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Professor Yiannis Papadopoulos


Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems (2021)
Journal Article
Aslansefat, K., Kabir, S., Abdullatif, A., Vasudevan Nair, V., & Papadopoulos, Y. (in press). Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems. Computer,

The application of artificial intelligence (AI) and data-driven decision-making systems in autonomous vehicles is growing rapidly. As autonomous vehicles operate in dynamic environments, the risk that they can face an unknown observation is relativel... Read More about Towards Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems.

Computational Intelligence for Safety Assurance of Cooperative Systems of Systems (2020)
Journal Article
Kabir, S., & Papadopoulos, Y. (2020). Computational Intelligence for Safety Assurance of Cooperative Systems of Systems. Computer, 53(12), 24-34. https://doi.org/10.1109/MC.2020.3014604

Cooperative systems of systems (CSoSs) form a new technological frontier for their enormous economic and societal potentials in various domains. This article presents a novel framework for dynamic safety assurance of CSoSs that integrates design time... Read More about Computational Intelligence for Safety Assurance of Cooperative Systems of Systems.

SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures (2020)
Journal Article
Aslansefat, K., Sorokos, I., Whiting, D., Tavakoli Kolagari, R., & Papadopoulos, Y. (2020). SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures. Lecture notes in computer science, 12297, 197-211. https://doi.org/10.1007/978-3-030-58920-2_13

Ensuring safety and explainability of machine learning (ML) is a topic of increasing relevance as data-driven applications venture into safety-critical application domains, traditionally committed to high safety standards that are not satisfied with... Read More about SafeML: Safety Monitoring of Machine Learning Classifiers Through Statistical Difference Measures.

Failure Mode Reasoning in Model Based Safety Analysis (2020)
Journal Article
Jahanian, H., Parker, D., Zeller, M., McIver, A., & Papadopoulos, Y. (2020). Failure Mode Reasoning in Model Based Safety Analysis. Lecture notes in computer science, 12297 LNCS, 130-145. https://doi.org/10.1007/978-3-030-58920-2_9

© 2020, Springer Nature Switzerland AG. Failure Mode Reasoning (FMR) is a novel approach for analyzing failure in a Safety Instrumented System (SIS). The method uses an automatic analysis of an SIS program to calculate potential failures in parts of... Read More about Failure Mode Reasoning in Model Based Safety Analysis.

An Integrated Approach to Support the Process-Based Certification of Variant-Intensive Systems (2020)
Journal Article
Bressan, L., de Oliveira, A. L., Campos, F., Papadopoulos, Y., & Parker, D. (2020). An Integrated Approach to Support the Process-Based Certification of Variant-Intensive Systems. Lecture notes in computer science, 12297 LNCS, 179-193. https://doi.org/10.1007/978-3-030-58920-2_12

© 2020, Springer Nature Switzerland AG. Component-based approaches and software product lines have been adopted by industry to manage the diversity of configurations on safety-critical software. Safety certification demands compliance with standards.... Read More about An Integrated Approach to Support the Process-Based Certification of Variant-Intensive Systems.

A Hybrid Modular Approach for Dynamic Fault Tree Analysis (2020)
Journal Article
Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., & Konur, S. (2020). A Hybrid Modular Approach for Dynamic Fault Tree Analysis. IEEE Access, 8, 97175-97188. https://doi.org/10.1109/ACCESS.2020.2996643

Over the years, several approaches have been developed for the quantitative analysis of dynamic fault trees (DFTs). These approaches have strong theoretical and mathematical foundations; however, they appear to suffer from the state-space explosion a... Read More about A Hybrid Modular Approach for Dynamic Fault Tree Analysis.

A conceptual framework to incorporate complex basic events in HiP-HOPS (2019)
Book Chapter
Kabir, S., Aslansefat, K., Sorokos, I., Papadopoulos, Y., & Gheraibia, Y. (2019). A conceptual framework to incorporate complex basic events in HiP-HOPS. In Y. Papadopoulos, K. Aslansefat, P. Katsaros, & M. Bozzano (Eds.), Model-Based Safety and Assessment. IMBSA 2019 (109-124). Cham: Springer Verlag. https://doi.org/10.1007/978-3-030-32872-6_8

Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOP... Read More about A conceptual framework to incorporate complex basic events in HiP-HOPS.

A runtime safety analysis concept for open adaptive systems (2019)
Journal Article
Kabir, S., Sorokos, I., Aslansefat, K., Papadopoulos, Y., Gheraibia, Y., Reich, J., …Wei, R. (2019). A runtime safety analysis concept for open adaptive systems. Lecture notes in computer science, 11842, 332-346. https://doi.org/10.1007/978-3-030-32872-6_22

© Springer Nature Switzerland AG 2019. In the automotive industry, modern cyber-physical systems feature cooperation and autonomy. Such systems share information to enable collaborative functions, allowing dynamic component integration and architectu... Read More about A runtime safety analysis concept for open adaptive systems.

Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks (2019)
Journal Article
Kabir, S., Taleb-Berrouane, M., & Papadopoulos, Y. (in press). Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks. Energy Sources, Part A, https://doi.org/10.1080/15567036.2019.1670287

Flaring is a combustion process commonly used in the oil and gas industry to dispose flammable waste gases. Flare flameout occurs when these gases escape unburnt from the flare tip causing the discharge of flammable and/or toxic vapor clouds. The tox... Read More about Dynamic reliability assessment of flare systems by combining fault tree analysis and Bayesian networks.

Safety + AI: A novel approach to update safety models using artificial intelligence (2019)
Journal Article
Gheraibia, Y., Kabir, S., Aslansefat, K., Sorokos, I., & Papadopoulos, Y. (2019). Safety + AI: A novel approach to update safety models using artificial intelligence. IEEE Access, 7, 135855-135869. https://doi.org/10.1109/ACCESS.2019.2941566

Safety-critical systems are becoming larger and more complex to obtain a higher level of functionality. Hence, modeling and evaluation of these systems can be a difficult and error-prone task. Among existing safety models, Fault Tree Analysis (FTA) i... Read More about Safety + AI: A novel approach to update safety models using artificial intelligence.