Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains
Само за регистроване кориснике
2023
Аутори
Babović, ZoranBajat, Branislav
Barac, Dusan
Bengin, Vesna
Đokić, Vladan
Đorđević, Filip
Drašković, Dražen
Filipović, Nenad
French, Stephan
Furht, Borko
Ilić, Marija
Irfanoglu, Ayhan
Kartelj, Aleksandar
Kilibarda, Milan
Klimeck, Gerhard
Korolija, Nenad
Kotlar, Miloš
Kovačević, Miloš
Kuzmanović, Vladan
Lehn, Jean-Marie
Madić, Dejan
Marinković, Marko
Mateljević, Miodrag
Mendelson, Avi
Mesinger, Fedor
Milovanović, Gradimir
Milutinović, Veljko
Mitić, Nenad
Nešković, Aleksandar
Nešković, Nataša
Nikolić, Boško
Novoselov, Konstantin
Prakash, Arun
Protić, Jelica
Ratković, Ivan
Rios, Diego
Shechtman, Dan
Stojadinović, Zoran
Ustyuzhanin, Andrey
Zak, Stan
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number of other related fields. The course derived from this strategy includes four parts: (a) Computing with a selected set of modern paradigms—the stress is on Control Flow and Data Flow computing paradigms, but paradigms conditionally referred to as Energy Flow and Diffusion Flow are also covered; (b) Project management that is holistic—the stress is on the wide plethora of issues spanning from the preparation of project proposals, all the way to incorporation activities to follow after the completion of a successful project; (c) Examples from past research and development experiences—the stress is on experiences of leading experts from academia and industry; (d) Student projects that stimulate creativity—the stress is on methods that educators could use to induce and acc...elerate the creativity of students in general. Finally, the article ends with selected pearls of wisdom that could be treated as suggestions for further elaboration.
Кључне речи:
Education / Computing paradigms / Artificial intelligence / Big data / Nature-based constructionИзвор:
Journal of Big Data, 2023, 10Издавач:
- Springer
Колекције
Институција/група
GraFarTY - JOUR AU - Babović, Zoran AU - Bajat, Branislav AU - Barac, Dusan AU - Bengin, Vesna AU - Đokić, Vladan AU - Đorđević, Filip AU - Drašković, Dražen AU - Filipović, Nenad AU - French, Stephan AU - Furht, Borko AU - Ilić, Marija AU - Irfanoglu, Ayhan AU - Kartelj, Aleksandar AU - Kilibarda, Milan AU - Klimeck, Gerhard AU - Korolija, Nenad AU - Kotlar, Miloš AU - Kovačević, Miloš AU - Kuzmanović, Vladan AU - Lehn, Jean-Marie AU - Madić, Dejan AU - Marinković, Marko AU - Mateljević, Miodrag AU - Mendelson, Avi AU - Mesinger, Fedor AU - Milovanović, Gradimir AU - Milutinović, Veljko AU - Mitić, Nenad AU - Nešković, Aleksandar AU - Nešković, Nataša AU - Nikolić, Boško AU - Novoselov, Konstantin AU - Prakash, Arun AU - Protić, Jelica AU - Ratković, Ivan AU - Rios, Diego AU - Shechtman, Dan AU - Stojadinović, Zoran AU - Ustyuzhanin, Andrey AU - Zak, Stan PY - 2023 UR - https://grafar.grf.bg.ac.rs/handle/123456789/3114 AB - This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number of other related fields. The course derived from this strategy includes four parts: (a) Computing with a selected set of modern paradigms—the stress is on Control Flow and Data Flow computing paradigms, but paradigms conditionally referred to as Energy Flow and Diffusion Flow are also covered; (b) Project management that is holistic—the stress is on the wide plethora of issues spanning from the preparation of project proposals, all the way to incorporation activities to follow after the completion of a successful project; (c) Examples from past research and development experiences—the stress is on experiences of leading experts from academia and industry; (d) Student projects that stimulate creativity—the stress is on methods that educators could use to induce and accelerate the creativity of students in general. Finally, the article ends with selected pearls of wisdom that could be treated as suggestions for further elaboration. PB - Springer T2 - Journal of Big Data T1 - Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains VL - 10 DO - 10.1186/s40537-023-00730-7 ER -
@article{ author = "Babović, Zoran and Bajat, Branislav and Barac, Dusan and Bengin, Vesna and Đokić, Vladan and Đorđević, Filip and Drašković, Dražen and Filipović, Nenad and French, Stephan and Furht, Borko and Ilić, Marija and Irfanoglu, Ayhan and Kartelj, Aleksandar and Kilibarda, Milan and Klimeck, Gerhard and Korolija, Nenad and Kotlar, Miloš and Kovačević, Miloš and Kuzmanović, Vladan and Lehn, Jean-Marie and Madić, Dejan and Marinković, Marko and Mateljević, Miodrag and Mendelson, Avi and Mesinger, Fedor and Milovanović, Gradimir and Milutinović, Veljko and Mitić, Nenad and Nešković, Aleksandar and Nešković, Nataša and Nikolić, Boško and Novoselov, Konstantin and Prakash, Arun and Protić, Jelica and Ratković, Ivan and Rios, Diego and Shechtman, Dan and Stojadinović, Zoran and Ustyuzhanin, Andrey and Zak, Stan", year = "2023", abstract = "This article describes a teaching strategy that synergizes computing and management, aimed at the running of complex projects in industry and academia, in the areas of civil engineering, physics, geosciences, and a number of other related fields. The course derived from this strategy includes four parts: (a) Computing with a selected set of modern paradigms—the stress is on Control Flow and Data Flow computing paradigms, but paradigms conditionally referred to as Energy Flow and Diffusion Flow are also covered; (b) Project management that is holistic—the stress is on the wide plethora of issues spanning from the preparation of project proposals, all the way to incorporation activities to follow after the completion of a successful project; (c) Examples from past research and development experiences—the stress is on experiences of leading experts from academia and industry; (d) Student projects that stimulate creativity—the stress is on methods that educators could use to induce and accelerate the creativity of students in general. Finally, the article ends with selected pearls of wisdom that could be treated as suggestions for further elaboration.", publisher = "Springer", journal = "Journal of Big Data", title = "Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains", volume = "10", doi = "10.1186/s40537-023-00730-7" }
Babović, Z., Bajat, B., Barac, D., Bengin, V., Đokić, V., Đorđević, F., Drašković, D., Filipović, N., French, S., Furht, B., Ilić, M., Irfanoglu, A., Kartelj, A., Kilibarda, M., Klimeck, G., Korolija, N., Kotlar, M., Kovačević, M., Kuzmanović, V., Lehn, J., Madić, D., Marinković, M., Mateljević, M., Mendelson, A., Mesinger, F., Milovanović, G., Milutinović, V., Mitić, N., Nešković, A., Nešković, N., Nikolić, B., Novoselov, K., Prakash, A., Protić, J., Ratković, I., Rios, D., Shechtman, D., Stojadinović, Z., Ustyuzhanin, A.,& Zak, S.. (2023). Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains. in Journal of Big Data Springer., 10. https://doi.org/10.1186/s40537-023-00730-7
Babović Z, Bajat B, Barac D, Bengin V, Đokić V, Đorđević F, Drašković D, Filipović N, French S, Furht B, Ilić M, Irfanoglu A, Kartelj A, Kilibarda M, Klimeck G, Korolija N, Kotlar M, Kovačević M, Kuzmanović V, Lehn J, Madić D, Marinković M, Mateljević M, Mendelson A, Mesinger F, Milovanović G, Milutinović V, Mitić N, Nešković A, Nešković N, Nikolić B, Novoselov K, Prakash A, Protić J, Ratković I, Rios D, Shechtman D, Stojadinović Z, Ustyuzhanin A, Zak S. Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains. in Journal of Big Data. 2023;10. doi:10.1186/s40537-023-00730-7 .
Babović, Zoran, Bajat, Branislav, Barac, Dusan, Bengin, Vesna, Đokić, Vladan, Đorđević, Filip, Drašković, Dražen, Filipović, Nenad, French, Stephan, Furht, Borko, Ilić, Marija, Irfanoglu, Ayhan, Kartelj, Aleksandar, Kilibarda, Milan, Klimeck, Gerhard, Korolija, Nenad, Kotlar, Miloš, Kovačević, Miloš, Kuzmanović, Vladan, Lehn, Jean-Marie, Madić, Dejan, Marinković, Marko, Mateljević, Miodrag, Mendelson, Avi, Mesinger, Fedor, Milovanović, Gradimir, Milutinović, Veljko, Mitić, Nenad, Nešković, Aleksandar, Nešković, Nataša, Nikolić, Boško, Novoselov, Konstantin, Prakash, Arun, Protić, Jelica, Ratković, Ivan, Rios, Diego, Shechtman, Dan, Stojadinović, Zoran, Ustyuzhanin, Andrey, Zak, Stan, "Teaching computing for complex problems in civil engineering and geosciences using big data and machine learning: synergizing four different computing paradigms and four different management domains" in Journal of Big Data, 10 (2023), https://doi.org/10.1186/s40537-023-00730-7 . .