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Piloting the learning by developing action model pedagogy in Finland HEIs. (2022)
Presentation / Conference Contribution
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..

Model predictive control of connected spacecraft formation. (2022)
Presentation / Conference Contribution
KANNAN, S., BHOWMICK, P. and ALAMDARI, S.A.S. 2022. Model predictive control of connected spacecraft formation. IFAC papers online [online], 55(22): proceedings of the 22nd IFAC (International Federation of Automatic Control) symposium on Automatic control in aerospace 2022 (ACA 2022), 21-25 November 2022, Mumbai, India, pages 322-327. Available from: https://doi.org/10.1016/j.ifacol.2023.03.054

In this contribution the authors discuss the application of Model Predictive Control (MPC) to achieve a connected network formation of spacecrafts. A set of three spacecrafts are used to achieve in-plane formation which are initially in a connected n... Read More about Model predictive control of connected spacecraft formation..

Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. (2022)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

Microporous alumina–silica composite membrane with very low N2 permeability but high CO2 selectivity for direct air capture. (2022)
Presentation / Conference Contribution
GIWA, A., SHEHU, H., RAMALAN, M., ORAKWE, I., ABUNOMAH, O., OGUNLUDE, P., WILLIAMWEST, T., IGBAGARA, W., OGOUN, E., HASHIM, I., AISUENI, F. and GOBINA, E. 2022. Microporous alumina–silica composite membrane with very low N2 permeability but high CO2 selectivity for direct air capture. In Khan, A.A., Ciddi, M.L. and Unal, M. (eds.) Proceedings of the 2022 International conference on studies in engineering, science and technology (ICSEST 2022), 10-13 November 2022, Antalya, Turkey. Ames, IA: International Society for Technology, Education and Science (ISTES) [online], pages 182-210. Available from: https://www.istes.org/seeder/books/files/54c86815762a9dac0440e35d04a1e05c.pdf

This research involves technical approaches to capture carbon dioxide (CO2) from ambient air, involving a filter with a transport mechanism described based on experimental results. A silica inorganic composite membrane was prepared by using a silicon... Read More about Microporous alumina–silica composite membrane with very low N2 permeability but high CO2 selectivity for direct air capture..

The impact of COVID-19 on the CS student learning experience: how the pandemic has shaped the educational landscape. (2022)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

Effects of titanium oxide and graphene as nano-fillers on the thermal conductivity of biobased phase change materials as latent thermal heat storage. (2022)
Presentation / Conference Contribution
HASBI, S., NORAZMAN, N. and SAHARUDIN, M.S. 2023. Effects of titanium oxide and graphene as nano-fillers on the thermal conductivity of biobased phase change materials as latent thermal heat storage. Materials today: proceedings [online], 75(1): proceedings of the 2022 Innovative manufacturing, mechatronics and material forum (iM3F 2022), pages 181-187. Available from: https://doi.org/10.1016/j.matpr.2022.11.426

Biobased phase change materials (BPCMs) have attracted much attention as they offer proper melting temperature, high heat capacity, non-corrosive, low cost, and are abundantly available. However, the BPCMs have a low thermal conductivity which limits... Read More about Effects of titanium oxide and graphene as nano-fillers on the thermal conductivity of biobased phase change materials as latent thermal heat storage..

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)
Presentation / Conference Contribution
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..

Scalable metamaterial thermally sprayed catalyst coatings for nuclear reactor high temperature solid oxide steam electrolysis. (2022)
Presentation / Conference Contribution
HOSSAIN, M., FAISAL, N., PRATHURU, A., KURUSHINA, V., CAI, Q., HORRI, B. and SOMAN, A. 2022. Scalable metamaterial thermally sprayed catalyst coatings for nuclear reactor high temperature solid oxide steam electrolysis. Presented at the 4th International conference on energy and power 2022 (ICEP2022), 11-13 December 2022, Dhaka, Bangledesh: [virtual conference].

The UK government in their 2021 Hydrogen Strategy recognises that the low carbon hydrogen plays a critical role in achieving transition to net zero and sets a target of 5GW of low carbon hydrogen production capacity by 2030 for use across the economy... Read More about Scalable metamaterial thermally sprayed catalyst coatings for nuclear reactor high temperature solid oxide steam electrolysis..

GEMv2: multilingual NLG benchmarking in a single line of code. (2022)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

Reconfigured metallic membrane technology for maintaining hydrogen concentration below 4% in fuel debris canisters. (2022)
Presentation / Conference Contribution
SHEHU, H., ORAKWE, I., ABUNOMAH, O., OGUNLUDE, P., RAMALAN, M., WILLIAMWEST, T., IGBAGARA, W., OGOUN, E., HASHIM, I., AISUENI, F. and GOBINA, E. 2022. Reconfigured metallic membrane technology for maintaning hydrogen concentration below 4% in fuel debris canisters. In Dincer, I., Ratlamwala, T.A.H. and Kamal, K. (eds.) Proceedings of the 13th International conference on hydrogen production (ICH2P 2022): hydrogen for a green future, 11-14 December 2022, [virtual event]. Hosted on ICH2P [online], pages 237-239. Available from: http://www.ich2p.org/wp-content/uploads/2023/01/Conference-Proceedings.pdf

The use of hydrogen in the energy sector has been in the headlines in recent times, due to its promising future as a replacement for fossil fuels; it can be produced sustainably from a wide variety of feedstocks, including traditional hydrocarbons de... Read More about Reconfigured metallic membrane technology for maintaining hydrogen concentration below 4% in fuel debris canisters..

Dense metallic membranes for high-density hydrogen production from different feedstocks for PEM fuel cells power generation. (2022)
Presentation / Conference Contribution
SHEHU, H., ORAKWE, I., ABUNOMAH, O., OGUNLUDE, P., RAMALAN, M., WILLIAMWEST, T., IGBAGARA, W., OGOUN, E., HASHIM, I., AISUENI, F. and GOBINA, E. 2022. Dense metallic membranes for high-density hydrogen production from different feedstocks for PEM fuel cells power generation. In Dincer, I., Ratlamwala, T.A.H. and Kamal, K. (eds.) Proceedings of the 13th International conference on hydrogen production (ICH2P 2022): hydrogen for a green future, 11-14 December 2022, [virtual event]. Hosted on ICH2P [online], pages 203-205. Available from: http://www.ich2p.org/wp-content/uploads/2023/01/Conference-Proceedings.pdf

The International Electrotechnical Commission (IEC), through Technical Committee 105 Fuel Cell Technologies, prepares international standards regarding fuel cell technologies for all fuel types and various associated applications, such as: stationary... Read More about Dense metallic membranes for high-density hydrogen production from different feedstocks for PEM fuel cells power generation..

Characteristics of gas transport through inorganic ceramic membranes as porous media using air and nitrogen. (2022)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..