All Outputs (30)

Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI (2020)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI. Presented at The Science of Making Torque from Wind (TORQUE 2020), Online, Netherlands

© 2020 Published under licence by IOP Publishing Ltd. Machine learning techniques have been widely used for condition-based monitoring of wind turbines using Supervisory Control & Acquisition (SCADA) data. However, many machine learning models, inclu... Read More about Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI.

The Promise of Causal Reasoning in Reliable Decision Support for Wind Turbines (2020)
Presentation / Conference Contribution
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.

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 Contribution
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.

Middle-out domain-specific aspect languages and their application in agent-based modelling runtime inspection (2019)
Thesis
Maddra, C. A. Middle-out domain-specific aspect languages and their application in agent-based modelling runtime inspection. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4221550

Domain-Specific Aspect Languages (DSALs) are a valuable tool for separating cross-cutting concerns, particularly within fields with endemic cross-cutting practices. Agent-Based Modelling (ABM) runtime inspection, which cuts across the core concern of... Read More about Middle-out domain-specific aspect languages and their application in agent-based modelling runtime inspection.

Transparency Of Execution Using Epigenetic Networks (2017)
Presentation / Conference Contribution
Dethlefs, N., & Turner, A. (2017, September). Transparency Of Execution Using Epigenetic Networks. Presented at 14th European Conference on Artificial Life, ECAL 2017, Lyon, France

This paper describes how the recurrent connectionist architecture epiNet, which is capable of dynamically modifying its topology, is able to provide a form of transparent execution. EpiNet, which is inspired by eukaryotic gene regulation in nature, i... Read More about Transparency Of Execution Using Epigenetic Networks.

Domain transfer for deep natural language generation from abstract meaning representations (2017)
Journal Article
Dethlefs, N. (2017). Domain transfer for deep natural language generation from abstract meaning representations. IEEE computational intelligence magazine, 12(3), 18-28. https://doi.org/10.1109/mci.2017.2708558

Stochastic natural language generation systems that are trained from labelled datasets are often domainspecific in their annotation and in their mapping from semantic input representations to lexical-syntactic outputs. As a result, learnt models fail... Read More about Domain transfer for deep natural language generation from abstract meaning representations.

A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology : a pilot study (2017)
Journal Article
Cuayahuitl, H., Dethlefs, N., Milders, M., Cuayáhuitl, H., Al-Salkini, T., & Douglas, L. (2017). A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology : a pilot study. Informatics for Health and Social Care, 42(4), 349-360. https://doi.org/10.1080/17538157.2016.1255627

Currently, an estimated 36 million people worldwide are affected by Alzheimer’s disease or related dementias. In the absence of a cure, non-pharmacological interventions, such as cognitive stimulation, which slow down the rate of deterioration can be... Read More about A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology : a pilot study.

Information density and overlap in spoken dialogue (2015)
Journal Article
Dethlefs, N., Hastie, H., Cuayáhuitl, H., Yu, Y., Rieser, V., & Lemon, O. (2016). Information density and overlap in spoken dialogue. Computer speech & language, 37, 82-97. https://doi.org/10.1016/j.csl.2015.11.001

Incremental dialogue systems are often perceived as more responsive and natural because they are able to address phenomena of turn-taking and overlapping speech, such as backchannels or barge-ins. Previous work in this area has often identified disti... Read More about Information density and overlap in spoken dialogue.

Hierarchical reinforcement learning for situated natural language generation (2014)
Journal Article
Dethlefs, N., & Cuayáhuitl, H. (2015). Hierarchical reinforcement learning for situated natural language generation. Natural language engineering, 21(3), 391-435. https://doi.org/10.1017/S1351324913000375

Natural Language Generation systems in interactive settings often face a multitude of choices, given that the communicative effect of each utterance they generate depends crucially on the interplay between its physical circumstances, addressee and in... Read More about Hierarchical reinforcement learning for situated natural language generation.