TY - JOUR AU - Polcz, Péter AU - Tornai, Kálmán AU - Juhász, János AU - Cserey, György Gábor AU - Surján, György AU - Pándics, Tamás AU - Róka, Eszter AU - Vargha, Márta AU - Reguly, István Zoltán AU - Csikász-Nagy, Attila AU - Pongor, Sándor AU - Szederkényi, Gábor TI - Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants JF - WATER RESEARCH J2 - WATER RES VL - 241 PY - 2023 PG - 18 SN - 0043-1354 DO - 10.1016/j.watres.2023.120098 UR - https://m2.mtmt.hu/api/publication/33864634 ID - 33864634 N1 - National Laboratory for Health Security, Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter utca 85, Budapest, H-1083, Hungary Department of Public Health Laboratory, National Public Health Centre, Albert Flórián út 2-6, Budapest, H-1097, Hungary Institute of Medical Microbiology, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary Department of Digital Health Sciences, Semmelweis University, Üllői út 26, Budapest, H-1085, Hungary Department of Public Health Sciences, Faculty of Health Sciences, Semmelweis University, Vas utca 17, Budapest, H-1088, Hungary Export Date: 28 July 2023 CODEN: WATRA Correspondence Address: Polcz, P.; National Laboratory for Health Security, Práter utca 85, Hungary; email: polcz.peter@itk.ppke.hu LA - English DB - MTMT ER - TY - CONF AU - Kiss, Réka AU - Köves, Áron Boldizsár AU - Pelyva, Dávid László AU - Tasi, József Benedek AU - Földi, Sándor AU - Cserey, György Gábor AU - Koller, Miklós TI - Control design for a soft exoskeleton in simulation and identification of the role of different sensor modalities T2 - NSF DARE Conference: Transformative Opportunities for Modeling in Neurorehabilitation PY - 2023 SP - 1 UR - https://m2.mtmt.hu/api/publication/33692360 ID - 33692360 N1 - https://sites.usc.edu/dare2023/ LA - English DB - MTMT ER - TY - BOOK AU - Keömley-Horváth, Bence AU - Horváth, Gergely AU - Polcz, Péter AU - Siklósi, Bálint AU - Tornai, Kálmán AU - Juhász, János AU - Szederkényi, Gábor AU - Cserey, György Gábor AU - Csikász-Nagy, Attila AU - Reguly, István Zoltán TI - The Design and Utilisation of PanSim, a Portable Pandemic Simulator PB - IEEE CY - Piscataway (NJ) PY - 2022 SP - 1 EP - 9 SP - 9 DO - 10.1109/CIW-IUS56691.2022.00006 UR - https://m2.mtmt.hu/api/publication/33704221 ID - 33704221 LA - English DB - MTMT ER - TY - JOUR AU - Badics, Tamás AU - Hajtó, Dániel AU - Tornai, Kálmán AU - Kiss, Levente AU - Reguly, István Zoltán AU - Pesti, István AU - Sváb, Péter AU - Cserey, György Gábor TI - Integral representation method based efficient rule optimizing framework for anti-money laundering JF - JOURNAL OF MONEY LAUNDERING CONTROL J2 - J MONEY LAUNDER CONT VL - 26 PY - 2022 IS - 2 SP - 290 EP - 308 PG - 19 SN - 1368-5201 DO - 10.1108/JMLC-12-2021-0137 UR - https://m2.mtmt.hu/api/publication/32784092 ID - 32784092 AB - Purpose This paper aims to introduce a framework for optimizing rule-based anti-money laundering systems with a clear economic interpretation, and the authors introduce the integral representation method. Design/methodology/approach By using a microeconomic model, the authors reformulate the threshold optimization problem as a decision problem to gain insights from economics regarding the main properties of the optimum. The authors used algorithmic considerations to find an efficient implementation by using a kind of weak mode estimate of the distribution and the authors extend this approach to classes of alerts or cases. Findings The method provides a new and efficient alternative for the sampling method or the multidimensional optimization technique described in the literature to decrease the bias emanating from multiple alerts by smoothing the number of alerts across classes in the optimum and decrease the overlapping between scenarios at the case level. Using the method for real bank data, the authors were able to decrease the number of false positives cases by about 18% while retaining almost 98% of the true-positive cases. Research limitations/implications The model assumes that alerts from different scenarios are indifferent to the bank. To include scenario-specific preferences or constraints demands further research. Originality/value The new framework presented in the paper is a flexible extension of the usual above-the-line method, which makes it possible to include bank preferences and use the parallelization capabilities of modern processors. LA - English DB - MTMT ER - TY - JOUR AU - Reguly, István Zoltán AU - Csercsik, Dávid AU - Juhász, János AU - Tornai, Kálmán AU - Bujtár, Zsófia AU - Horváth, Gergely AU - Keömley-Horváth, Bence AU - Kós, Tamás AU - Cserey, György Gábor AU - Iván, Kristóf AU - Pongor, Sándor AU - Szederkényi, Gábor AU - Röst, Gergely AU - Csikász-Nagy, Attila TI - Microsimulation based quantitative analysis of COVID-19 management strategies JF - PLOS COMPUTATIONAL BIOLOGY J2 - PLOS COMPUT BIOL VL - 18 PY - 2022 IS - 1 PG - 14 SN - 1553-734X DO - 10.1371/journal.pcbi.1009693 UR - https://m2.mtmt.hu/api/publication/32574366 ID - 32574366 N1 - Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary Cytocast Kft., Vecses, Hungary Institute of Medical Microbiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary Bolyai Institute, University of Szeged, Szeged, Hungary Randall Centre for Cell and Molecular Biophysics, King’s College London, London, United Kingdom Cited By :1 Export Date: 16 June 2022 Correspondence Address: Reguly, I.Z.; Faculty of Information Technology and Bionics, Hungary; email: reguly.istvan.zoltan@itk.ppke.hu Correspondence Address: Csikász-Nagy, A.; Faculty of Information Technology and Bionics, Hungary; email: csikasz-nagy.attila@itk.ppke.hu LA - English DB - MTMT ER - TY - JOUR AU - Ignácz, A. AU - Földi, Sándor AU - Sótonyi, Péter AU - Cserey, György Gábor TI - NB-SQI: A novel non-binary signal quality index for continuous blood pressure waveforms JF - BIOMEDICAL SIGNAL PROCESSING AND CONTROL J2 - BIOMED SIGNAL PROCES VL - 70 PY - 2021 PG - 15 SN - 1746-8094 DO - 10.1016/j.bspc.2021.103035 UR - https://m2.mtmt.hu/api/publication/32179694 ID - 32179694 N1 - Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary Department of Vascular Surgery, Semmelweis University, Budapest, Hungary Export Date: 14 November 2022 Correspondence Address: Földi, S.Práter u. 50/A, Hungary; email: foldi.sandor@itk.ppke.hu AB - Continuous blood pressure monitoring has utmost importance in healthcare, but is usually realised by invasive arterial cannulation. Non-invasive solutions are starting to become a viable option, but these solutions are more sensitive to sensor placement and patient movement. To support these non-invasive monitoring devices, a continuous signal quality feedback would be advantageous. The aim of this study is to define a non-binary signal quality index (NB-SQI) for continuous blood pressure waveforms that can be used for monitoring devices. The definition of this NB-SQI is based on features derived from the continuous waveform of the cardiac cycle and it tests the abnormality of the signal and measures the normalised deviation of its characteristics from an expected value. The method was validated with a dataset of 20 signals, each 10 s long, and labelled by senior specialists in the field of vascular surgery and anesthesiology. The NB-SQI showed a 0.95 correlation with the labels of the validation set. The tendency of the NB-SQI was tested on generated and measured signals corrupted by generated noises on different levels. The results showed that the NB-SQI gives a quantitative estimation in the higher quality range, and recognises the abnormal and noise corrupted segments. The defined NB-SQI can have a significant contribution to the development of non-invasive continuous blood pressure monitors, but it can also be used in signal processing or signal classification for diagnostic purposes. © 2021 The Author(s) LA - English DB - MTMT ER - TY - JOUR AU - Epifanovsky, E AU - Gilbert, ATB AU - Feng, XT AU - Lee, J AU - Mao, YZ AU - Mardirossian, N AU - Pokhilko, P AU - White, AF AU - Coons, MP AU - Dempwolff, AL AU - Gan, ZT AU - Hait, D AU - Horn, PR AU - Jacobson, LD AU - Kaliman, I AU - Kussmann, J AU - Lange, AW AU - Lao, KU AU - Levine, DS AU - Liu, J AU - McKenzie, SC AU - Morrison, AF AU - Nanda, KD AU - Plasser, F AU - Rehn, DR AU - Vidal, ML AU - You, ZQ AU - Zhu, Y AU - Alam, B AU - Albrecht, BJ AU - Aldossary, A AU - Alguire, E AU - Andersen, JH AU - Athavale, V AU - Barton, D AU - Begam, K AU - Behn, A AU - Bellonzi, N AU - Bernard, YA AU - Berquist, EJ AU - Burton, HGA AU - Carreras, A AU - Carter-Fenk, K AU - Chakraborty, R AU - Chien, AD AU - Closser, KD AU - Cofer-Shabica, V AU - Dasgupta, S AU - de, Wergifosse M AU - Deng, J AU - Diedenhofen, M AU - Do, H AU - Ehlert, S AU - Fang, PT AU - Fatehi, S AU - Feng, QG AU - Friedhoff, T AU - Gayvert, J AU - Ge, QH AU - Gidofalvi, G AU - Goldey, M AU - Gomes, J AU - Gonzalez-Espinoza, CE AU - Gulania, S AU - Gunina, AO AU - Hanson-Heine, MWD AU - Harbach, PHP AU - Hauser, A AU - Herbst, MF AU - Vera, MH AU - Hodecker, M AU - Holden, ZC AU - Houck, S AU - Huang, XK AU - Hui, K AU - Huynh, BC AU - Ivanov, M AU - Jasz, A AU - Ji, H AU - Jiang, HJ AU - Kaduk, B AU - Kahler, S AU - Khistyaev, K AU - Kim, J AU - Kis, G AU - Klunzinger, P AU - Koczor-Benda, Z AU - Koh, JH AU - Kosenkov, D AU - Koulias, L AU - Kowalczyk, T AU - Krauter, CM AU - Kue, K AU - Kunitsa, A AU - Kus, T AU - Ladjanszki, I AU - Landau, A AU - Lawler, KV AU - Lefrancois, D AU - Lehtola, S AU - Li, RR AU - Li, YP AU - Liang, JS AU - Liebenthal, M AU - Lin, HH AU - Lin, YS AU - Liu, FL AU - Liu, KY AU - Loipersberger, M AU - Luenser, A AU - Manjanath, A AU - Manohar, P AU - Mansoor, E AU - Manzer, SF AU - Mao, SP AU - Marenich, AV AU - Markovich, T AU - Mason, S AU - Maurer, SA AU - McLaughlin, PF AU - Menger, MFSJ AU - Mewes, JM AU - Mewes, SA AU - Morgante, P AU - Mullinax, JW AU - Oosterbaan, KJ AU - Paran, G AU - Paul, AC AU - Paul, SK AU - Pavosevic, F AU - Pei, Z AU - Prager, S AU - Proynov, EI AU - Rak, A AU - Ramos-Cordoba, E AU - Rana, B AU - Rask, AE AU - Rettig, A AU - Richard, RM AU - Rob, F AU - Rossomme, E AU - Scheele, T AU - Scheurer, M AU - Schneider, M AU - Sergueev, N AU - Sharada, SM AU - Skomorowski, W AU - Small, DW AU - Stein, CJ AU - Su, YC AU - Sundstrom, EJ AU - Tao, Z AU - Thirman, J AU - Tornai, GJ AU - Tsuchimochi, T AU - Tubman, NM AU - Veccham, SP AU - Vydrov, O AU - Wenzel, J AU - Witte, J AU - Yamada, A AU - Yao, K AU - Yeganeh, S AU - Yost, SR AU - Zech, A AU - Zhang, IY AU - Zhang, X AU - Zhang, Y AU - Zuev, D AU - Aspuru-Guzik, A AU - Bell, AT AU - Besley, NA AU - Bravaya, KB AU - Brooks, BR AU - Casanova, D AU - Chai, JD AU - Coriani, S AU - Cramer, CJ AU - Cserey, György Gábor AU - DePrince, AE AU - DiStasio, RA AU - Dreuw, A AU - Dunietz, BD AU - Furlani, TR AU - Goddard, WA AU - Hammes-Schiffer, S AU - Head-Gordon, T AU - Hehre, WJ AU - Hsu, CP AU - Jagau, TC AU - Jung, YS AU - Klamt, A AU - Kong, J AU - Lambrecht, DS AU - Liang, WZ AU - Mayhall, NJ AU - McCurdy, CW AU - Neaton, JB AU - Ochsenfeld, C AU - Parkhill, JA AU - Peverati, R AU - Rassolov, VA AU - Shao, YH AU - Slipchenko, LV AU - Stauch, T AU - Steele, RP AU - Subotnik, JE AU - Thom, AJW AU - Tkatchenko, A AU - Truhlar, DG AU - Van, Voorhis T AU - Wesolowski, TA AU - Whaley, KB AU - Woodcock, HL AU - Zimmerman, PM AU - Faraji, S AU - Gill, PMW AU - Head-Gordon, M AU - Herbert, JM AU - Krylov, AI TI - Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package JF - JOURNAL OF CHEMICAL PHYSICS J2 - J CHEM PHYS VL - 155 PY - 2021 IS - 8 SN - 0021-9606 DO - 10.1063/5.0055522 UR - https://m2.mtmt.hu/api/publication/32175451 ID - 32175451 LA - English DB - MTMT ER - TY - JOUR AU - Aziez, Sameir A. AU - Al Hemeary, Nawar AU - Reja, Ahmed Hameed AU - Zsedrovits, Tamás AU - Cserey, György Gábor TI - Using KNN Algorithm Predictor for Data Synchronization of Ultra-Tight GNSS/INS Integration JF - ELECTRONICS (SWITZ) VL - 10 PY - 2021 IS - 13 SP - 1513 SN - 2079-9292 DO - 10.3390/electronics10131513 UR - https://m2.mtmt.hu/api/publication/32078648 ID - 32078648 AB - The INS system’s update rate is faster than that of the GNSS receiver. Additionally, GNSS receiver data may suffer from blocking for a few seconds for different reasons, affecting architecture integrations between GNSS and INS. This paper proposes a novel GNSS data prediction method using the k nearest neighbor (KNN) predictor algorithm to treat data synchronization between the INS sensors and GNSS receiver and overcome those GNSS receiver’s blocking, which may occur for a few seconds. The experimental work was conducted on a flying drone over a minor Hungarian (Mátyásföld, 47.4992 N, 19.1977 E) model airfield. The GNSS data are predicted by four different scenarios: the first is no blocking of data, and the other three have blocking periods of 1, 4, and 8 s, respectively. Ultra-tight architecture integration is used to perform the GNSS/INS integration to deal with the INS sensors’ inaccuracy and their divergence throughout the operation. The results show that using the GNSS/INS integration system yields better positioning data (in three axes (X, Y, and Z)) than using a stand-alone INS system or GNSS without a predictor. LA - English DB - MTMT ER - TY - JOUR AU - Bors, Luca Anna AU - Bajza, Ágnes AU - Mándoki, Míra AU - Tasi, Benedek József AU - Cserey, György Gábor AU - Imre, Timea AU - Szabó, Pál Tamás AU - Erdő, Franciska TI - Modulation of nose-to-brain delivery of a P-glycoprotein (MDR1) substrate model drug (quinidine) in rats JF - BRAIN RESEARCH BULLETIN J2 - BRAIN RES BULL VL - 160 PY - 2020 SP - 65 EP - 73 PG - 9 SN - 0361-9230 DO - 10.1016/j.brainresbull.2020.04.012 UR - https://m2.mtmt.hu/api/publication/31333738 ID - 31333738 N1 - Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary University of Veterinary Medicine, Department of Pathology, Budapest, Hungary Research Centre for Natural Sciences, Instrumentation Centre, Budapest, Hungary Cited By :2 Export Date: 2 June 2021 CODEN: BRBUD Correspondence Address: Erdő, F.; Pázmány Péter Catholic University, 1083 Budapest, Práter u. 50a, Hungary; email: erdo.franciska@itk.ppke.hu Funding Agency and Grant Number: National Research, Development and Innovation Fund of Hungary; National Bionics Program funding scheme [ED_17-1-2017-0009]; European UnionEuropean Commission [EFOP-3.6.3-VEKOP16-2017-00002] Funding text: This research was funded by the National Research, Development and Innovation Fund of Hungary, financed under the National Bionics Program funding scheme, Project no. ED_17-1-2017-0009 and co-financed by the European Union through grant no. EFOP-3.6.3-VEKOP16-2017-00002. LA - English DB - MTMT ER - TY - JOUR AU - Jász, Ádám AU - Rák, Ádám AU - Ladjánszki, István AU - Tornai, Gábor János AU - Cserey, György Gábor TI - Towards chemically accurate QM/MM simulations on GPUs JF - JOURNAL OF MOLECULAR GRAPHICS AND MODELLING J2 - J MOL GRAPH MODEL VL - 96 PY - 2020 SN - 1093-3263 DO - 10.1016/j.jmgm.2020.107536 UR - https://m2.mtmt.hu/api/publication/31237482 ID - 31237482 LA - English DB - MTMT ER -