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On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. (2022)
Conference Proceeding
HAN, K., CHRISTIE, L.A., ZAVOIANU, A.-C. and MCCALL, J. 2022. On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 104-111. Available from: https://doi.org/10.1007/978-3-031-25312-6_12

While self-driving technology is still being perfected, public transport authorities are increasingly interested in the ability to model and optimise the benefits of adding connected and autonomous vehicles (CAVs) to existing multi-modal transport sy... Read More about On discovering optimal trade-offs when introducing new routes in existing multi-modal public transport systems..

Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation. (2022)
Conference Proceeding
ZAVOIANU, A.-C., LACROIX, B. and MCCALL, J. 2022. Lightweight Interpolation-based surrogate modelling for multiobjective continuous optimisation. In Moreno-Díaz, R., Pichler, F. and Quesada-Arencibia, A. (eds.) Computer aided systems theory: Eurocast 2022; revised selected papers from the 18th International conference on computer aided systems theory (Eurocast 2022), 20-25 February 2022, Las Palmas, Spain. Lecture notes in computer science, 13789. Cham: Springer [online], pages 53-60. Available from: https://doi.org/10.1007/978-3-031-25312-6_6

We propose two surrogate-based strategies for increasing the convergence speed of multi-objective evolutionary algorithms (MOEAs) by stimulating the creation of high-quality individuals early in the run. Both offspring generation strategies are desig... Read More about Lightweight interpolation-based surrogate modelling for multi-objective continuous optimisation..

Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search. (2022)
Conference Proceeding
RICA, E., ALVAREZ, S., MORENO-GARCIA, C.F. and SERRATOSA, F. 2022. Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search. In Krzyzak, A., Suen, C.Y., Torsello, A. and Nobile, N. (eds.) Structural, syntactic, and statistical pattern recognition: proceedings of the 2022 Joint International Association for Pattern Recognition (IAPR) international workshops on statistical techniques in pattern recognition, and structural and syntactic pattern recognition (S+SSPR 2022), 26-27 August 2022, Montréal, Canada. Lecture notes in computer science, 13813. Cham: Springer [online], pages 274-282. Available from: https://doi.org/10.1007/978-3-031-23028-8_28

Thousands of huge printed sheets depicting engineering drawings keep record of complex industrial structures from Oil & Gas facilities. Currently, there is a trend of digitising these drawings, having as final end the regeneration of the original com... Read More about Zero-error digitisation and contextualisation of piping and instrumentation diagrams using node classification and sub-graph search..

The impact of COVID-19 on the CS student learning experience: how the pandemic has shaped the educational landscape. (2022)
Conference Proceeding
SIEGEL, A.A., ZARB, M., ANDERSON, E., CRANE, B., GAO, A., LATULIPE, C., LOVELLETTE, E., MCNEILL, F. and MEHARG, D. 2022. The impact of COVID-19 on the CS student learning experience: how the pandemic has shaped the educational landscape. In ITiCSE-WGR'22: proceedings of the 2022 Working group reports (WGR), co-located with the 27th Innovation and technology in computer science education annual conference (ITiCSE-WGR '22), 11-13 July 2022, Dublin, Ireland. New York: ACM [online], pages 165-190. Available from: https://doi.org/10.1145/3571785.3574126

Students have experienced incredible shifts in their learning environments, brought about by the response of universities to the ever-changing public health mandates driven by waves and stages of the coronavirus pandemic (COVID-19). Initially, these... Read More about The impact of COVID-19 on the CS student learning experience: how the pandemic has shaped the educational landscape..

Mobile Platform for livestock monitoring and inspection. (2022)
Conference Proceeding
FABIYI, S.D., REN, J., HAN, Y., ZHU, Q. and BARCLAY, D. 2022. Mobile platform for livestock monitoring and inspection. In Proceedings of the 3rd International informatics and software engineering conference 2022 (IISEC 2022), 15-16 December 2022, Ankara, Turkey. Piscataway: IEEE [online], article 9998279. Available from: https://doi.org/10.1109/iisec56263.2022.9998297

Livestock keepers acquire and manage information (e.g. identification numbers, images, etc.) about livestock to identify and keep track of livestock using systems with capabilities to extract such information. Examples of such systems are Radio Frequ... Read More about Mobile Platform for livestock monitoring and inspection..

GEMv2: multilingual NLG benchmarking in a single line of code. (2022)
Conference Proceeding
GEHRMANN, S., BHATTACHARJEE, A., MAHENDIRAN, A., WANG, A., PAPANGELIS, A., MADAAN, A., MCMILLAN-MAJOR, A., SHVETS, A., UPADHYAY, A. and BOHNET, B. 2022. GEMv2: multilingual NLG benchmarking in a single line of code. In Proceedings of the 2022 Conference on Empirical methods in natural language processing: system demonstrations, 7-11 December 2022, Abu Dhabi, UAE. Stroudsburg: Association for Computational Linguistics [online], pages 266-281. Available from: https://aclanthology.org/2022.emnlp-demos.27/

Evaluations in machine learning rarely use the latest metrics, datasets, or human evaluation in favor of remaining compatible with prior work. The compatibility, often facilitated through leaderboards, thus leads to outdated but standardized evaluati... Read More about GEMv2: multilingual NLG benchmarking in a single line of code..

Resource efficient federated deep learning for IoT security monitoring. (2022)
Conference Proceeding
ZAKARIYYA, I., KALUTARAGE, H. and AL-KADRI, M.O. 2022. Resource efficient federated deep learning for IoT security monitoring. In Li, W., Furnell, S. and Meng, W. (eds.) Attacks and defenses for the Internet-of-Things: revised selected papers from the 5th International workshop on Attacks and defenses for Internet-of-Things 2022 (ADIoT 2022), in conjunction with 27th European symposium on research in computer security 2022 (ESORICS 2022) 29-30 Septempber 2022, Copenhagen, Denmark. Lecture notes in computer science (LNCS), 13745. Cham: Springer [online], pages 122-142. Available from: https://doi.org/10.1007/978-3-031-21311-3_6

Federated Learning (FL) uses a distributed Machine Learning (ML) concept to build a global model using multiple local models trained on distributed edge devices. A disadvantage of the FL paradigm is the requirement of many communication rounds before... Read More about Resource efficient federated deep learning for IoT security monitoring..

Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. (2022)
Conference Proceeding
DANG, T., NGUYEN, T.T., MCCALL, J. and LIEW, A.W.-C. 2022. Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation. In Ishibuchi, H., Kwoh, C.-K., Tan, A.-H., Srinivasan, D., Miao, C., Trivedi, A. and Crockett, K. (eds.) Proceedings of the 2022 IEEE Symposium series on computational intelligence (SSCI 2022), 4-7 December 2022, Singapore. Piscataway: IEEE [online], pages 269-276. Available from: https://doi.org/10.1109/SSCI51031.2022.10022114

Segmentation, a process of partitioning an image into multiple segments to locate objects and boundaries, is considered one of the most essential medical imaging process. In recent years, Deep Neural Networks (DNN) have achieved many notable successe... Read More about Ensemble learning based on classifier prediction confidence and comprehensive learning particle swarm optimisation for medical image segmentation..

Job assignment problem and traveling salesman problem: a linked optimisation problem. (2022)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2022. Job assignment problem and traveling salesman problem: a linked optimisation problem. In Bramer, M. and Stahl, F (eds.) Artificial intelligence XXXIX: proceedings of the 42nd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2022 (AI 2022), 13-15 December 2022, Cambridge, UK. Lecture notes in computer science (LNCS), 13652. Cham: Springer [online], pages 19-33. Available from: https://doi.org/10.1007/978-3-031-21441-7_2

Linked decision-making in service management systems has attracted strong adoption of optimisation algorithms. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems. This paper, theref... Read More about Job assignment problem and traveling salesman problem: a linked optimisation problem..

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..

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..

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..

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..

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..

Explainable weather forecasts through an LSTM-CBR twin system. (2022)
Conference Proceeding
PIRIE, C., SURESH, M., SALIMI, P., PALIHAWADANA, C. and NANAYAKKARA, G. 2022. Explainable weather forecasts through an LSTM-CBR twin system. In Reuss, P. and Schönborn, J. (eds.) ICCBR-WS 2022: proceedings of the 30th International conference on Case-based reasoning workshops 2022 (ICCBR-WS 2022) co-located with the 30th International conference on Case-based reasoning 2022 (ICCBR 2022), 12-15 September 2022, Nancy, France. Aachen: CEUR workshop proceedings [online], 3389, pages 256-260. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_XCBR_Challenge_RGU.pdf

In this paper, we explore two methods for explaining LSTM-based temperature forecasts using previous 14 day progressions of humidity and pressure. First, we propose and evaluate an LSTM-CBR twin system that generates nearest-neighbors that can be vis... Read More about Explainable weather forecasts through an LSTM-CBR twin system..

Introducing Clood CBR: a cloud based CBR framework. (2022)
Conference Proceeding
PALIHAWADANA, C., NKISI-ORJI, I., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2022. Introducing Clood CBR: a cloud based CBR framework. In Reuss, P. and Schönborn, J. (eds.) ICCBR-WS 2022: proceedings of the 30th International conference on Case-based reasoning workshops 2022 (ICCBR-WS 2022) co-located with the 30th International conference on Case-based reasoning 2022 (ICCBR 2022), 12-15 September 2022, Nancy, France. Aachen: CEUR workshop proceedings [online], 3389, pages 233-234. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_Workshop_paper_108.pdf

CBR applications have been deployed in a wide range of sectors, from pharmaceuticals; to defence and aerospace to IoT and transportation, to poetry and music generation; for example. However, a majority of applications have been built using monolithi... Read More about Introducing Clood CBR: a cloud based CBR framework..