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DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. (2021)
Conference Proceeding
WIRATUNGA, N., WIJEKOON, A., NKISI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. To be presented at 33rd IEEE (Institute of Electrical and Electronics Engineers) International conference on tools with artificial intelligence 2021 (ICTAI 2021), 1-3 November 2021, [virtual conference].

Counterfactual explanations focus on 'actionable knowledge' to help end-users understand how a machine learning outcome could be changed to a more desirable outcome. For this purpose a counterfactual explainer needs to discover input dependencies tha... Read More about DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods..

A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. (2021)
Conference Proceeding
TORAL, L., MORENO-GARCIA, C.F., ELYAN, E. and MEMON, S. 2021. A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. In Barney Smith, E.H. and Pal, U. (eds.) Document analysis and recognition: ICDAR 2021 workshops, part II: proceedings of 16th International conference on document analysis and recognition 2021 (ICDAR 2021), 5-10 September 2021, Lausanne, Switzerland. Lecture notes in computer science, 12917. Cham: Springer [online], pages 268-276. Available from: https://doi.org/10.1007/978-3-030-86159-9_18

Corrosion circuit mark up in engineering drawings is one of the most crucial tasks performed by engineers. This process is currently done manually, which can result in errors and misinterpretations depending on the person assigned for the task. In th... Read More about A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams..

Towards explainable metaheuristics: PCA for trajectory mining in evolutionary algorithms. (2021)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W. and CHRISTIE, L.A. [2021]. Towards explainable metaheuristics: PCA for trajectory mining in evolutionary algorithms. To be presented at 41st British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2021 (AI-2021), 14-16 December 2021, [virtual conference].

The generation of explanations regarding decisions made by population-based meta-heuristics is often a difficult task due to the nature of the mechanisms employed by these approaches. With the increase in use of these methods for optimisation in indu... Read More about Towards explainable metaheuristics: PCA for trajectory mining in evolutionary algorithms..

Predicting multicomponent gas transport in hybrid inorganic membranes. (2021)
Conference Proceeding
GOBINA, E., SHEHU, H. and ORAKWE, I. 2021. Predicting multicomponent gas transport in hybrid inorganic membranes. In Proceedings of the ICANM 2021: 8th International conference and exhibition on advanced and nanomaterials 2021 (ICANM 2021), 9-11 August 2021, [virtual conference]. Ontario: ICANM, pages 47-56.

A repeated dip-coating technique has been used to prepare novel inorganic multilayered membranes. The membranes have been characterizated by Scanning Electron Microscopy (SEM) and nitrogen adsorption (ASAP 2010) respectively. The three-parameter mode... Read More about Predicting multicomponent gas transport in hybrid inorganic membranes..

The effect of pressure and porous media structural parameters coupling on gas apparent viscosity. (2021)
Conference Proceeding
ABUNUMAH, O., OGUNLUDE, P. and GOBINA, E. 2021. The effect of pressure and porous media structural parameters coupling on gas apparent viscosity. In Proceedings of the ICANM 2021: 8th International conference and exhibition on advanced and nanomaterials 2021 (ICANM 2021), 9-11 August 2021, [virtual conference]. Ontario: ICANM, pages 42-46.

Crude oil production is still considered a significant contributor to global energy security. To improve oil production, gases such as CH4, N2, Air and CO2 are injected into oil reservoirs in a process called gas Enhanced Oil Recovery (EOR). Authors... Read More about The effect of pressure and porous media structural parameters coupling on gas apparent viscosity..

A study of biogas upgrading to bio-methane with carbon dioxide capture using ceramic membranes. (2021)
Conference Proceeding
OGUNLUDE, P., ABUNUMAH, O., MOHAMMAD-SUKKI, F. and GOBINA, E. 2021. A study of biogas upgrading to bio-methane with carbon dioxide capture using ceramic membranes. In Proceedings of the ICANM 2021: 8th International conference and exhibition on advanced and nanomaterials 2021 (ICANM 2021), 9-11 August 2021, [virtual conference]. Ontario: IAEMM, pages 27-33.

Greenhouse gas emissions (GHGs) and their effects have been a matter of global concern over the past decade. With growing energy demands to support developing economies, there has been a challenge of harnessing and utilizing sustainable forms of ener... Read More about A study of biogas upgrading to bio-methane with carbon dioxide capture using ceramic membranes..

Characterization and evaluation of nanoparticles ceramic membrane for the separation of oil-in-water emulsion. (2021)
Conference Proceeding
AISUENI, F.A., OGUON, E., HASHIM, I. and GOBINA, E. 2021. Characterization and evaluation of nanoparticles ceramic membrane for the separation of oil-in-water emulsion. In Proceedings of the ICANM 2021: 8th International conference and exhibition on advanced and nanomaterials 2021 (ICANM 2021), 9-11 August 2021, [virtual conference]. Ontario: ICANM, pages 17-26.

The mixture of oil with water from industrial activities creates an emulsion which is now termed as Oil-in-Water (O/W) emulsion. Several chemical and physical methods have been successfully used for the separation of O/W emulsions; however, the trace... Read More about Characterization and evaluation of nanoparticles ceramic membrane for the separation of oil-in-water emulsion..

Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. (2021)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2021. Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. In Chicano, F. (ed.) GECCO '21: proceedings of 2021 Genetic and evolutionary computation conference companion, 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 1405-1413. Available from: https://doi.org/10.1145/3449726.3463139

Recent work in combinatorial optimisation have demonstrated that neighbouring solutions of a local optima may belong to more favourable attraction basins. In this sense, the perturbation strategy plays a critical role on local search based algorithms... Read More about Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem..

Experiences of piloting the learning by developing action model in a computing science context. (2021)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2021. Experiences of piloting the learning by developing action model in a computing science context. In Gómez Chova, L., López Martínez, A. and Candel Torres, I. (eds.) EDULEARN 21: proceedings of the 13th international conference on Education and new learning technologies 2021 (EDULEARN 2021), 5-6 July 2021, [virtual conference]. Valencia: International Academy of Technology, Education and Development (IATED) [online], pages 3036-3042. To be available from: https://doi.org/10.21125/edulearn.2021

This article describes the piloting of the Learning by Developing (LbD) action model in the UK. The purpose of the pilot is to study how a pedagogical method based on the LbD can be introduced in computing students in the UK. The LbD action model has... Read More about Experiences of piloting the learning by developing action model in a computing science context..

Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. (2021)
Conference Proceeding
DANG, T., NGUYEN, T.T., MORENO-GARCIA, C.F., ELYAN, E. and MCCALL, J. 2021. Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. In Proceeding of 2021 IEEE (Institute of electrical and electronics engineers) Congress on evolutionary computation (CEC 2021), 28 June - 1 July 2021, [virtual conference]. Piscataway: IEEE [online], pages 744-751. Available from: https://doi.org/10.1109/CEC45853.2021.9504929

In recent years, deep learning has rapidly becomea method of choice for segmentation of medical images. Deep neural architectures such as UNet and FPN have achieved high performances on many medical datasets. However, medical image analysis algorithm... Read More about Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation..

Face detection with YOLO on edge. (2021)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCIA, C.F. and ZWIEGELAAR, J. 2021. Face detection with YOLO on edge. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Enginering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 284-292. Available from: https://doi.org/10.1007/978-3-030-80568-5_24

Significant progress has been achieved in objects detection applications such as Face Detection. This mainly due to the latest development in deep learning-based approaches and especially in the computer vision domain. However, deploying deep-learnin... Read More about Face detection with YOLO on edge..

Image pre-processing and segmentation for real-time subsea corrosion inspection. (2021)
Conference Proceeding
PIRIE, C. and MORENO-GARCIA, C.F. 2021. Image pre-processing and segmentation for real-time subsea corrosion inspection. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Enginering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 220-231. Available from: https://doi.org/10.1007/978-3-030-80568-5_19

Inspection engineering is a highly important field in the Oil & Gas sector for analysing the health of offshore assets. Corrosion, a naturally occurring phenomenon, arises as a result of a chemical reaction between a metal and its environment, causin... Read More about Image pre-processing and segmentation for real-time subsea corrosion inspection..

Educational landscapes during and after COVID-19. (2021)
Conference Proceeding
SIEGEL, A.A., ZARB, M., ALSHAIGY, B., BLANCHARD, J., CRICK, T., GLASSEY, R., HOTT, J.R., LATULIPE, C., RIEDESEL, C., SENAPATHI, M., SIMON. and WILLIAMS, D. 2021. Educational landscapes during and after COVID-19. In Proceedings of the 26th Association for Computing Machinery (ACM) Innovation and technology in computer science education conference 2021 (ITiCSE '21), 26 June - 1 July 2021, [virtual conference]. New York: ACM [online], pages 597-598. Available from: https://doi.org/10.1145/3456565.3461439

The coronavirus (COVID-19) pandemic has forced an unprecedented global shift within higher education in the ways that we communicate with and educate students. This necessary paradigm shift has compelled educators to take a critical look at their tea... Read More about Educational landscapes during and after COVID-19..

Evaluating the learning by development action model with CS students. (2021)
Conference Proceeding
LINTILÄ, T. 2021. Evaluating the learning by development action model with CS students. In Proceedings of the 26th Association for Computing Machinery (ACM) Innovation and technology in computer science education conference 2021 (ITiCSE '21), 26 June - 1 July 2021, [virtual conference]. New York: ACM [online], pages 670-671. Available from: https://doi.org/10.1145/3456565.3460020

The purpose of the study is to find out how the competence of computing students develops throughout a study module as they are exposed to a Learning by Developing (LbD) Action Model. Furthermore, their perception of the model is evaluated against ex... Read More about Evaluating the learning by development action model with CS students..

Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. (2021)
Conference Proceeding
LIEFOOGHE, A., VEREL, S., LACROIX, B., ZĂVOIANU, A.-C. and MCCALL, J. 2021. Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. In Chicano, F. (ed) Proceedings of 2021 Genetic and evolutionary computation conference (GECCO 2021), 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 421-429. Available from: https://doi.org/10.1145/3449639.3459353

In this paper, we demonstrate the application of features from landscape analysis, initially proposed for multi-objective combinatorial optimisation, to a benchmark set of 1 200 randomly-generated multiobjective interpolated continuous optimisation p... Read More about Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems..

EV specific time-of-use rates analysis for workplace charging. (2021)
Conference Proceeding
KUCUKSARI, S. and ERDOGAN, N. 2021. EV specific time-of-use rates analysis for workplace charging. In Proceedings of 2021 IEEE (Institute of Electrical and Electronics Engineers) Transportation electrification conference (ITEC 2021), 21-25 June 2021, [virtual conference]. Piscataway: IEEE [online], pages 783-788. Available from: https://doi.org/10.1109/itec51675.2021.9490039

EV specific time-of-use rate plans have been recently introduced by several utilities to overcome the demand charge issue that is the main barrier impeding EV growth in the commercial and industrial sector. This study analyses two EV specific TOU rat... Read More about EV specific time-of-use rates analysis for workplace charging..

Indoor characterisation of a reverse truncated pyramid concentrator. (2021)
Conference Proceeding
TAMUNO-IBUOMI, L.O., MUHAMMAD-SUKKI, F., RAMIREZ-INIGUEZ, R., ARDILA-REY, J.A., ABU-BAKAR, S.H., BANI, N.A., SEE, C.H., FAISAL, N.H. and SELLAMI, N. 2021. Indoor characterisation of a reverse truncated pyramid concentrator. In Proceedings of 48th Institute of Electrical and Electronics Engineers (IEEE) Photovoltaic specialists 2021 (PVSC48), 20-25 June 2021, [virtual conference]. Piscataway: IEEE [online], pages 2348-2350. Available from: https://doi.org/10.1109/PVSC43889.2021.9518741

The development of concentrating photovoltaic (PV) started in 1960s and over the years, a variety of concentrator designs have been explored. One of its applications is for use in building integrated photovoltaic (BIPV) with the aim of producing a ch... Read More about Indoor characterisation of a reverse truncated pyramid concentrator..

Designing laboratory experiments for electricity grid integration of renewable energy using microgrid, test-rig emulators and real time simulation tools. (2021)
Conference Proceeding
MURRAY, D.B., ERDOGAN, N., ZEHIR, A. and HAYES, B.P. 2021. Designing laboratory experiments for electricity grid integration of renewable energy using microgrid, test-rig emulators and real time simulation tools. In Proceedings of the 10th Engineering education for sustainable development conference 2021 (EESD2021): building flourishing communities, 14-16 June 2021, Cork Ireland. Cork: University College Cork, pages 380-387. Hosted on CORA [online]. Available from: https://cora.ucc.ie/handle/10468/11674

This paper describes efforts to integrate advanced approaches in microgrid, test-rig emulators and real time simulation into early postgraduate and undergraduate engineering education. It describes two experiments designed for groups of early stage r... Read More about Designing laboratory experiments for electricity grid integration of renewable energy using microgrid, test-rig emulators and real time simulation tools..

Non-deterministic solvers and explainable AI through trajectory mining. (2021)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W. and CHRISTIE, L.A. 2021. Non-deterministic solvers and explainable AI through trajectory mining. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 4, pages 75-78. Available from: http://ceur-ws.org/Vol-2894/poster2.pdf

Traditional methods of creating explanations from complex systems involving the use of AI have resulted in a wide variety of tools available to users to generate explanations regarding algorithm and network designs. This however has traditionally bee... Read More about Non-deterministic solvers and explainable AI through trajectory mining..

Counterfactual explanations for student outcome prediction with Moodle footprints. (2021)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., NKILSI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Counterfactual explanations for student outcome prediction with Moodle footprints. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 1, pages 1-8. Available from: http://ceur-ws.org/Vol-2894/short1.pdf

Counterfactual explanations focus on “actionable knowledge” to help end-users understand how a machine learning outcome could be changed to one that is more desirable. For this purpose a counterfactual explainer needs to be able to reason with simila... Read More about Counterfactual explanations for student outcome prediction with Moodle footprints..