Annals of Computer Science and Intelligence Systems, Volume 49
Communication Papers of the 21st Conference on Computer Science and Intelligence Systems (FedCSIS)
Preface
Dear Reader it is our pleasure to present to you the Communication Papers of the 21th Conference on Computer Science and Intelligence Systems (FedCSIS 2026), which took place on 23-26 August, 2026, in Riga, Latvia.
In the context of the FedCSIS conference series, the communication papers were introduced in 2017, as a separate category of contributions. They report on research topics worthy of immediate communication. They may be used to mark a new research territory, or to describe work in progress, in order to quickly present it to the scientific community. They may also contain additional information, omitted from the earlier papers, or may present software tools and products in a research state.
FedCSIS 2026 was chaired by Oksana Nikiforova. Moreover, Andrejs Romānovs was the Chair of the Organizing Committee. Furthermore, this year, FedCSIS was organized by the Polish Information Processing Society (Mazovia Chapter), IEEE Poland Section Computer Society Chapter, Systems Research Institute Polish Academy of Sciences, The Faculty of Mathematics and Information Science of the Warsaw University of Technology, The Faculty of Electrical and Computer Engineering of the Rzeszów University of Technology, The Faculty of Electrical Engineering af the Riga Technical University and The Faculty of Engineering and Management of the University of Technology and Arts in Applied Sciences.
FedCSIS 2026 was technically co-sponsored by IEEE Poland Section, IEEE Serbia and Montenegro Section, IEEE Estonia Section, IEEE Latvia Section, IEEE Lithuania Section, IEEE South Africa Section, Serbia and Montenegro Section Computational Intelligence Society Chapter, IEEE Young Professionals Affinity Group, Novi Sad, Republic of Serbia, IEEE Romania Section WIE Affinity Group, Czechoslovakia Section Computer Society Chapter, Poland Section Computer Society (Gdańsk) Chapter, Estonia Section Computer Society Chapter, Latvia Section Computer Society Chapter, Lithuania Section Computer Society Chapter.
FedCSIS 2026 was sponsored by InfoSoftware Polska as well as MDPI Information, MDPI Electronics, MDPI Technologies, MDPI Applied Sciences journals. Moreover, FedCSIS 2026 has been conducted under patronages of: INFORMS Poland Chapter, Latvian Information and communications technology association (LIKTA), Naukowe Towarzystwo Informatyki Ekonomicznej, International Rough Set Society, Web Intelligence Consortium, Polish Neural Network Society, European Society for Fuzzy Logic and Technology, Polish Artificial Intelligence Society (PSSI). Finally, media patronage was provided by Forum Akademickie.
During FedCSIS 2026 four keynote speakers delivered lectures providing a broader context for the conference participants. These presentations were:
- Ginter, Filip, TurkuNLP, Department of Computing University of Turku, Finland and ELLIS Institute, Finland
Keynote title: The Challenges of Tracing Meaning at Scale across Multilingual Historical Texts - Pechenizkiy, Mykola, Department of Mathematics and Computer Science, Eindhoven University of Technology, Netherlands
Keynote title: Advancing the Science of Safe and Trustworthy AI Evaluation - Prodan, Radu, Edge AI at the Department of Computer Science, University of Innsbruck, Austria
Keynote title: Distribute and Learn 1 Billion - Sabou, Marta, Vienna University of Economics and Business (WU), Austria
Keynote title: Neuro-Symbolic Knowledge Engineering: Emerging Paradigms and Challenges
Moreover, four past FedCSIS keynote speakers have been invited to prepare and deliver special contributions, which refer to the core focus of the conference series. These were:
- Atiquzzaman, Mohammed, School of Computer Science, University of Oklahoma, USA
EnsembleClassifier: Using Machine Learning to Select Exact Packet Classification Structures for Partitioned Rule Subsets - Blum, Christian, Artificial Intelligence Research Institute (IIIA-CSIC), Spain
Contribution title:Preserving Optimization Algorithm Expertise by means of Executable Algorithm Knowledge Graphs: A Worked Example on the TSP - Skowron, Andrzej, Systems Research Institute Polish Academy of Sciences, Poland
Contribution title:Evolution of Approximation Spaces in Rough Sets: From Relational Systems to Complex Adaptive Systems - van der Aalst, Wil M.P., RWTH Aachen University, Germany
Contribution title: Mining Bureaucracy Debt: Process Intelligence for Evidence-Based Deregulation
At the time, when you are reading this text, videos of the keynote presentations and of invited contributions, delivered during the FedCSIS 2026 conference, are already available on the official conference website (www.fedcsis.org). We warmly encourage you to visit the website and watch these recordings to gain additional insights and perspectives shared by distinguished speakers.
This year, the structure of the conference remained the same as last year. FedCSIS 2026 had a single Main Track with 5 Topical Areas, which was supported by 16 Thematic Sessions and an Industrial Track. Such a structure emphasizes the integrity of the conference and its closeness to the issues that are crucial for the world around us. Here, we recognize the fact that today (in 2026) it is difficult to envision research (and its applications) without an intelligence component. Reflecting this, all five Topical Areas, which constitute the Main Track, represent various aspects of Intelligence Systems. Moreover, the Thematic Sessions provide further insights into selected areas of Intelligence Systems, approached from different perspectives.
Articles are ordered alphabetically by the last name of the first author. The specific Topical Area or Thematic Session that given contribution was associated with is listed in the article metadata. Each contribution, found in this volume, was refereed by at least two referees.
Delivery of FedCSIS 2026 required a dedicated effort of many people. We would like to express our warmest gratitude to all Topical Area Curators, Thematic Session organizers, members of the FedCSIS 2026 Senior Program Committee, and members of the FedCSIS 2026 Program Committee (a total of more than 300 individuals), for their hard work in attracting and reviewing all submissions. We thank the authors of papers for their great contribution to the theory and practice of Computer Science and Intelligence Systems. We are grateful to Keynote and Invited Speakers for sharing their knowledge and experiences with the participants. Last, but not least, we acknowledge Andrejs Romānovs, Megija Krista Miļūne, Rihards Bobkovs, Uldis Karlovs-Karlovskis, Kristaps Babris, Veronika Tatjana Vucāne, Zane Bičevska Anastasiya Danilenka and Paweł Szmeja, as well as a fantastic group of student helpers. We are very grateful for your efforts!
We also hope to meet you again for the 22nd Conference on Computer Science and Intelligence Systems (FedCSIS 2027), which will take place in Gdynia, Poland, on September 12-15, 2027.
Co-Chairs of the FedCSIS Conference Series
Marek Bolanowski, Rzeszow University of Technology, Poland.
Maria Ganzha, Warsaw University of Technology, Poland and Systems Research Institute Polish Academy of Sciences, Warsaw, Poland.
Marek Grzegorowski, Samsung Research, Warsaw, Poland.
Leszek Maciaszek, Wrocław University of Economics and Business, Wrocław, Poland and Macquarie University, Sydney, Australia.
Marcin Paprzycki, Systems Research Institute Polish Academy of Sciences, Warsaw Poland and Management Academy, Warsaw, Poland.
Andrzej Paszkiewicz, Rzeszów University of Technology, Poland.
Dominik Ślęzak, Institute of Informatics, University of Warsaw, Poland and QED Software, Poland and DeepSeas, USA.
Communication Papers
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Phase-Dependent Drivers and Cumulative Institutional Impacts of Digital Transformation Adoption in Saudi Public Universities
4340 Digital transformation, Institutional impacts, Phase-Dependent Drivers, Mixed-Methods Research, Saudi Public Universities, TAM, TOE, Institutional Performance, Saudi Vision 2030, Cumulative Impacts, Thematic Analysis Saleh Z Alshehri, Natalia Beloff, Martin White, Imran Khan, pages 1–9. ITBS -
A multithreaded Java implementation of Monte Carlo simulation for Value-at-Risk estimation
1699 Multithreading, Value-at-Risk estimation, Mont Carlo, Java Paweł Borowiecki, Beata Bylina, pages 11–16. CANA -
INCLUDE-AI and G.I.U.L.I.A.: A Multi-Level European and Territorial Framework for Inclusive, Trustworthy, and Gender-Aware Artificial Intelligence in Education
8742 AI Ethics, Complex Systems Management, Inclusive Education Matteo Ciaschi, Daniel Dan, pages 17–24. EDUC‑AI‑TION -
Predicting Centrality Measures in Complex Networks Utilizing Markov Chains
9619 Centrality Measures, Complex Networks, MArkov Chains Anchal Gera, Jens Dörpinghaus, Robert Rockenfeller, pages 25–35. CO -
Potential of Found Establishment Data Linkage for the Social Sciences
4286 establishment research, online job advertisements, OpenStreetMap (OSM), AI-supported data linkage Christian Gerhards, pages 37–43. AI‑HuSo -
A Holistic CPS for Smart Precision Livestock Farming: Multi-Actor Collaborative Decision-Making Across Ecosystem Domains
3040 Cyber-Physical System, Multi-actors, Collaborative Decision-Making, AI-driven intelligence Sonia Hajri-Gabouj, Imen Harbaoui, Rabaa Youssef, pages 45–52. IS3E -
Semantic Matching of IT Vocational Training Offers with the ESCO Ontology
8838 Semantic matching, ESCO Ontology, Sentence Transformers, Vocational training, LLM-based cleaning, Competency frameworks Katerina Kostadinovska, Kristine Hein, pages 53–57. AI‑HuSo -
Incorporation of Min/Max, With/Without and Pairing Restrictions in Column Generation Solution Algorithms for Aircrew Rostering
4530 Column generation, Branch & price, Commercial aviation, Airline management, Crew rostering, Min/max restrictions, With/without restrictions, Pairing restrictions George Kozanidis, Nikos Polychronopoulos, Andreas Gavranis, pages 59–66. CO -
Software System for Optimization of Metallic Nanostructures
4023 nanostructures, simulation, software systems, Monte Carlo methods, optimization Rossen Mikhov, Vladimir Myasnichenko, Leoneed Kirilov, Nikolay Sdobnyakov, Stefka Fidanova, pages 67–72. CO -
A Reproducible Zero Trust Testbed for Dynamic Trust Evaluation Using Emulation and Virtualization Tools
5993 Zero Trust Testbed, Software Defined Perimeters, Software Defined Networking, Dynamic Trust Evaluation, Virtualization, Emulation, Containerization, Reproducibility. Tiberius Nkinyili, Vincent Omwenga, Solomon Ogara, pages 73–80. NEMESIS -
Cosine Colorization for Enhancement of Magnetic Resonance Angiography (MRA)
8443 Anatomical Fidelity, Cosine Colorization, Enhancement, MRA, Vessel-Restricted Mapping Modupe Odusami, Robertas Damaševičius, Olusola Abayomi-Alli, Rytis Maskeliūnas, pages 81–88. MMAP -
Data collection, aggregation, and analysis in the Internet of Everything environment – a case study
2726 IoE, cybersecurity, data aggregation, anomaly detection, ML, event correlation, adaptive architecture Andrzej Paszkiewicz, Andrzej Gołąbek, Piotr Sowa, Mateusz Kozik, Marek Bolanowski pages 89–92. INDT -
Parsing Hierarchical Document Structure with Graph Neural Networks
3376 document hierarchy parsing, document understanding, digital humanities Thomas Reiser, Veronika Vasileva, Volker Riediger, Alexander Esser, Petra Steiner, Jan Jürjens, pages 93–100. AI‑HuSo -
Still Waiting for the Shock: AI’s Limited Impact on Early-Career Vacancies, Skills and Tasks
3431 Computational Text Analysis, Applied Econometrics, Methodological Integration of Large Language Models, Education and Labour Economics Stefan Speckesser, Lei Xu, pages 101–109. AI‑HuSo -
Iterative Inductive Learning for Generalized Modeling of Technical Systems
6359 Inductive Learning, Rough Set Theory, Performance Modelling Balázs Ádám Toldi, András Földvári, Zsigmond Pap, András Pataricza, pages 111–118. IS3E -
Acceptance of Generative AI in Higher Education in Software Engineering Education—A Systematic Literature Review
3410 Generative AI, Acceptance, Higher Education, Software Engineering, Systematic Literature Review Veronika Vasileva, Thomas Reiser, Jan Jürjens, pages 119–126. AI‑HuSo
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