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Piloting the learning by developing action model pedagogy in Finland HEIs. (2022)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2022. Piloting the learning by developing action model pedagogy in Finland HEIs. In Chova, L.G., Martínez, A.L. and Lees, J. (eds.) Proceedings of the 15th Annual international conference of education, research and innovation (ICERI2022), 7-9 November 2022, Seville, Spain. Valenca: IATED [online], pages 1856-1865. Available from: https://doi.org/10.21125/iceri.2022.0474

This article describes a study at Haaga-Helia University of Applied Sciences (Haaga-Helia) that aims to understand how suitable the Learning by Developing (LbD) action model is as a teaching and learning method for computing students. The research al... Read More about Piloting the learning by developing action model pedagogy in Finland HEIs..

Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. (2022)
Conference Proceeding
ADEGBOYE, M.A., KARNIK, A., FUNG, W.-K. and PRABHU, R. 2022. Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. In Proceedings of the 9th International conference on soft computing and machine intelligence 2022 (ISCMI 2022), 26-27 November 2022, Toronto, Candada. Piscataway: IEEE [online], pages 129-134. Available from: https://doi.org/10.1109/iscmi56532.2022.10068436

Pipelines are often subject to leakage due to ageing, corrosion, and weld defects, and it is difficult to avoid as the sources of leakages are diverse. Several studies have demonstrated the applicability of the machine learning model for the timely p... Read More about Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation..

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..

Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares. (2022)
Conference Proceeding
LIANG, Y., WANG, S., FAN, Y., YANG, X., XIE, Y. and FERNANDEZ, C. 2022. Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares. In Proceedings of the 4th Smart power and internet energy systems international conference 2022 (SPIES 2022): towards a net-zero carbon future, 9-12 December 2022, Beijing, China. Piscataway: IEEE [online], pages 1923-1927. Available from https://doi.org/10.1109/spies55999.2022.10082478

This work aims to improve the accuracy of state of charge estimation for lithium-ion battery, as well as to accurately estimate state of health. This study presents a piecewise forgetting factor recursive least squares method based on integral separa... Read More about Joint state of charge and state of health estimation of lithium-ion battery using improved adaptive dual extended Kalman filter based on piecewise forgetting factor recursive least squares..

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..

Characteristics of gas transport through inorganic ceramic membranes as porous media using air and nitrogen. (2022)
Conference Proceeding
IGBAGARA, W., HASHM, I.A., AISUENI, F., OGUNLUDE, P., RAMALAN, M., OGOUN, E., ASIM, T. and GOBINA, E. 2022. Characteristics of gas transport through inorganic ceramic membranes as porous media using air and nitrogen. In Proceedings of the 2nd International congress on scientific advances 2022 (ICONSAD'22), 21-24 December 2022, [virtual conference]. Turkey: ICONSAD [online], pages 417-425. Available from: https://en.iconsad.org/_files/ugd/1dd905_c45aeddf416d497e93113f00f465739b.pdf

Permeation experiments have been conducted using porous ceramic membranes having different pore sizes of 200nm and 6000nm respectively. Air and N2 gases were used as the characterizing fluids and experiments were carried out at temperatures of 20 C,... Read More about Characteristics of gas transport through inorganic ceramic membranes as porous media using air and nitrogen..

Knudsen number sensitivity to pressure drop in a nanoscale membrane. (2022)
Conference Proceeding
RAMALAN, M.M., PRABHU, R., HASHM, I., OGUNLUDE, P., AISUENI, F., ABUNOMAH, O. and GOBINA, E. 2022. Knudsen number sensitivity to pressure drop in a nanoscale membrane. In Proceedings of the 2nd International congress on scientific advances 2022 (ICONSAD'22), 21-24 December 2022, [virtual conference]. Turkey: ICONSAD [online], pages 276-281. Available from: https://en.iconsad.org/_files/ugd/1dd905_c45aeddf416d497e93113f00f465739b.pdf

According to the kinetic theory of gases, gas molecules are in constant random motion and frequently collide with one another and with the walls of their container. They continuously experience changes in velocity and direction. Between collisions, m... Read More about Knudsen number sensitivity to pressure drop in a nanoscale membrane..

Gas diffusion, transport characteristics and modelling in porous membrane systems with application for polymer electrolyte membrane fuel cells. (2022)
Conference Proceeding
AISUENI, F., RAMALAN, M., ABUNUMAH, O., OGUNLUDE, P., ORAKWE, I., OGOUN, E., GIWA, A., SHEHU, H. and GOBINA, E. 2022. Gas diffusion, transport characteristics and modelling in porous membrane systems with application for polymer electrolyte membrane fuel cells. In Proceedings of the 2nd International congress on scientific advances 2022 (ICONSAD'22), 21-24 December 2022, [virtual conference]. Turkey: ICONSAD [online], pages 144-157. Available from: https://en.iconsad.org/_files/ugd/1dd905_c45aeddf416d497e93113f00f465739b.pdf

Fuel cells convert chemical energy in electrical energy and heat by consuming typically hydrogen and oxygen and producing water as the main by-product. This is achieved by reducing hydrogen at the anode (left hand side) and oxidising oxygen at the ca... Read More about Gas diffusion, transport characteristics and modelling in porous membrane systems with application for polymer electrolyte membrane fuel cells..

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..

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..

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..