All Outputs (520)

A robust exploration strategy in reinforcement learning based on temporal difference error. (2022)
Conference Proceeding
HAJAR, M.S., KALUTARAGE, H. and AL-KADRI, M.O. 2022. A robust exploration strategy in reinforcement learning based on temporal difference error. In Aziz, H., Corrêa, D. and French, T. (eds.) AI 2022: advances in artificial intelligence; proceedings of the 35th Australasian joint conference 2022 (AI 2022), 5-8 December 2022, Perth, Australia. Lecture notes in computer science (LNCS), 13728. Cham: Springer [online], pages 789-799. Available from: https://doi.org/10.1007/978-3-031-22695-3_55

Exploration is a critical component in reinforcement learning algorithms. Exploration exploitation trade-off is still a fundamental dilemma in reinforcement learning. The learning agent needs to learn how to deal with a stochastic environment in orde... Read More about A robust exploration strategy in reinforcement learning based on temporal difference error..

Clinical dialogue transcription error correction using Seq2Seq models. (2022)
Conference Proceeding
NANAYAKKARA, G., WIRATURNGA, N., CORSAR, D., MARTIN, K. and WIJEKOON, A. 2022. Clinical dialogue transcription error correction using Seq2Seq models. In Shaban-Nejad, A., Michalowski, M. and Bianco, S. (eds.) Multimodal AI in healthcare: a paradigm shift in health intelligence; selected papers from the 6th International workshop on health intelligence (W3PHIAI-22), co-located with the 34th AAAI (Association for the Advancement of Artificial Intelligence) Innovative applications of artificial intelligence (IAAI-22), 28 February - 1 March 2022, [virtual event]. Studies in computational intelligence, 1060. Cham: Springer [online], pages 41-57. Available from: https://doi.org/10.1007/978-3-031-14771-5_4

Good communication is critical to good healthcare. Clinical dialogue is a conversation between health practitioners and their patients, with the explicit goal of obtaining and sharing medical information. This information contributes to medical decis... Read More about Clinical dialogue transcription error correction using Seq2Seq models..

Piloting the learning by development action model pedagogy in UK HEIs. (2022)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2022. Piloting the learning by development action model pedagogy in UK HEIs. In Proceedings of the 2022 Frontiers in education conference (FIE 2022): grand challenges in engineering education, 8-11 October 2022, Uppsala, Sweden. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/FIE56618.2022.9962469

This Research to Practice full paper presents pilot implementations of the Learning by Developing (LbD) at a higher educational institution in the UK as part of a project-based module. The study analyses the students' experiences of LbD and the perce... Read More about Piloting the learning by development action model pedagogy in UK HEIs..

Topology for preserving feature correlation in tabular synthetic data. (2022)
Conference Proceeding
ARIFEEN, M. and PETROVSKI, A. 2022. Topology for preserving feature correlation in tabular synthetic data. In Proceedings of the 15th IEEE (Institute of Electrical and Electronics Engineers) International conference on security of information and networks 2022 (SINCONF 2022), 11-13 November 2022, Sousse, Tunisia. Piscataway: IEEE [online], pages 61-66. Available from: https://doi.org/10.1109/SIN56466.2022.9970505

Tabular synthetic data generating models based on Generative Adversarial Network (GAN) show significant contributions to enhancing the performance of deep learning models by providing a sufficient amount of training data. However, the existing GAN-ba... Read More about Topology for preserving feature correlation in tabular synthetic data..

Programming language evaluation criteria for safety-critical software in the air domain. (2022)
Conference Proceeding
ASHMORE, R., HOWE, A., CHILTON, R. and FAILY, S. 2022. Programming language evaluation criteria for safety-critical software in the air domain. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) International symposium on software reliability engineering workshops (ISSREW 2022), 31 October - 3 November 2022, Charlotte, NC, USA. Los Alamitos: IEEE Computer Society [online], pages 230-237. Available from: https://doi.org/10.1109/ISSREW55968.2022.00072

Safety-critical software in the air domain typically conforms to RTCA DO-178C. However, latent failures might arise based on assumptions underpinning the programming language used to write the software, whereas the lack of empirical data may constrai... Read More about Programming language evaluation criteria for safety-critical software in the air domain..

Content type profiling of data-to-text generation datasets. (2022)
Conference Proceeding
UPADHYAY, A. and MASSIE, S. 2022. Content type profiling of data-to-text generation datasets. In N. Calzolari, C.-R. Huang, H. Kim. et al. (eds.) Proceedings of the 29th International conference on computational linguistics (COLING 2022), 12-17 October 2022, Gyeongju, Republic of Korea. Stroudsburg, PA: International Committee on Computational Linguistics [online], 29(1), pages 5770–5782. Available from: https://aclanthology.org/2022.coling-1.pdf

Data-to-Text Generation (D2T) problems can be considered as a stream of time-stamped events with a text summary being produced for each. The problem becomes more challenging when event summaries contain complex insights derived from multiple records... Read More about Content type profiling of data-to-text generation datasets..

Phronesis: deliberative judgement as a key competence in the post-Covid educational environment. (2022)
Conference Proceeding
MCDERMOTT, R. and DANIELS, M. 2022. Phronesis: deliberative judgement as a key competence in the post-Covid educational environment. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2022), 8-11 October 2022, Uppsala, Sweden. Piscataway: IEEE [online], article 9962515. Available from: https://doi.org/10.1109/FIE56618.2022.9962515

The global Covid19 pandemic which began in early 2020 is one of the most socially disruptive events to have occurred since the Second World War. It has left a profound mark on the institutions of society, including those charged with education, and i... Read More about Phronesis: deliberative judgement as a key competence in the post-Covid educational environment..

Influencing student academic integrity choices using ethics scenarios. (2022)
Conference Proceeding
DANIELS, M., BERGLUND, A. and MCDERMOTT, R. 2022. Influencing student academic integrity choices using ethics scenarios. In Proceedings of the 2022 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2022), 8-11 October 2022, Uppsala, Sweden. Piscataway: IEEE [online], article 9962607. Available from: https://doi.org/10.1109/FIE56618.2022.9962607

Academic misconduct seems to have increased substantially during the pandemic, with a worldwide upsurge in reported cases. The aim of this project is to construct a framework for helping students engage with issues concerning academic integrity and a... Read More about Influencing student academic integrity choices using ethics scenarios..

Crowdsourced quality assessment of enhanced underwater images: a pilot study. (2022)
Conference Proceeding
LIN, H., MEN, H., YAN, Y., REN, J. and SAUPE, D. 2022. Crowdsourced quality assessment of enhanced underwater images: a pilot study. In Proceedings of 14th International conference on quality of multimedia experience 2022 (QoMEX 2022), 5-7 September 2022, Lippstadt, Germany. Piscataway: IEEE [online], article 9900904. Available from: https://doi.org/10.1109/QoMEX55416.2022.9900904

Underwater image enhancement (UIE) is essential for a high-quality underwater optical imaging system. While a number of UIE algorithms have been proposed in recent years, there is little study on image quality assessment (IQA) of enhanced underwater... Read More about Crowdsourced quality assessment of enhanced underwater images: a pilot study..

Machine learning approach to predict mental distress of IT workforce in remote working environments. (2022)
Conference Proceeding
GAMAGE, S.N. and ASANKA, P.P.G.D. 2022. Machine learning approach to predict mental distress of IT workforce in remote working environments. In Proceedings of 2022 International research conference on Smart computing and systems engineering (SCSE 2022), 1 September 2022, Colombo, Sri Lanka. Hosted on IEEE [online], pages 211-216. Available from: https://doi.org/10.1109/scse56529.2022.9905229

When considering online workers, due to the emergence of the coronavirus pandemic prevailing in the world, employees have been restricted to work remotely for a prolonged period. All the working arrangements are now based at home than before. Since t... Read More about Machine learning approach to predict mental distress of IT workforce in remote working environments..

Deep learning based short-term total cloud cover forecasting. (2022)
Conference Proceeding
BANDARA, I., ZHANG, L. and MISTRY, K. 2022. Deep learning based short-term total cloud cover forecasting. In Proceedings of the 2022 International joint conference on neural networks (IJCNN 2022), co-located with the 2022 conference proceedings of Institute of Electrical and Electronics Engineers (IEEE) World congress on computational intelligence (IEEE WCCI 2022), 18-23 July 2022, Padua, Italy. Piscataway: IEEE [online], article 9892773. Available from: https://doi.org/10.1109/IJCNN55064.2022.9892773

In this research, we conduct deep learning based Total Cloud Cover (TCC) forecasting using satellite images. The proposed system employs the Otsu's method for cloud segmentation and Long Short-Term Memory (LSTM) variant models for TCC prediction. Spe... Read More about Deep learning based short-term total cloud cover forecasting..

CBR for interpretable response selection in conversational modelling. (2022)
Conference Proceeding
SURESH, M. 2022. CBR for interpretable response selection in conversational modelling. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 28-33. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper25.pdf

Current state-of-the-art dialogue systems are increasingly complex. When used in applications such as motivational interviewing, the lack of interpretability is a concern. CBR offers to bridge this gap by using the most similar past cases to decide t... Read More about CBR for interpretable response selection in conversational modelling..

Explaining and upsampling anomalies in time-series sensor data. (2022)
Conference Proceeding
PIRIE, C. 2022. Explaining and upsampling anomalies in time-series sensor data. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 16-21. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper13.pdf

The aims of this research was to improve anomaly detection methods in multi-sensor data by extending current re-sampling and explanation methods to work in a time-series setting. While there is a plethora of literature surrounding XAI for tabular dat... Read More about Explaining and upsampling anomalies in time-series sensor data..

Addressing trust and mutability issues in XAI utilising case based reasoning. (2022)
Conference Proceeding
SALIMI, P. 2022. Addressing trust and mutability issues in XAI utilising case based reasoning. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 22-27. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper19.pdf

Explainable AI (XAI) research is required to ensure that explanations are human readable and understandable. The present XAI approaches are useful for observing and comprehending some of the most important underlying properties of any Black-box AI mo... Read More about Addressing trust and mutability issues in XAI utilising case based reasoning..

Cross domain evaluation of text detection models. (2022)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCÍA, C. and JAYNE, C. 2022. Cross domain evaluation of text detection models. In Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A. and Aydin, M. (eds.) Artificial neural networks and machine learning - ICANN 2022: proceedings of the 31st International conference on artificial neural networks (ICANN 2022), 6-9 September 2022, Bristol, UK, part III. Lecture notes in computer science, 13531. Cham: Springer [online], pages 50-61. Available from: https://doi.org/10.1007/978-3-031-15934-3_5

Text detection is a very common task across a wide range of domains, such as document image analysis, remote identity verification, amongst others. It is also considered an integral component of any text recognition system, where the performance of r... Read More about Cross domain evaluation of text detection models..

Reconsidering RepStat rules in dialectic games. (2022)
Conference Proceeding
WELLS, S. and SNAITH, M. 2022. Reconsidering RepStat rules in dialectical games. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Proceedings of the 22nd Workshop on computational models of natural argument (CMNA 2022), 12 September 2022, Cardiff, UK. CEUR workshop proceedings, 3205. Aachen: CEUR-WS [online], pages 18-28. Available from: http://ceur-ws.org/Vol-3205/paper3.pdf

Prohibition of repeated statements has benefits for the tractability and predictability of dialogues carried out by machines, but doesn't match the real world behaviour of people. This gap between human and machine behaviour leads to problems when fo... Read More about Reconsidering RepStat rules in dialectic games..

A case-based approach for content planning in data-to-text generation. (2022)
Conference Proceeding
UPADHYAY, A. and MASSIE, S. 2022. A case-based approach for content planning in data-to-text generation. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 380-394. Available from: https://doi.org/10.1007/978-3-031-14923-8_25

The problem of Data-to-Text Generation (D2T) is usually solved using a modular approach by breaking the generation process into some variant of planning and realisation phases. Traditional methods have been very good at producing high quality texts b... Read More about A case-based approach for content planning in data-to-text generation..

How close is too close? Role of feature attributions in discovering counterfactual explanations. (2022)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., NKISI-ORJI, I., PALIHAWADANA, C., CORSAR, D. and MARTIN, K. 2022. How close is too close? Role of feature attributions in discovering counterfactual explanations. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 33-47. Available from: https://doi.org/10.1007/978-3-031-14923-8_3

Counterfactual explanations describe how an outcome can be changed to a more desirable one. In XAI, counterfactuals are "actionable" explanations that help users to understand how model decisions can be changed by adapting features of an input. A cas... Read More about How close is too close? Role of feature attributions in discovering counterfactual explanations..

Adapting semantic similarity methods for case-based reasoning in the Cloud. (2022)
Conference Proceeding
NKISI-ORJI, I., PALIHAWADANA, C., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2022. Adapting semantic similarity methods for case-based reasoning in the Cloud. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 125-139. Available from: https://doi.org/10.1007/978-3-031-14923-8_9

CLOOD is a cloud-based CBR framework based on a microservices architecture, which facilitates the design and deployment of case-based reasoning applications of various sizes. This paper presents advances to the similarity module of CLOOD through the... Read More about Adapting semantic similarity methods for case-based reasoning in the Cloud..

Analysing the fitness landscape rotation for combinatorial optimisation. (2022)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2022. Analysing the fitness landscape rotation for combinatorial optimisation. In Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G. and Tušar, T. (eds.) Parallel problem solving from nature (PPSN XVII): proceedings of 17th Parallel problem solving from nature international conference 2022 (PPSN 2022), 10-14 September 2022, Dortmund, Germany. Lecture notes in computer science, 13398. Cham: Springer [online], pages 533-547. Available from: https://doi.org/10.1007/978-3-031-14714-2_37

Fitness landscape rotation has been widely used in the field of dynamic combinatorial optimisation to generate test problems with academic purposes. This method changes the mapping between solutions and objective values, but preserves the structure o... Read More about Analysing the fitness landscape rotation for combinatorial optimisation..