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Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines. IEEE Access, 10, 84710-84737. https://doi.org/10.1109/ACCESS.2022.3197167

Intelligent question-answering (QA) systems have witnessed increased interest in recent years, particularly in their ability to facilitate information access, data interpretation or decision support. The wind energy sector is one of the most promisin... Read More about Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines.

Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines (2022)
Conference Proceeding
Chatterjee, J. (2022). Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines. In J. M. Alonso, & U. Cortés (Eds.), Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI2020-proceedings) (53-54)

As global efforts in transitioning to sustainable energy sources rise, wind energy has become a leading renewable energy resource. However, turbines are complex engineering systems and rely on effective operations & maintenance (O&M) to prevent catas... Read More about Explainable AI for Intelligent Decision Support in Operations & Maintenance of Wind Turbines.

XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines (2021)
Working Paper
Chatterjee, J., & Dethlefs, N. (2021). XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines

Condition-based monitoring (CBM) has been widely utilised in the wind industry for monitoring operational inconsistencies and failures in turbines, with techniques ranging from signal processing and vibration analysis to artificial intelligence (AI)... Read More about XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines.

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.

Deep reinforcement learning for maintenance planning of offshore vessel transfer (2020)
Conference Proceeding
Chatterjee, J., & Dethlefs, N. (2020). Deep reinforcement learning for maintenance planning of offshore vessel transfer. In C. Guedes Soares (Ed.), Developments in Renewable Energies Offshore Proceedings of the 4th International Conference on Renewable Energies Offshore (RENEW 2020, 12 - 15 October 2020, Lisbon, Portugal) (435-443)

Offshore wind farm operators need to make short-term decisions on planning vessel transfers to turbines for preventive or corrective maintenance. These decisions can play a pivotal role in ensuring maintenance actions are carried out in a timely and... Read More about Deep reinforcement learning for maintenance planning of offshore vessel transfer.

A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines (2020)
Conference Proceeding
Chatterjee, J., & Dethlefs, N. (2020). A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.9206839

© 2020 IEEE. Wind energy is one of the fastest-growing sustainable energy sources in the world but relies crucially on efficient and effective operations and maintenance to generate sufficient amounts of energy and reduce downtime of wind turbines an... Read More about A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines.

The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines (2020)
Presentation / Conference
Chatterjee, J., & Dethlefs, N. (2020, August). The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines. Paper presented at Fragile Earth: Data Science for a Sustainable Planet. KDD 2020, Virtual Conference

The global pursuit towards sustainable development is leading to increased adaptation of renewable energy sources. Wind turbines are promising sources of clean energy, but regularly suffer from failures and down-times, primarily due to the complex en... Read More about The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines.

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.

Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines (2020)
Journal Article
Chatterjee, J., & Dethlefs, N. (2020). Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines. Wind energy, 23(8), 1693-1710. https://doi.org/10.1002/we.2510

The last decade has witnessed an increased interest in applying machine learning techniques to predict faults and anomalies in the operation of wind turbines. These efforts have lately been dominated by deep learning techniques which, as in other fie... Read More about Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines.

Natural Language Generation for Operations and Maintenance in Wind Turbines (2019)
Presentation / Conference
Chatterjee, J., & Dethlefs, N. (2019, December). Natural Language Generation for Operations and Maintenance in Wind Turbines. Paper presented at NeurIPS 2019 Workshop: Tackling Climate Change with Machine Learning, Vancouver Convention Center, British Columbia, Canada

Wind energy is one of the fastest-growing sustainable energy sources in the world but relies crucially on efficient and effective operations and maintenance to generate sufficient amounts of energy and reduce downtime of wind turbines and associated... Read More about Natural Language Generation for Operations and Maintenance in Wind Turbines.

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.

Variability management in safety-critical systems design and dependability analysis (2019)
Journal Article
de Oliveira, A. L., Braga, R., Masiero, P., Parker, D., Papadopoulos, Y., Habli, I., & Kelly, T. (2019). Variability management in safety-critical systems design and dependability analysis. Journal of software : evolution and process, 31(8), Article e2202. https://doi.org/10.1002/smr.2202

Safety-critical systems are of paramount importance for many application domains, where safety properties are a key driver to engineer critical aspects and avoid system failures. For the benefits of large-scale reuse, software product lines (SPL) hav... Read More about Variability management in safety-critical systems design and dependability analysis.

Smart, social, flexible and fun: Escaping the flatlands of virtual learning environments (2019)
Journal Article
Brayshaw, M., Gordon, N. A., & Grey, S. (2019). Smart, social, flexible and fun: Escaping the flatlands of virtual learning environments. Advances in Intelligent Systems and Computing, 998, 1047-1060. https://doi.org/10.1007/978-3-030-22868-2_70

© 2019, Springer Nature Switzerland AG. This paper describes the development of intelligent, social, flexible and game-based pedagogic approaches and their applications in Virtual Learning Environment based Education. Applications of computer science... Read More about Smart, social, flexible and fun: Escaping the flatlands of virtual learning environments.

Model transformation for analyzing dependability of AADL model by using HiP-HOPS (2019)
Journal Article
Mian, Z., Bottaci, L., Papadopoulos, Y., & Mahmud, N. (2019). Model transformation for analyzing dependability of AADL model by using HiP-HOPS. Journal of Systems and Software, 151, 258-282. https://doi.org/10.1016/j.jss.2019.02.019

The Architecture Analysis and Design Language (AADL) has emerged as a potential future standard in aerospace, automobile and avionics industries for model-based development of dependability-critical systems. As AADL is relatively new, some existing a... Read More about Model transformation for analyzing dependability of AADL model by using HiP-HOPS.

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review (2019)
Journal Article
Kabir, S., & Papadopoulos, Y. (2019). Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review. Safety science, 115, 154-175. https://doi.org/10.1016/j.ssci.2019.02.009

System safety, reliability and risk analysis are important tasks that are performed throughout the system life-cycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches are comprehensive, structured... Read More about Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review.

An adaptive ensemble approach to ambient intelligence assisted people search (2018)
Journal Article
Xue, D., Wang, X., Zhu, J., Davis, D. N., Wang, B., Zhao, W., …Cheng, Y. (2018). An adaptive ensemble approach to ambient intelligence assisted people search. Applied System Innovation, 1(3), 1-18. https://doi.org/10.3390/asi1030033

Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algor... Read More about An adaptive ensemble approach to ambient intelligence assisted people search.

Explicit Modelling and Treatment of Repair in Prediction of Dependability (2018)
Journal Article
Aizpurua, J. I., Papadopoulos, Y., & Merle, G. (2018). Explicit Modelling and Treatment of Repair in Prediction of Dependability. IEEE Transactions on Dependable and Secure Computing, 17(6), 1147-1162. https://doi.org/10.1109/TDSC.2018.2857810

In engineering practice, multiple repair actions are considered carefully by designers, and their success or failure defines further control actions and the evolution of the system state. Such treatment is not fully supported by the current state-of-... Read More about Explicit Modelling and Treatment of Repair in Prediction of Dependability.

Uncertainty-aware dynamic reliability analysis framework for complex systems (2018)
Journal Article
Kabir, S., Yazdi, M., Aizpurua, J. I., & Papadopoulos, Y. (2018). Uncertainty-aware dynamic reliability analysis framework for complex systems. IEEE Access, 6, Article ACCESS2843166. https://doi.org/10.1109/ACCESS.2018.2843166

Critical technological systems exhibit complex dynamic characteristics such as time-dependent behaviour, functional dependencies among events, sequencing and priority of causes that may alter the effects of failure. Dynamic fault trees (DFTs) have be... Read More about Uncertainty-aware dynamic reliability analysis framework for complex systems.

Prior knowledge-based deep learning method for indoor object recognition and application (2018)
Journal Article
Ding, X., Luo, Y., Li, Q., Cheng, Y., Cai, G., Munnoch, R., …Wang, B. (2018). Prior knowledge-based deep learning method for indoor object recognition and application. Systems Science and Control Engineering, 6(1), 249-257. https://doi.org/10.1080/21642583.2018.1482477

Indoor object recognition is a key task for indoor navigation by mobile robots. Although previous work has produced impressive results in recognizing known and familiar objects, the research of indoor object recognition for robot is still insufficien... Read More about Prior knowledge-based deep learning method for indoor object recognition and application.

A review of applications of fuzzy sets to safety and reliability engineering (2018)
Journal Article
Kabir, S., & Papadopoulos, Y. (2018). A review of applications of fuzzy sets to safety and reliability engineering. International Journal of Approximate Reasoning, 100, 29-55. https://doi.org/10.1016/j.ijar.2018.05.005

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limi... Read More about A review of applications of fuzzy sets to safety and reliability engineering.