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Chemical detection of explosives in soil for locating buried landmines. (2021)
Conference Proceeding
KARNIK, S. and PRABHU, R. 2021. Chemical detection of explosives in soil for locating buried landmines. In Bouma, H., Prabhu, R., Stokes, R.J. and Yitzhaky, Y. (eds.) Proceedings of the 5th Counterterrorism, crime fighting, forensics, and surveillance technologies conference, part of the 2021 SPIE Security + defence conference, 13-17 September 2021, [virtual conference]. Proceedings of SPIE, 11869. Bellingham, WA: SPIE [online], article ID 118690A. Available from: https://doi.org/10.1117/12.2601741

Trinitrotoluene (TNT) is a highly explosive nitroaromatic compound that is used for military and terrorist activities such as the development of improvised explosive devices (IEDs), landmines and is the main charge or explosive in most of the anti-pe... Read More about Chemical detection of explosives in soil for locating buried landmines..

A case-based approach to data-to-text generation. (2021)
Conference Proceeding
UPADHYAY, A., MASSIE, S., SINGH, R.K., GUPTA, G. and OJHA, M. 2021. A case-based approach to data-to-text generation. In Sánchez-Ruiz, A.A. and Floyd, M.W. (eds.) Case-based reasoning research and development: proceedings of 29th International conference case-based reasoning 2021 (ICCBR 2021), 13-16 September 2021, Salamanca, Spain. Lecture notes in computer science (LNCS), 12877. Cham: Springer [online], pages 232-247. Available from: https://doi.org/10.1007/978-3-030-86957-1_16

Traditional Data-to-Text Generation (D2T) systems utilise carefully crafted domain specific rules and templates to generate high quality accurate texts. More recent approaches use neural systems to learn domain rules from the training data to produce... Read More about A case-based approach to data-to-text generation..

Forensic delay analysis: an investigation of the reasons for disagreements in time-related disputes. (2021)
Conference Proceeding
ATANASOV, V., GREENWOOD, D., THURAIRAJAH, N. and HATCHER, C. 2021. Forensic delay analysis: an investigation of the reasons for disagreements in time-related disputes. In Scott, L., Neilson, C.J. (eds.) Proceedings of 37th ARCOM (Association of Researchers in Construction Management) annual conference 2021: recover, rebuild and renew: shifting mindsets and practices to change the future, 6-7 September 2021, [virtual conference]. Leeds: ARCOM [online], pages 460-469. Available from: http://www.arcom.ac.uk/-docs/proceedings/c53e4fee934df27582826028fc94751f.pdf

Construction project delays are widespread and persistent. Disputes frequently occur, and their complexity and value has produced a role for experts specialising in Forensic Delay Analysis (FDA). Previous literature suggests that the main problem (an... Read More about Forensic delay analysis: an investigation of the reasons for disagreements in time-related disputes..

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 a declarative approach to constructing dialogue games. (2021)
Conference Proceeding
SNAITH, M. and WELLS, S. 2021. Towards a declarative approach to constructing dialogue games. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) 2021. 2021 Computational models of natural argument (CMNA 2021): proceedings of the 21st workshop on Computational models on natural argument, 2-3 September 2021, [virtual conference]. CEUR workshop proceedings, 2937. Aachen: CEUR-WS [online], pages 9-18. Available from: http://ceur-ws.org/Vol-2937/paper2.pdf

In this paper we sketch a new approach to the development of dialogue games that builds upon the knowledge gained from several decades of dialogue game research across a variety of communities and which leverages the capabilities of the Dialogue Game... Read More about Towards a declarative approach to constructing dialogue games..

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..

Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. (2021)
Conference Proceeding
WALL, C., ZHANG, L., YU, Y. and MISTRY, K. 2021. Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533966. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533966

In recent years, a variety of deep learning techniques and methods have been adopted to provide AI solutions to issues within the medical field, with one specific area being audio-based classification of medical datasets. This research aims to create... Read More about Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification..

Class-decomposition and augmentation for imbalanced data sentiment analysis. (2021)
Conference Proceeding
MORENO-GARCIA, C.F., JAYNE, C. and ELYAN, E. 2021. Class-decomposition and augmentation for imbalanced data sentiment analysis. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533603. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533603

Significant progress has been made in the area of text classification and natural language processing. However, like many other datasets from across different domains, text-based datasets may suffer from class-imbalance. This problem leads to model's... Read More about Class-decomposition and augmentation for imbalanced data sentiment analysis..

An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. (2021)
Conference Proceeding
JIANG, M. and ZHANG, L. 2021. An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533847. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533847

The generation of desirable video game contents has been a challenge of games level design and production. In this research, we propose a game player flow experience driven interactive latent variable evolution strategy incorporated with a Deep Convo... Read More about An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation..

Numerical simulation and geological modelling of conceptual fluvial reservoir systems. (2021)
Conference Proceeding
IBRAHIM, K.S., OLUYEMI, G.F. and NZEREM, P. 2021. Numerical simulation and geological modelling of conceptual fluvial reservoir systems. In Proceedings of 1st International conference on multidisciplinary engineering and applied science 2021 (ICMEAS 2021), 15-16 July 2021, Abujua, Nigeria. Piscataway: IEEE [online], article 9692381. Available from: https://doi.org/10.1109/ICMEAS52683.2021.9692381

The development of a fluvial reservoir oil or gas field poses complex challenges in field development strategies during appraisal and exploration stage due to some subsurface uncertainties. In this study, the channel geometries such as straight-chann... Read More about Numerical simulation and geological modelling of conceptual fluvial reservoir systems..

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, Kraków, Poland : [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 become a 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 algorith... 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 Engineering 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..

Weighted ensemble of gross error detection methods based on particle swarm optimization. (2021)
Conference Proceeding
DOBOS, D., NGUYEN, T.T., MCCALL, J., WILSON, A., STOCKTON, P. and CORBETT, H. 2021. Weighted ensemble of gross error detection methods based on particle swarm optimization. In Chicano, F. (ed) Proceedings of the 2021 Genetic and evolutionary computation conference (GECCO 2021), 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 307-308. Available from: https://doi.org/10.1145/3449726.3459415

Gross errors, a kind of non-random error caused by process disturbances or leaks, can make reconciled estimates can be very inaccurate and even infeasible. Detecting gross errors thus prevents financial loss from incorrectly accounting and also ident... Read More about Weighted ensemble of gross error detection methods based on particle swarm optimization..

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..