Citácie 2022

Vedecké monografie vydané v zahraničných vydavateľstvách

 

  • CAPEK, Ignác. Noble Metal Nanoparticles : Preparation, Composite Nanostructures, Biodecoration and Collective Properties. Springer, 2017. xvii, 554 p. ISBN 978-4-431-56554-3. https://doi.org/10.1007/978-4-431-56556-7_2

Citácie WOS: 2; iné citácie: 1

1. [1.1] KIM, D. – LEE, C. – ISLAM, A. – CHOI, D. – JEONG, G. – KIM, T. – CHO, H. – KIM, Y. – SHAH, S. – PARK, M. – KIM, S. – LEE, H. – LEE, J. – BANG, S. – BAE, T. – PARK, J. – YU, S. – KANG, Y. – PARK, J. – PARK, M. – JEONG, Y. – LEE, S. – JIN, J. – KIM, K. – SUJAK, M. – MOON, S. – PARK, S. – SONG, M. – KIM, C. – RYU, S. Efficient Photon Extraction in Top‐Emission Organic Light‐Emitting Devices Based on Ampicillin Microstructures. In ADVANCED MATERIALS. ISSN 1521-4095, 2022, vol. 34, no. 32. https://doi.org/10.1002/adma.202202866; WOS

2. [1.1] VERKHOVTSEV, A.V. – NICHOLS, A. – MASON, N.J. – SOLOVYOV, A.V. Molecular Dynamics Characterization of Radiosensitizing Coated Gold Nanoparticles in Aqueous Environment. In JOURNAL OF PHYSICAL CHEMISTRY A. ISSN 1089-5639, APR 14 2022, vol. 126, no. 14, p. 2170-2184. https://doi.org/10.1021/acs.jpca.2c00489; WOS

3. [3.1] ALLHIBY, M.T. – ALJUBOORI, M.S. Study of Optical and Structural Properties of Silver Solution Ag Nanoparticles. In JOURNAL OF EDUCATION AND SCIENCE, 2022, vol. 31, no. 4, p. 10-16. https://doi.org/10.33899/edusj.2022.134548.1256

 

  • CAPEK, Ignác. Nanocomposite Structures and Dispersions : Second Edition. Elsevier, 2019. 458 p. ISBN 978-0-444-63748-2. https://doi.org/10.1016/C2015-0-00616-5

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] WU, Z.Q. – YANG, F. – LI, X.M. – CARROLL, A. – LOA-KUM-CHEUNG, W. – SHEWAN, H.M. – STOKES, J.R. – ZHAO, D.Y. – LI, Q. Solid and hollow nanoparticles templated using non-ionic surfactant-based reverse micelles and vesicles. In COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS. ISSN 0927-7757, FEB 5 2022, vol. 634. https://doi.org/10.1016/j.colsurfa.2021.127917; WOS

2. [1.2] HUSEIEN, G.F. – KHALID, N.H.A. – MIRZAN, J. Nanotechnology for Smart Concrete. Routledge, 2022, ISBN 9781032051277. https://doi.org/10.1201/9781003196143.; SCOPUS

 

Kapitoly vo vedeckých monografiách vydaných v zahraničných vydavateľstvách

 

  • PETRÁK, J. – MRAVEC, B. – JURÁNI, M. – BARANOVSKÁ, M. – TILLINGER, A. – HAPALA, I. – FROLLO, Ivan – KVETŇANSKÝ, R. Hypergravity-induced increase in plasma catecholamine and corticosterone levels in telemetrically collected blood of rats during centrifugation. In Stress, Neurotransmitters, and Hormones : Neuroendocrine and Genetic Mechanisms. – Wiley-Blackwell, 2008, vol. 1148, p. 201-208. ISBN 978-1-57331-692-7. https://doi.org/10.1196/annals.1410.060

Citácie WOS: 1

1. [1.1] MHATRE, S.D. – IYER, J. – PUUKILA, S. – PAUL, A.M. – TAHIMIC, C. – RUBINSTEIN, L. – LOWE, M. – ALWOOD, J.S. – SOWA, M.B. – BHATTACHARYA, S. – GLOBUS, R.K. – RONCA, A.E. Neuro-consequences of the spaceflight environment. In NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS. ISSN 0149-7634, 2022, vol. 132, p. 908-935. https://doi.org/10.1016/j.neubiorev.2021.09.055; WOS

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. Microintonation analysis of emotional speech. In Development of Multimodal Interfaces : Active Listening and Synchrony. – Berlin : Springer-Verlag, 2010, lNCS 5967, P. 268-279. ISBN 978-3-642-12396-2. https://doi.org/10.1007/978-3-642-12397-9-22

Citácie WOS: 1

1. [1.1] GARCIA, M.N.D. Discourse markers in emotional contexts. In ESTUDIOS DE LINGUISTICA-UNIVERSIDAD DE ALICANTE-ELUA. ISSN 0212-7636, 2022, no. 37, p. 155-183. https://doi.org/10.14198/ELUA.19882; WOS

 

  • ROSIPAL, Roman. Nonlinear partial least squares: An overview. In Chemoinformatics and Advanced Machine Learning Perspectives : Complex Computational Methods and Collaborative Techniques. – IGI Global, 2010, p. 169-189. ISBN 978-1-61520-911-8. https://doi.org/10.4018/978-1-61520-911-8.ch009

Citácie WOS: 8; iné citácie: 1

1. [1.1] EHRE, M. – PAPAIOANNOU, I. – SUDRET, B. – STRAUB, D. Sequential active learning of low-dimensional model representations for reliability analysis. In SIAM JOURNAL ON SCIENTIFIC COMPUTING. ISSN 1064-8275, 2022, vol. 44, no. 3, p. B558-B584. https://doi.org/10.1137/21M1416758; WOS

2. [1.1] GAUTIER, R. – PANDITA, P. – GHOSH, S. – MAVRIS, D. A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes. In INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION. ISSN 2152-5080, 2022, vol. 12, no. 2, p. 19-51. http://dx.doi.org/10.1615/Int.J.UncertaintyQuantification.2021035621; WOS

3. [1.1] HOU, C.K.J. – BEHDINAN, K. Dimensionality Reduction in Surrogate Modeling: A Review of Combined Methods. In DATA SCIENCE AND ENGINEERING. ISSN 2364-1185, 2022, vol. 7, no. 4, p. 402-427. https://doi.org/10.1007/s41019-022-00193-5; WOS

4. [1.1] ISACHENKO, R.V. – STRIJOV, V.V. Quadratic programming feature selection for multicorrelated signal decoding with partial least squares. In EXPERT SYSTEMS WITH APPLICATIONS. ISSN 0957-4174, 2022, vol. 207. https://doi.org/10.1016/j.eswa.2022.117967; WOS

5. [1.1] LEMARCQ, V. – VAN DE WALLE, D. – MONTERDE, V. – SIORIKI, E. – DEWETTINCK, K. Assessing the flavor of cocoa liquor and chocolate through instrumental and sensory analysis: a critical review. In CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION. ISSN 1040-8398, NOV 13 2022, vol. 62, no. 20, p. 5523-5539. https://doi.org/10.1080/10408398.2021.1887076; WOS

6. [1.1] QIN, Y. – LOU, Z. – WANG, Y. – LU, S. – SUN, P. An analytical partial least squares method for process monitoring. In CONTROL ENGINEERING PRACTICE. ISSN 0967-0661, 2022, vol. 124. https://doi.org/10.1016/j.conengprac.2022.105182; WOS

7. [1.1] SETON, R. – PERSSON, A. A structured evaluation of regression models for predicting CO2 concentration from plasma emission spectra. In SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY. ISSN 0584-8547, 2022, vol. 194. https://doi.org/10.1016/j.sab.2022.106467; WOS

8. [1.1] XIOURAS, C. – CAMELI, F. – QUILLO, G.L. – KAVOUSANAKIS, M.E. – VLACHOS, D.G. – STEFANIDIS, G.D. Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization. In CHEMICAL REVIEWS. ISSN 0009-2665, 2022. https://doi.org/10.1021/acs.chemrev.2c00141; WOS

9. [3.1] WANG, Z. – IERAPETRITOU, M. Applications of optimization in the pharmaceutical process development. In HOW TO DESIGN AND IMPLEMENT POWDER-TO-TABLET CONTINUOUS MANUFACTURING SYSTEMS, 2022, p. 271-299. https://doi.org/10.1016/B978-0-12-813479-5.00012-4

 

  • WITKOVSKÝ, Viktor – WIMMER, G. Generalized polynomial comparative calibration: Parameter estimation and applications. In Advances in Measurements and Instrumentation : Reviews, Vol. 1. – International Frequency Sensor Association (IFSA) Publishing, 2018, p. 15-52. ISBN 978-84-09-07321-4.

Iné citácie: 1

1. [3.1] ZAKHAROV, I. – NEYEZHMAKOV, P. – SEMENIKHIN, V. – WARSZAM, Z.L. Measurement Uncertainty Evaluation of Parameters Describing the Calibrated Curves. In AUTOMATION 2022: NEW SOLUTIONS AND TECHNOLOGIES FOR AUTOMATION, ROBOTICS AND MEASUREMENT TECHNIQUES. Springer, 2022, AISC vol. 1427. https://doi.org/10.1007/978-3-031-03502-9_38

 

Vysokoškolské učebnice vydané v domácich vydavateľstvách

 

  • PALENČÁR, R. – WIMMER, G. – PALENČÁR, J. – WITKOVSKÝ, Viktor. Navrhovanie a vyhodnocovanie meraní [Design and Evaluation of Measurements]. Recenzenti: M. Dovica, D. Janáčová, J. Markovič. 1. vydanie. Bratislava : Slovenská technická univerzita v Bratislave, 2021. 160 s. ISBN 978-80-227-5080-6.

Citácie WOS: 1

1. [1.1] JABLONICKY, J. – FERIANCOVA, P. – TULIK, J. – HUJO, L. – TKAC, Z. – KUCHAR, P. – TOMIC, M. – KASZKOWIAK, J. Assessment of Technical and Ecological Parameters of a Diesel Engine in the Application of New Samples of Biofuels. In JOURNAL OF MARINE SCIENCE AND ENGINEERING. ISSN 2077-1312, 2022, vol. 10, no. 1. https://doi.org/10.3390/jmse10010001; WOS

 

Vedecké práce v zahraničných karentovaných časopisoch, impaktovaných

 

  • ANDRIS, PeterDERMEK, TomášFROLLO, Ivan. Simplified matching and tuning experimental receive coils for low-field NMR measurements. In Measurement, 2015, vol. 64, p. 29-33. (2014: 1.484 – IF, Q2 – JCR, 0.676 – SJR, Q1 – SJR). (2015 – Current Contents). ISSN 0263-2241. https://doi.org/10.1016/j.measurement.2014.12.035

Citácie WOS: 1

1. [1.1] LIN, T.T. – ZHOU, K. – CAO, Y.M. – WAN, L. A review of Air-Core coil sensors in surface geophysical exploration. In MEASUREMENT. ISSN 0263-2241, JAN 2022, vol. 188. https://doi.org/10.1016/j.measurement.2021.110554; WOS

 

  • APPRICH, S. – SCHREINER, M. – SZOMOLÁNYI, Pavol – WELSCH, G.H. – KOLLER, U.K. – WEBER, M. – WINDHAGER, R. – TRATTNIG, S. Potential predictive value of axial T2 mapping at 3 Tesla MRI in patients with untreated patellar cartilage defects over a mean follow-up of four years. In Osteoarthritis and Cartilage, 2020, vol. 28, no. 2, p. 215-222. (2019: 4.793 – IF, Q1 – JCR, 1.828 – SJR, Q1 – SJR). (2020 – Current Contents). ISSN 1063-4584. https://doi.org/10.1016/j.joca.2019.10.009

Citácie WOS: 1

1. [1.1] LIU, L.L. – LIU, H.A. – ZHEN, Z.M. – ZHENG, Y.L. – ZHOU, X.Y. – RAITHEL, E. – DU, J. – HU, Y. – CHEN, W. – HU, X.F. Analysis of Knee Joint Injury Caused by Physical Training of Freshmen Students Based on 3T MRI and Automatic Cartilage Segmentation Technology: A Prospective Study. In FRONTIERS IN ENDOCRINOLOGY. ISSN 1664-2392, MAY 9 2022, vol. 13. https://doi.org/10.3389/fendo.2022.839112; WOS

 

  • APPRICH, S. – WELSCH, G.H. – MAMISCH, T.C. – SZOMOLÁNYI, Pavol – MAYERHOEFER, M.E. – PINKER, K. – TRATTNIG, S. Detection of degenerative cartilage disease: Comparison of high-resolution morphological MR and quantitative T2 mapping at 3.0 Tesla. In Osteoarthritis and Cartilage, 2010, vol. 18, no. 9, p. 1211-1217. (2009: 3.888 – IF, Q2 – JCR, 1.797 – SJR, Q1 – SJR). (2010 – Current Contents). ISSN 1063-4584. https://doi.org/10.1016/j.joca.2010.06.002

Citácie WOS: 6; citácie SCOPUS: 1; iné citácie: 3

1. [1.1] BANJAR, M. – HORIUCHI, S. – GEDEON, D.N. – YOSHIOKA, H. An Invited Review for the Special 20th Anniversary Issue of MRMS Review of Quantitative Knee Articular Cartilage MR Imaging. In MAGNETIC RESONANCE IN MEDICAL SCIENCES. ISSN 1347-3182, 2022, vol. 21, no. 1, p. 29-40. https://doi.org/10.2463/mrms.rev.2021-0052; WOS

2. [1.1] GUNAY, A.E. – KARAMAN, I. – GUNEY, A. – KARAMAN, Z.F. – DEMIRPOLAT, E. – GONEN, Z.B. – DOGAN, S. – YERER, M.B. Assessment of clinical, biochemical, and radiological outcomes following intra-articular injection of Wharton jelly-derived mesenchymal stromal cells in patients with knee osteoarthritis: A prospective clinical study. In MEDICINE. ISSN 0025-7974, SEP 16 2022, vol. 101, no. 37. https://doi.org/10.1097/MD.0000000000030628; WOS

3. [1.1] KASAR, S. – OZTURK, M. – POLAT, A.V. Quantitative T2 mapping of the sacroiliac joint cartilage at 3T in patients with axial spondyloarthropathies. In EUROPEAN RADIOLOGY. ISSN 0938-7994, FEB 2022, vol. 32, no. 2, p. 1395-1403. https://doi.org/10.1007/s00330-021-08357-z; WOS

4. [1.1] OCHI, H. – KOBAYASHI, H. – BABA, T. – NAKAJIMA, R. – KURITA, Y. – KATO, S. – SASAKI, K. – NOZAWA, M. – KIM, S.G. – SAKAMOTO, Y. – HOMMA, Y. – KANEKO, K. – ISHIJIMA, M. Acetabular cartilage abnormalities in elderly patients with femoral neck fractures. In SICOT-J. ISSN 2426-8887, JUN 14 2022, vol. 8. https://doi.org/10.1051/sicotj/2022022; WOS

5. [1.1] SCHUTZ, U. – MARTENSEN, T. – KLEINER, S. – DREYHAUPT, J. – WEGENER, M. – WILKE, H.J. – BEER, M. T2*-Mapping of Knee Cartilage in Response to Mechanical Loading in Alpine Skiing: A Feasibility Study. In DIAGNOSTICS. JUN 2022, vol. 12, no. 6. https://doi.org/10.3390/diagnostics12061391; WOS

6. [1.1] WONGRATWANICH, P. – NAGASAKI, T. – SHIMABUKURO, K. – KONISHI, M. – OHTSUKA, M. – SUEI, Y. – NAKAMOTO, T. – AKIYAMA, Y. – AWAI, K. – KAKIMOTO, N. Intra- and inter-examination reproducibility of T2 mapping for temporomandibular joint assessment at 3.0 T. In SCIENTIFIC REPORTS. ISSN 2045-2322, JUN 29 2022, vol. 12, no. 1. https://doi.org/10.1038/s41598-022-15184-9; WOS

7. [1.2] FERNANDES, T.L. – DE SANTANNA, J.P.C. – FIORIO, B.A.P. – DE FARIA, R.R. – PEDRINELLI, A. – BORDALO, M. State of the art for articular cartilage morphological and composition imaging evaluation in football players. In JOURNAL OF CARTILAGE AND JOINT PRESERVATION, 2022, vol. 2, no. 2. https://doi.org/10.1016/j.jcjp.2022.100067; SCOPUS

8. [3.1] ABREU, F.G. – ANDRADE, R. – PERETTI, A.T. – CANADAS, R.F. – REIS, R.L. – OLIVEIRA, J.M. – ESPREGUEIRA-MENDES, J. Diagnosis of Cartilage and Osteochondral Defect. In JOINT FUNCTION PRESERVATION. Springer, 2022, 95-106. https://doi.org/10.1007/978-3-030-82958-2_8

9. [3.1] DAI, X. – LI, M. – MA, H. Weight-bearing cross-country running influences on the knee articular cartilage -a study using T2 MRI and muscle monitoring. In FRONTIERS IN COMPUTING AND INTELLIGENT SYSTEMS, 2022, vol. 1, no. 3, p. 17–20. https://doi.org/10.54097/fcis.v1i3.2017

10. [3.1] RAJITHA, D. – ELANGOVAN, S. – RAJADURAI, M. – SATHYANATH, A. Early degenerative changes in shoulder joint on T2 relaxometry (Cartigram). In OPEN JOURNAL OF CLINICAL AND MEDICAL CASE REPORTS, 2022, vol. 8, no. 14. https://jclinmedcasereports.com/articles/OJCMCR-1903.pdf

 

  • APPS, A. – VALKOVIČ, Ladislav – PETERZAN, M. – LAU, J.Y.C. – HUNDERTMARK, M. – CLARKE, W. – TUNNICLIFFE, E.M. – ELLIS, J. – TYLER, D.J. – NEUBAUER, S. – RIDER, O. – RODGERS, C.T. – SCHMID, A.I. Quantifying the effect of dobutamine stress on myocardial Pi and pH in healthy volunteers: A 31P MRS study at 7T. In Magnetic Resonance in Medicine, 2021, vol. 85, no. 3, p. 1147-1159. (2020: 4.668 – IF, Q1 – JCR, 1.696 – SJR, Q1 – SJR). (2021 – Current Contents). ISSN 0740-3194. https://doi.org/10.1002/mrm.28494

Citácie WOS: 1; iné citácie: 1

1. [1.1] GUPTA, A. Cardiac P-31 MR spectroscopy: development of the past five decades and future vision-will it be of diagnostic use in clinics? In HEART FAILURE REVIEWS, 2022. ISSN 1382-4147. https://doi.org/10.1007/s10741-022-10287-x; WOS

2. [3.1] CHEN, Y. – DONG, W. – YANG, Y. – CHRISTEL BELL, A. – AZURE, J.A. – WANG, Y. Mechanical stress concealed force enhancement and ionic transient membrane potential and metabolism in akinesia of stress cardiomyopathy. In SCIENCE OPEN, 2022, https://doi.org/10.14293/S2199-1006.1.SOR-.PPQOCKA.v1

 

  • ARENDACKÁ, Barbora. Generalized confidence intervals on the variance component in mixed linear models with two variance components. In Statistics, 2005, vol. 39, no. 4, p. 275-286. (2004: 0.323 – IF). (2005 – Current Contents). ISSN 0233-1888.

Citácie SCOPUS: 1

1. [1.2] JIRATAMPRADAB, A. – SUPAPAKORN, T. – SUNTORNCHOST, J. Comparison of confidence intervals for variance components in an unbalanced one-way random effects model. In STATISTICS IN TRANSITION NEW SERIES, 2022, vol. 23, no. 4, p. 149-160. ISSN 1234-7655. https://doi.org/10.2478/stattrans-2022-0047; SCOPUS

 

  • BALÁŽ, P. – ACHIMOVIČOVÁ, M. – BALÁŽ, M. – BILLIK, Peter – CHERKEZOVA-ZHELEVA, Z. – CRAIDO, J.M. – DELOGU, F. – DUTKOVÁ, E. – GAFFET, E. – GOTOR, F.J. – KUMAR, R. – MITOV, I. – ROJAC, T. – SENNA, M. – STRELETSKII, A. – WIECZOREK-CIUROWA, K. Hallmarks of mechanochemistry: From nanoparticles to technology. In Chemical Society Reviews, 2013, vol. 42, p. 7571-7637. (2012: 24.892 – IF, Q1 – JCR, 15.022 – SJR, Q1 – SJR). (2013 – Current Contents). ISSN 0306-0012. https://doi.org/10.1039/c3cs35468g

Citácie WOS: 78; citácie SCOPUS: 5; iné citácie: 11

1. [1.1] ABED, M.H. – ABBAS, I.S. – CANAKCI, H. Effect of glass powder on the rheological and mechanical properties of slag-based mechanochemical activation geopolymer grout. In EUROPEAN JOURNAL OF ENVIRONMENTAL AND CIVIL ENGINEERING. 2022, ISSN 1964-8189. https://doi.org/10.1080/19648189.2022.2145374; WOS

2. [1.1] ABED, M.H. – ABBAS, I.S. – HAMED, M. – CANAKCI, H. Rheological, fresh, and mechanical properties of mechanochemically activated geopolymer grout: A comparative study with conventionally activated geopolymer grout. In CONSTRUCTION AND BUILDING MATERIALS. ISSN 0950-0618, MAR 7 2022, vol. 322. https://doi.org/10.1016/j.conbuildmat.2022.126338; WOS

3. [1.1] ALBAB, N.D. – NAM, H. – HAN, C. – OMASTOVA, M. – CHEHIMI, M.M. – MOHAMED, A.A. Mechanochemical synthesis of gold-silver nanocomposites via diazonium salts. In INORGANIC CHEMISTRY COMMUNICATIONS. ISSN 1387-7003, MAR 2022, vol. 137. https://doi.org/10.1016/j.inoche.2022.109231; WOS

4. [1.1] ALRBAIHAT, M. – AL-ZEIDANEEN, F.K. – ABU-AFIFEH, Q. Reviews of the kinetics of Mechanochemistry: Theoretical and Modeling Aspects. In MATERIALS TODAY-PROCEEDINGS. ISSN 2214-7853, 2022, vol. 65, 8, p. 3651-3656. https://doi.org/10.1016/j.matpr.2022.06.195; WOS

5. [1.1] ALRBAIHAT, M. A Review of Size Reduction techniques Using Mechanochemistry Approach. In EGYPTIAN JOURNAL OF CHEMISTRY. ISSN 0449-2285, JUN 2022, vol. 65, no. 6, p. 551-558. https://doi.org/10.21608/EJCHEM.2021.105136.4848; WOS

6. [1.1] AMGHAR, N. – ORTIZ, C. – PEREJON, A. – VALVERDE, J.M. – MAQUEDA, L.P. – JIMENEZ, P.E.S. The SrCO3/SrO system for thermochemical energy storage at ultra-high temperature. In SOLAR ENERGY MATERIALS AND SOLAR CELLS. ISSN 0927-0248, MAY 2022, vol. 238. https://doi.org/10.1016/j.solmat.2022.111632; WOS

7. [1.1] BLAZQUEZ, J.S. – ROMERO, F.J. – CONDE, C.F. – CONDE, A. A Review of Different Models Derived from Classical Kolmogorov, Johnson and Mehl, and Avrami (KJMA) Theory to Recover Physical Meaning in Solid-State Transformations. In PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS. ISSN 0370-1972, JUN 2022, vol. 259, no. 6. https://doi.org/10.1002/pssb.202100524; WOS

8. [1.1] CHATZIADI, A. – SKOREPOVA, E. – KOHOUT, M. – RIDVAN, L. – SOOS, M. Exploring the polymorphism of sofosbuvir via mechanochemistry: effect of milling jar geometry and material. In CRYSTENGCOMM. MAR 14 2022, vol. 24, no. 11, p. 2107-2117. https://doi.org/10.1039/d1ce01561c; WOS

9. [1.1] CHEN, Y.Q. – QIAO, S.S. – TANG, Y.H. – DU, Y. – ZHANG, D.Y. – WANG, W.J. – XIE, H.J. – LIU, C.B. Precise and scalable fabrication of metal pair-site catalysts enabled by intramolecular integrated donor atoms. In JOURNAL OF MATERIALS CHEMISTRY A. ISSN 2050-7488, DEC 6 2022, vol. 10, no. 47, p. 25307-25318. https://doi.org/10.1039/d2ta06091d; WOS

10. [1.1] DE BELLIS, J. – OCHOA-HERNANDEZ, C. – FARES, C. – PETERSEN, H. – TERNIEDEN, J. – WEIDENTHALER, C. – AMRUTE, A.P. – SCHUTH, F. Surface and Bulk Chemistry of Mechanochemically Synthesized Tohdite Nanoparticles. In JOURNAL OF THE AMERICAN CHEMICAL SOCIETY. ISSN 0002-7863, JUN 1 2022, vol. 144, no. 21, p. 9421-9433. https://doi.org/10.1021/jacs.2c02181; WOS

11. [1.1] EL-SADEK, M.H. – FARAHAT, M.M. – ALI, H.H. – ZAKI, Z.I. Synthesis of SrTiO3 from celestite and rutile by mechanical activation assisted Solid-State reaction. In ADVANCED POWDER TECHNOLOGY. ISSN 0921-8831, MAY 2022, vol. 33, no. 5. https://doi.org/10.1016/j.apt.2022.103548; WOS

12. [1.1] ESPERTO, L. – FIGUEIRA, I. – MASCARENHAS, J. – SILVA, T.P. – CORREIA, J.B. – NEVES, F. Structural and Optical Characterization of Mechanochemically Synthesized CuSbS2 Compounds. In MATERIALS. JUN 2022, vol. 15, no. 11. https://doi.org/10.3390/ma15113842; WOS

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11. [1.1] TARDIEU, M. – LAKHMAN, Y. – KHELLAF, L. – CARDOSO, M. – SGARBURA, O. – COLOMBO, P.E. – CRISPIN-ORTUZAR, M. – SALA, E. – GOZE-BAC, C. – NOUGARET, S. Assessing Histology Structures by Ex Vivo MR Microscopy and Exploring the Link Between MRM-Derived Radiomic Features and Histopathology in Ovarian Cancer. In FRONTIERS IN ONCOLOGY. ISSN 2234-943X, JAN 19 2022, vol. 11. https://doi.org/10.3389/fonc.2021.771848; WOS

12. [1.1] VALLADARES, A. – BEYER, T. – PAPP, L. – SALOMON, E. – RAUSCH, I. A multi-modality physical phantom for mimicking tumor heterogeneity patterns in PET/CT and PET/MRI. In MEDICAL PHYSICS. ISSN 0094-2405, SEP 2022, vol. 49, no. 9, p. 5819-5829. https://doi.org/10.1002/mp.15853; WOS

13. [1.1] VERES, G. – KISS, J. – VAS, N.F. – KALLOS-BALOGH, P. – MATHE, N.B. – LASSEN, M.L. – BERENYI, E. – BALKAY, L. Phantom Study on the Robustness of MR Radiomics Features: Comparing the Applicability of 3D Printed and Biological Phantoms. In DIAGNOSTICS. SEP 2022, vol. 12, no. 9. https://doi.org/10.3390/diagnostics12092196; WOS

 

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Citácie WOS: 15; citácie SCOPUS: 3; iné citácie: 1

1. [1.1] BARAKATI, N. – BUSTOS, R.Z. – COLETTA, D.K. – LANGLAIS, P.R. – KOHLER, L.N. – LUO, M.L. – FUNK, J.L. – WILLIS, W.T. – MANDARINO, L.J. Fuel Selection in Skeletal Muscle Exercising at Low Intensity; Reliance on Carbohydrate in Very Sedentary Individuals. In METABOLIC SYNDROME AND RELATED DISORDERS, 2022. ISSN 1540-4196. https://doi.org/10.1089/met.2022.0062; WOS

2. [1.1] CARRELL, T. – GU, M.Y. – BOSSHARD, J.C. – SUN, C.H. – MCDOUGALL, M.P. – WRIGHT, S.M. Assessing the Feasibility of Dynamic P-31 Spectroscopy for Metabolic Studies With a 1.0T Extremity Scanner. In IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. ISSN 0018-9294, JUN 2022, vol. 69, no. 6, p. 1975-1982. https://doi.org/10.1109/TBME.2021.3132252; WOS

3. [1.1] DORST, J. – BORBATH, T. – RUHM, L. – HENNING, A. Phosphorus transversal relaxation times and metabolite concentrations in the human brain at 9.4 T. In NMR IN BIOMEDICINE. ISSN 0952-3480, OCT 2022, vol. 35, no. 10. https://doi.org/10.1002/nbm.4776; WOS

4. [1.1] ELLIS, C. – BURNS, D. All about oxygen: using near-infrared spectroscopy to understand bioenergetics. In ADVANCES IN PHYSIOLOGY EDUCATION. ISSN 1043-4046, DEC 2022, vol. 46, no. 4, p. 685-692. https://doi.org/10.1152/advan.00106.2022; WOS

5. [1.1] FRANKE, V.L. – BREITLING, J. – LADD, M.E. – BACHERT, P. – KORZOWSKI, A. P-31 MRSI at 7 T enables high-resolution volumetric mapping of the intracellular magnesium ion content in human lower leg muscles. In MAGNETIC RESONANCE IN MEDICINE. ISSN 0740-3194, AUG 2022, vol. 88, no. 2, p. 511-523. https://doi.org/10.1002/mrm.29231; WOS

6. [1.1] GARIBALDI, M. – NICOLETTI, T. – BUCCI, E. – FIONDA, L. – LEONARDI, L. – MORINO, S. – TUFANO, L. – ALFIERI, G. – LAULETTA, A. – MERLONGHI, G. – PERNA, A. – ROSSI, S. – RICCI, E. – PEREZ, J.A. – TARTAGLIONE, T. – PETRUCCI, A. – PENNISI, E.M. – SALVETTI, M. – CUTTER, G. – DIAZ-MANERA, J. – SILVESTRI, G. – ANTONINI, G. Muscle magnetic resonance imaging in myotonic dystrophy type 1 (DM1): Refining muscle involvement and implications for clinical trials. In EUROPEAN JOURNAL OF NEUROLOGY, 2022, vol. 29, no. 3, p. 843-854. ISSN 1351-5101. https://doi.org/10.1111/ene.15174; WOS

7. [1.1] GRUNDLER, F. – VIALLON, M. – MESNAGE, R. – RUSCICA, M. – VON SCHACKY, C. – MADEO, F. – HOFER, S.J. – MITCHELL, S.J. – CROISILLE, P. – DE TOLEDO, F.W. Long-term fasting: Multi-system adaptations in humans (GENESIS) study-A single-arm interventional trial. In FRONTIERS IN NUTRITION. ISSN 2296-861X, NOV 17 2022, vol. 9. https://doi.org/10.3389/fnut.2022.951000; WOS

8. [1.1] HABETS, L.E. – BARTELS, B. – ASSELMAN, F.L. – HOOIJMANS, M.T. – VAN DEN BERG, S. – NEDERVEEN, A.J. – VAN DER POL, W.L. – JENESON, J.A.L. Magnetic resonance reveals mitochondrial dysfunction and muscle remodelling in spinal muscular atrophy. In BRAIN. ISSN 0006-8950, MAR 24 2022, vol. 145, no. 4, p. 1422-1435. https://doi.org/10.1093/brain/awab411; WOS

9. [1.1] KRACIKOVA, L. – ZIOLKOWSKA, N. – ANDROVIC, L. – KLIMANKOVA, I. – CERVENY, D. – VIT, M. – POMPACH, P. – KONEFAL, R. – JANOUSKOVA, O. – HRUBY, M. – JIRAK, D. – LAGA, R. Phosphorus-Containing Polymeric Zwitterion: A Pioneering Bioresponsive Probe for P-31-Magnetic Resonance Imaging. In MACROMOLECULAR BIOSCIENCE. ISSN 1616-5187, MAY 2022, vol. 22, no. 5. https://doi.org/10.1002/mabi.202100523; WOS

10. [1.1] NIJHOLT, K.T. – SANCHEZ-AGUILERA, P.I. – VOORRIPS, S.N. – DE BOER, R.A. – WESTENBRINK, B.D. Exercise: a molecular tool to boost muscle growth and mitochondrial performance in heart failure?. In EUROPEAN JOURNAL OF HEART FAILURE. ISSN 1388-9842, FEB 2022, vol. 24, no. 2, p. 287-298. https://doi.org/10.1002/ejhf.2407; WOS

11. [1.1] OBERDIER, M.T. – ALGHATRIF, M. – ADELNIA, F. – ZAMPINO, M. – MORRELL, C.H. – SIMONSICK, E. – FISHBEIN, K. – LAKATTA, E.G. – MCDERMOTT, M.M. – FERRUCCI, L. Ankle-Brachial Index and Energy Production in People Without Peripheral Artery Disease: The BLSA. In JOURNAL OF THE AMERICAN HEART ASSOCIATION. MAR 15 2022, vol. 11, no. 6. https://doi.org/10.1161/JAHA.120.019014; WOS

12. [1.1] PROCTOR, D.N. – NEELY, K.A. – MOOKERJEE, S. – TUCKER, J. – SOMANI, Y.B.B. – FLANAGAN, M. – KIM-SHAPIRO, D.B.B. – BASU, S. – MULLER, M.D.D. – KIM, D.J.K. Inorganic nitrate supplementation and blood flow restricted exercise tolerance in post-menopausal women. In NITRIC OXIDE-BIOLOGY AND CHEMISTRY. ISSN 1089-8603, MAY 1 2022, vol. 122, p. 26-34. https://doi.org/10.1016/j.niox.2022.02.004; WOS

13. [1.1] TIAN, Q. – MITCHELL, B.A. – ZAMPINO, M. – FERRUCCI, L. Longitudinal associations between blood lysophosphatidylcholines and skeletal muscle mitochondrial function. In GEROSCIENCE. ISSN 2509-2715, AUG 2022, vol. 44, no. 4, SI, p. 2213-2221. https://doi.org/10.1007/s11357-022-00548-w; WOS

14. [1.1] VAN DEN WYNGAERT, T. – DE SCHEPPER, S. – ELVAS, F. – SEYEDINIA, S.S. – BEHESHTI, M. Positron emission tomography-magnetic resonance imaging as a research tool in musculoskeletal conditions. In QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING. ISSN 1824-4785, MAR 2022, vol. 66, no. 1, p. 15-30. https://doi.org/10.23736/S1824-4785.22.03434-3; WOS

15. [1.1] YURISTA, S.R. – EDER, R.A. – KWON, D.H. – FARRAR, C.T. – YEN, Y.F. – TANG, W.H.W. – NGUYEN, C.T. Magnetic resonance imaging of cardiac metabolism in heart failure: how far have we come?. In EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING. ISSN 2047-2404, SEP 10 2022, vol. 23, no. 10, p. 1277-1289. https://doi.org/10.1093/ehjci/jeac121; WOS

16. [1.2] JETT, S. – DYKE, J.P. – ANDY, C. – SCHELBAUM, E. – JANG, G. – BONEU YEPEZ, C. – PAHLAJANI, S. – DIAZ, I. – DIAZ BRINTON, R. – MOSCONI, L. Sex and menopause impact sup31/supP-Magnetic Resonance Spectroscopy brain mitochondrial function in association with sup11/supC-PiB PET amyloid-beta load. In SCIENTIFIC REPORTS, 2022, vol. 12, no. 1. https://doi.org/10.1038/s41598-022-26573-5; SCOPUS

17. [1.2] LEWIS, M.T. – LEVITSKY, Y. – BAZIL, J.N. – WISEMAN, R.W. Measuring Mitochondrial Function: From Organelle to Organism. In METHODS IN MOLECULAR BIOLOGY, 2022, vol. 2497, p. 141-172. ISSN 1064-3745. https://doi.org/10.1007/978-1-0716-2309-1_10; SCOPUS

18. [1.2] PARASOGLOU, P. – OSORIO, R.S. – KHEGAI, O. – KOVBASYUK, Z. – MILLER, M. – HO, A. – DEHKHARGHANI, S. – WISNIEWSKI, T. – CONVIT, A. – MOSCONI, L. – BROWN, R. Phosphorus metabolism in the brain of cognitively normal midlife individuals at risk for Alzheimer’s disease. In NEUROIMAGE: REPORTS, 2022, vol. 2, no. 4. https://doi.org/10.1016/j.ynirp.2022.100121; SCOPUS

19. [3.1] JETT, S. – DYKE, J. – ANDY, C. – SCHELBAUM, E. – JANG, G. – YEPEZ, C.B. – PAHLAJANI, S. – DÍAZ, I. – BRINTON, R.D. – MOSCONI, L. Sex, menopause, and Alzheimer’s risk: a 31P-MR spectroscopy study of brain mitochondrial function in association with 11C-PiB PET amyloid-beta load. In RESEARCH SQUARE, 2022, https://doi.org/10.21203/rs.3.rs-1723651/v1.

 

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Citácie WOS: 7; citácie SCOPUS: 4; iné citácie: 1

1. [1.1] BABU, V.S. – VAIDYA, A.S. An In-depth Analysis of Automatic Sleep Stage Categorization. In INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY. ISSN 1738-7906, SEP 30 2022, vol. 22, no. 9, p. 816-826. https://doi.org/10.22937/IJCSNS.2022.22.9.106; WOS

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4. [1.1] KUO, C.E. – LU, T.H. – CHEN, G.T. – LIAO, P.Y. Towards precision sleep medicine: Self-attention GAN as an innovative data augmentation technique for developing personalized automatic sleep scoring classification. In COMPUTERS IN BIOLOGY AND MEDICINE. ISSN 0010-4825, SEP 2022, vol. 148. https://doi.org/10.1016/j.compbiomed.2022.105828; WOS

5. [1.1] MEHRABBEIK, M. – SHAMS-AHMAR, M. – LEVINE, A.T. – JAFARI, S. – MERRIKHI, Y. Distinctive nonlinear dimensionality of neural spiking activity in extrastriate cortex during spatial working memory; a Higuchi fractal analysis. In CHAOS SOLITONS & FRACTALS. ISSN 0960-0779, MAY 2022, vol. 158. https://doi.org/10.1016/j.chaos.2022.112051; WOS

6. [1.1] YOU, Y.Y. – ZHONG, X.Y. – LIU, G.Z. – YANG, Z.H. Automatic sleep stage classification: A light and efficient deep neural network model based on time, frequency and fractional Fourier transform domain features. In ARTIFICIAL INTELLIGENCE IN MEDICINE. ISSN 0933-3657, MAY 2022, vol. 127. https://doi.org/10.1016/j.artmed.2022.102279; WOS

7. [1.1] ZHOU, D.D. – WANG, J. – HU, G.Q. – ZHANG, J.C. – LI, F. – YAN, R. – KETTUNEN, L. – CHANG, Z. – XU, Q. – CONG, F.Y. SingleChannelNet: A model for automatic sleep stage classification with raw single-channel EEG. In BIOMEDICAL SIGNAL PROCESSING AND CONTROL. ISSN 1746-8094, MAY 2022, vol. 75. https://doi.org/10.1016/j.bspc.2022.103592; WOS

8. [1.2] FAN, X. – KANG, T. – LUO, R. – LAI, D. Two-Dimensional Deep Learning Based Classification of Sleep Stages with Time-Frequency Maps of Single-Lead EEG Segment. In 2022 3RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND MACHINE LEARNING, 2022, p. 211-215. https://doi.org/10.1109/PRML56267.2022.9882257; SCOPUS

9. [1.2] KHARE, S.K. – BAJAJ, V. – TARAN, S. – SINHA, G.R. Multiclass sleep stage classification using artificial intelligence based time-frequency distribution and CNN. In ARTIFICIAL INTELLIGENCE-BASED BRAIN-COMPUTER INTERFACE, 2022, p. 1-21. https://doi.org/10.1016/B978-0-323-91197-9.00012-6; SCOPUS

10. [1.2] WOO, S.W. – KANG, M.K. – PARK, B.J. – HONG, K.S. Sleep stage classification using electroencephalography via Mel frequency cepstral coefficients. In 2022 13TH ASIAN CONTROL CONFERENCE, 2022, p. 42-47. https://doi.org/10.23919/ASCC56756.2022.9828340; SCOPUS

11. [1.2] ZHURAVLEV, M.O. – AGALTSOV, M.V. – RUNNOVA, A.E. The Use of Wavelet Analysis for the Diagnosis of Obstructive Sleep Apnea Syndrome. In 2022 INTERNATIONAL CONFERENCE „QUALITY MANAGEMENT, TRANSPORT AND INFORMATION SECURITY, INFORMATION TECHNOLOGIES“, 2022, p. 348-351. https://doi.org/10.1109/ITQMIS56172.2022.9976671; SCOPUS

12. [3.1] LABRADA, A. – FEBLES, E.S. – ANTELO, J.M. Comparison of Automatic Sleep Stage Classification Methods for Clinical Use. In GLOBAL CLINICAL ENGINEERING JOURNAL, 2022, vol. 5, no. 1, p. 8–17. https://doi.org/10.31354/globalce.v5i1.125

 

  • MEZEIOVÁ, Kristína – PALUŠ, M. Comparison of coherence and phase synchronization of the human sleep electroencephalogram. In Clinical Neurophysiology, 2012, vol. 123, no. 9, p. 1821-1830. (2011: 3.406 – IF, Q1 – JCR, 1.717 – SJR, Q1 – SJR). (2012 – Current Contents). ISSN 1388-2457. https://doi.org/10.1016/j.clinph.2012.01.016

Citácie WOS: 4

1. [1.1] CHUNG, Y.G. – JEON, Y. – KIM, R.G. – CHO, A. – KIM, H. – HWANG, H. – CHOI, J. – KIM, K.J. Variations of Resting-State EEG-Based Functional Networks in Brain Maturation From Early Childhood to Adolescence. In JOURNAL OF CLINICAL NEUROLOGY. ISSN 1738-6586, SEP 2022, vol. 18, no. 5, p. 581-593. https://doi.org/10.3988/jcn.2022.18.5.581; WOS

2. [1.1] MIASNIKOVA, A. – FRANZ, E.A. Brain dynamics in alpha and beta frequencies underlies response activation during readiness of goal-directed hand movement. In NEUROSCIENCE RESEARCH. ISSN 0168-0102, JUL 2022, vol. 180, p. 36-47. https://doi.org/10.1016/j.neures.2022.03.004; WOS

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  • MIČUROVÁ, A. – KLUKNAVSKÝ, M. – LÍŠKOVÁ, S. – BALIŠ, P. – ŠKRÁTEK, Martin – OKRUHLICOVÁ, Ľ. – MAŇKA, Ján – BERNÁTOVÁ, I. Differences in distribution and biological effects of F3O4@PEG nanoparticles in normotensive and hypertensive rats—focus on vascular function and liver. In Biomedicines, 2021, vol. 9, no. 12, art. no. 1855. (2020: 6.081 – IF, Q1 – JCR, 1.511 – SJR, Q1 – SJR). (2021 – Current Contents). ISSN 2227-9059. https://doi.org/10.3390/biomedicines9121855

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1. [1.1] FENG, X.T. – SONG, H. – ZHANG, T.H. – YAO, S. – WANG, Y. Magnetic Technologies and Green Solvents in Extraction and Separation of Bioactive Molecules Together with Biochemical Objects: Current Opportunities and Challenges. In SEPARATIONS. NOV 2022, vol. 9, no. 11. https://doi.org/10.3390/separations9110346; WOS

 

  • MILLER, J.J. – VALKOVIČ, Ladislav – KERR, M. – TIMM, K.N. – WATSON, W.D. – LAU, J.Y.C. – TYLER, A. – RODGERS, C. – BOTTOMLEY, P.A. – HEATHER, L.C. – TYLER, D.J. Rapid, B1-insensitive, dual-band quasi-adiabatic saturation transfer with optimal control for complete quantification of myocardial ATP flux. In Magnetic Resonance in Medicine, 2021, vol. 85, no. 6, p. 2978-2991. (2020: 4.668 – IF, Q1 – JCR, 1.696 – SJR, Q1 – SJR). (2021 – Current Contents). ISSN 0740-3194. https://doi.org/10.1002/mrm.28647

Citácie SCOPUS: 1

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  • MINARIKOVA, L. – BOGNER, W. – PINKER, K. – VALKOVIČ, Ladislav – ZARIC, O. – BAGO-HORVATH, Z. – BARTSCH, R. – HELBICH, T. – TRATTNIG, S. – GRUBER, S. Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer. In European Radiology, 2017, vol. 27, no. 5, p. 1901-1911. (2016: 3.967 – IF, Q1 – JCR, 1.943 – SJR, Q1 – SJR). (2017 – Current Contents). ISSN 0938-7994. https://doi.org/10.1007/s00330-016-4565-2

Citácie WOS: 12; citácie SCOPUS: 2; iné citácie: 1

1. [1.1] DU, S.Y. – GAO, S. – ZHAO, R.M. – LIU, H.B. – WANG, Y. – QI, X.X. – LI, S. – CAO, J.B. – ZHANG, L.N. Contrast-free MRI quantitative parameters for early prediction of pathological response to neoadjuvant chemotherapy in breast cancer. In EUROPEAN RADIOLOGY. ISSN 0938-7994, AUG 2022, vol. 32, no. 8, p. 5759-5772. https://doi.org/10.1007/s00330-022-08667-w; WOS

2. [1.1] GALATI, F. – MOFFA, G. – PEDICONI, F. Breast imaging: Beyond the detection. In EUROPEAN JOURNAL OF RADIOLOGY. ISSN 0720-048X, JAN 2022, vol. 146. https://doi.org/10.1016/j.ejrad.2021.110051; WOS

3. [1.1] GENG, X.C. – ZHANG, D.D. – SUO, S.T. – CHEN, J. – CHENG, F. – ZHANG, K.B. – ZHANG, Q. – LI, L. – LU, Y. – HUA, J. – ZHUANG, Z.G. Using the apparent diffusion coefficient histogram analysis to predict response to neoadjuvant chemotherapy in patients with breast cancer: comparison among three region of interest selection methods. In ANNALS OF TRANSLATIONAL MEDICINE. ISSN 2305-5839, MAR 2022, vol. 10, no. 6. https://doi.org/10.21037/atm-22-1078; WOS

4. [1.1] GUO, L.C. – DU, S.Y. – GAO, S. – ZHAO, R.M. – HUANG, G.L. – JIN, F. – TENG, Y.E. – ZHANG, L.N. Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI Predicts Pathologic Complete Response in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy. In CANCERS. JUL 2022, vol. 14, no. 14. https://doi.org/10.3390/cancers14143515; WOS

5. [1.1] HOTTAT, N.A. – BADR, D.A. – LECOMTE, S. – BESSE-HAMMER, T. – JANI, J.C. – CANNIE, M.M. Value of diffusion-weighted MRI in predicting early response to neoadjuvant chemotherapy of breast cancer: comparison between ROI-ADC and whole-lesion-ADC measurements. In EUROPEAN RADIOLOGY. ISSN 0938-7994, JUN 2022, vol. 32, no. 6, p. 4067-4078. https://doi.org/10.1007/s00330-021-08462-z; WOS

6. [1.1] KONG, X.S. – ZHANG, Q. – WU, X.M. – ZOU, T.N. – DUAN, J.J. – SONG, S.J. – NIE, J.Y. – TAO, C. – TANG, M. – WANG, M.H. – ZOU, J.Y. – XIE, Y. – LI, Z.H. – LI, Z. Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer. In FRONTIERS IN ONCOLOGY. ISSN 2234-943X, MAY 20 2022, vol. 12. https://doi.org/10.3389/fonc.2022.816297; WOS

7. [1.1] LI, W. – LE, N.N. – ONISHI, N. – NEWITT, D.C. – WILMES, L.J. – GIBBS, J.E. – CARMONA-BOZO, J. – LIANG, J.C. – PARTRIDGE, S.C. – PRICE, E.R. – JOE, B.N. – KORNAK, J. – MAGBANUA, M.J.M. – NANDA, R. – LESTAGE, B. – ESSERMAN, L.J. – VAN’T VEER, L.J. – HYLTON, N.M. Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy. In CANCERS. SEP 2022, vol. 14, no. 18. https://doi.org/10.3390/cancers14184436; WOS

8. [1.1] MASSAFRA, R. – COMES, M.C. – BOVE, S. – DIDONNA, V. – GATTA, G. – GIOTTA, F. – FANIZZI, A. – LA FORGIA, D. – LATORRE, A. – PASTENA, M.I. – POMARICO, D. – RINALDI, L. – TAMBORRA, P. – ZITO, A. – LORUSSO, V. – PARADISO, A.V. Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy. In JOURNAL OF PERSONALIZED MEDICINE. JUN 2022, vol. 12, no. 6. https://doi.org/10.3390/jpm12060953; WOS

9. [1.1] OTA, R. – KATAOKA, M. – IIMA, M. – HONDA, M. – OHASHI, A. – KISHIMOTO, A.O. – MIYAKE, K.K. – YAMADA, Y. – TAKEUCHI, Y. – TOI, M. – NAKAMOTO, Y. Evaluation of pathological complete response after neoadjuvant systemic treatment of invasive breast cancer using diffusion-weighted imaging compared with dynamic contrast-enhanced based kinetic analysis. In EUROPEAN JOURNAL OF RADIOLOGY. ISSN 0720-048X, SEP 2022, vol. 154. https://doi.org/10.1016/j.ejrad.2022.110372; WOS

10. [1.1] PINTICAN, R. – FECHETE, R. – BOCA, B. – CAMBREA, M. – LEONTE, T. – CAMUESCU, O. – GHERMAN, D. – BENE, I. – CIULE, L.D. – CIORTEA, C.A. – DUDEA, S.M. – CIUREA, A.I. Predicting the Early Response to Neoadjuvant Therapy with Breast MR Morphological, Functional and Relaxometry Features-A Pilot Study. In CANCERS. DEC 2022, vol. 14, no. 23. https://doi.org/10.3390/cancers14235866; WOS

11. [1.1] SOBHI, A. – HAMED, S.T. – HUSSEIN, E.S. – LASHEEN, S. – HUSSEIN, M. – EBRAHIM, Y. Predicting pathological response of locally advanced breast cancer to neoadjuvant chemotherapy: comparing the performance of whole body F- 18-FDG PETCT versus DCE-MRI of the breast. In EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE. MAR 31 2022, vol. 53, no. 1. https://doi.org/10.1186/s43055-022-00743-x; WOS

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2. [1.1] BI, X.T. – QIN, R.S. – WU, D.Y. – ZHENG, S.D. – ZHAO, J.S. One step forward for smart chemical process fault detection and diagnosis. In COMPUTERS & CHEMICAL ENGINEERING. ISSN 0098-1354, AUG 2022, vol. 164. https://doi.org/10.1016/j.compchemeng.2022.107884; WOS

3. [1.1] CHAKRABORTY, R. – KERESZTURI, G. – PULLANAGARI, R. – DURANCE, P. – ASHRAF, S. – ANDERSON, C. Mineral prospecting from biogeochemical and geological information using hyperspectral remote sensing – Feasibility and challenges. In JOURNAL OF GEOCHEMICAL EXPLORATION. ISSN 0375-6742, JAN 2022, vol. 232. https://doi.org/10.1016/j.gexplo.2021.106900; WOS

4. [1.1] DIAS, T. – OLIVEIRA, R. – SARAIVA, P. – REIS, M.S. Forecasting the research octane number in a Continuous Catalyst Regeneration (CCR) reformer. In QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL. ISSN 0748-8017, APR 2022, vol. 38, no. 3, SI, p. 1463-1481. https://doi.org/10.1002/qre.2968; WOS

5. [1.1] DIAS, T. – OLIVEIRA, R. – SARAIVA, P.M. – REIS, M.S. Linear and Non-Linear Soft Sensors for Predicting the Research Octane Number (RON) through Integrated Synchronization, Resolution Selection and Modelling. In SENSORS. MAY 2022, vol. 22, no. 10. https://doi.org/10.3390/s22103734; WOS

6. [1.1] DONG, J. – WANG, Y.Q. – PENG, K.X. A Novel Fault Detection Method Based on the Extraction of Slow Features for Dynamic Nonstationary Processes. In IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. ISSN 0018-9456, 2022, vol. 71. https://doi.org/10.1109/TIM.2021.3136260; WOS

7. [1.1] EDELMANN, D. – GOEMAN, J. A Regression Perspective on Generalized Distance Covariance and the Hilbert-Schmidt Independence Criterion. In STATISTICAL SCIENCE. ISSN 0883-4237, NOV 2022, vol. 37, no. 4, p. 562-579. https://doi.org/10.1214/21-STS841; WOS

8. [1.1] EL BILALI, A. – MOUKHLISS, M. – TALEB, A. – NAFII, A. – ALABJAH, B. – BROUZIYNE, Y. – MAZIGH, N. – TEZNINE, K. – MHAMED, M. Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling. In ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. ISSN 0944-1344, 2022, vol. 29, no. 31, p. 47382-47398. https://doi.org/10.1007/s11356-022-18559-7; WOS

9. [1.1] EL BILALI, A. – MOUKHLISS, M. – TALEB, A. – NAFII, A. – ALABJAH, B. – BROUZIYNE, Y. – MAZIGH, N. – TEZNINE, K. – MHAMED, M. Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling. In ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH. ISSN 0944-1344, JUL 2022, vol. 29, no. 31, p. 47382-47398. https://doi.org/10.1007/s11356-022-18559-7; WOS

10. [1.1] GUO, S. – SONG, L. – XIE, R. – LI, L. – LIU, S.L. Multiview nonlinear discriminant structure learning for emotion recognition. In KNOWLEDGE-BASED SYSTEMS. ISSN 0950-7051, DEC 22 2022, vol. 258. https://doi.org/10.1016/j.knosys.2022.110042; WOS

11. [1.1] IRAKI, T. – LINK, N. Generative models for capturing and exploiting the influence of process conditions on process curves. In JOURNAL OF INTELLIGENT MANUFACTURING. ISSN 0956-5515, FEB 2022, vol. 33, no. 2, p. 473-492. https://doi.org/10.1007/s10845-021-01846-4; WOS

12. [1.1] JIANG, D. – LI, W. Quantitative Evaluation of Sensor Reconfigurability Based on Data-driven Method. In INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, vol. 20, no. 9, p. 2879-2891. ISSN 1598-6446. https://doi.org/10.1007/s12555-021-0590-2; WOS

13. [1.1] JIANG, D.N. – LI, W. Quantitative Evaluation of Sensor Reconfigurability Based on Data-driven Method. In INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS. ISSN 1598-6446, SEP 2022, vol. 20, no. 9, p. 2879-2891. https://doi.org/10.1007/s12555-021-0590-2; WOS

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15. [1.1] KHANESAR, M.A. – PIANO, S. – BRANSON, D. Improving the Positional Accuracy of Industrial Robots by Forward Kinematic Calibration using Laser Tracker System. In PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (ICINCO), 2022, p. 263-270. https://doi.org/10.5220/0011340200003271; WOS

16. [1.1] KONG, X.Y. – JIANG, X.Y. – ZHANG, B.X. – YUAN, J.S. – GE, Z.Q. Latent variable models in the era of industrial big data: Extension and beyond. In ANNUAL REVIEWS IN CONTROL. ISSN 1367-5788, 2022, vol. 54, p. 167-199. https://doi.org/10.1016/j.arcontrol.2022.09.005; WOS

17. [1.1] LEI, C. – ZHENG, S.Z. – ZHANG, X. – WANG, D.X. – WU, H.T. – PENG, H. – HU, B. Epileptic Seizure Detection in EEG Signals Using Discriminative Stein Kernel-Based Sparse Representation. In IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. ISSN 0018-9456, 2022, vol. 71. https://doi.org/10.1109/TIM.2021.3137159; WOS

18. [1.1] LI, C. – LI, G. – CHEN, X. – ZHOU, P. – HE, X. A Multiblock Kernel Dynamic Latent Variable Model for Large-Scale Industrial Process Monitoring. In IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. ISSN 0018-9456, 2022, vol. 71. https://doi.org/10.1109/TIM.2022.3217572; WOS

19. [1.1] LI, Z. – YAN, Z. – LI, S. – SUN, G. – WANG, X. – ZHAO, D. – LI, Y. – LIU, X. Comparative study for multi-variable regression methods based on Laguerre polynomial and manifolds optimization. In ENGINEERING COMPUTATIONS, 2022, vol. 39, no. 8, p. 3058-3082. ISSN 0264-4401. https://doi.org/10.1108/EC-12-2021-0766; WOS

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21. [1.1] LIN, J.Q. – LI, X.L. – CHEN, M.S. – WANG, C.D. – ZHANG, H.Z. Incomplete Data Meets Uncoupled Case: A Challenging Task of Multiview Clustering. In IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. 2022, ISSN 2162-237X. https://doi.org/10.1109/TNNLS.2022.3224748; WOS

22. [1.1] LIU, Q. – JIA, M.W. – GAO, Z.L. – XU, L.F. – LIU, Y. Correntropy long short term memory soft sensor for quality prediction in industrial polyethylene process. In CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. ISSN 0169-7439, DEC 15 2022, vol. 231. https://doi.org/10.1016/j.chemolab.2022.104678; WOS

23. [1.1] MA, H. – WANG, Y. – JI, Z.C. – DING, F. A Novel Three-Stage Quality Oriented Data-Driven Nonlinear Industrial Process Monitoring Strategy. In IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. ISSN 0018-9456, 2022, vol. 71. https://doi.org/10.1109/TIM.2022.3208652; WOS

24. [1.1] PICCA, A. – CALVANI, R. – COELHO-JUNIOR, H.J. – MARINI, F. – LANDI, F. – MARZETTI, E. Circulating Inflammatory, Mitochondrial Dysfunction, and Senescence-Related Markers in Older Adults with Physical Frailty and Sarcopenia: A BIOSPHERE Exploratory Study. In INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. NOV 2022, vol. 23, no. 22. https://doi.org/10.3390/ijms232214006; WOS

25. [1.1] REIS, M.S. – JIANG, B.B. Predicting the lifetime of Lithium-Ion batteries: Integrated feature extraction and modeling through sequential Unsupervised-Supervised Projections (USP). In CHEMICAL ENGINEERING SCIENCE. ISSN 0009-2509, APR 28 2022, vol. 252. https://doi.org/10.1016/j.ces.2022.117510; WOS

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27. [1.1] SETON, R. – PERSSON, A. A structured evaluation of regression models for predicting CO2 concentration from plasma emission spectra. In SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY. ISSN 0584-8547, 2022, vol. 194. https://doi.org/10.1016/j.sab.2022.106467; WOS

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Citácie WOS: 6; citácie SCOPUS: 2; iné citácie: 1

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Citácie WOS: 1

1. [2.1] SIRUCKOVA, K. – MARCON, P. – DOSTAL, M. – SIRUCKOVA, A. – DOHNAL, P. Dual-Energy Spectral Computed Tomography: Comparing True and Virtual Non Contrast Enhanced Images. In MEASUREMENT SCIENCE REVIEW. ISSN 1335-8871, DEC 1 2022, vol. 22, no. 6, p. 261-268. https://doi.org/10.2478/msr-2022-0033; WOS

 

  • GÁBELOVÁ, A. – FARKAŠOVÁ, T. – GURSKÁ, S. – MACHÁČKOVÁ, Z. – LUKAČKO, P. – WITKOVSKÝ, Viktor. Radiosensitivity of peripheral blood lymphocytes from healthy donors and cervical cancer patients; the correspondence of in vitro data with the clinical outcome. In Neoplasma, 2008, vol. 55, no. 3, p. 182-191. (2007: 1.208 – IF, Q4 – JCR, 0.527 – SJR, Q3 – SJR). (2008 – Current Contents). ISSN 0028-2685.

Citácie WOS: 1

1. [1.1] HUANG, Y.-M. – HSU, H.-H. – LIU, C.-K. – YANG, C.-K. – TSAI, P.-L. – TANG, T.-Y. – HSU, S.-M. – CHEN, Y.-J. Histopathological and Haemogram Features Correlate with Prognosis in Rectal Cancer Patients Receiving Neoadjuvant Chemoradiation without Pathological Complete Response. In JOURNAL OF CLINICAL MEDICINE, 2022, vol. 11, no. 17; WOS

 

  • GOGOLA, DanielSZOMOLÁNYI, PavolŠKRÁTEK, MartinFROLLO, Ivan. Design and construction of novel instrumentation for low-field MR tomography. In Measurement Science Review, 2018, vol. 18, no. 3, p. 107-112. (2017: 1.345 – IF, Q3 – JCR, 0.441 – SJR, Q2 – SJR). (2018 – Current Contents). ISSN 1335-8871. https://doi.org/10.1515/msr-2018-0016

Citácie WOS: 2

1. [1.1] GIOVANNETTI, G. – GUERRINI, A. – MINOZZI, S. – PANETTA, D. – SALVADORI, P.A. Computer tomography and magnetic resonance for multimodal imaging of fossils and mummies. In MAGNETIC RESONANCE IMAGING. ISSN 0730-725X, DEC 2022, vol. 94, p. 7-17. https://doi.org/10.1016/j.mri.2022.08.019; WOS

2. [1.1] PERRON, S. – OURIADOV, A. – WAWRZYN, K. – HICKLING, S. – FOX, M.S. – SERRAI, H. – SANTYR, G. Application of a 2D frequency encoding sectoral approach to hyperpolarized Xe-129 MRI at low field. In JOURNAL OF MAGNETIC RESONANCE. ISSN 1090-7807, MAR 2022, vol. 336. https://doi.org/10.1016/j.jmr.2022.107159; WOS

 

  • ROŠŤÁKOVÁ, ZuzanaROSIPAL, RomanSEIFPOUR, Saman – TREJO, L.J. A comparison of non-negative tucker decomposition and parallel factor analysis for identification and measurement of human EEG rhythms. In Measurement Science Review, 2020, vol. 20, no. 3, p. 126-138. (2019: 0.900 – IF, Q4 – JCR, 0.326 – SJR, Q3 – SJR). (2020 – Current Contents). ISSN 1335-8871. https://doi.org/10.2478/msr-2020-0015

Citácie WOS: 1

1. [1.1] ZDUNEK, R. – FONAL, K. Incremental Nonnegative Tucker Decomposition with Block-Coordinate Descent and Recursive Approaches. In SYMMETRY, 2022, vol. 14, no. 1. https://doi.org/10.3390/sym14010113; WOS

 

  • VRŠANSKÝ, P. – SENDI, H. – HINKELMAN, J. – HAIN, Miroslav. Alienopterix Mlynský et al., 2018 complex in North Myanmar amber supports Umenocoleoidea/ae status. In Biologia, 2021, vol. 76, no. 8, p. 2207-2224. (2020: 1.350 – IF, Q4 – JCR, 0.282 – SJR, Q3 – SJR). (2021 – Current Contents). ISSN 0006-3088. https://doi.org/10.1007/s11756-021-00689-x

Citácie WOS: 5

1. [1.1] KACEROVA, J. – AZAR, D. Mesozoic cockroaches (Insecta: Mesoblattinidae, Blattulidae) from shale and dysodile of Lebanon. In BIOLOGIA, 2022. ISSN 0006-3088. https://doi.org/10.1007/s11756-022-01209-1; WOS

2. [1.1] LI, X. – HUANG, D. Predators or Herbivores: Cockroaches of Manipulatoridae Revisited with a New Genus from Cretaceous Myanmar Amber (Dictyoptera: Blattaria: Corydioidea). In INSECTS, 2022, vol. 13, no. 8. ttps://doi.org/10.3390/insects13080732; WOS

3. [1.1] ROSS, A.J. Supplement to the Burmese (Myanmar) amber checklist and bibliography, 2021. In PALAEOENTOMOLOGY, 2022, vol. 5, no. 1, p. 27-45. ISSN 2624-2826. https://doi.org/10.11646/palaeoentomology.5.1.4; WOS

4. [1.1] SZABO, M. – SZABO, P. – KOBOR, P. – OSI, A. Alienopterix santonicus sp. n., a metallic cockroach from the Late Cretaceous ajkaite amber (Bakony Mts, western Hungary) documents Alienopteridae within the Mesozoic Laurasia. In BIOLOGIA, 2022. ISSN 0006-3088. https://doi.org/10.1007/s11756-022-01265-7; WOS

5. [1.1] XU, C. – LUO, C. – JARZEMBOWSKI, E.A. – FANG, Y. – WANG, B. Aposematic coloration from Mid-Cretaceous Kachin amber. In PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2022, vol. 377, no. 1847. ISSN 0962-8436. https://doi.org/10.1098/rstb.2021.0039; WOS

 

  • WITKOVSKÝ, ViktorFROLLO, Ivan. Measurement science is the science of sciences – there is no science without measurement. In Measurement Science Review, 2020, vol. 20, no. 1, p. 1-5. (2019: 0.900 – IF, Q4 – JCR, 0.326 – SJR, Q3 – SJR). (2020 – Current Contents). ISSN 1335-8871. https://doi.org/10.2478/msr-2020-0001

Citácie WOS: 2

1. [1.1] VERMA, A.K. – RADHIKA, S. Multi-Level Stator Winding Failure Analysis on the Insulation Material for Industrial Induction Motor. In EXPERIMENTAL TECHNIQUES. ISSN 0732-8818, 2022, vol. 46, no. 3, p. 441-455. https://doi.org/10.1007/s40799-021-00490-0; WOS

2. [2.1] MEI, Z. – KUTS, Y. – KOCHAN, O. – LYSENKO, I. – LEVCHENKO, O. – VLAKH-VYHRYNOVSKA, H. Using Signal Phase in Computerized Systems of Non-destructive Testing. In MEASUREMENT SCIENCE REVIEW. ISSN 1335-8871, 2022, vol. 22, no. 1, p. 32-43. https://doi.org/10.2478/msr-2022-0004; WOS

 

Vedecké práce v zahraničných impaktovaných časopisoch registrovaných v databázach WOS alebo SCOPUS

 

  • AMANN, A. – SCHWARZ, K. – WIMMER, G. – WITKOVSKÝ, Viktor. Model based determination of detection limits for proton transfer reaction mass spectrometer. In Measurement Science Review, 2010, vol. 10, no. 6, p. 180-188. (2009: 0.115 – SJR, Q4 – SJR). (2010 – WOS, SCOPUS). ISSN 1335-8871. https://doi.org/10.2478/v10048-010-0031-5

Citácie SCOPUS: 1

1. [1.2] REN, M. – CHEN, J. – LI, M. Design and development of High voltage power and vacuum system for proton transfer reaction mass spectrometry. In 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION PROCESSING (IIP), 2022. https://doi.org/10.1109/IIP57348.2022.00035; SCOPUS

 

  • CLUITMANS, M. – BROOKS, D.H. – MACLEOD, R. – DOSSEL, O. – GUILLEM, M.S. – VAN DAM, P.M. – ŠVEHLÍKOVÁ, Jana – HE, B. – SAPP, J. – WANG, L. – BEAR, L. Validation and opportunities of electrocardiographic imaging: From technical achievements to clinical applications. In Frontiers in Physiology, 2018, vol. 9, art. no. 1305. (2017: 3.394 – IF, Q1 – JCR, 1.590 – SJR, Q1 – SJR). (2018 – WOS, SCOPUS). ISSN 1664-042X. https://doi.org/10.3389/fphys.2018.01305

Citácie WOS: 11; citácie SCOPUS: 1; iné citácie: 2

1. [1.1] CHAUMONT, C. – SUFFEE, N. – GANDJBAKHCH, E. – BALSE, E. – ANSELME, F. – HATEM, S.N. Epicardial origin of cardiac arrhythmias: clinical evidences and pathophysiology. In CARDIOVASCULAR RESEARCH. ISSN 0008-6363, JUN 22 2022, vol. 118, no. 7, p. 1693-1702. https://doi.org/10.1093/cvr/cvab213; WOS

2. [1.1] FEHRENBACH, J. – WEYNANS, L. SOURCE AND METRIC ESTIMATION IN THE EIKONAL EQUATION USING OPTIMIZATION ON A MANIFOLD. In INVERSE PROBLEMS AND IMAGING. ISSN 1930-8337, 2022. https://doi.org/10.3934/ipi.2022050; WOS

3. [1.1] GILLETTE, K. – GSELL, M.A.F. – STROCCHI, M. – GRANDITS, T. – NEIC, A. – MANNINGER, M. – SCHERR, D. – RONEY, C.H. – PRASSL, A.J. – AUGUSTIN, C.M. – VIGMOND, E.J. – PLANK, G. A personalized real-time virtual model of whole heart electrophysiology. In FRONTIERS IN PHYSIOLOGY. SEP 23 2022, vol. 13. https://doi.org/10.3389/fphys.2022.907190; WOS

4. [1.1] HAMEED, N.M. – AL-TUWAIJARI, J.M. A survey on various machine learning approaches for human electrocardiograms identification. In INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS. ISSN 2008-6822, 2022, vol. 13, no. 1, p. 4017-4035. https://doi.org/10.22075/ijnaa.2022.6223; WOS

5. [1.1] MARASHLY, Q. – NAJJAR, S.N. – HAHN, J. – RECTOR, G.J. – KHAWAJA, M. – CHELU, M.G. Innovations in ventricular tachycardia ablation. In JOURNAL OF INTERVENTIONAL CARDIAC ELECTROPHYSIOLOGY. 2022, ISSN 1383-875X. https://doi.org/10.1007/s10840-022-01311-z; WOS

6. [1.1] MONACO, C. – GALLI, A. – PANNONE, L. – BISIGNANI, A. – MIRAGLIA, V. – GAUTHEY, A. – AL HOUSARI, M. – MOJICA, J. – DEL MONTE, A. – LIPARTITI, F. – RIZZI, S. – MOURAM, S. – CALBUREAN, P.A. – RAMARK, R. – PAPPAERT, G. – ELTSOV, I. – BALA, G. – SORGENTE, A. – OVEREINDER, I. – ALMORAD, A. – STROKER, E. – SIEIRA, J. – BRUGADA, P. – CHIERCHIA, G.B. – LA MEIR, M. – DE ASMUNDIS, C. Hybrid-Approach Ablation in Drug-Refractory Arrhythmogenic Right Ventricular Cardiomyopathy. In AMERICAN JOURNAL OF CARDIOLOGY. ISSN 0002-9149, OCT 15 2022, vol. 181, p. 45-54. https://doi.org/10.1016/j.amjcard.2022.07.011; WOS

7. [1.1] NJERU, D.K. – ATHAWALE, T.M. – FRANCE, J.J. – JOHNSON, C.R. Quantifying and Visualizing Uncertainty for Source Localisation in Electrocardiographic Imaging. In COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION. 2022, ISSN 2168-1163. https://doi.org/10.1080/21681163.2022.2113824; WOS

8. [1.1] TALEVI, G. – PANNONE, L. – MONACO, C. – BORI, E. – CAPPELLO, I.A. – CANDELARI, M. – RAMAK, R. – LA MEIR, M. – GHARAVIRI, A. – CHIERCHIA, G.B. – INNOCENTI, B. – DE ASMUNDIS, C. Development of a 3D printed surgical guide for Brugada syndrome substrate ablation. In FRONTIERS IN CARDIOVASCULAR MEDICINE. ISSN 2297-055X, NOV 15 2022, vol. 9. https://doi.org/10.3389/fcvm.2022.1029685; WOS

9. [1.1] TENDERINI, R. – PAGANI, S. – QUARTERONI, A. – DEPARIS, S. PDE-aware deep learning for inverse problems in cardiac electrophysiology. In SIAM JOURNAL ON SCIENTIFIC COMPUTING. ISSN 1064-8275, 2022, vol. 44, no. 3, p. B605-B639. https://doi.org/10.1137/21M1438529; WOS

10. [1.1] VERHEUL, L.M. – GROENEVELD, S.A. – KIRKELS, F.P. – VOLDERS, P.G.A. – TESKE, A.J. – CRAMER, M.J. – GUGLIELMO, M. – HASSINK, R.J. State-of-the-Art Multimodality Imaging in Sudden Cardiac Arrest with Focus on Idiopathic Ventricular Fibrillation: A Review. In JOURNAL OF CLINICAL MEDICINE. AUG 2022, vol. 11, no. 16. https://doi.org/10.3390/jcm11164680; WOS

11. [1.1] YADAN, Z. – XIN, L. – JIAN, W. Solving the inverse problem in electrocardiography imaging for atrial fibrillation using various time-frequency decomposition techniques based on empirical mode decomposition: A comparative study. In FRONTIERS IN PHYSIOLOGY. NOV 2 2022, vol. 13. https://doi.org/10.3389/fphys.2022.999900; WOS

12. [1.2] SALMAN, A.A. – IBARAHIM, A. Detection of Cardiac Arrhythmias in Electroc Ardiograms Using Deep Learning. In ISMSIT 2022 6TH INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES, 2022, p. 466-471. https://doi.org/10.1109/ISMSIT56059.2022.9932742; SCOPUS

13. [3.1] ORINI, M. – WADDINGHAM, P.H. – DENNIS, A. – MANGUAL, J.O. –  LAMBIASE, P.D. – CHOW, A.W.C. Assessment of inter-operator Reproducibility of CardioInsight ECG-Imaging. In COMPUTING IN CARDIOLOGY 2022 (CinC 2022), 2022. https://doi.org/10.22489/cinc.2022.232

14. [3.1] PANKEWITZ, L. – ABDALA, L. – BUSSOOA, A. – AREVALO, H. A Pipeline for Automated Coordinate Assignment in Anatomically Accurate Biventricular Models. In COMPUTATIONAL PHYSIOLOGY: SIMULA SUMMER SCHOOL 2021. Springer, 2022, vol. 12, p. 1-11. https://doi.org/10.1007/978-3-031-05164-7_1

 

  • HANIC, FrantišekCIGÁŇ, Alexander – BRIANČIN, J. – VAN DRIESSCHE, I. – MAŇKA, JánBUCHTA, Štefan – BRUNEEL, E. – ZRUBEC, Vladimír. Substitution of Ti4+ for Cun+ in YBa2Cu3-xTxO7-δ. In Solid State Phenomena, 2003, vol. 90-91, p. 297-302. (2003 – WOS, SCOPUS). ISSN 1012-0394. https://doi.org/10.4028/www.scientific.net/SSP.90-91.297

Citácie WOS: 1

1. [1.1] BOONSONG, P. – WATCHARAPASORN, A. High-temperature thermoelectric properties of (1-x)DyBCO – xBNT ceramics. In JOURNAL OF ASIAN CERAMIC SOCIETIES. ISSN 2187-0764, OCT 2 2022, vol. 10, no. 4, p. 766-778. https://doi.org/10.1080/21870764.2022.2127505; WOS

 

  • JANUSEK, D. – ŠVEHLÍKOVÁ, JanaZELINKA, Ján – WEIGL, W. – ZACZEK, R. – OPOLSKI, G. – TYŠLER, Milan – MANIEWSKI, R. The roles of mid-myocardial and epicardial cells in T-wave alternans development: A simulation study. In BioMedical Engineering OnLine, 2018, vol. 17, no. 1, p. 57. (2017: 1.676 – IF, Q3 – JCR, 0.542 – SJR, Q2 – SJR). (2018 – WOS, SCOPUS). ISSN 1475-925X. https://doi.org/10.1186/s12938-018-0492-6

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] QAULI, A.I. – YOO, Y. – MARCELLINUS, A. – LIM, K.M. Verification of the Efficacy of Mexiletine Treatment for the A1656D Mutation on Downgrading Reentrant Tachycardia Using a 3D Cardiac Electrophysiological Model. In BIOENGINEERING-BASEL. OCT 2022, vol. 9, no. 10. https://doi.org/10.3390/bioengineering9100531; WOS

2. [1.2] BUKHARI, H.A. – SANCHEZ, C. – LAGUNA, P. – POTSE, M. – PUEYO, E. Inter-individual Differences in Cell Composition across the Ventricular Wall May Explain Variability in ECG Response to Serum Potassium and Calcium Variations. In COMPUTING IN CARDIOLOGY, 2022. ISSN 2325-8861. https://doi.org/10.22489/CinC.2022.166; SCOPUS

 

  • JURÁŠ, VladimírSZOMOLÁNYI, Pavol – SCHREINER, M. – UNTERBERGER, K. – KUREKOVA, A. – HAGER, B. – LAURENT, D. – RAITHEL, E. – MEYER, H. – TRATTNIG, S. Reproducibility of an automated quantitative MRI assessment of low-grade knee articular cartilage lesions. In Cartilage, 2021, vol. 13, suppl. 1, p. 646S-657S. (2020: 4.634 – IF, Q1 – JCR, 0.705 – SJR, Q2 – SJR). (2021 – WOS, SCOPUS). ISSN 1947-6035. https://doi.org/10.1177/1947603520961165

Citácie WOS: 2

1. [1.1] CHEN, E. – HOU, W. – WANG, H. – LI, J. – LIN, Y. – LIU, H. – DU, M. – LI, L. – WANG, X. – YANG, J. – YANG, R. – ZHOU, C. – CHEN, P. – ZENG, M. – YAO, Q. – CHEN, W. Quantitative MRI evaluation of articular cartilage in patients with meniscus tear. In FRONTIERS IN ENDOCRINOLOGY, 2022, vol. 13. ISSN 1664-2392. https://doi.org/10.3389/fendo.2022.911893; WOS

2. [1.1] OEI, E.H.G. – HIRVASNIEMI, J. – VAN ZADELHOFF, T.A. – VAN DER HEIJDEN, R.A. Osteoarthritis year in review 2021: imaging. In OSTEOARTHRITIS AND CARTILAGE, 2022, vol. 30, no. 2, p. 226-236. ISSN 1063-4584. https://doi.org/10.1016/j.joca.2021.11.012; WOS

 

  • KLUKNAVSKÝ, M. – BALIŠ, P. – ŠKRÁTEK, MartinMAŇKA, Ján – BERNÁTOVÁ, I. (-)-Epicatechin reduces the blood pressure of young borderline hypertensive rats during the post-treatment period. In Antioxidants, 2020, vol. 9, no. 2, article no. 96. (2019: 5.014 – IF, Q1 – JCR, 1.100 – SJR, Q1 – SJR). (2020 – WOS, SCOPUS). ISSN 2076-3921. https://doi.org/10.3390/antiox9020096

Citácie WOS: 4

1. [1.1] AKOMOLAFE, S.F. – OLASEHINDE, T.A. – OLADAPO, I.F. – OYELEYE, S. Diet Supplemented with Chrysophyllum albidum G. Don (Sapotaceae) Fruit Pulp Improves Reproductive Function in Hypertensive Male Rats. In REPRODUCTIVE SCIENCES. ISSN 1933-7191, 2022, vol. 29, no. 2, p. 540-556. https://doi.org/10.1007/s43032-021-00746-5; WOS

2. [1.1] DEL SEPPIA, C. – FEDERIGHI, G. – LAPI, D. – GEROSOLIMO, F. – SCURI, R. Effects of a catechins-enriched diet associated with moderate physical exercise in the prevention of hypertension in spontaneously hypertensive rats. In SCIENTIFIC REPORTS, 2022, vol. 12, no. 1. ISSN 2045-2322. https://doi.org/10.1038/s41598-022-21458-z; WOS

3. [1.1] HID, E.J. – MOSELE, J. – PRINCE, P.D. – FRAGA, C.G. – GALLEANO, M. (-)-Epicatechin and cardiometabolic risk factors: a focus on potential mechanisms of action. In PFLUGERS ARCHIV-EUROPEAN JOURNAL OF PHYSIOLOGY. ISSN 0031-6768, 2022, vol. 474, no. 1, p. 99-115. https://doi.org/10.1007/s00424-021-02640-0; WOS

4. [1.1] LUO, Y. – LU, J. – WANG, Z. – WANG, L. – WU, G. – GUO, Y. – DONG, Z. Small ubiquitin-related modifier (SUMO)ylation of SIRT1 mediates (-)-epicatechin inhibited- differentiation of cardiac fibroblasts into myofibroblasts. In PHARMACEUTICAL BIOLOGY, 2022, vol. 60, no. 1, p. 1762-1770. ISSN 1388-0209. https://doi.org/10.1080/13880209.2022.2101672; WOS

 

  • KOLLER, U. – SPRINGER, B. – RENTENBERGER, C. – SZOMOLÁNYI, Pavol – WALDSTEIN, W. – WINDHAGER, R. – TRATTNIG, S. – APPRICH, S. Radiofrequency chondroplasty may not have a long-lasting effect in the treatment of concomitant grade II patellar cartilage defects in humans. In Journal of Clinical Medicine, 2020, vol. 9, no. 4, art. no. 1202. (2019: 3.303 – IF, Q1 – JCR, karentované – CCC). (2020 – WOS, SCOPUS). ISSN 2077-0383. https://doi.org/10.3390/jcm9041202

Citácie WOS: 2

1. [1.1] LIN, C. – DENG, Z. – XIONG, J. – LU, W. – CHEN, K. – ZHENG, Y. – ZHU, W. The Arthroscopic Application of Radiofrequency in Treatment of Articular Cartilage Lesions. In FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2022, vol. 9. ISSN 2296-4185. https://doi.org/10.3389/fbioe.2021.822286; WOS

2. [1.1] YAZDANSHENAS, H. – MADADI, F. – SADEGHI-NAINI, M. – MADADI, F. – BUGARIN, A. – SABAGH, M.S. – HING, C. – SHAMIE, A.N. – HORNICEK, F.J. – WASHINGTON, E.R. Introducing a Novel Combined Acetabuloplasty and Chondroplasty Technique for the Treatment of Developmental Dysplasia of the Hip. In CUREUS, 2022, vol. 14, no. 1, e21787. https://doi.org/10.7759/cureus.21787; WOS

 

  • KRUMPOLEC, P. – KLEPOCHOVÁ, R. – JUST KUKUROVA, I. – JELENC, M.T. – FROLLO, Ivan – UKROPEC, J. – UKROPCOVÁ, B. – TRATTNIG, S. – KRŠŠÁK, M. – VALKOVIČ, Ladislav. Multinuclear MRS at 7T uncovers exercise driven differences in skeletal muscle energy metabolism between young and seniors. In Frontiers in Physiology, 2020, vol. 11, art.no. 644. (2019: 3.367 – IF, Q1 – JCR, 1.211 – SJR, Q2 – SJR). (2020 – WOS, SCOPUS). ISSN 1664-042X. https://doi.org/10.3389/fphys.2020.00644

Citácie WOS: 1

1. [1.1] YAN, K.Q. – MEI, Z.L. – ZHAO, J.J. – PRODHAN, M.A.I. – OBAL, D. – KATRAGADDA, K. – DOELLING, B. – HOETKER, D. – POSA, D.K. – HE, L.Q. – YIN, X.M. – SHAH, J. – PAN, J.N. – RAI, S. – LORKIEWICZ, P.K. – ZHANG, X. – LIU, S.Q. – BHATNAGAR, A. – BABA, S.P. Integrated Multilayer Omics Reveals the Genomic, Proteomic, and Metabolic Influences of Histidyl Dipeptides on the Heart. In JOURNAL OF THE AMERICAN HEART ASSOCIATION. JUL 5 2022, vol. 11, no. 13. https://doi.org/10.1161/JAHA.121.023868; WOS

 

  • LEWANDOWSKI, A. – ROSIPAL, Roman – DORFFNER, G. On the individuality of sleep EEG spectra. In Journal of Psychophysiology, 2013, vol. 27, no. 3, p. 105-112. (2012: 1.000 – IF, Q4 – JCR, 0.604 – SJR). (2013 – WOS, SCOPUS). ISSN 0269-8803. https://doi.org/10.1027/0269-8803/a000092

Citácie WOS: 2

1. [1.1] EGGERT, T. – DORN, H. – DANKER-HOPFE, H. The Fingerprint-Like Pattern of Nocturnal Brain Activity Demonstrated in Young Individuals is Also Present in Senior Adulthood. In NATURE AND SCIENCE OF SLEEP. ISSN 1179-1608, 2022, vol. 14, p. 109-120. https://doi.org/10.2147/NSS.S336379; WOS

2. [1.1] MAYELI, A. – JANSSEN, S.A. – SHARMA, K. – FERRARELLI, F. Examining First Night Effect on Sleep Parameters with hd-EEG in Healthy Individuals. In BRAIN SCIENCES. FEB 2022, vol. 12, no. 2. https://doi.org/10.3390/brainsci12020233; WOS

 

  • LIPTÁK, P. – BANOVCIN, P. – ROSOĽANKA, R. – PROKOPIČ, M. – KOCAN, I. – ŽIAČIKOVÁ, I. – UHRIK, P. – GRENDÁR, Marián – HYRDEL, R. A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization. In PeerJ, 2022, art. no. e13124. (2021: 3.061 – IF, Q2 – JCR, 0.766 – SJR, Q1 – SJR). (2022 – WOS, SCOPUS). ISSN 2167-8359. https://doi.org/10.7717/peerj.13124

Citácie WOS: 2

1. [1.1] LEE, K.S. – KIM, E.S. Explainable Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease. In DIAGNOSTICS. NOV 2022, vol. 12, no. 11. https://doi.org/10.3390/diagnostics12112740; WOS

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1. [1.1] KUNISCH, K. – TRAUTMANN, P. An Inverse Problem Involving a Viscous Eikonal Equation with Applications in Electrophysiology. In VIETNAM JOURNAL OF MATHEMATICS, 2022, vol. 50, no. 1, p. 301-317. ISSN 2305-221X. https://doi.org/10.1007/s10013-021-00509-4; WOS

 

  • POPOVIĆ, B.V. – MIJANOVIĆ, A. – WITKOVSKÝ, Viktor. Computing the exact distribution of a linear combination of generalized logistic random variables and its applications. In Journal of Statistical Computation and Simulation, 2022, vol. 92, no. 5, p. 1015-1033. (2021: 1.225 – IF, Q3 – JCR, 0.588 – SJR, Q2 – SJR). (2022 – WOS, SCOPUS). ISSN 0094-9655. https://doi.org/10.1080/00949655.2021.1982942

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  • PŘIBIL, Jiří – PŘIBILOVÁ, A. – FROLLO, Ivan. Vibration and noise in magnetic resonance imaging of the vocal tract: Differences between whole-body and open-air devices. In Sensors, 2018, vol. 18, no. 4, p. 1112. (2017: 2.475 – IF, Q2 – JCR, 0.584 – SJR, Q2 – SJR). (2018 – WOS, SCOPUS). ISSN 1424-8220. https://doi.org/10.3390/s18041112

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  • SPRINGER, E. – CARDOSO, P.L. – STRASSER, B. – BOGNER, W. – PREUSSER, M. – WIDHALM, G. – NITTKA, M. – KOERZDOERFER, G. – SZOMOLÁNYI, Pavol – HANGEL, G. – HAINFELLNER, J.A. – MARIK, W. – TRATTNIG, S. MR fingerprinting—A radiogenomic marker for diffuse gliomas. In Cancers, 2022, vol. 14, no. 3, art. no. 723. (2021: 6.575 – IF, Q1 – JCR, 1.349 – SJR, Q1 – SJR). (2022 – WOS, SCOPUS). ISSN 2072-6694. https://doi.org/10.3390/cancers14030723

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  • VALKOVIČ, Ladislav – DRAGONU, I. – ALMUJAYYAZ, S. – BATZAKIS, A. – YOUNG, L.A.J. – PURVIS, L.A.B. – CLARKE, W.T. – WICHMANN, T. – LANZ, T. – NEUBAUER, S. – ROBSON, M.D. – KLOMP, D.W.J. – RODGERS, C.T. Using a whole-body 31P birdcage transmit coil and 16-element receive array for human cardiac metabolic imaging at 7T. In PLoS ONE, 2017, vol. 12, no. 10, art. no. e0187153. (2016: 2.806 – IF, Q1 – JCR, 1.236 – SJR, Q1 – SJR). (2017 – WOS, SCOPUS). ISSN 1932-6203. https://doi.org/10.1371/journal.pone.0187153

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1. [1.1] COELHO, C.A. Likelihood Ratio Tests for Elaborate Covariance Structures and for MANOVA Models with Elaborate Covariance Structures-A Review. In JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE. ISSN 0970-4140, 2022. https://doi.org/10.1007/s41745-022-00300-5; WOS

2. [1.1] KUMAR, M. – UPADHYE, N.S. – CHAND, A.K.B. Linear fractal interpolation function for data set with random noise. In FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY. ISSN 0218-348X, DEC 2022, vol. 30, no. 9. https://doi.org/10.1142/S0218348X22501869; WOS

 

  • WITKOVSKÝ, Viktor. Computing the exact distribution of the Bartlett’s test statistic by numerical inversion of its characteristic function. In Journal of Applied Statistics, 2020, vol. 47, no. 13-15, p. 2749-2764. (2019: 1.031 – IF, Q3 – JCR, 0.528 – SJR, Q3 – SJR). (2020 – WOS, SCOPUS). ISSN 0266-4763. https://doi.org/10.1080/02664763.2019.1675608

Citácie WOS: 1; iné citácie: 1

1. [1.1] COELHO, C.A. Likelihood Ratio Tests for Elaborate Covariance Structures and for MANOVA Models with Elaborate Covariance Structures-A Review. In JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE. ISSN 0970-4140, 2022. https://doi.org/10.1007/s41745-022-00300-5; WOS

2. [3.1] MURAKAMI, A. – SHIROTA, Y. Effects of Coronavirus on Vegetable Juice Manufacturers. In INTERNATIONAL JOURNAL OF TRADE, ECONOMICS AND FINANCE, 2022, vol. 13, no. 2, p. 42-46. https://doi.org/10.18178/ijtef.2022.13.2.721

 

Vedecké práce v zahraničných neimpaktovaných časopisoch registrovaných v databázach WOS alebo SCOPUS

 

  • ARENDACKÁ, Barbora – SCHWARZ, K. – ŠTOLC, SvoradWIMMER, Gejza, ml.WITKOVSKÝ, Viktor. Variability issues in determining the concentration of isoprene in human breath by PTR-MS. In Journal of Breath Research, 2008, vol. 2, p. 037007. (2008 – WOS, SCOPUS). ISSN 1752-7155. https://doi.org/10.1088/1752-7155/2/3/037007

Citácie WOS: 1

1. [1.1] WEI, X. – LI, Q.Y. – WU, Y.H. – LI, J. – ZHANG, G.K. – SUN, M.X. – LI, Y.X. Determination of breath isoprene in 109 suspected lung cancer patients using cavity ringdown spectroscopy. In JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES. ISSN 1793-5458, SEP 2022, vol. 15, no. 05. https://doi.org/10.1142/S1793545822500298; WOS

 

  • BEAR, L. – DOGRUSOZ, Y.S. – ŠVEHLÍKOVÁ, Jana – COLL-FONT, J. – GOOD, W. – VAN DAM, E. – MACLEOD, R. – ABELL, E. – WALTON, R. – CORONEL, R. – HAISSAGUERRE, M. – DUBOIS, R. Effects of ECG signal processing on the inverse problem of electrocardiography. In Computing in Cardiology, 2019, vol. 45, 4 p. (2018: 0.202 – SJR). (2019 – WOS, SCOPUS). ISSN 2325-8861. https://doi.org/10.22489/CinC.2018.070

Citácie WOS: 3

1. [1.1] GRAHAM, A.J. – ORINI, M. – ZACUR, E. – DHILLON, G. – JONES, D. – PRABHU, S. – PUGLIESE, F. – LOWE, M. – AHSAN, S. – EARLEY, M.J. – CHOW, A. – SPORTON, S. – DHINOJA, M. – HUNTER, R.J. – SCHILLING, R.J. – LAMBIASE, P.D. Assessing Noninvasive Delineation of Low-Voltage Zones Using ECG Imaging in Patients With Structural Heart Disease. In JACC-CLINICAL ELECTROPHYSIOLOGY. ISSN 2405-500X, APR 2022, vol. 8, no. 4, p. 426-436. https://doi.org/10.1016/j.jacep.2021.11.011; WOS

2. [1.1] MAH, S.A. – DU, P. – AVCI, R. – VANDERWINDEN, J.M. – CHENG, L.K. Analysis of Regional Variations of the Interstitial Cells of Cajal in the Murine Distal Stomach Informed by Confocal Imaging and Machine Learning Methods. In CELLULAR AND MOLECULAR BIOENGINEERING. ISSN 1865-5025, APR 2022, vol. 15, no. 2, p. 193-205. https://doi.org/10.1007/s12195-021-00716-6; WOS

3. [1.1] YADAN, Z. – XIN, L. – JIAN, W. Solving the inverse problem in electrocardiography imaging for atrial fibrillation using various time-frequency decomposition techniques based on empirical mode decomposition: A comparative study. In FRONTIERS IN PHYSIOLOGY. NOV 2 2022, vol. 13. https://doi.org/10.3389/fphys.2022.999900; WOS

 

  • CAPEK, Ignác. Preparation and functionalization of gold nanoparticles. In Journal of Surface Science and Technology, 2013, vol. 29, no. 3-4, p. 1-18. (2012: 0.137 – SJR). (2013 – SCOPUS). ISSN 0970-1893.

Citácie SCOPUS: 1

1. [1.2] YASSIN, H.A.L. – SUBHI, B.F. Studying the effect of Gold Nanoparticles on some bacterial species isolated from surgical wound infections. In JOURNAL OF PHARMACEUTICAL NEGATIVE RESULTS, 2022, vol. 13, no. 4, p. 798-803. ISSN 0976-9234. https://doi.org/10.47750/pnr.2022.13.04.106; SCOPUS

 

  • GÄBLER, S. – STAMPFL, J. – KOCH, T. – SEIDLER, S. – SCHÜLLER, G.C. – REDL, H. – JURÁŠ, Vladimír – TRATTNIG, S. – WEIDISCH, R. Determination of the viscoelastic properties of hydrogels based on polyethylene glycol diacrylate (PEG-DA) and human articular cartilage. In International Journal of Materials Engineering Innovation, 2009, vol. 1, no. 1, p. 3-20. (2009 – WOS, SCOPUS). ISSN 1757-2754. https://doi.org/10.1504/IJMATEI.2009.024024

Citácie WOS: 3

1. [1.1] SHARMA, S. – GUPTA, V. – MUDGAL, D. Current trends, applications, and challenges of coatings on additive manufacturing based biopolymers: A state of art review. In POLYMER COMPOSITES. ISSN 0272-8397, OCT 2022, vol. 43, no. 10, p. 6749-6781. https://doi.org/10.1002/pc.26809; WOS

2. [1.1] TODROS, S. – SPADONI, S. – BARBON, S. – STOCCO, E. – CONFALONIERI, M. – PORZIONATO, A. – PAVAN, P.G. Compressive Mechanical Behavior of Partially Oxidized Polyvinyl Alcohol Hydrogels for Cartilage Tissue Repair. In BIOENGINEERING-BASEL. DEC 2022, vol. 9, no. 12. https://doi.org/10.3390/bioengineering9120789; WOS

3. [1.1] XU, D.C. – HARVEY, T. – BEGIRISTAIN, E. – DOMINGUEZ, C. – SANCHEZ-ABELLA, L. – BROWNE, M. – COOK, R.B. Measuring the elastic modulus of soft biomaterials using nanoindentation. In JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS. ISSN 1751-6161, SEP 2022, vol. 133. https://doi.org/10.1016/j.jmbbm.2022.105329; WOS

 

  • GRENDÁR, Marián – JUDGE, G. Empty set problem of maximum empirical likelihood methods. In Electronic Journal of Statistics, 2009, vol. 3, p. 1542-1555. (2009 – WOS, SCOPUS). ISSN 1935-7524. https://doi.org/10.1214/09-EJS528

Iné citácie: 1

1. [3.1] KIEN, D.T. – WEI, N.H. – CHAUDHURI, S. elhmc: An R Package for Hamiltonian Monte Carlo Sampling in Bayesian Empirical Likelihood. In arXiv, 2022, https://doi.org/10.48550/arXiv.2209.01289.

 

  • GRENDÁR, Marián. Entropy and effective support size. In Entropy, 2006, vol. 8, no. 3, p. 169-174. (2005: 0.300 – SJR, Q3 – SJR). (2005 – WOS, SCOPUS). ISSN 1099-4300. https://doi.org/10.3390/e8030169

Citácie WOS: 1

1. [1.1] NASCIMENTO, S.M.C. – FOSTER, D.H. Information gains from commercial spectral filters in anomalous trichromacy. In OPTICS EXPRESS. ISSN 1094-4087, MAY 9 2022, vol. 30, no. 10, p. 16883-16895. https://doi.org/10.1364/OE.451407; WOS

 

  • GRENDÁR JR., Marián – GRENDÁR, M. Maximum entropy: Clearing up mysteries. In Entropy, 2001, vol. 3, p. 58-63. (2001 – WOS, SCOPUS). ISSN 1099-4300. https://doi.org/10.3390/e3020058

Iné citácie: 1

1. [3.1] SIM, H.S. – LEE, M.-K. – LEE, C.-B. Evaluation of Habitat Suitability of Honey Tree Species, Kalopanax septemlobus Koidz., Tilia amurensis Rupr. and Styrax obassis Siebold & Z ucc. in the Baekdudaegan Mountains using MaxEnt Model. In JOURNAL OF KOREAN SOCIETY OF FOREST SCIENCE, 2022, vol. 111. no. 1, p. 50-60. ISSN 2586-6613. https://doi.org/10.14578/jkfs.2022.111.1.50

 

  • JURÁŠ, Vladimír – MLYNÁRIK, V. – SZOMOLÁNYI, PavolVALKOVIČ, Ladislav – TRATTNIG, S. Magnetic resonance imaging of the musculoskeletal system at 7T: Morphological imaging and beyond. In Topics in Magnetic Resonance Imaging, 2019, vol. 28, no. 3, p. 125-135. (2018: 0.601 – SJR, Q2 – SJR). (2019 – WOS, SCOPUS). ISSN 0899-3459. https://doi.org/10.1097/RMR.0000000000000205

Citácie WOS: 3; citácie SCOPUS: 1; iné citácie: 2

1. [1.1] MANSUR, H. – ESTANISLAU, G. – DE NORONHA, M. – MARQUETI, R. – FACHIN-MARTINS, E. – QUAGLIOTTI DURIGAN, J.L. Intra- and inter-rater reliability for the measurement of the cross-sectional area of ankle tendons assessed by magnetic resonance imaging. In ACTA RADIOLOGICA, 2022, vol. 63, no. 4, p. 481-488. ISSN 0284-1851. https://doi.org/10.1177/02841851211003284; WOS

2. [1.1] ZHENG, L.Y. – YANG, C. – LIANG, L. – RAO, S.X. – DAI, Y.M. – ZENG, M.S. T2-weighted MRI and reduced-FOV diffusion-weighted imaging of the human pancreas at 5 T: A comparison study with 3 T. In MEDICAL PHYSICS, 2022. ISSN 0094-2405. https://doi.org/10.1002/mp.15970; WOS

3. [1.1] ZHENG, L.Y. – YANG, C. – SHENG, R.F. – DAI, Y.M. – ZENG, M.S. Renal imaging at 5 T versus 3 T: a comparison study. In INSIGHTS INTO IMAGING. ISSN 1869-4101, SEP 24 2022, vol. 13, no. 1. https://doi.org/10.1186/s13244-022-01290-9; WOS

4. [1.2] TRANG, G. – DEL SOL, S.R. – JENKINS, S. – BRYANT, S. – GARDNER, B. – CHAKRABARTI, M.O. – MCGAHAN, P.J. – CHEN, J.L. Evaluation of Osteochondral Allograft Transplant Using In-Office Needle Arthroscopy. In ARTHROSCOPY TECHNIQUES, 2022, vol. 11, no. 12, p. e2243-e2248. https://doi.org/10.1016/j.eats.2022.08.032; SCOPUS

5. [3.1] CHEBROLU, V.V. – STINSON, E. – KOLLASCH, P. Subtle intensity graduating homomorphic transform to improve conspicuity of low-intensity pathologies. In US Patent US11448718B2, 2022, https://patents.google.com/patent/US11448718B2/en.

6. [3.1] PERRY, M.T. – ANDERSON, M.W. MR Imaging for the Orthopedic Surgeon. In MRI-ARTHROSCOPY CORRELATIONS. Springer, 2022, p. 1-16. https://doi.org/10.1007/978-3-030-94789-7_1

 

  • KAČUR, J. – MINÁR, J. – BUDÁČOVÁ, Hana. Determination of soil parameters based on mathematical modelling of centrifugation. In International Journal of Mathematical Modelling and Numerical Optimisation, 2014, vol. 5, no. 3, p. 153-170. (2013: 0.419 – SJR, Q3 – SJR). (2014 – SCOPUS). ISSN 2040-3607. https://doi.org/10.1504/IJMMNO.2014.063265

Citácie SCOPUS: 1

1. [1.2] TRNÍK, A. – MÁNIK, M. – KURUC, M. – MEDVED, I. Implementation of an Experimental Method in the Investigation of Hygrothermal Properties of Porous Materials in the Education of Graduate Students. In AIP CONFERENCE PROCEEDINGS, 2022, vol. 2458. ISSN 0094-243X. https://doi.org/10.1063/5.0078255; SCOPUS

 

  • KHUNOVÁ, V. – PAVLIŇÁKOVÁ, V. – ŠKRÁTEK, Martin – ŠAFAŘÍK, I. – PAVLIŇÁK, D. Magnetic halloysite reinforced biodegradable nanofibres: New challenge for medical applications. In AIP Conference Proceedings, 2018, vol. 1981, p. 020074. (2017: 0.165 – SJR). (2018 – SCOPUS, WOS). ISSN 0094-243X. https://doi.org/10.1063/1.5045936

Citácie WOS: 1

1. [1.1] FIZIR, M. – LIU, W. – TANG, X. – WANG, F.Q. – BENMOKADEM, Y. Design Approaches, Functionalization, and Environmental and Analytical Applications of Magnetic Halloysite Nanotubes: A Review. In CLAYS AND CLAY MINERALS. ISSN 0009-8604, OCT 2022, vol. 70, no. 5, p. 660-694. https://doi.org/10.1007/s42860-022-00210-8; WOS

 

  • MATEJ, Samuel – LEWITT, R. M. Practical considerations for 3-D image reconstruction using spherically symmetric volume elements. In IEEE Transactions on Medical Imaging, 1996, vol. 15, p. 68-78. (1996 – WOS, SCOPUS). ISSN 0278-0062. https://doi.org/10.1109/42.481442

Citácie WOS: 2; citácie SCOPUS: 1; iné citácie: 1

1. [1.1] CENSOR, Y. – SCHUBERT, K.E. – SCHULTE, R.W. Developments in Mathematical Algorithms and Computational Tools for Proton CT and Particle Therapy Treatment Planning. In IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES. ISSN 2469-7311, MAR 2022, vol. 6, no. 3, p. 313-324. https://doi.org/10.1109/TRPMS.2021.3107322; WOS

2. [1.1] EFTHIMIOU, N. – KARP, J.S. – SURTI, S. Data-driven, energy-based method for estimation of scattered events in positron emission tomography. In PHYSICS IN MEDICINE AND BIOLOGY. ISSN 0031-9155, MAY 7 2022, vol. 67, no. 9. https://doi.org/10.1088/1361-6560/ac62fc; WOS

3. [1.2] HAWKES, P. – KASPER, E. Principles of Electron Optics, Volume 4: Advanced Wave Optics, 2022, pp. 1-2639. https://doi.org/10.1016/C2021-0-01238-4; SCOPUS

4. [3.1] WANG, L. – CAO, W. System and method for image reconstruction. In US Patent, US11341613B2, 2022. https://patents.google.com/patent/US11341613B2/en

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. – MATOUŠEK, J. Evaluation of synthetic speech quality by statistical analysis of voiced and unvoiced part durations. In 41st International Conference on Telecommunications and Signal Processing (TSP 2018). – Brno, Czech Republic : Faculty of Electrical Engineering and Communication, Brno University of Technology, 2018, p. 396-399. (2018 – WOS, SCOPUS). ISBN 978-1-5386-4695-3. https://doi.org/10.1109/TSP.2018.8441352

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] MALUCHA, J. – SIGMUND, M. Comparison of methods for determining speech voicing based on tests performed on paired consonants and continuous speech. In JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS. ISSN 1335-3632, SEP 1 2022, vol. 73, no. 5, p. 359-362. https://doi.org/10.2478/jee-2022-0049; WOS

2. [1.2] MALUCHA, J. Software Tool for Pronunciation Training of Specific English Terminology. In INTERNATIONAL CONFERENCE ON NEW TRENDS IN SIGNAL PROCESSING, 2022. https://doi.org/10.23919/NTSP54843.2022.9920469; SCOPUS

 

  • RADIL, R. – BARABAS, J. – JANOUSEK, L. – BERETA, Martin. Frequency dependent alterations of S. Cerevisiae proliferation due to LF EMF exposure. In Advances in Electrical and Electronic Engineering, 2020, vol. 18, no. 2, p. 99-106. (2019: 0.205 – SJR, Q3 – SJR). (2020 – WOS, SCOPUS). ISSN 1336-1376. https://doi.org/10.15598/aeee.v18i2.3461

Citácie WOS: 2; citácie SCOPUS: 1; iné citácie: 2

1. [1.1] JAKUSOVA, V. – SLADICEKOVA, K.H. Electromagnetic Fields as a Health Risk Factor. In CLINICAL SOCIAL WORK AND HEALTH INTERVENTION. ISSN 2222-386X, 2022, vol. 13, no. 6, p. 49-57. https://doi.org/10.22359/cswhi_13_6_10; WOS

2. [1.1] SLADICEKOVA, K.H. – MISEK, J. – JAKUSOVA, V. – ULBRICHTOVA, R. – VETERNIK, M. – PARIZEK, D. – JAKUS, J. Attenuation properties of health protection accessories during mobile phone exposure on the human head phantom. In PRZEGLAD ELEKTROTECHNICZNY. ISSN 0033-2097, 2022, vol. 98, no. 8, p. 63-68. https://doi.org/10.15199/48.2022.08.12; WOS

3. [1.2] PSENAKOVA, Z. – GOMBARSKA, D. – BACOVA, F. – CARNECKA, L. Simulation of different antennae arrangement for study of high frequency electromagnetic field influence to tumor tissue. In 14TH INTERNATIONAL CONFERENCE ELEKTRO 2022, 2022. https://doi.org/10.1109/ELEKTRO53996.2022.9803594; SCOPUS

4. [3.1] JOSHI, A.A. – WINGKAR, K.C. – JOSHI, A.G. – KAKADE, S. Long term effects of mobile phone use on sleep quality, stress score and depression score in female medical students. In BLDE UNIVERSITY JOURNAL OF HEALTH SCIENCES, 2022, vol. 7, no. 1, p. 121-125. https://doi.org/10.4103/bjhs.bjhs_120_20

5. [3.1] MISEK, J. – LAPOSOVA, S. – HAMZA SLADICEKOVA, K. – JAKUSOVA, J. – PARIZEK, D. – JAKUSOVA, V. – VETERNIK, M. – JAKUS, J. Measurement of Base Transceiver Station Exposure in the Extra-Village Environment- A Pilot Study. In ACTA MEDICA MARTINIANA, 2022, vol. 22, no. 1, p. 15-23. https://doi.org/10.2478/acm-2022-0003

 

  • ROSIPAL, Roman. Kernel partial least squares for nonlinear regression and discrimination. In Neural Network World, 2003, vol. 13, no. 3, p. 291-300. (2003 – WOS, SCOPUS). ISSN 1210-0552.

Citácie WOS: 1; iné citácie: 2

1. [1.1] WANG, H.P. – CHU, X.L. – CHEN, P. – LI, J.Y. – LIU, D. – XU, Y.P. Partial least squares regression residual extreme learning machine (PLSRR-ELM) calibration algorithm applied in fast determination of gasoline octane number with near-infrared spectroscopy. In FUEL. ISSN 0016-2361, FEB 1 2022, vol. 309. https://doi.org/10.1016/j.fuel.2021.122224; WOS

2. [3.1] BIAN, X. Nonlinear Calibration Methods. In CHEMOMETRIC METHODS IN ANALYTICAL SPECTROSCOPY TECHNOLOGY. Springer, ISBN 978-981-19-1624-3, 2022, p. 255–295. https://www.springerprofessional.de/nonlinear-calibration-methods/22835930

3. [3.1] SCHULTZ, L. – AULD, J. – SOKOLOV, V. Bayesian Calibration for Activity Based Models. In arXiv, 2022, https://doi.org/10.48550/arXiv.2203.04414.

 

  • RUBLÍK, František. A quantile goodness-of-fit test for Cauchy distribution, based on extreme order statistics. In Applications of Mathematics, 2001, vol. 46, no. 5, p. 339-351. (2001 – SCOPUS). ISSN 0862-7940. https://doi.org/10.1023/A:1013704326683

Citácie WOS: 3

1. [1.1] AKAOKA, Y. – OKAMURA, K. – OTOBE, Y. Bahadur efficiency of the maximum likelihood estimator and one-step estimator for quasi-arithmetic means of the Cauchy distribution. In ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS. ISSN 0020-3157, OCT 2022, vol. 74, no. 5, p. 895-923. https://doi.org/10.1007/s10463-021-00818-y; WOS

2. [1.1] AKAOKA, Y. – OKAMURA, K. – OTOBE, Y. Limit theorems for quasi-arithmetic means of random variables with applications to point estimations for the Cauchy distribution. In BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS. ISSN 0103-0752, JUN 2022, vol. 36, no. 2, p. 385-407. https://doi.org/10.1214/22-BJPS531; WOS

3. [1.1] OKAMURA, K. – OTOBE, Y. Characterizations of the Maximum Likelihood Estimator of the Cauchy Distribution. In LOBACHEVSKII JOURNAL OF MATHEMATICS. ISSN 1995-0802, SEP 2022, vol. 43, no. 9, SI, p. 2576-2590. https://doi.org/10.1134/S1995080222120216; WOS

 

  • SCHWARZ, K. – PIZZINI, A. – ARENDACKÁ, Barbora – ZERLAUTH, K. – FILIPIAK, W. – SCHMID, A. – DZIEN, A. – NEUNER, S. – LECHLEITNER, M. – SCHOLL-BÜRGI, S. – MIEKISCH, W. – SCHUBERT, J. – UNTERKOFLER, K. – WITKOVSKÝ, Viktor – GASTL, G. – AMANN, A. Breath acetone – aspects of normal physiology related to age and gender as determined in a PTR-MS study. In Journal of Breath Research, 2009, vol. 3, p. 027003. (2008: 0.418 – SJR, Q2 – SJR). (2009 – WOS, SCOPUS). ISSN 1752-7155. https://doi.org/10.1088/1752-7155/3/2/027003

Citácie WOS: 10; iné citácie: 3

1. [1.1] AHMADIPOUR, M. – PANG, A.L. – ARDANI, M.R. – PUNG, S.Y. – OOI, P.C. – HAMZAH, A.A. – WEE, M.F.M.R. – HANIFF, M.A.S.M. – DEE, C.F. – MAHMOUDI, E. – ARSAD, A. – AHMAD, M.Z. – PAL, U. – CHAHROUR, K.M. – HADDADI, S.A. Detection of breath acetone by semiconductor metal oxide nanostructures-based gas sensors: A review. In MATERIALS SCIENCE IN SEMICONDUCTOR PROCESSING. ISSN 1369-8001, OCT 2022, vol. 149. https://doi.org/10.1016/j.mssp.2022.106897; WOS

2. [1.1] CRUZ, N. – FLORES, M. – URQUIAGA, I. – AVILA, F. Modulation of 1,2-Dicarbonyl Compounds in Postprandial Responses Mediated by Food Bioactive Components and Mediterranean Diet. In ANTIOXIDANTS. AUG 2022, vol. 11, no. 8. https://doi.org/10.3390/antiox11081513; WOS

3. [1.1] DONG, H. – QIAN, L.B. – CUI, Y.X. – ZHENG, X.B. – CHENG, C. – CAO, Q.P. – XU, F. – WANG, J. – CHEN, X. – WANG, D. Online Accurate Detection of Breath Acetone Using Metal Oxide Semiconductor Gas Sensor and Diffusive Gas Separation. In FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY. ISSN 2296-4185, MAR 8 2022, vol. 10. https://doi.org/10.3389/fbioe.2022.861950; WOS

4. [1.1] GOUZI, F. – AYACHE, D. – HEDON, C. – MOLINARI, N. – VICET, A. Breath acetone concentration: too heterogeneous to constitute a diagnosis or prognosis biomarker in heart failure? A systematic review and meta-analysis. In JOURNAL OF BREATH RESEARCH. ISSN 1752-7155, JAN 2022, vol. 16, no. 1. https://doi.org/10.1088/1752-7163/ac356d; WOS

5. [1.1] GUNTNER, A.T. – WEBER, I.C. – SCHON, S. – PRATSINIS, S.E. – GERBER, P.A. Monitoring rapid metabolic changes in health and type-1 diabetes with breath acetone sensors. In SENSORS AND ACTUATORS B-CHEMICAL. SEP 15 2022, vol. 367. https://doi.org/10.1016/j.snb.2022.132182; WOS

6. [1.1] HOLCZMANN, P. – LEDERER, W. – ISSER, M. – KLINGER, A. – JURSCHIK, S. – WIESENHOFER, H. – MAYHEW, C.A. – RUZSANYI, V. Adsorption Capacity of Plastic Foils Suitable for Barrier Resuscitation. In COATINGS. OCT 2022, vol. 12, no. 10. https://doi.org/10.3390/coatings12101545; WOS

7. [1.1] OBEIDAT, Y. – RAWASHDEH, A.M. – HAMMOUDEH, A. – AL-ASSI, R. – DAGAMSEH, A. – QANANWAH, Q. Acetone sensing in liquid and gas phases using cyclic voltammetry. In SCIENTIFIC REPORTS. ISSN 2045-2322, JUN 30 2022, vol. 12, no. 1. https://doi.org/10.1038/s41598-022-15135-4; WOS

8. [1.1] PALECZEK, A. – RYDOSZ, A. Review of the algorithms used in exhaled breath analysis for the detection of diabetes. In JOURNAL OF BREATH RESEARCH. ISSN 1752-7155, 2022, vol. 16, no. 2. https://doi.org/10.1088/1752-7163/ac4916; WOS

9. [1.1] ZHANG, C. – ZHENG, Y. – DING, Y.W. – ZHENG, X.K. – XIANG, Y. – TONG, A.J. A ratiometric solid AIE sensor for detection of acetone vapor. In TALANTA. ISSN 0039-9140, JAN 1 2022, vol. 236. https://doi.org/10.1016/j.talanta.2021.122845; WOS

10. [1.1] ZOU, Z.W. – YANG, X.D. Volatile organic compound emissions from the human body: Decoupling and comparison between whole-body skin and breath emissions. In BUILDING AND ENVIRONMENT. ISSN 0360-1323, DEC 2022, vol. 226. https://doi.org/10.1016/j.buildenv.2022.109713; WOS

11. [3.1] AHMAD, L.M. – AHMAD, S.A. – SMITH, Z. Analyte measurement analysis using baseline levels. In US Patent, US11253194B2, 2022, https://patents.google.com/patent/US11253194B2/en.

12. [3.1] AHMED, L.M. – SATTERFIELD, B.C. – MARTINEAU, R.L. Method and apparatus for analyzing acetone in breath. In US Patent, US11353462B2, 2022, https://patents.google.com/patent/US11353462B2/en.

13. [3.1] BEKÖ, G. – WARGOCKI, P. – DUFFY, E. Occupant Emissions and Chemistry. In HANDBOOK OF INDOOR AIR QUALITY. Springer, 2022, 903-929. https://doi.org/10.1007/978-981-16-7680-2_33

 

  • ŠVEHLÍKOVÁ, JanaLENKOVÁ, Jana – DRKOŠOVÁ, A. – FOLTÍN, M. – TYŠLER, Milan. ECG based assessment of the heart position in standard torso model. In IFMBE Proceedings, 2012, vol. 37, p. 474-477. (2012 – WOS, SCOPUS). ISSN 1680-0737. https://doi.org/10.1007/978-3-642-23508-5_123

Citácie WOS: 1

1. [1.1] BERGQUIST, J.A. – COLL-FONT, J. – ZENGER, B. – RUPP, L.C. – GOOD, W.W. – BROOKS, D.H. – MACLEOD, R.S. Reconstruction of cardiac position using body surface potentials. In COMPUTERS IN BIOLOGY AND MEDICINE. ISSN 0010-4825, MAR 2022, vol. 142. https://doi.org/10.1016/j.compbiomed.2021.105174; WOS

 

  • TYŠLER, MilanLENKOVÁ, JanaŠVEHLÍKOVÁ, Jana. Impact of the patient torso model on the solution of the inverse problem of electrocardiography. In Advances in Electrical and Electronic Engineering, 2014, vol. 12, no. 1, p. 58-65. (2013: 0.212 – SJR, Q3 – SJR). (2014 – SCOPUS). ISSN 1336-1376. https://doi.org/10.15598/aeee.v12i1.648

Citácie WOS: 1

1. [1.1] KAGHAZCHI, N. – UN, M.K. A novel iterative finite element optimisation method of solving inverse problem of electrocardiography to localise ischemic region on the heart. In MAEJO INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY. ISSN 1905-7873, SEP-DEC 2022, vol. 16, no. 03, p. 275-290; WOS

 

  • VU VIET, HoangTEPLAN, Michal. Impact of magnetic field on yeast cells monitored by impedance spectroscopy. In Proceedings of International Workshop on Impedance Spectroscopy : IWIS 2021. – [s.l.] : IEEE, 2021, p. 85-88. (2021 – WOS, SCOPUS). ISBN 978-1-6654-9472-4. https://doi.org/10.1109/IWIS54661.2021.9711789

Citácie WOS: 1

1. [1.1] JUDAKOVA, Z. – JANOUSEK, L. – CARNECKA, L. – SVANTNEROVA, I. Conductometry as an evaluation tool in research into the impact of low-frequency electromagnetic field irradiation on cells. In 2022 23RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL PROBLEMS OF ELECTRICAL ENGINEERING (CPEE). 2022. https://doi.org/10.1109/CPEE56060.2022.9919688; WOS

 

  • WITKOVSKÝ, Viktor. Numerical inversion of a characteristic function: An alternative tool to form the probability distribution of output quantity in linear measurement models. In Acta IMEKO, 2016, vol. 5, no. 3, p. 32-44. (2015: 0.136 – SJR, Q4 – SJR). (2016 – SCOPUS). ISSN 2221-870X. https://doi.org/http://dx.doi.org/10.21014/acta_imeko.v5i3.382

Citácie WOS: 3

1. [1.1] CUINGNET, R. – LADEGAILLERIE, Y. – JOSSENT, J. – MAITROT, A. – CHEDAL-ANGLAY, J. – RICHARD, W. – BERNARD, M. – WOOLFENDEN, J. – BIROT, E. – CHENU, D. PortiK: A computer vision based solution for real-time automatic solid waste characterization-Application to an aluminium stream. In WASTE MANAGEMENT. ISSN 0956-053X, SEP 2022, vol. 151, p. 267-279. https://doi.org/10.1016/j.wasman.2022.05.021; WOS

2. [1.1] HANCOVA, M. – GAJDOS, A. – HANC, J. A practical, effective calculation of gamma difference distributions with open data science tools. In JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. ISSN 0094-9655, JUL 24 2022, vol. 92, no. 11, p. 2205-2232. https://doi.org/10.1080/00949655.2021.2023873; WOS

3. [1.1] SIVARAMAKRISHNAN, V. – PILIPOVSKY, J. – OISHI, M. – TSIOTRAS, P. Distribution Steering for Discrete-Time Linear Systems with General Disturbances using Characteristic Functions. In 2022 AMERICAN CONTROL CONFERENCE (ACC). 2022, p. 4183-4190; WOS

 

  • WITKOVSKÝ, Viktor. On the exact two-sided tolerance intervals for univariate normal distribution and linear regression. In Austrian Journal of Statistics, 2014, vol. 43, no. 3-4, p. 279-292. (2014 – WOS). ISSN 1026-597X. https://doi.org/10.17713/ajs.v43i4.46

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] OH, Y. – KWAK, J. – KIM, S. Time delay estimation of traffic congestion propagation due to accidents based on statistical causality. In ELECTRONIC RESEARCH ARCHIVE. 2022, vol. 31, no. 2, p. 691-707. https://doi.org/10.3934/era.2023034; WOS

2. [1.2] KANG, P. A double integration method for generating exact tolerance limit factors for normal populations. In INTERNATIONAL JOURNAL OF METROLOGY AND QUALITY ENGINEERING, 2022, vol. 13. https://doi.org/10.1051/ijmqe/2022015; SCOPUS

 

Vedecké práce v domácich impaktovaných časopisoch registrovaných v databázach WOS alebo SCOPUS

 

  • BULAS, J. – POTOCAROVA, M. – KUPCOVA, V. – GASPAR, L. – WIMMER, Gejza, ml. – MURIN, J. Central systolic blood pressure increases with aortic stiffness. In Bratislava Medical Journal, 2019, vol. 120, no. 12, p. 894-898. (2018: 0.859 – IF, Q3 – JCR, 0.264 – SJR, Q3 – SJR). (2019 – WOS, SCOPUS). ISSN 0006-9248. https://doi.org/10.4149/BLL_2019_150

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] TAKAMI, T. – HOSHIDE, S. – KARIO, K. Differential impact of antihypertensive drugs on cardiovascular remodeling: a review of findings and perspectives for HFpEF prevention. In HYPERTENSION RESEARCH. ISSN 0916-9636, JAN 2022, vol. 45, no. 1, p. 53-60. https://doi.org/10.1038/s41440-021-00771-6; WOS

2. [1.2] AKOPYAN, A.A. – STRAZHESKO, I.D. – KLYASHTORNY, V.G. – ORLOVA, Y.A. Biological vascular age and its relationship with cardiovascular risk factors. In CARDIOVASCULAR THERAPY AND PREVENTION (RUSSIAN FEDERATION), 2022, vol. 21, no. 1, p. 12-19. ISSN 1728-8800. https://doi.org/10.15829/1728-8800-2022-2877; SCOPUS

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. – MATOUŠEK, J. Evaluation of speaker de-identification based on voice gender and age conversion. In Journal of Electrical Engineering, 2018, vol. 69, no. 2, p. 138-147. (2017: 0.508 – IF, Q4 – JCR, 0.205 – SJR, Q3 – SJR). (2018 – SCOPUS, WOS). ISSN 1335-3632. https://doi.org/10.2478/jee-2018-0017

Citácie WOS: 2; citácie SCOPUS: 1

1. [1.1] MAWALIM, C.O. – OKADA, S. – UNOKI, M. F-0 Modification via PV-TSM Algorithm for Speaker Anonymization Across Gender. In PROCEEDINGS OF 2022 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC). ISSN 2309-9402, 2022, p. 196-203; WOS

2. [1.1] PRAJAPATI, G.P. – SINGH, D.K. – AMIN, P.P. – PATIL, H.A. Voice privacy using CycleGAN and time-scale modification. In COMPUTER SPEECH AND LANGUAGE. ISSN 0885-2308, JUL 2022, vol. 74. https://doi.org/10.1016/j.csl.2022.101353; WOS

3. [1.2] PRAJAPATI, G.P. – SINGH, D.K. – PATIL, H.A. Significance of Distance Measures for Speaker Anonymization. In SPCOM 2022 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS, 2022. https://doi.org/10.1109/SPCOM55316.2022.9840515; SCOPUS

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. – MATOUŠEK, J. GMM-based speaker age and gender classification in Czech and Slovak. In Journal of Electrical Engineering, 2017, vol. 68, no. 1, p. 3-12. (2016: 0.483 – IF, Q4 – JCR, 0.311 – SJR, Q2 – SJR). (2017 – WOS, SCOPUS). ISSN 1335-3632. https://doi.org/10.1515/jee-2017-0001

Citácie WOS: 3; citácie SCOPUS: 1

1. [1.1] BADR, A. – ABDUL-HASSAN, A. VoxCeleb1: Speaker Age-Group Classification Probabilistic Neural Network. In INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY. ISSN 1683-3198, NOV 2022, vol. 19, no. 6, p. 854-860. https://doi.org/10.34028/iajit/19/6/2; WOS

2. [1.1] BADR, A.A. – ABDUL-HASSAN, A.K. Speaker gender identification in matched and mismatched conditions based on stacking ensemble method. In JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY. APR 2022, vol. 17, no. 2, p. 1119-1134; WOS

3. [1.1] VETRAB, M. – GOSZTOLYA, G. Using the Bag-of-Audio-Words approach for emotion recognition. In ACTA UNIVERSITATIS SAPIENTIAE INFORMATICA. ISSN 1844-6086, AUG 1 2022, vol. 14, no. 1, p. 1-21. https://doi.org/10.2478/ausi-2022-0001; WOS

4. [1.2] GOUD, K.M. – HUSSAIN, S.J. Estimation of Gender Using Convolutional Neural Network. In 6TH INTERNATIONAL CONFERENCE ON MICROELECTRONICS, ELECTROMAGNETICS, AND TELECOMMUNICATIONS (ICMEET 2021), 2022, LNEE 839, p. 33-38. https://doi.org/10.1007/978-981-16-8554-5_4.

 

  • STEIN, G.J. – CHMÚRNY, R. – ROSÍK, Vladimír. Compact vibration measuring system for in-vehicle applications. In Measurement Science Review, 2011, vol. 11, no. 5, p. 154-159. (2010: 0.400 – IF, Q4 – JCR, 0.209 – SJR, Q3 – SJR). (2011 – WOS, SCOPUS). ISSN 1335-8871. https://doi.org/10.2478/v10048-011-0030-1

Citácie WOS: 3; citácie SCOPUS: 2

1. [1.1] MUCKA, P. New Transverse Unevenness Indexes of the Road Profile. In JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS. ISSN 2573-5438, 2022, vol. 148, no. 3. https://doi.org/10.1061/JPEODX.0000387; WOS

2. [1.1] MUCKA, P. Probability density function of whole-body vibration in passenger car. In PROBABILISTIC ENGINEERING MECHANICS. ISSN 0266-8920, 2022, vol. 69. https://doi.org/10.1016/j.probengmech.2022.103311; WOS

3. [1.1] NITHIN, S.K. – HEMANTH, K. – SHAMANTH, V. – MAHALE, R.S. – SHARATH, P.C. – PATIL, A. Importance of condition monitoring in mechanical domain. In MATERIALS TODAY-PROCEEDINGS. ISSN 2214-7853, 2022, vol. 54, p. 234-239. https://doi.org/10.1016/j.matpr.2021.08.299; WOS

4. [1.2] GUEORGUIEV, N. – TODOROV, M. – BOYCHEV, Y. – TODOROV, M. Vehicle’s seismic waves measurements. In INTERNATIONAL MULTIDISCIPLINARY SCIENTIFIC GEOCONFERENCE SURVEYING GEOLOGY AND MINING ECOLOGY MANAGEMENT, 2022, vol. 22, p. 575-590. https://doi.org/10.5593/sgem2022/1.1/s05.067; SCOPUS

5. [1.2] HASSINE, H. – CHAEIB, H. – BARKALLAH, M. – LOUATI, J. – HADDAR, M. Experimental Study and Measurement of Vehicle Interior Vibration. In ADVANCES IN MATERIALS, MECHANICS AND MANUFACTURING II. A3M 2021. Springer, p. 333-341. https://doi.org/10.1007/978-3-030-84958-0_36; SCOPUS

 

  • TEPLAN, MichalKRAKOVSKÁ, Anna – ŠPAJDEL, M. Spectral EEG features of a short psycho-physiological relaxation. In Measurement Science Review, 2014, vol. 14, no. 4, p. 237-242. (2013: 1.162 – IF, Q3 – JCR, 0.340 – SJR, Q3 – SJR). (2014 – WOS, SCOPUS). ISSN 1335-8871. https://doi.org/10.2478/msr-2014-0032

Citácie SCOPUS: 1

1. [1.2] WEEKES, T.R. – ESKRIDGE, T.C. Design Thinking the Human-AI Experience of Neurotechnology for Knowledge Workers. In LECTURE NOTES IN COMPUTER SCIENCE, 2022, vol. 13519 LNCS, p. 527-545. ISSN 0302-9743. https://doi.org/10.1007/978-3-031-17618-0_37; SCOPUS

 

  • VOJTÍŠEK, LubomírFROLLO, IvanVALKOVIČ, LadislavGOGOLA, DanielJURÁŠ, Vladimír. Phased array receiving coils for low field lungs MRI: Design and optimization. In Measurement Science Review, 2011, vol. 11, no. 2, p. 61-66. (2010: 0.400 – IF, Q4 – JCR, 0.209 – SJR, Q3 – SJR). (2011 – WOS, SCOPUS). ISSN 1335-8871. https://doi.org/10.2478/v10048-011-0012-3

Citácie WOS: 1

1. [1.1] GIOVANNETTI, G. – FRIJIA, F. – FLORI, A. Radiofrequency Coils for Low-Field (0.18-0.55 T) Magnetic Resonance Scanners: Experience from a Research Lab-Manufacturing Companies Cooperation. In ELECTRONICS, 2022, vol. 11, no. 24. https://doi.org/10.3390/electronics11244233; WOS

 

  • WITKOVSKÝ, Viktor – WIMMER, G. – DUBY, T. Estimating the distribution of a stochastic sum of IID random variables. In Mathematica Slovaca, 2020, vol. 70. no. 3, p. 759-774. (2019: 0.654 – IF, Q3 – JCR, 0.397 – SJR, Q3 – SJR). (2020 – WOS, SCOPUS). ISSN 0139-9918. https://doi.org/10.1515/ms-2017-0389

Citácie WOS: 1

1. [1.1] COELHO, C.A. Likelihood Ratio Tests for Elaborate Covariance Structures and for MANOVA Models with Elaborate Covariance Structures-A Review. In JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE. ISSN 0970-4140, 2022; WOS

 

Vedecké práce v domácich neimpaktovaných časopisoch registrovaných v databázach WOS alebo SCOPUS

 

  • FROLLO, IvanANDRIS, PeterKRAFČÍK, AndrejGOGOLA, DanielDERMEK, Tomáš. Comparative magnetic field measurements for homogeneity adjustment of magnetic resonance imaging equipments. In MEASUREMENT 2017 : Proceedings of the 11th International Conference on Measurement. – Bratislava, Slovakia : Institute of Measurement Science, SAS, 2017, p. 259-262. (2017 – WOS, SCOPUS). ISBN 978-80-972629-0-7. https://doi.org/10.23919/MEASUREMENT.2017.7983585

Citácie WOS: 1; citácie SCOPUS: 1

1. [1.1] LI, Z. – OUYANG, Z.R. – LENG, Z.K. – ZHANG, Y.B. – ZHANG, S. – LU, Y.F. – YAN, Z.D. Precise Strong Magnet Measurement Method Based on Magnetic Flux Modulation Principle. In ELECTRONICS. MAR 2022, vol. 11, no. 6. https://doi.org/10.3390/electronics11060970; WOS

2. [1.2] WANG, Y. – HU, H. – SHANG, H. – PENG, T. Measuring System with a Probe Array for Magnetic Field Homogeneity. In 2022 IEEE 3RD CHINA INTERNATIONAL YOUTH CONFERENCE ON ELECTRICAL ENGINEERING, 2022. https://doi.org/10.1109/CIYCEE55749.2022.9958965; SCOPUS

 

  • KADANEC, JanZELINKA, JánBUKOR, GabrielTYŠLER, Milan. ProCardio 8 – system for high resolution ECG mapping. In MEASUREMENT 2017 : Proceedings of the 11th International Conference on Measurement. – Bratislava, Slovakia : Institute of Measurement Science, SAS, 2017, p. 263-266. (2017 – WOS, SCOPUS). ISBN 978-80-972629-0-7. https://doi.org/10.23919/MEASUREMENT.2017.7983586

Citácie SCOPUS: 1

1. [1.2] RASOOLZADEH, N. – SVEHLIKOVA, J. – ONDRUSOVA, B. – DOGRUSOZ, Y.S. Variability of Premature Ventricular Contraction Localization with Respect to Source and Forward Model Variation in Clinical Data. In COMPUTING IN CARDIOLOGY, 2022. ISSN 2325-8861. https://doi.org/10.22489/CinC.2022.353; SCOPUS

 

  • PIGOŠOVÁ, Jana CIGÁŇ, AlexanderMAŇKA, Ján. Thermal synthesis of bismuth-doped yttrium iron garnet for magneto-optical imaging. In Measurement Science Review, 2008, vol. 8, no. 5, p. 126-128. (2008 – WOS). ISSN 1335-8871. https://doi.org/10.2478/v10048-008-0030-y

Citácie WOS: 1

1. [1.1] SPIVAKOV, A. – LIN, C.R. – TSAI, C.Y. – CHEN, Y.Z. Size-Dependent Magnetic and Magneto-Optical Properties of Bi-Doped Yttrium Iron Garnet Nanopowders. In NANOSCALE RESEARCH LETTERS. ISSN 1931-7573, AUG 4 2022, vol. 17, no. 1. https://doi.org/10.1186/s11671-022-03709-0; WOS

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. An experiment with evaluation of emotional speech conversion by spectrograms. In Measurement Science Review, 2010, vol. 10, no. 3, p. 72-77. (2009: 0.115 – SJR, Q4 – SJR). (2010 – WOS, SCOPUS). ISSN 1335-8871. https://doi.org/10.2478/v10048-010-0017-3

Citácie WOS: 1

1. [1.1] ALNUAIM, A.A. – ZAKARIAH, M. – ALHADLAQ, A. – SHASHIDHAR, C. – HATAMLEH, W.A. – TARAZI, H. – SHUKLA, P.K. – RATNA, R. Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks. In COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE. ISSN 1687-5265, MAR 31 2022, vol. 2022. https://doi.org/10.1155/2022/7463091; WOS

 

  • WIMMER, G. – WITKOVSKÝ, Viktor. Two-dimensional linear comparative calibration and measurement uncertainty. In MEASUREMENT 2019 : Proceedings of the 12th International Conference on Measurement. – Bratislava, Slovakia : Institute of Measurement Science, Slovak Academy of Sciences, 2019, p. 66-69. (2019 – WOS, SCOPUS). ISBN 978-80-972629-2-1. https://doi.org/10.23919/MEASUREMENT47340.2019.8779887

Iné citácie: 1

1. [3.1] ZAKHAROV, I. – NEYEZHMAKOV, P. – SEMENIKHIN, V. – WARSZAM, Z.L. Measurement Uncertainty Evaluation of Parameters Describing the Calibrated Curves. In AUTOMATION 2022: NEW SOLUTIONS AND TECHNOLOGIES FOR AUTOMATION, ROBOTICS AND MEASUREMENT TECHNIQUES. Springer, 2022, AISC vol. 1427. https://doi.org/10.1007/978-3-031-03502-9_38

 

  • WITKOVSKÝ, Viktor – WIMMER, G. – ĎURIŠOVÁ, Z. – ĎURIŠ, S. – PALENČÁR, R. Brief overview of methods for measurement uncertainty analysis: GUM uncertainty framework, Monte Carlo method, characteristic function approach. In MEASUREMENT 2017 : Proceedings of the 11th International Conference on Measurement. – Bratislava, Slovakia : Institute of Measurement Science, SAS, 2017, p. 35-38. (2017 – WOS, SCOPUS). ISBN 978-80-972629-0-7. https://doi.org/10.23919/MEASUREMENT.2017.7983530

Citácie WOS: 2

1. [1.1] CHEN, Y.M. – LI, X.H. – HUANG, L.X. – WANG, X. – LIU, C.H. – ZHAO, F. – HUA, Y. – FENG, P. GUM method for evaluation of measurement uncertainty: BPL long wave time service monitoring. In MEASUREMENT. ISSN 0263-2241, FEB 15 2022, vol. 189. https://doi.org/10.1016/j.measurement.2021.110459; WOS

2. [2.1] KUWALEK, P. – WICZYNSKI, G. Problem of Total Harmonic Distortion Measurement Performed by Smart Energy Meters. In MEASUREMENT SCIENCE REVIEW. ISSN 1335-8871, FEB 1 2022, vol. 22, no. 1, p. 1-10. https://doi.org/10.2478/msr-2022-0001; WOS

 

  • WITKOVSKÝ, Viktor – WIMMER, G. Inverse and direct prediction and its effect on measurement uncertainty in polynomial comparative calibration. In MEASUREMENT 2019 : Proceedings of the 12th International Conference on Measurement. – Bratislava, Slovakia : Institute of Measurement Science, Slovak Academy of Sciences, 2019, p. 62-65. (2019 – WOS, SCOPUS). ISBN 978-80-972629-2-1. https://doi.org/10.23919/MEASUREMENT47340.2019.8779926

Citácie WOS: 1; iné citácie: 1

1. [1.1] FARAYOLA, P.O. – BRUCE, I. – CHAGANTI, S.K. – SHEIKH, A. – RAVI, S. – CHEN, D. The Least-Squares Approach to Systematic Error Identification and Calibration in Semiconductor Multisite Testing. In 2022 IEEE 40TH VLSI TEST SYMPOSIUM (VTS). ISSN 1093-0167, 2022; WOS

2. [3.1] ZAKHAROV, I. – NEYEZHMAKOV, P. – SEMENIKHIN, V. – WARSZAM, Z.L. Measurement Uncertainty Evaluation of Parameters Describing the Calibrated Curves. In AUTOMATION 2022: NEW SOLUTIONS AND TECHNOLOGIES FOR AUTOMATION, ROBOTICS AND MEASUREMENT TECHNIQUES. Springer, 2022, AISC vol. 1427. https://doi.org/10.1007/978-3-031-03502-9_38

 

Vedecké práce v ostatných zahraničných časopisoch, neimpaktovaných

 

  • CIMERMANOVÁ, Katarína. Estimation of confidence intervals for the log-normal means and for the ratio and difference of log-normal means. In Measurement Science Review, 2007, vol. 7, no. 3, p. 31-34. ISSN 1335-8871.

Citácie WOS: 1

1. [1.1] MARIMUTHU, S. – MANI, T. – SUDARSANAM, T.D. – GEORGE, S. – JEYASEELAN, L. Preferring Box-Cox transformation, instead of log transformation to convert skewed distribution of outcomes to normal in medical research. In CLINICAL EPIDEMIOLOGY AND GLOBAL HEALTH. ISSN 2452-0918, MAY-JUN 2022, vol. 15. https://doi.org/10.1016/j.cegh.2022.101043; WOS

 

  • KLEMBARA, J. – MIKUDÍKOVÁ, M. – ŠTAMBERG, S. – HAIN, Miroslav. First record of the stem amniote Discosauriscus (Seymouriamorpha, Discosauriscidae) from the Krkonoše Piedmont Basin (the Czech Republic). In Fossil Imprint, 2020, vol. 76, no. 2, p. 243-251. (2019: 0.395 – SJR, Q3 – SJR). ISSN 2533-4050. https://doi.org/http://dx.doi.org/10.37520/fi.2020.020

Citácie WOS: 1

1. [1.1] CALABKOVA, G. – BREZINA, J. – MADZIA, D. Evidence of large terrestrial seymouriamorphs in the lowermost Permian of the Czech Republic. In PAPERS IN PALAEONTOLOGY, 2022, vol. 8, no. 2. ISSN 2056-2799. https://doi.org/10.1002/spp2.1428; WOS

 

  • KRAKOVSKÁ, AnnaMEZEIOVÁ, KristínaBUDÁČOVÁ, Hana. Use of false nearest neighbours for selecting variables and embedding parameters for state space reconstruction. In Journal of Complex Systems, 2015, article ID 932750, p. 1-12. ISSN 2356-7244.

Citácie WOS: 3; citácie SCOPUS: 1; iné citácie: 4

1. [1.1] GU, H. – CHOU, C.-A. Optimizing non-uniform multivariate embedding for multiscale entropy analysis of complex systems. In BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, vol. 71. ISSN 1746-8094. https://doi.org/10.1016/j.bspc.2021.103206; WOS

2. [1.1] KRAEMER, K.H. – GELBRECHT, M. – PAVITHRAN, I. – SUJITH, R.I. – MARWAN, N. Optimal state space reconstruction via Monte Carlo decision tree search. In NONLINEAR DYNAMICS. ISSN 0924-090X, APR 2022, vol. 108, no. 2, p. 1525-1545. https://doi.org/10.1007/s11071-022-07280-2; WOS

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140. [3.1] ANUMALA, V. – DHULIPALLA, V.R. EMD Inspired by Wavelet Thresholding for Correction of Blink Artifacts from Single-Channel Cerebral Signals. In INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) FRAMEWORKS IN TELEHEALTH. Springer, 2022, p. 255-271. https://doi.org/10.1007/978-3-031-05049-7_16.

141. [3.1] CHAUDHARI, S.A. – GAWALI, B.W. –  OMPRAKASH, S. Jadhav Statistical Analysis of EEG Data For Attention Deficit Hyperactivity Disorder. In JOURNAL OF POSITIVE SCHOOL, 2022, vol. 6, no. 5, p. 4046-4053. https://www.journalppw.com/index.php/jpsp/article/view/6975/4542.

142. [3.1] DASDEMİR, Y. A brain-computer interface for gamification in the Metaverse. In DICLE UNIVERSITY JOURNAL OF ENGINEERING, 2022, vol. 13, no. 4, p. 645-652. https://doi.org/10.24012/dumf.1134296.

143. [3.1] EYAD TALAL ATTAR. A Review of Mental Stress and EEG Band Power. In INTERNATIONAL JOURNAL OF NANOTECHNOLOGY & NANOMEDICINE, 2022, vol. 7, no. 2, p. 112-118. ISSN 2476- 2334.

144. [3.1] HOSSAIN, G. – BELLO, M. – FAIYAZUDDIN, M. Blink Rate Variability as a Measure of Computer Vision Syndrome. In RESEARCH SQUARE, 2022. https://doi.org/10.21203/rs.3.rs-1550893/v1.

145. [3.1] KHOR, E.Y. – LIM, C.C. – CHONG, Y.F. – LEE, P.F. Features Analysis of Electroencephalography (EEG) for Mindfulness Meditation Effect on Cancer Patients Toward Stress Level. In PROCEEDINGS OF THE INTERNATIONAL E-CONFERENCE ON INTELLIGENT SYSTEMS AND SIGNAL PROCESSING. Springer, 2022, p. 203-218. https://doi.org/10.1007/978-981-16-2123-9_15.

146. [3.1] KOSE, M.R. – AHIRWAL, M.K. – MITHILESH, A. A Review on Biomedical Signals with Fundamentals of Digital Signal Processing. In ARTIFICIAL INTELLIGENCE APPLICATIONS FOR HEALTH CARE. CRC Press, 2022, ISBN 9781003241409.

147. [3.1] KUMAR, C. – KUMAR, M. Comparative Analysis of Emotional State Classification Using Different Machine Learning Techniques. In INDUSTRIAL INTERNET OF THINGS. CRC Press, 2022, ISBN 9781003145004.

148. [3.1] LEE, E. – HONG. J.K. – CHOI, H. – YOON, I. Modest effect of neurofeedback-assisted meditation using wearable device on stress reduction: A randomized, double-blind and controlled Study. In RESEARCH SQUARE, 2022. https://doi.org/10.21203/rs.3.rs-1907600/v1.

149. [3.1] LU, L. – XIE, Z. – WANG, H. – LI, L. – XU, X. Measurements of Mental Stress and Safety Awareness during Human Robot Collaboration – Review. In PROCEEDINGS OF THE 2022 HFES 66TH INTERNATIONAL ANNUAL MEETING, 2022, p. 2273-2277. https://journals.sagepub.com/doi/pdf/10.1177/1071181322661549.

150. [3.1] LUKAČEVIC, F. – BECATTINI, N. – ŠKEC, S. Differences in engineers‘; brain activity when CAD modelling from isometric and orthographic projections. In RESEARCH SQUARE, 2022. https://doi.org/10.21203/rs.3.rs-2154458/v1.

151. [3.1] MIDER, D. Badanie aktywności elektrycznej ludzkiego mózgu w zakresie potencjałów wywołanych – nowe narzędzie Nauk Społecznych. In COLLECTION OF SCIENTIFIC ARTICLES ON CONTEMPORARY PROBLEMS OF PHILOSOPHY, CULTURAL STUDIES, PSYCHOLOGY, PEDAGOGY AND HISTORY. Kyiv, Ukrainian: Drahomanov National Pedagogical University, 2022, p. 138-143. ISBN 978-966-999-273-4.

152. [3.1] MOKHTAR, A.S. – FUAD, N. – MARWAN, M.E. – NORAZLIN. Electroencephalogram (EEG) pattern for human smoke habit. In PENYELIDIKAN ISLAM: INTEGRASI ILMU NAQLI DAN AQLI. Penerbit UTHM, p. 86-103. ISBN 978-967-2817-72-7. http://eprints.uthm.edu.my/id/eprint/7289.

153. [3.1] NARMADA, A. Deep learning for EEG Channel Selection for Epilepsy Detection and Classification. In JOURNAL OF POSITIVE SCHOOL PSYCHOLOGY, 2022, vol. 6, no. 5, p. 6511–6524. https://journalppw.com/index.php/jpsp/article/view/8177.

154. [3.1] NETO, F. – JORGE, V. – SILVA, C. Comparison of performance of scenarios with one and three brain-machine interfaces applied. In ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 2022, vol. 19., p. 198-209. https://doi.org/10.5753/eniac.2022.227599.

155. [3.1] NOUIRA, I. – BEDOUI, M.H. Parallel Implementation for EEG Artifact Rejection. In ELECTROENCEPHALOGRAM SIGNAL ANALYSIS: EPILEPTIC CEREBRAL ACTIVITY LOCALIZATION AND IMPLEMENTATION. Cambridge Scholars Publishing, 2022, p. 97-119. ISBN 978-1-5275-8451-8.

156. [3.1] PAN, Y. – CHOU, J. – WEI, C. MAtt: A Manifold Attention Network for EEG Decoding. In arXiv 2022, https://doi.org/10.48550/arXiv.2210.01986.

157. [3.1] PANTONGRUK, P. – HORNGKITIYANON, T. The Body Systems, Brains and Learning Directions of Thai Children in the New Normal Lifestyle. In SIKKHA JOURNAL OF EDUCATION, 2022, vol. 9, no. 1, p. 1–12. https://so05.tci-thaijo.org/index.php/sikkha/article/view/253492.

158. [3.1] PRADA, E. – TAVARES, M. – GARCIA, A. – SATLER, C. – MARTINEZ, L. – ALVES, C. – TOMAZ, C. EEG Mapping of Cortical Activation Related to Emotional Stroop with Facial Expressions: A TREFACE Study. In JOURNAL OF BEHAVIORAL AND BRAIN SCIENCE, 2022, vol. 12, p. 514-532. https://doi.org/10.4236/jbbs.2022.1210030.

159. [3.1] RAHIM, A. – FUAD, N. – MARWAN, M. – NORAZLIN, N. EEG pattern of human calmness during listening to Al-Quran recitation and soft instrumental music. In PENYELIDIKAN ISLAM: INTEGRASI ILMU NAQLI DAN AQLI. Penerbit UTHM, UTHM, 2022, p. 39-59. ISBN 978-967-2817-72-7.

160. [3.1] REDWAN, S. – UDDIN, P. – ULHAQ, A. – SHARIF, M.I. Power Spectral Density-Based Resting-State EEG Classification of First-Episode Psychosis. In arXiv 2022, https://doi.org/10.48550/arXiv.2301.01588.

161. [3.1] SRIVASTAVA, S. Classifying REM Sleep Behavior Disorder through CNNs with Image-Based Representations of EEGs. In medRxiv 2022, https://doi.org/10.1101/2022.04.03.22273365.

162. [3.1] WEI, X. – SURJANA, A.I. – SOFFKER, D. Inner speech classification based on electroencephalography (EEG) signals and support vector machine (SVM). In RESEARCH SQUARE, 2022, https://doi.org/10.21203/rs.3.rs-2287259/v1.

163. [3.1] WEON, H. – PARK, P. – KIM, H. – SON, H. A Study on the Influence of Future Journaling on Metacognition, Mental Fitness and Quantitative Electroencephalogram in Elementary and Middle School Students. In JOURNAL OF THE KOREA ACADEMIA-INDUSTRIAL COOPERATION SOCIETY, 2022, vol. 23, no. 9, p. 226-237. https://doi.org/10.5762/KAIS.2022.23.9.226.

164. [3.1] ZAKERIAN, S.A. – KOUHNAVARD, B. Application of Electroencephalography (EEG) in Ergonomics: A systematic review study. In IRANIAN JOURNAL OF ERGONOMICS, 2022, vol. 9, no. 3, p. 1-18. http://journal.iehfs.ir/article-1-833-en.html.

 

  • WIMMER, G. – WITKOVSKÝ, Viktor. Proper rounding of the measurement results under the assumption of uniform distribution. In Measurement Science Review, 2002, vol. 2, p. 1-7. ISSN 1335-8871.

Citácie WOS: 1

1. [1.1] SUPELETO, F.A. – SANTOS, B.F. – AGUIAR, A.P. Revision of Fortipalpa Kasparyan & Ruiz-Cancino, (Ichneumonidae, Cryptinae). In ZOOTAXA. ISSN 1175-5326, DEC 14 2022, vol. 5219, no. 6, p. 501-533; WOS

 

Vedecké práce v zahraničných recenzovaných vedeckých zborníkoch, monografiách

 

  • GRENDÁR, Marián – GRENDÁR, M. What is the question that MaxEnt answers? A probabilistic interpretation. In Bayesian Inference and Maximum Entropy Methods in Science and Engineering : 20th International Workshop. Editor A. Mohammad-Djafari. – Melville : American Institute of Physics, 2001, p. 83-93. ISBN 0-7354-0004-0.

Citácie WOS: 1

1. [1.1] ARAUJO, F.H.V. – DA SILVA, A.F. – RAMOS, R.S. – FERREIRA, S.R. – DOS SANTOS, J.B. – DA SILVA, R.S. – SHABANI, F. Modelling climate suitability for Striga asiatica, a potential invasive weed of cereal crops. In CROP PROTECTION. ISSN 0261-2194, OCT 2022, vol. 160. https://doi.org/10.1016/j.cropro.2022.106050; WOS

 

  • PIGOŠOVÁ, Jana – KILIÁNOVÁ, A. – VOJTEK, P. – KOPČOK, MichalCIGÁŇ, Alexander. Preparation of bismuth-doped yttrium iron garnets and their characterization. In Wave and Quantum Aspects of Contemporary Optics : 15th Czech-Polish-Slovak Conference. Editors M. Miler, D. Senderáková, M. Hrabovský. – Bellingham, Washington : SPIE, 2007, p. M1-M6. ISBN 9780819467485. https://doi.org/10.1117/12.739727

Citácie WOS: 1

1. [1.1] MARTIN, M. – MARTIN, R.C. – ANDREWS, H.B. – ALLMAN, S. – BRICE, D. – MARTIN, S. – ANDRE, N. Quantification of Rare Earth Elements in the Parts Per Million Range: A Novel Approach in the Application of Laser-Induced Breakdown Spectroscopy. In APPLIED SPECTROSCOPY. ISSN 0003-7028, AUG 2022, vol. 76, no. 8, p. 937-945. https://doi.org/10.1177/00037028221092051; WOS

 

  • ROSIPAL, Roman – TREJO, L.J. – MATTHEWS, B. Kernel PLS-SVC for linear and nonlinear classification. In Twentieth International Conference on Machine Learning (ICML-2003). Editors T. Fawcett, N. Mishra. – 2003, p. 640-647. ISBN 0-1-57735-189-4.

Citácie SCOPUS: 1

1. [1.2] OUAARI, S. – TASHU, T.M. – HORVATH, T. Multimodal Feature Extraction for Memes Sentiment Classification. In 2022 IEEE 2ND CONFERENCE ON INFORMATION TECHNOLOGY AND DATA SCIENCE, 2022, p. 285-290. https://doi.org/10.1109/CITDS54976.2022.9914260; SCOPUS

 

  • WITKOVSKÝ, Viktor. On the exact tolerance intervals for univariate normal distribution. In Computer Data Analysis and Modeling (CDAM 2013) : Theoretical and Applied Stochastics. 10th International Conference. Vol. 1. Editors S. Aivazian, P. Filzmoser, Y. Kharin. – Minsk, Belarus : Belarusian State University, 2013, p. 130-137. ISBN 978-985-553-137-2.

Citácie WOS: 1

1. [1.1] TANNER, H.G. – STAGER, A. Data-Driven Abstractions for Robots With Stochastic Dynamics. In IEEE TRANSACTIONS ON ROBOTICS. ISSN 1552-3098.2022, vol. 38, no. 3, p. 1686-1702; WOS

 

  • WITKOVSKÝ, Viktor. Matlab algorithm TDIST: The distribution of a linear combination of Student‘;s t random variables. In COMPSTAT 2004 : Proceedings in Computational Statistics. Ed. Jaromír Antoch. – Physica-Verlag, 2004, p. 1995-2002. ISBN 3-7908-1554-3.

Citácie WOS: 1; iné citácie: 1

1. [1.1] COELHO, C.A. Likelihood Ratio Tests for Elaborate Covariance Structures and for MANOVA Models with Elaborate Covariance Structures-A Review. In JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE. ISSN 0970-4140, 2022; WOS

2. [3.1] BALTAGI, B.H. – BRESSON, G. – CHATURVEDI, A. – LACROIX, G. Robust Dynamic Panel Data Models Using ε-Contamination. In ESSAYS IN HONOR OF M. HASHEM PESARAN, 2022, Vol. 43B, p. 307-336. https://doi.org/10.1108/S0731-90532021000043B013

 

Vedecké  práce  v  domácich   recenzovaných   vedeckých zborníkoch, monografiách

 

  • BUDÁČOVÁ, HanaŠTOLC, Svorad. Comparison of novel methods for correlation dimension estimation. In MEASUREMENT 2013 : 9th International Conference on Measurement. Editors J. Maňka, M. Tyšler, V. Witkovský, I. Frollo. – Bratislava, Slovakia : Institute of Measurement Science, SAS, 2013, p. 27-30. ISBN 978-80-969-672-5-4.

Citácie WOS: 1

1. [1.1] KRAKOVSKA, A. – POCOS, S. – MOJZISOVA, K. – BETKOVA, I. – GUBAS, J.X. State space reconstruction techniques and the accuracy of prediction. In COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION. ISSN 1007-5704, AUG 2022, vol. 111. https://doi.org/10.1016/j.cnsns.2022.106422; WOS

 

  • STRBAK, O. – GOGOLA, DanielFROLLO, Ivan. Cube model approach in simulating of magnetite nanoparticles behaviour in external magnetic fields. In MEASUREMENT 2011 : Proceedings of the 8th International Conference on Measurement. Editors J. Maňka, V. Witkovský, M. Tyšler, I. Frollo. – Bratislava : Institute of Measurement Science SAS, 2011, p. 115-118. ISBN 978-80-969-672-4-7.

Citácie WOS: 1

1. [1.1] MOHAMMADI, S. – RAFII-TABAR, H. – SASANPOUR, P. Contribution of the dipole-dipole interaction to targeting efficiency of magnetite nanoparticles inside the blood vessel: A computational modeling analysis with different magnet geometries. In PHYSICS OF FLUIDS. ISSN 1070-6631, MAR 2022, vol. 34, no. 3. https://doi.org/10.1063/5.0082882; WOS

 

Vedecké práce v zahraničných nerecenzovaných vedeckých zborníkoch, monografiách

 

  • NÖEBAUER-HUHMANN, I.M. – KRAFF, O. – JURÁŠ, VladimírSZOMOLÁNYI, Pavol – MADERWALD, S. – MLYNÁRIK, V. – THYESOHN, J. M. – LADD, S. C. – LADD, M.E. – TRATTNIG, S. MR contrast media at 7 Tesla – preliminary study on relaxivities. In International Society for Magnetic Resonance in Medicine (ISMRM 2008) : 16th Scientific Meeting and Exhibition. – Toronto, Canada, 2008, p. 1457. ISSN 1545-4428.

Citácie WOS: 2

1. [1.1] ANDERSON, V.C. – TAGGE, I.J. – DOUD, A. – LI, X. – SPRINGER, C.S. – QUINN, J.F. – KAYE, J.A. – WILD, K.V. – ROONEY, W.D. DCE-MRI of Brain Fluid Barriers: In Vivo Water Cycling at the Human Choroid Plexus. In TISSUE BARRIERS. ISSN 2168-8370, JAN 2 2022, vol. 10, no. 1. https://doi.org/10.1080/21688370.2021.1963143; WOS

2. [1.1] LIACHENKO, S.M. – SADOVOVA, N.V. – TRIPP, A. – GHORAI, S. – PATRI, A.K. – HANIG, J.P. – COHEN, J.E. – KREFTING, I. Optimization of Detection of Gadodiamide Brain Retention in Rats Using Quantitative T-2 Mapping and Intraperitoneal Administration. In JOURNAL OF MAGNETIC RESONANCE IMAGING. ISSN 1053-1807, NOV 2022, vol. 56, no. 5, p. 1499-1504. https://doi.org/10.1002/jmri.28149; WOS

 

Publikované príspevky na zahraničných vedeckých konferenciách

 

  • KOREČKO, Š. – HUDÁK, M. – SOBOTA, B. – MARKO, M. – CIMROVÁ, B. – FARKAŠ, I. – ROSIPAL, Roman. Assessment and training of visuospatial cognitive functions in virtual reality: Proposal and perspective. In CogInfoCom : 9th IEEE International Conference on Cognitive InfoCommunications. – IEEE, 2018, p. 39-43. ISBN 978-1-5386-7094-1. https://doi.org/10.1109/CogInfoCom.2018.8639958

Citácie WOS: 1

1. [1.1] VARELA-ALDAS, J. – BUELE, J. – AMARIGLIO, R. – GARCIA-MAGARINO, I. – PALACIOS-NAVARRO, G. The cupboard task: An immersive virtual reality-based system for everyday memory assessment. In INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2022, vol. 167, p. ISSN 1071-5819. https://doi.org/10.1016/j.ijhcs.2022.102885; WOS

 

  • PŘIBIL, Jiří – PŘIBILOVÁ, A. – MATOUŠEK, J. GMM-based speaker gender and age classification after voice conversion. In First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016). – Aalborg : IEEE, 2016, p. 89-93. ISBN 978-1-4673-8916-7. https://doi.org/10.1109/SPLIM.2016.7528391

Citácie WOS: 3

1. [1.1] ALKHAMMASH, E.H. – HADJOUNI, M. – ELSHEWEY, A.M. A Hybrid Ensemble Stacking Model for Gender Voice Recognition Approach. In ELECTRONICS. JUN 2022, vol. 11, no. 11. https://doi.org/10.3390/electronics11111750; WOS

2. [1.1] BADR, A.A. – ABDUL-HASSAN, A.K. Speaker gender identification in matched and mismatched conditions based on stacking ensemble method. In JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY. APR 2022, vol. 17, no. 2, p. 1119-1134; WOS

3. [1.1] SHAKIL, S. – ARORA, D. – ZAIDI, T. Feature based classification of voice based biometric data through Machine learning algorithm. In MATERIALS TODAY-PROCEEDINGS. ISSN 2214-7853, 2022, vol. 51, 1, SI, p. 240-247. https://doi.org/10.1016/j.matpr.2021.05.261; WOS

 

  • PŘIBIL, JiříPŘIBILOVÁ, AnnaFROLLO, Ivan. Comparative measurement of the PPG signal on different human body positions by sensors working in reflection and transmission modes. In Engineering Proceedings, 2020, vol. 2, no. 1, p. 69. ISSN 2673-4591. https://doi.org/10.3390/ecsa-7-08204

Citácie WOS: 6; iné citácie: 3

1. [1.1] BURTON, T. – SAIKO, G. – DOUPLIK, A. Towards Development of Specular Reflection Vascular Imaging. In SENSORS. APR 2022, vol. 22, no. 8. https://doi.org/10.3390/s22082830; WOS

2. [1.1] FUADAH, Y.N. – LIM, K.M. Classification of Blood Pressure Levels Based on Photoplethysmogram and Electrocardiogram Signals with a Concatenated Convolutional Neural Network. In DIAGNOSTICS. NOV 2022, vol. 12, no. 11. https://doi.org/10.3390/diagnostics12112886; WOS

3. [1.1] GEORGIEVA-TSANEVA, G. – GOSPODINOVA, E. – CHESHMEDZHIEV, K. Cardiodiagnostics Based on Photoplethysmographic Signals. In DIAGNOSTICS. FEB 2022, vol. 12, no. 2. https://doi.org/10.3390/diagnostics12020412; WOS

4. [1.1] PAEZ-MONTORO, A. – MARCOS-TORERO, J. – MIRANDA-CALERO, J.A. – LOPEZ-ONGIL, C. Towards a Smart Earring for Continuous Heart Rate and Audio Monitoring. In PROCEEDINGS OF THE 37TH CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS 2022). ISSN 2471-6170, 2022, p. 59-64. https://doi.org/10.1109/DCIS55711.2022.9970091; WOS

5. [1.1] POLI, A. – COSOLI, G. – VERDENELLI, L. – SCARDULLA, F. – D’ACQUISTO, L. – SPINSANTE, S. – SCALISE, L. DIY Wrist-Worn Device for Physiological Monitoring: Metrological Evaluation at Different Band Tightening Levels. In IOT TECHNOLOGIES FOR HEALTH CARE, HEALTHYIOT 2021. ISSN 1867-8211, 2022, vol. 432, p. 214-229. https://doi.org/10.1007/978-3-030-99197-5_17; WOS

6. [1.1] YU, S.N. – WANG, S.W. – CHANG, Y.P. Improving Distinguishability of Photoplethysmography in Emotion Recognition Using Deep Convolutional Generative Adversarial Networks. In IEEE ACCESS. ISSN 2169-3536, 2022, vol. 10, p. 119630-119640. https://doi.org/10.1109/ACCESS.2022.3221774; WOS

7. [3.1] ALCHIERI, L. – ABDALAZIM, N. – ALECCI, L. – GASHI, S. – DI LASCIO, E. – SANTINI, S. On the Impact of Lateralization in Physiological Signals from Wearable Sensors. In 2022 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, 2022. https://doi.org/10.1145/3544793.3563427

8. [3.1] GEORGIEVA-TSANEVA, G. – GOSPODINOVA, E. Software system for cardiological data analysis oriented to the training of medical students. In INTED2022 PROCEEDINGS. ISSN 2340-1079, 2022, p. 7441-7449. https://doi.org/10.21125/inted.2022.1879

9. [3.1] PAMUK, Z. – KAYA, C. Detection of Heart Rate Variability from Photoplethysmography (PPG) Signals Obtained by Raspberry Pi Microcomputer. In SAKARYA UNIVERSITY JOURNAL OF COMPUTER AND INFORMATION SCIENCES, 2022, vol. 5, no. 1, p. 104-120. https://doi.org/10.35377/saucis…1024414

 

Dizertačné a habilitačné práce

 

  • ŠUŠMÁKOVÁ, Kristína. Nelineárne a spektrálne charakteristiky spánkového elektroencefalogramu. Kandidátska dizertačná práca. Bratislava, 2009.

Citácie WOS: 1

1. [1.1] NAGWANSHI, K.K. – NOONIA, A. – TIWARI, S. – DOOHAN, N.V. – KUMAWAT, V. – AHANGER, T.A. – AMOATEY, E.T. Wearable Sensors with Internet of Things (IoT) and Vocabulary-Based Acoustic Signal Processing for Monitoring Children’s Health. In COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE. ISSN 1687-5265, APR 28 2022, vol. 2022; WOS

 

Práce zverejnené spôsobom umožňujúcim hromadný prístup

 

  • KRAKOVSKÁ, AnnaJAKUBÍK, JozefBUDÁČOVÁ, HanaHOLECYOVÁ, Mária. Causality studied in reconstructed state space. Examples of uni-directionally connected chaotic systems. In arXiv:1511.00505 [nlin.CD], 2015, p. 1-41.

Citácie WOS: 3; iné citácie: 1

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