied. Two phenols, widely different in the terms of their pKa values (phenol and 2,4-dinitrophenol), have been chosen as the model compounds. It has been shown that phenol adsorption was favored by low pH values of solution and high point of zero charge values of activated carbon cloths. The adsorption of 2,4-dinitrophenol was promoted at very low pH values of solution and it was less influenced by activated carbon cloth surface acidity.",
publisher = "Taylor & Francis Inc, Philadelphia",
journal = "Separation Science and Technology",
title = "Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH",
pages = "1075-1061",
number = "6",
volume = "41",
doi = "10.1080/01496390600588853"
}

Vasiljević, T., Spasojević, J., Baćić, M., Onjia, A.,& Laušević, M.. (2006). Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH. in Separation Science and Technology
Taylor & Francis Inc, Philadelphia., 41(6), 1061-1075.
https://doi.org/10.1080/01496390600588853

Vasiljević T, Spasojević J, Baćić M, Onjia A, Laušević M. Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH. in Separation Science and Technology. 2006;41(6):1061-1075.
doi:10.1080/01496390600588853 .

Vasiljević, Tatjana, Spasojević, J., Baćić, M., Onjia, Antonije, Laušević, Mila, "Adsorption of phenol and 2,4-dinitrophenol on activated carbon cloth: The influence of sorbent surface acidity and pH" in Separation Science and Technology, 41, no. 6 (2006):1061-1075,
https://doi.org/10.1080/01496390600588853 . .

TY  - JOUR
AU  - Dragović, Snežana D.
AU  - Janković-Mandić, Ljiljana
AU  - Onjia, Antonije
PY  - 2006
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/981
AB  - The gamma dose rates due to naturally occuring terrestrial radionuclides (Ra-226, Th-232 and K-40) were calculated based on their activities in soil samples, determined by gamma-ray spectrometry. A total of 140 soil samples from 21 different regions of Serbia and Montenegro were collected. The gamma dose rates ranged from 7.40 to 29.7 nGy h(-1) for Ra-226, from 12.9 to 46.5 nGy h(-1) for Th-232 and from 12.5 to 37.1 nGy h(-1) for K-40. The total absorbed gamma dose rate due to these radionuclides varied from 34.5 to 97.6 nGy h(-1) with mean of 66.8 nGy h(-1). Assuming a 20% occupancy factor, the corresponding annual effective dose varied from 4.23 x 10(-5) to 11.9 x 10(-5) Sv with mean of 8.19 x 10(-5) Sv, i.e. the dose was lower than world wide average value. According to the values of external hazard index (mean: 0.39) obtained in this study, the radiation hazard was found to be insignificant for population living in the investigated area.
PB  - Oxford Univ Press, Oxford
T2  - Radiation Protection Dosimetry
T1  - Assessment of gamma dose rates from terrestrial exposure in Serbia and Montenegro
EP  - 302
IS  - 3
SP  - 297
VL  - 121
DO  - 10.1093/rpd/ncl099
ER  - 

@article{
author = "Dragović, Snežana D. and Janković-Mandić, Ljiljana and Onjia, Antonije",
year = "2006",
abstract = "The gamma dose rates due to naturally occuring terrestrial radionuclides (Ra-226, Th-232 and K-40) were calculated based on their activities in soil samples, determined by gamma-ray spectrometry. A total of 140 soil samples from 21 different regions of Serbia and Montenegro were collected. The gamma dose rates ranged from 7.40 to 29.7 nGy h(-1) for Ra-226, from 12.9 to 46.5 nGy h(-1) for Th-232 and from 12.5 to 37.1 nGy h(-1) for K-40. The total absorbed gamma dose rate due to these radionuclides varied from 34.5 to 97.6 nGy h(-1) with mean of 66.8 nGy h(-1). Assuming a 20% occupancy factor, the corresponding annual effective dose varied from 4.23 x 10(-5) to 11.9 x 10(-5) Sv with mean of 8.19 x 10(-5) Sv, i.e. the dose was lower than world wide average value. According to the values of external hazard index (mean: 0.39) obtained in this study, the radiation hazard was found to be insignificant for population living in the investigated area.",
publisher = "Oxford Univ Press, Oxford",
journal = "Radiation Protection Dosimetry",
title = "Assessment of gamma dose rates from terrestrial exposure in Serbia and Montenegro",
pages = "302-297",
number = "3",
volume = "121",
doi = "10.1093/rpd/ncl099"
}

Dragović, S. D., Janković-Mandić, L.,& Onjia, A.. (2006). Assessment of gamma dose rates from terrestrial exposure in Serbia and Montenegro. in Radiation Protection Dosimetry
Oxford Univ Press, Oxford., 121(3), 297-302.
https://doi.org/10.1093/rpd/ncl099

Dragović SD, Janković-Mandić L, Onjia A. Assessment of gamma dose rates from terrestrial exposure in Serbia and Montenegro. in Radiation Protection Dosimetry. 2006;121(3):297-302.
doi:10.1093/rpd/ncl099 .

Dragović, Snežana D., Janković-Mandić, Ljiljana, Onjia, Antonije, "Assessment of gamma dose rates from terrestrial exposure in Serbia and Montenegro" in Radiation Protection Dosimetry, 121, no. 3 (2006):297-302,
https://doi.org/10.1093/rpd/ncl099 . .

TY  - JOUR
AU  - Dragović, Snežana D.
AU  - Onjia, Antonije
PY  - 2006
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/976
AB  - A principal component analysis (PCA) was used for classification of soil samples from different locations in Serbia and Montenegro. Based on activities of radionuclides (Ra-226, U-238, U-235, K-40, Cs-134, Cs-131, Th-232 and Be-7) detected by gamma-ray spectrometry, the classification of soils according to their geographical origin was performed. Application of PCA to our experimental data resulted in satisfactory classification rate (86.0% correctly classified samples). The obtained results indicate that gamma-ray spectrometry in conjunction with PCA is a viable tool for soil classification.
PB  - Elsevier Sci Ltd, Oxford
T2  - Journal of Environmental Radioactivity
T1  - Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principal component analysis
EP  - 158
IS  - 2
SP  - 150
VL  - 89
DO  - 10.1016/j.jenvrad.2006.05.002
ER  - 

@article{
author = "Dragović, Snežana D. and Onjia, Antonije",
year = "2006",
abstract = "A principal component analysis (PCA) was used for classification of soil samples from different locations in Serbia and Montenegro. Based on activities of radionuclides (Ra-226, U-238, U-235, K-40, Cs-134, Cs-131, Th-232 and Be-7) detected by gamma-ray spectrometry, the classification of soils according to their geographical origin was performed. Application of PCA to our experimental data resulted in satisfactory classification rate (86.0% correctly classified samples). The obtained results indicate that gamma-ray spectrometry in conjunction with PCA is a viable tool for soil classification.",
publisher = "Elsevier Sci Ltd, Oxford",
journal = "Journal of Environmental Radioactivity",
title = "Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principal component analysis",
pages = "158-150",
number = "2",
volume = "89",
doi = "10.1016/j.jenvrad.2006.05.002"
}

Dragović, S. D.,& Onjia, A.. (2006). Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principal component analysis. in Journal of Environmental Radioactivity
Elsevier Sci Ltd, Oxford., 89(2), 150-158.
https://doi.org/10.1016/j.jenvrad.2006.05.002

Dragović SD, Onjia A. Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principal component analysis. in Journal of Environmental Radioactivity. 2006;89(2):150-158.
doi:10.1016/j.jenvrad.2006.05.002 .

Dragović, Snežana D., Onjia, Antonije, "Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principal component analysis" in Journal of Environmental Radioactivity, 89, no. 2 (2006):150-158,
https://doi.org/10.1016/j.jenvrad.2006.05.002 . .

TY  - JOUR
AU  - Dragović, Snežana
AU  - Onjia, Antonije
AU  - Bacić, Goran
PY  - 2006
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/970
AB  - A three-layer feed-forward artificial neural network (ANN) with a back-propagation learning algorithm was used to predict the minimum detectable activity (AD) of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in environmental soil samples as a function of measurement time. The ANN parameters (learning rate, momentum, number of epochs, and the number of nodes in the hidden layer) were optimized simultaneously employing a variable-size simplex method. The optimized ANN model revealed satisfactory predictions, with correlation coefficients between experimental and predicted values 0.9517 for 232 Th (sample with U-238/Th-232 ratio of 1.14) to 0.9995 for K-40 (sample with U-238/Th-232 ratio of 0.43). Neither the differences between the measured and the predicted A(D) values nor the correlation coefficients were influenced by the absolute values of AD for the investigated radionuclides.
PB  - Elsevier, Amsterdam
T2  - Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors And
T1  - Simplex optimization of artificial neural networks for the prediction of minimum detectable activity in gamma-ray spectrometry
EP  - 314
IS  - 1
SP  - 308
VL  - 564
DO  - 10.1016/j.nima.2006.03.047
ER  - 

@article{
author = "Dragović, Snežana and Onjia, Antonije and Bacić, Goran",
year = "2006",
abstract = "A three-layer feed-forward artificial neural network (ANN) with a back-propagation learning algorithm was used to predict the minimum detectable activity (AD) of radionuclides (Ra-226, U-238, U-235, K-40, Th-232, Cs-134, Cs-137 and Be-7) in environmental soil samples as a function of measurement time. The ANN parameters (learning rate, momentum, number of epochs, and the number of nodes in the hidden layer) were optimized simultaneously employing a variable-size simplex method. The optimized ANN model revealed satisfactory predictions, with correlation coefficients between experimental and predicted values 0.9517 for 232 Th (sample with U-238/Th-232 ratio of 1.14) to 0.9995 for K-40 (sample with U-238/Th-232 ratio of 0.43). Neither the differences between the measured and the predicted A(D) values nor the correlation coefficients were influenced by the absolute values of AD for the investigated radionuclides.",
publisher = "Elsevier, Amsterdam",
journal = "Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors And",
title = "Simplex optimization of artificial neural networks for the prediction of minimum detectable activity in gamma-ray spectrometry",
pages = "314-308",
number = "1",
volume = "564",
doi = "10.1016/j.nima.2006.03.047"
}

Dragović, S., Onjia, A.,& Bacić, G.. (2006). Simplex optimization of artificial neural networks for the prediction of minimum detectable activity in gamma-ray spectrometry. in Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors And
Elsevier, Amsterdam., 564(1), 308-314.
https://doi.org/10.1016/j.nima.2006.03.047

Dragović S, Onjia A, Bacić G. Simplex optimization of artificial neural networks for the prediction of minimum detectable activity in gamma-ray spectrometry. in Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors And. 2006;564(1):308-314.
doi:10.1016/j.nima.2006.03.047 .

Dragović, Snežana, Onjia, Antonije, Bacić, Goran, "Simplex optimization of artificial neural networks for the prediction of minimum detectable activity in gamma-ray spectrometry" in Nuclear Instruments & Methods in Physics Research Section A-Accelerators Spectrometers Detectors And, 564, no. 1 (2006):308-314,
https://doi.org/10.1016/j.nima.2006.03.047 . .

TY  - JOUR
AU  - Dragović, Snežana D.
AU  - Janković-Mandić, Ljiljana
AU  - Onjia, Antonije
AU  - Bacić, G
PY  - 2006
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/937
AB  - The specific activities of primordial radionuclides in soil samples from 21 different locations in Serbia and Montenegro were determined by gamma-ray spectrometry. The results obtained were compared with those from other studies conducted worldwide. Concentrations of radionuclides in soils analyzed in this study ranged from 1.28 to 4.80 ppm for uranium, from 5.26 to 19.0 ppm for thorium, and from 0.97% to 2.87% for potassium. The mean concentrations of U (2.76 ppm) and Th (10.4 ppm) are similar to the world average (2.64 and 11.1 ppm for U and Th, respectively), whereas the mean concentration of K (1.98%) is about 1.4 times higher than world average value (1.37%).
PB  - Pergamon-Elsevier Science Ltd, Oxford
T2  - Radiation Measurements
T1  - Distribution of primordial radionuclides in surface soils from Serbia and Montenegro
EP  - 616
IS  - 5
SP  - 611
VL  - 41
DO  - 10.1016/j.radmeas.2006.03.007
ER  - 

@article{
author = "Dragović, Snežana D. and Janković-Mandić, Ljiljana and Onjia, Antonije and Bacić, G",
year = "2006",
abstract = "The specific activities of primordial radionuclides in soil samples from 21 different locations in Serbia and Montenegro were determined by gamma-ray spectrometry. The results obtained were compared with those from other studies conducted worldwide. Concentrations of radionuclides in soils analyzed in this study ranged from 1.28 to 4.80 ppm for uranium, from 5.26 to 19.0 ppm for thorium, and from 0.97% to 2.87% for potassium. The mean concentrations of U (2.76 ppm) and Th (10.4 ppm) are similar to the world average (2.64 and 11.1 ppm for U and Th, respectively), whereas the mean concentration of K (1.98%) is about 1.4 times higher than world average value (1.37%).",
publisher = "Pergamon-Elsevier Science Ltd, Oxford",
journal = "Radiation Measurements",
title = "Distribution of primordial radionuclides in surface soils from Serbia and Montenegro",
pages = "616-611",
number = "5",
volume = "41",
doi = "10.1016/j.radmeas.2006.03.007"
}

Dragović, S. D., Janković-Mandić, L., Onjia, A.,& Bacić, G.. (2006). Distribution of primordial radionuclides in surface soils from Serbia and Montenegro. in Radiation Measurements
Pergamon-Elsevier Science Ltd, Oxford., 41(5), 611-616.
https://doi.org/10.1016/j.radmeas.2006.03.007

Dragović SD, Janković-Mandić L, Onjia A, Bacić G. Distribution of primordial radionuclides in surface soils from Serbia and Montenegro. in Radiation Measurements. 2006;41(5):611-616.
doi:10.1016/j.radmeas.2006.03.007 .

Dragović, Snežana D., Janković-Mandić, Ljiljana, Onjia, Antonije, Bacić, G, "Distribution of primordial radionuclides in surface soils from Serbia and Montenegro" in Radiation Measurements, 41, no. 5 (2006):611-616,
https://doi.org/10.1016/j.radmeas.2006.03.007 . .