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433 results on '"İş, Merih"'

1. Quadruped-Frog: Rapid Online Optimization of Continuous Quadruped Jumping

Author

Bellegarda, Guillaume, Shafiee, Milad, Özberk, Merih Ekin, and Ijspeert, Auke

Subjects
Computer Science - Robotics
Abstract

Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e. the behavior is designed for before it is needed), either through model-based trajectory optimization, or through deep learning-based methods involving millions of timesteps of simulation interactions. Notably, such offline-designed locomotion controllers cannot perfectly model the true dynamics of the system, such as the motor dynamics. In contrast, in this paper, we consider a quadruped jumping task that we rapidly optimize online. We design foot force profiles parameterized by only a few parameters which we optimize for directly on hardware with Bayesian Optimization. The force profiles are tracked at the joint level, and added to Cartesian PD impedance control and Virtual Model Control to stabilize the jumping motions. After optimization, which takes only a handful of jumps, we show that this control architecture is capable of diverse and omnidirectional jumps including forward, lateral, and twist (turning) jumps, even on uneven terrain, enabling the Unitree Go1 quadruped to jump 0.5 m high, 0.5 m forward, and jump-turn over 2 rad. Video results can be found at https://youtu.be/SvfVNQ90k_w., Comment: Accepted for 2024 IEEE International Conference on Robotics and Automation (ICRA)

Published
2024

2. Discovering High-Quality Process Models Despite Data Scarcity

Author

Adams, Jan Niklas, Peeperkorn, Jari, Brockhoff, Tobias, Terrier, Isabelle, Göhner, Heiko, Uysal, Merih Seran, Broucke, Seppe vanden, De Weerdt, Jochen, and van der Aalst, Wil M. P.

Subjects
Computer Science - Databases
Abstract

Process discovery algorithms learn process models from executed activity sequences, describing concurrency, causality, and conflict. Concurrent activities require observing multiple permutations, increasing data requirements, especially for processes with concurrent subprocesses such as hierarchical, composite, or distributed processes. While process discovery algorithms traditionally use sequences of activities as input, recently introduced object-centric process discovery algorithms can use graphs of activities as input, encoding partial orders between activities. As such, they contain the concurrency information of many sequences in a single graph. In this paper, we address the research question of reducing process discovery data requirements when using object-centric event logs for process discovery. We classify different real-life processes according to the control-flow complexity within and between subprocesses and introduce an evaluation framework to assess process discovery algorithm quality of traditional and object-centric process discovery based on the sample size. We complement this with a large-scale production process case study. Our results show reduced data requirements, enabling the discovery of large, concurrent processes such as manufacturing with little data, previously infeasible with traditional process discovery. Our findings suggest that object-centric process mining could revolutionize process discovery in various sectors, including manufacturing and supply chains.

Published
2023

4. Resolving Uncertain Case Identifiers in Interaction Logs: A User Study

Author

Pegoraro, Marco, Uysal, Merih Seran, Hülsmann, Tom-Hendrik, and van der Aalst, Wil M. P.

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence
Abstract

Modern software systems are able to record vast amounts of user actions, stored for later analysis. One of the main types of such user interaction data is click data: the digital trace of the actions of a user through the graphical elements of an application, website or software. While readily available, click data is often missing a case notion: an attribute linking events from user interactions to a specific process instance in the software. In this paper, we propose a neural network-based technique to determine a case notion for click data, thus enabling process mining and other process analysis techniques on user interaction data. We describe our method, show its scalability to datasets of large dimensions, and we validate its efficacy through a user study based on the segmented event log resulting from interaction data of a mobility sharing company. Interviews with domain experts in the company demonstrate that the case notion obtained by our method can lead to actionable process insights., Comment: 36 pages, 17 figures, 1 table, 45 references. arXiv admin note: substantial text overlap with arXiv:2204.04164

Published
2022

5. Process Comparison Using Petri Net Decomposition

Author

Brockhoff, Tobias, Gose, Moritz Nicolas, Uysal, Merih Seran, van der Aalst, Wil M. P., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Kristensen, Lars Michael, editor, and van der Werf, Jan Martijn, editor

Published
2024
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6. Process Comparison Based on Selection-Projection Structures

Author

Brockhoff, Tobias, Uysal, Merih Seran, van der Aalst, Wil M. P., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Guizzardi, Giancarlo, editor, Santoro, Flavia, editor, Mouratidis, Haralambos, editor, and Soffer, Pnina, editor

Published
2024
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8. Actionable Artificial Intelligence for the Future of Production

Author

Behery, Mohamed, Brauner, Philipp, Zhou, Hans Aoyang, Uysal, Merih Seran, Samsonov, Vladimir, Bellgardt, Martin, Brillowski, Florian, Brockhoff, Tobias, Ghahfarokhi, Anahita Farhang, Gleim, Lars, Gorißen, Leon, Grochowski, Marco, Henn, Thomas, Iacomini, Elisa, Kaster, Thomas, Koren, István, Liebenberg, Martin, Reinsch, Leon, Tirpitz, Liam, Trinh, Minh, Posada-Moreno, Andres Felipe, Liehner, Luca, Schemmer, Thomas, Vervier, Luisa, Völker, Marcus, Walderich, Philipp, Zhang, Song, Brecher, Christian, Schmitt, Robert H., Decker, Stefan, Gries, Thomas, Häfner, Constantin Leon, Herty, Michael, Jarke, Matthias, Kowalewski, Stefan, Kuhlen, Torsten W., Schleifenbaum, Johannes Henrich, Trimpe, Sebastian, Aalst, Wil van der, Ziefle, Martina, Lakemeyer, Gerhard, Padberg, Melanie, Series editor, Brecher, Christian, Series Editor, Padberg, Melanie, Series Editor, Schuh, Günther, editor, van der Aalst, Wil, editor, Jarke, Matthias, editor, and Piller, Frank T., editor

Published
2024
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9. Internet of Medical Things (IoMT): An Overview and Applications

Author

Doğan Merih, Yeliz, Aktan, Mehmet Emin, Akdoğan, Erhan, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Şen, Zekâi, editor, Uygun, Özer, editor, and Erden, Caner, editor

Published
2024
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17. Uncertain Case Identifiers in Process Mining: A User Study of the Event-Case Correlation Problem on Click Data

Author

Pegoraro, Marco, Uysal, Merih Seran, Hülsmann, Tom-Hendrik, and van der Aalst, Wil M. P.

Subjects
Computer Science - Databases, Computer Science - Artificial Intelligence
Abstract

Among the many sources of event data available today, a prominent one is user interaction data. User activity may be recorded during the use of an application or website, resulting in a type of user interaction data often called click data. An obstacle to the analysis of click data using process mining is the lack of a case identifier in the data. In this paper, we show a case and user study for event-case correlation on click data, in the context of user interaction events from a mobility sharing company. To reconstruct the case notion of the process, we apply a novel method to aggregate user interaction data in separate user sessions-interpreted as cases-based on neural networks. To validate our findings, we qualitatively discuss the impact of process mining analyses on the resulting well-formed event log through interviews with process experts., Comment: 15 pages, 10 figures, 1 table, 18 references

Published
2022

18. An XES Extension for Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Databases
Abstract

Event data, often stored in the form of event logs, serve as the starting point for process mining and other evidence-based process improvements. However, event data in logs are often tainted by noise, errors, and missing data. Recently, a novel body of research has emerged, with the aim to address and analyze a class of anomalies known as uncertainty-imprecisions quantified with meta-information in the event log. This paper illustrates an extension of the XES data standard capable of representing uncertain event data. Such an extension enables input, output, and manipulation of uncertain data, as well as analysis through the process discovery and conformance checking approaches available in literature., Comment: 9 pages, 1 figure, 3 tables, 11 references

Published
2022

19. Association of BMI, lipid-lowering medication, and age with prevalence of type 2 diabetes in adults with heterozygous familial hypercholesterolaemia: a worldwide cross-sectional study

Author

Elshorbagy, Amany, Lyons, Alexander R.M., Vallejo-Vaz, Antonio J., Stevens, Christophe A.T., Dharmayat, Kanika I., Brandts, Julia, Catapano, Alberico L., Freiberger, Tomas, Hovingh, G. Kees, Mata, Pedro, Raal, Frederick J., Santos, Raul D., Soran, Handrean, Watts, Gerald F., Abifadel, Marianne, Aguilar-Salinas, Carlos A., Alhabib, Khalid F., Alkhnifsawi, Mutaz, Almahmeed, Wael, Alonso, Rodrigo, Al-Rasadi, Khalid, Al-Sarraf, Ahmad, Ashavaid, Tester F., Banach, Maciej, Binder, Christoph J., Bourbon, Mafalda, Brunham, Liam R., Chlebus, Krzysztof, Corral, Pablo, Cruz, Diogo, Davletov, Kairat, Descamps, Olivier S., Ezhov, Marat, Gaita, Dan, Groselj, Urh, Harada-Shiba, Mariko, Holven, Kirsten B., Kayikcioglu, Meral, Khovidhunkit, Weerapan, Lalic, Katarina, Latkovskis, Gustavs, Laufs, Ulrich, Liberopoulos, Evangelos, Lima-Martinez, Marcos M., Lin, Jie, Maher, Vincent, Marais, A. David, März, Winfried, Mirrakhimov, Erkin, Miserez, André R., Mitchenko, Olena, Nawawi, Hapizah, Nordestgaard, Børge G., Panayiotou, Andrie G., Paragh, György, Petrulioniene, Zaneta, Pojskic, Belma, Postadzhiyan, Arman, Reda, Ashraf, Reiner, Željko, Reyes, Ximena, Sadiq, Fouzia, Sadoh, Wilson E., Schunkert, Heribert, Shek, Aleksandr B., Stroes, Erik, Su, Ta-Chen, Subramaniam, Tavintharan, Susekov, Andrey V., Tilney, Myra, Tomlinson, Brian, Truong, Thanh-Huong, Tselepis, Alexandros D., Tybjærg-Hansen, Anne, Vázquez, Alejandra C., Viigimaa, Margus, Vohnout, Branislav, Wang, Luya, Yamashita, Shizuya, Arca, Marcello, Averna, Maurizio, Schreier, Laura, Pang, Jing, Ebenbichler, Christoph, Dieplinger, Hans, Innerhofer, Reinhold, Winhofer-Stöckl, Yvonne, Greber-Platzer, Susanne, Krychtiuk, Konstantin, Speidl, Walter, Toplak, Hermann, Widhalm, Kurt, Stulnig, Thomas, Huber, Kurt, Höllerl, Florian, Rega-Kaun, Gersina, Kleemann, Lucas, Mäser, Martin, Scholl-Bürgi, Sabine, Säly, Christoph, Mayer, Florian J., Sperone, Alexandra, Tanghe, Chloé, Gérard, Anne-Catherine, Pojskic, Lamija, Sisic, Ibrahim, Durak Nalbantic, Azra, Ejubovic, Malik, Jannes, Cinthia E., Pereira, Alexandre C., Krieger, Jose E., Petrov, Ivo, Goudev, Assen, Nikolov, Fedya, Tisheva, Snejana, Yotov, Yoto, Tzvetkov, Ivajlo, Baass, Alexis, Bergeron, Jean, Bernard, Sophie, Brisson, Diane, Cermakova, Lubomira, Couture, Patrick, Francis, Gordon A., Gaudet, Daniel, Hegele, Robert A., Khoury, Etienne, Mancini, G.B. John, McCrindle, Brian W., Paquette, Martine, Ruel, Isabelle, Iatan, Iulia, Cuevas, Ada, Wang, Xumin, Meng, Kang, Song, Xiantao, Yong, Qiang, Jiang, Tao, Liu, Ziyou, Duan, Yanyu, Hong, Jing, Ye, Pucong, Chen, Yan, Qi, Jianguang, Liu, Zesen, Li, Yuntao, Zhang, Chaoyi, Peng, Jie, Yang, Ya, Yu, Wei, Wang, Qian, Yuan, Hui, Cheng, Shitong, Jiang, Long, Chong, Mei, Jiao, Jian, Wu, Yue, Wen, Wenhui, Xu, Liyuan, Zhang, Ruiying, Qu, Yichen, He, Jianxun, Fan, Xuesong, Wang, Zhenjia, Chow, Elaine, Pećin, Ivan, Perica, Dražen, Symeonides, Phivos, Vrablik, Michal, Ceska, Richard, Soska, Vladimir, Tichy, Lukas, Adamkova, Vera, Franekova, Jana, Cifkova, Renata, Kraml, Pavel, Vonaskova, Katerina, Cepova, Jana, Dusejovska, Magdalena, Pavlickova, Lenka, Blaha, Vladimir, Rosolova, Hana, Nussbaumerova, Barbora, Cibulka, Roman, Vaverkova, Helena, Cibickova, Lubica, Krejsova, Zdenka, Rehouskova, Katerina, Malina, Pavel, Budikova, Milena, Palanova, Vaclava, Solcova, Lucie, Lubasova, Alena, Podzimkova, Helena, Bujdak, Juraj, Vesely, Jiri, Jordanova, Marta, Salek, Tomas, Urbanek, Robin, Zemek, Stanislav, Lacko, Jan, Halamkova, Hana, Machacova, Sona, Mala, Sarka, Cubova, Eva, Valoskova, Katerina, Burda, Lukas, Benn, Marianne, Bendary, Ahmed, Daoud, Ihab, Emil, Sameh, Elbahry, Atef, Rafla, Samir, Sanad, Osama, Kazamel, Ghada, Ashraf, Dr Mohamed, Sobhy, Mohamed, El-Hadidy, Amro, Shafy, Mohamed Abdoul, Kamal, Saif, Bendary, Mohamed, Talviste, Grete, Christmann, Jutta, Dressel, Alexander, Fath, Felix, Ferraro, Chiara, Frenzke, Lydia, Gopon, Alica, Klein, Isabel, Pienkowska, Dominika, Sietmann, Tobias, Sonntag, Antonia, Adjan, Omar, Bahrmann, Philipp, Baessler, Andrea, Barkowski, Rasmus, Beckerdjian, Raffi, Berr, Christina, Birkenfeld, Andreas, Böll, Gereon, Carstensen, Avisha, Demuth, Ilya, Finkernagel, Holger, Gouni-Berthold, Ioanna, Hahmann, Harry, Hamerle, Michael, Halder, Julian, Heide, Maria, Julius, Ulrich, Kassner, Ursula, Katzmann, Julius L, Kirschbaum, Anja, Klose, Gerald, Könemann, Stephanie, König, Christel, König, Wolfgang, Krämer, Bernhard, Kuprat, Gerrit, Koschker, Ann-Cathrin, Kilic, Özlem, Lindenmeier, Gerd, Van de Loo, Iris, Lorenz, Babette, Lorenz, Elke, Löhr, Birgit, McChord, Johanna, Maslarska, Mariya, Methe, Heiko, Merkel, Martin, Moussaoui, Zineb, Müller-Kozarez, Irina, Olivier, Christoph B, Ong, Peter, Otte, Britta, Parhofer, Klaus, Partsch, Carl-Joachim, Paulus, Michael, Pehlivanli, Sinan, Pflederer, Tobias, Pusl, Thomas, Richter, Veronika, Rosner, Stefanie, Sanin, Veronika, Schäfer, Sebastian, Schäfer, Christoph, Schatz, Ulrike, Schirmer, Stephan, Schmidt, Christine, Seeger, Wolfgang, Sisovic, Snezna, Spens, Antje, Jablonski, Ksenija Stach, Stadelmann, Alexander, Steinhagen-Thiessen, Elisabeth, Stürzebecher, Paulina, Tafelmeier, Maria, Tillack, Dörthe, Tselmin, Sergey, Tünnemann-Tarr, Adrienn, Vogt, Anja, Beckerath, Jens von, Wilke, Andreas, Wolf, Ulrich, Zemmrich, Claudia, Rizos, Christos V., Skoumas, Ioannis, Tziomalos, Konstantinos, Rallidis, Loukianos, Kotsis, Vasileios, Doumas, Michalis, Athyros, Vasileios, Skalidis, Emmanouil, Kolovou, Genovefa, Kolovou, Vana, Garoufi, Anastasia, Bilianou, Eleni, Koutagiar, Iosif, Kiouri, Estela, Antza, Christina, Zacharis, Evangelos, Attilakos, Achilleas, Sfikas, George, Koumaras, Charalambos, Anagnostis, Panagiotis, Anastasiou, Georgia, Liamis, George, Koutsogianni, Amalia-Despoina, Petkou, Ermioni, Milionis, Haralambos, Koulouri, Anastasia, Prodromiadou, Elisavet, Karányi, Zsolt, Harangi, Mariann, Bajnok, László, Audikovszky, Mária, Márk, László, Benczúr, Béla, Reiber, István, Nagy, Gergely, Nagy, András, Reddy, Lakshmi Lavanya, Shah, Swarup A. V, Ponde, Chandrashekhar K., Dalal, Jamshed J., Sawhney, Jitendra P.S., Verma, Ishwar C., Altaey, Mays, Al-Jumaily, Khalid, Rasul, Dilshad, Abdalsahib, Ali Fawzi, Jabbar, Amer Abdl, Al-ageedi, Mohanad, Dhamin, Mohammed, AlFil, Sarmad, Khadhim, Foad, Miahy, Sabah, Agar, Ruth, Catapano, Alberico Luigi, Calandra, Sebastiano, Tarugi, Patrizia, Casula, Manuela, Galimberti, Federica, Olmastroni, Elena, Sarzani, Riccardo, Ferri, Claudio, Repetti, Elena, Piro, Salvatore, Suppressa, Patrizia, Meregalli, Giancarla, Borghi, Claudio, Muntoni, Sandro, Calabrò, Paolo, Cipollone, Francesco, Purrello, Francesco, Pujia, Arturo, Passaro, Angelina, Marcucci, Rossella, Pecchioli, Valerio, Pisciotta, Livia, Mandraffino, Giuseppe, Pellegatta, Fabio, Mombelli, Giuliana, Branchi, Adriana, Fiorenza, Anna Maria, Pederiva, Cristina, Werba, Josè Pablo, Parati, Gianfranco, Carubbi, Francesca, Iughetti, Lorenzo, Fortunato, Giuliana, Iannuzzi, Arcangelo, Iannuzzo, Gabriella, Cefalù, Angelo Baldassare, Biasucci, Giacomo, Zambon, Sabina, Pirro, Matteo, Sbrana, Francesco, Trenti, Chiara, D'Erasmo, Laura, Federici, Massimo, Ben, Maria Del, Bartuli, Andrea, Giaccari, Andrea, Pipolo, Antonio, Citroni, Nadia, Guardamagna, Ornella, Lia, Salvatore, Benso, Andrea, Biolo, Gianni, Maroni, Lorenzo, Lupi, Alessandro, Bonanni, Luca, Rinaldi, Elisabetta, Zenti, Maria Grazia, Matsuki, Kota, Hori, Mika, Ogura, Masatsune, Masuda, Daisaku, Kobayashi, Takuya, Nagahama, Kumiko, Al-Jarallah, Mohammed, Radovic, Mirjana, Lunegova, Olga, Bektasheva, Erkayim, Abilova, Saamay, Erglis, Andrejs, Gilis, Dainus, Nesterovics, Georgijs, Saripo, Vita, Meiere, Ruta, Skudrina, Gunda, Terauda, Elizabete, Jambart, Selim, Ayoub, Carine, Ghaleb, Youmna, Aliosaitiene, Urte, Kutkiene, Sandra, Abdul Kadir, Siti Hamimah Sheikh, Kasim, Noor Alicezah Mohd, Nor, Noor Shafina Mohd, Abdul Hamid, Hasidah, Abdul Razak, Suraya, Al-Khateeb, Alyaa, Abd Muid, Suhaila, Abdul Rahman, Thuhairah, Kasim, Sazzli Shahlan, Radzi, Ahmad Bakhtiar Md, Ibrahim, Khairul Shafiq, Rosli, Marshima Mohd, Razali, Rafezah, Chua, Yung An, Razman, Aimi Zafira, Nazli, Sukma Azureen, Aziz, Nazirul, Rosman, Azhari, Abdul Murad, NorAzian, Jalaludin, Mohd Amin, Abdul Latif, Ahmad Zubaidi, Azzopardi, C., Mehta, Roopa, Martagon, Alexandro J., Ramirez, Gabriela A. Galan, Villa, Neftali E Antonio, Vazquez, Arsenio Vargas, Elias-Lopez, Daniel, Retana, Gustavo Gonzalez, Rodriguez, Betsabel, Macías, Jose J. Ceballos, Zazueta, Alejandro Romero, Alvarado, Rocio Martinez, Portano, Julieta D. Morales, Lopez, Humberto Alvares, Sauque-Reyna, Leobardo, Herrera, Laura G. Gomez, Mendia, Luis E. Simental, Aguilar, Humberto Garcia, Cooremans, Elizabeth Ramirez, Aparicio, Berenice Peña, Zubieta, Victoria Mendoza, Gonzalez, Perla A. Carrillo, Ferreira-Hermosillo, Aldo, Portilla, Nacu Caracas, Dominguez, Guadalupe Jimenez, Garcia, Alinna Y. Ruiz, Cazares, Hector E. Arriaga, Gonzalez, Jesus R., Valencia, Carla V. Mendez, Padilla, Francisco G., Prado, Ramon Madriz, Ibarra, Manuel O. De los Rios, Villicaña, Ruy D. Arjona, Rivera, Karina J. Acevedo, Carrera, Ricardo Allende, Alvarez, Jose A., Martinez, Jose C. Amezcua, Bustillo, Manuel de los Reyes Barrera, Vargas, Gonzalo Carazo, Chacon, Roberto Contreras, Andrade, Mario H. Figueroa, Ortega, Ashanty Flores, Alcala, Hector Garcia, de Leon, Laura E. Garcia, Guzman, Berenice Garcia, Garcia, Jose J. Garduño, Cuellar, Juan C. Garnica, Cruz, Jose R. Gomez, Garcia, Anell Hernandez, Almada, Jesus R. Holguin, Herrera, Ursulo Juarez, Sobrevilla, Fabiola Lugo, Rodriguez, Eduardo Marquez, Sibaja, Cristina Martinez, Rodriguez, Alma B. Medrano, Oyervides, Jose C. Morales, Vazquez, Daniel I. Perez, Rodriguez, Eduardo A. Reyes, Osorio, Ma. Ludivina Robles, Saucedo, Juan Rosas, Tamayo, Margarita Torres, Talavera, Luis A. Valdez, Arroyo, Luis E. Vera, Carrillo, Eloy A. Zepeda, Stroes, Erik S, Defesche, J, Zuurbier, L, Reeskamp, L, Ibrahim, S, Roeters van Lennep, Jeanine, Wiegman, Albert, Isara, Alphonsus, Obaseki, Darlington E., Al-Waili, Khalid, Al-Zadjali, Fahad, Al-Zakwani, Ibrahim, Al-Kindi, Mohammed, Al-Mukhaini, Suad, Al-Barwani, Hamida, Rana, Asim, Shah, Lahore Saeed Ullah, Al-Nouri, Fahad, Starostecka, Ewa, Konopka, Agnieszka, Bielecka-Dabrowa, Agata, Lewek, Joanna, Sosnowska, Bozena, Gąsior, Mariusz, Dyrbuś, Krzysztof, Jóźwiak, Jacek, Pajkowski, Marcin, Romanowska-Kocejko, Marzena, Żarczyńska-Buchowiecka, Marta, Chmara, Magdalena, Wasąg, Bartosz, Stróżyk, Aneta, Michalska-Grzonkowska, Aleksandra, Medeiros, Ana Margarida, Alves, Ana Catarina, Silva, Francisco, Lobarinhas, Goreti, Palma, Isabel, de Moura, Jose Pereira, Rico, Miguel Toscano, Rato, Quitéria, Pais, Patrícia, Correia, Susana, Moldovan, Oana, Virtuoso, Maria João, Araujo, Francisco, Salgado, Jose Miguel, Colaço, Ines, Dumitrescu, Andreea, Lengher, Calin, Mosteoru, Svetlana, Meshkov, Alexey, Ershova, Alexandra, Rozhkova, Tatiana, Korneva, Victoria, Yu, Kuznetsova T., Zafiraki, Vitaliy, Voevoda, Mikhail, Gurevich, Victor, Duplyakov, Dmitry, Ragino, Yulia, Chubykina, Uliana, Shaposhnik, Igor, Alkaf, Fahmi, Khudari, Alia, Rwaili, Nawal, Al-Allaf, Faisal, Alghamdi, Mohammad, Batais, Mohammed A, Almigbal, Turky H, Kinsara, Abdulhalim, AlQudaimi, Ashraf Hammouda Ahmed, Awan, Zuhier, Elamin, Omer A, Altaradi, Hani, Popovic, Ljiljana, Singh, Sandra, Rasulic, Iva, Petakov, Ana, Lalic, Nebojsa M., Lam, Carolyn, Le, Tan Ju, Siang, Eric Lim Tien, Dissanayake, Sanjaya, I-Shing, Justin Tang, Shyong, Tai E, Jin, Terrance Chua Siang, Ting, Sharon Pek Li, Ming, Jeremy Hoe Kian, Drum, Chester Lee, Nastar, Fathima Ashna, Jia, Loh Wann, Ya, Natalie Koh Si, Jie, Marvin Chua Wei, Dalan, Rinkoo, Wei, Yong Quek, sian, Tiong Yee, Keong, Yeo Khung, Rong, Siau Kai, Jin, Darren Seah Ee, Ming, Ian Koh Jan, Chang, Tan Hong, Peng, Fabian Yap Kok, Vasanwala, Rashida Farhad, Raslova, Katarina, Balinth, Karin, Buganova, Ingrid, Fabryova, Lubomira, Kadurova, Michaela, Klabnik, Alexander, Kozárová, Miriam, Sirotiakova, Jana, Battelino, Tadej, Cevc, Matija, Debeljak, Marusa, Torkar, Ana Drole, Fras, Zlatko, Jug, Borut, Cugalj, Barbara Kern, Kovac, Jernej, Mlinaric, Matej, Sikonja, Jaka, Pilcher, Gillian Joan, Blom, D J, Wolmarans, K H, Brice, B C, Muñiz-Grijalvo, Ovidio, Díaz-Díaz, Jose Luis, de Isla, Leopoldo Pérez, Fuentes, Francisco, Badimon, Lina, Martin, François, Miserez, Eleonore B., Shipton, Janine L., Ganokroj, Poranee, Chattranukulchai, Pairoj, Jiamjarasrungsi, Wiroj, Thongtang, Nuntakorn, Krittayaphong, Rungroj, Vathesatogkit, Prin, Sriphrapradang, Chutintorn, Phimphilai, Mattabhorn, Leelawattana, Rattana, Anthanont, Pimjai, Suraamornkul, Swangjit, Deerochanawong, Chaicharn, Senthong, Vichai, Torpongpun, Artit, Suteerayongprasert, Panuwat, Pengpong, Nawarat, Sathavarodom, Nattapol, Sunanta, Usanee, Porntharukchareon, Thachanun, Kiatpanabhikul, Phatharaporn, Kaewkrasaesin, Chatchon, Kongkit, Jaruwan, Umphonsathien, Mongkontida, Akbulut, Mehmet, Alici, Gökhan, Bayram, Fahri, Can, Levent Hürkan, Celik, Ahmet, Ceyhan, Ceyhun, Coskun, Fatma Yilmaz, Demir, Mesut, Demircan, Sabri, Dogan, Volkan, Durakoglugil, Emre, Dural, İbrahim Etem, Gedikli, Omer, Hacioglu, Aysa, Ildizli, Muge, Kilic, Salih, Kirilmaz, Bahadir, Kutlu, Merih, Oguz, Aytekin, Ozdogan, Oner, Onrat, Ersel, Ozer, Savas, Sabuncu, Tevfik, Sahin, Tayfun, Sivri, Fatih, Sonmez, Alper, Temizhan, Ahmet, Topcu, Selim, Tokgozoglu, Lale, Tuncez, Abdullah, Vural, Mirac, Yenercag, Mustafa, Yesilbursa, Dilek, Yigit, Zerrin, Yildirim, Aytul Belgi, Yildirir, Aylin, Yilmaz, Mehmet Birhan, Atallah, Bassam, Traina, Mahmoud, Sabbour, Hani, Abdul Hay, Dana, Luqman, Neama, Elfatih, Abubaker, Abdulrasheed, Arshad, Manla, Yosef, Kwok, See, DellOca, Nicolas, Alieva, Rano B., Fozilov, Khurshid G., Hoshimov, Shavkat U., Nizamov, Ulugbek I., Kan, Liliya E., Kim, Andrey R., Abdullaeva, Guzal J., Abdullaev, Alisher A., Do, Doan Loi, Nguyen, Mai Ngoc Thi, Kim, Ngoc Thanh, Le, Thanh Tung, Le, Hong An, and Ray, Kausik K.

Published
2024
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25. Probability Estimation of Uncertain Process Trace Realizations

Author

Pegoraro, Marco, Bakullari, Bianka, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Artificial Intelligence
Abstract

Process mining is a scientific discipline that analyzes event data, often collected in databases called event logs. Recently, uncertain event logs have become of interest, which contain non-deterministic and stochastic event attributes that may represent many possible real-life scenarios. In this paper, we present a method to reliably estimate the probability of each of such scenarios, allowing their analysis. Experiments show that the probabilities calculated with our method closely match the true chances of occurrence of specific outcomes, enabling more trustworthy analyses on uncertain data., Comment: 12 pages, 7 figures, 4 tables, 11 references

Published
2021
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26. Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)

Author

van der Aalst, Wil, Brockhoff, Tobias, Ghahfarokhi, Anahita Farhang, Pourbafrani, Mahsa, Uysal, Merih Seran, and van Zelst, Sebastiaan

Subjects
Computer Science - Databases, Computer Science - Machine Learning, D.4.1, D.2.2, D.2.12, H.2
Abstract

Operational processes in production, logistics, material handling, maintenance, etc., are supported by cyber-physical systems combining hardware and software components. As a result, the digital and the physical world are closely aligned, and it is possible to track operational processes in detail (e.g., using sensors). The abundance of event data generated by today's operational processes provides opportunities and challenges for process mining techniques supporting process discovery, performance analysis, and conformance checking. Using existing process mining tools, it is already possible to automatically discover process models and uncover performance and compliance problems. In the DFG-funded Cluster of Excellence "Internet of Production" (IoP), process mining is used to create "digital shadows" to improve a wide variety of operational processes. However, operational processes are dynamic, distributed, and complex. Driven by the challenges identified in the IoP cluster, we work on novel techniques for comparative process mining (comparing process variants for different products at different locations at different times), object-centric process mining (to handle processes involving different types of objects that interact), and forward-looking process mining (to explore "What if?" questions). By addressing these challenges, we aim to develop valuable "digital shadows" that can be used to remove operational friction., Comment: 30 pages, 21 figures

Published
2021

27. Text-Aware Predictive Monitoring of Business Processes

Author

Pegoraro, Marco, Uysal, Merih Seran, Georgi, David Benedikt, and van der Aalst, Wil M. P.

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The real-time prediction of business processes using historical event data is an important capability of modern business process monitoring systems. Existing process prediction methods are able to also exploit the data perspective of recorded events, in addition to the control-flow perspective. However, while well-structured numerical or categorical attributes are considered in many prediction techniques, almost no technique is able to utilize text documents written in natural language, which can hold information critical to the prediction task. In this paper, we illustrate the design, implementation, and evaluation of a novel text-aware process prediction model based on Long Short-Term Memory (LSTM) neural networks and natural language models. The proposed model can take categorical, numerical and textual attributes in event data into account to predict the activity and timestamp of the next event, the outcome, and the cycle time of a running process instance. Experiments show that the text-aware model is able to outperform state-of-the-art process prediction methods on simulated and real-world event logs containing textual data., Comment: 14 pages, 4 figures, 5 tables, 16 references

Published
2021
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28. PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Artificial Intelligence
Abstract

The discipline of process mining aims to study processes in a data-driven manner by analyzing historical process executions, often employing Petri nets. Event data, extracted from information systems (e.g. SAP), serve as the starting point for process mining. Recently, novel types of event data have gathered interest among the process mining community, including uncertain event data. Uncertain events, process traces and logs contain attributes that are characterized by quantified imprecisions, e.g., a set of possible attribute values. The PROVED tool helps to explore, navigate and analyze such uncertain event data by abstracting the uncertain information using behavior graphs and nets, which have Petri nets semantics. Based on these constructs, the tool enables discovery and conformance checking., Comment: 11 pages, 6 figures, 1 table, 16 references

Published
2021
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32. Efficient Time and Space Representation of Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Data Structures and Algorithms
Abstract

Process mining is a discipline which concerns the analysis of execution data of operational processes, the extraction of models from event data, the measurement of the conformance between event data and normative models, and the enhancement of all aspects of processes. Most approaches assume that event data is accurately capture behavior. However, this is not realistic in many applications: data can contain uncertainty, generated from errors in recording, imprecise measurements, and other factors. Recently, new methods have been developed to analyze event data containing uncertainty; these techniques prominently rely on representing uncertain event data by means of graph-based models explicitly capturing uncertainty. In this paper, we introduce a new approach to efficiently calculate a graph representation of the behavior contained in an uncertain process trace. We present our novel algorithm, prove its asymptotic time complexity, and show experimental results that highlight order-of-magnitude performance improvements for the behavior graph construction., Comment: 34 pages, 16 figures, 5 tables. arXiv admin note: text overlap with arXiv:2002.08225

Published
2020
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33. Conformance Checking over Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Artificial Intelligence
Abstract

The strong impulse to digitize processes and operations in companies and enterprises have resulted in the creation and automatic recording of an increasingly large amount of process data in information systems. These are made available in the form of event logs. Process mining techniques enable the process-centric analysis of data, including automatically discovering process models and checking if event data conform to a given model. In this paper, we analyze the previously unexplored setting of uncertain event logs. In such event logs uncertainty is recorded explicitly, i.e., the time, activity and case of an event may be unclear or imprecise. In this work, we define a taxonomy of uncertain event logs and models, and we examine the challenges that uncertainty poses on process discovery and conformance checking. Finally, we show how upper and lower bounds for conformance can be obtained by aligning an uncertain trace onto a regular process model., Comment: 39 pages, 12 figures, 10 tables, 44 references. arXiv admin note: text overlap with arXiv:1910.00089

Published
2020
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41. Efficient Construction of Behavior Graphs for Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Data Structures and Algorithms
Abstract

The discipline of process mining deals with analyzing execution data of operational processes, extracting models from event data, checking the conformance between event data and normative models, and enhancing all aspects of processes. Recently, new techniques have been developed to analyze event data containing uncertainty; these techniques strongly rely on representing uncertain event data through graph-based models capturing uncertainty. In this paper we present a novel approach to efficiently compute a graph representation of the behavior contained in an uncertain process trace. We present our new algorithm, analyze its time complexity, and report experimental results showing order-of-magnitude performance improvements for behavior graph construction., Comment: 12 pages, 6 figures, 2 tables, 14 references

Published
2020
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45. Discovering Process Models from Uncertain Event Data

Author

Pegoraro, Marco, Uysal, Merih Seran, and van der Aalst, Wil M. P.

Subjects
Computer Science - Databases, Computer Science - Software Engineering
Abstract

Modern information systems are able to collect event data in the form of event logs. Process mining techniques allow to discover a model from event data, to check the conformance of an event log against a reference model, and to perform further process-centric analyses. In this paper, we consider uncertain event logs, where data is recorded together with explicit uncertainty information. We describe a technique to discover a directly-follows graph from such event data which retains information about the uncertainty in the process. We then present experimental results of performing inductive mining over the directly-follows graph to obtain models representing the certain and uncertain part of the process., Comment: 12 pages, 7 figures, 1 table, 9 references

Published
2019
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