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Outputs (33)

Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning (2023)
Journal Article
Chatterjee, J., Alvela Nieto, M. T., Gelbhardt, H., Dethlefs, N., Ohlendorf, J.-H., Greulich, A., & Thoben, K.-D. (2023). Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning. Environmental Data Science, 2, 1-15. https://doi.org/10.1017/eds.2023.9

Wind energy’s ability to liberate the world from conventional sources of energy relies on lowering the significant costs associated with the maintenance of wind turbines. Since icing events on turbine rotor blades are a leading cause of operational f... Read More about Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning.

This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy (2023)
Journal Article
Chatterjee, J., & Dethlefs, N. (2023). This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy. Patterns, 4(1), Article 100676. https://doi.org/10.1016/j.patter.2022.100676

We explore the recently released ChatGPT model, one of the most powerful conversational AI models that has ever been developed. This opinion provides a perspective on its strengths and weaknesses and a call to action for the AI community (including a... Read More about This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy.

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.

A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms (2022)
Journal Article
Walker, C., Rothon, C., Aslansefat, K., Papadopoulos, Y., & Dethlefs, N. (2022). A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms. Lecture notes in computer science, 13525 LNCS, 189-203. https://doi.org/10.1007/978-3-031-15842-1_14

With an increasing emphasis on driving down the costs of Operations and Maintenance (O &M) in the Offshore Wind (OSW) sector, comes the requirement to explore new methodology and applications of Deep Learning (DL) to the domain. Condition-based monit... Read More about A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms.

XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. XAI4Wind: A Multimodal Knowledge Graph Database for Explainable Decision Support in Operations & Maintenance of Wind Turbines. https://doi.org/10.48550/arXiv.2012.10489. Manuscript submitted for publication

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.

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.

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.

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., Peng, Y., & 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. (2020). 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., Xue, D., Yu, Q., Zheng, X., & 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.

Model-based assessment of energy-efficiency, dependability, and cost-effectiveness of waste heat recovery systems onboard ship (2018)
Journal Article
Lampe, J., Rüde, E., Papadopoulos, Y., & Kabir, S. (2018). Model-based assessment of energy-efficiency, dependability, and cost-effectiveness of waste heat recovery systems onboard ship. Ocean engineering, 157, 234-250. https://doi.org/10.1016/j.oceaneng.2018.03.062

Technological systems are not merely designed with a narrow function in mind. Good designs typically aim at reducing operational costs, e.g. through achieving high energy efficiency and improved dependability (i.e. reliability, availability and maint... Read More about Model-based assessment of energy-efficiency, dependability, and cost-effectiveness of waste heat recovery systems onboard ship.

Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks (2018)
Journal Article
Papadopoulos, Y., Walker, M., & Kabir, S. (2018). Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks. Safety science, 105, 55-70. https://doi.org/10.1016/j.ssci.2018.02.001

© 2018 Elsevier Ltd Dynamic systems exhibit time-dependent behaviours and complex functional dependencies amongst their components. Therefore, to capture the full system failure behaviour, it is not enough to simply determine the consequences of diff... Read More about Dynamic system safety analysis in HiP-HOPS with Petri Nets and Bayesian Networks.

Using formal game design methods to embed learning outcomes into game mechanics and avoid emergent behaviour (2017)
Journal Article
Grey, S., Grey, D., Gordon, N., & Purdy, J. (2017). Using formal game design methods to embed learning outcomes into game mechanics and avoid emergent behaviour. International Journal of Game-Based Learning, 7(3), 63-73. https://doi.org/10.4018/ijgbl.2017070106

This paper offers an approach to designing game based learning experiences inspired by the Mechanics-Dynamics-Aesthetics (MDA) model (Hunicke et al, 2004) and the elemental tetrad (Schell, 2008) model for game design. A case for game based learning a... Read More about Using formal game design methods to embed learning outcomes into game mechanics and avoid emergent behaviour.