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Extremely random forest based automatic tonic-clonic seizure detection using spectral analysis on electroencephalography data. (2023)
Conference Proceeding
STEWART, C., FUNG, WAI KEUNG, FOUGH, N. and PRABHU, R. 2023. Extremely random forest based automatic tonic-clonic seizure detection using spectral analysis on electroencephalography data. In Proceedings of the 21st IEEE (Institute of Electrical and Electronics Engineers) Interregional NEWCAS conference 2023 (NEWCAS 2023), 26-28 June 2023, Edinburgh, UK. Piscataway: IEEE [online], article 10198101. Available from: https://doi.org/10.1109/NEWCAS57931.2023.10198101

Machine learning proliferates society and has begun changing medicine. This report covers an investigation into how Extremely Random Forests combined with Fast Fourier Transform feature extraction performed on two-dimensional time-series Epileptic Se... Read More about Extremely random forest based automatic tonic-clonic seizure detection using spectral analysis on electroencephalography data..

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..

A low-complexity wavelet-based visual saliency model to predict fixations. (2020)
Conference Proceeding
NARAYANASWAMY, M., ZHAO, Y., FUNG, W.K. and FOUGH, N. 2020. A low-complexity wavelet-based visual saliency model to predict fixations. In Proceedings of 27th Institute of Electrical and Electronic Engineers (IEEE) International conference on electronics, circuits and systems 2020 (ICECS 2020), 23-25 November 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9294905. Available from: https://doi.org/10.1109/ICECS49266.2020.9294905

A low-complexity wavelet-based visual saliency model to predict the regions of human eye fixations in images using low-level features is proposed. Unlike the existing wavelet-based saliency detection models, the proposed model requires only two chann... Read More about A low-complexity wavelet-based visual saliency model to predict fixations..

Fluorescence lifetime assisted enhanced security feature in travel documents for border control and security applications. (2019)
Conference Proceeding
JOHNY, J., OFFICER, S., FUNG, W. K. and PRABHU, R. 2019. Fluorescence lifetime assisted enhanced security feature in travel documents for border control and security applications. In Bouma, H., Prabhu, R., Stokes, R.J. and Yitzhaky, Y. (eds.) Proceedings of the 3rd Counterterrorism, crime fighting, forensics, and surveillance technologies conference 2019: co-located with the Society of Photo-Optical Instrumentation Engineers (SPIE) Security and defence 2019 conference, 9-12 September 2019, Strasbourg, France. Proceedings of the SPIE, 11166. Bellingham, WA: SPIE [online], article ID 1116608. Available from: https://doi.org/10.1117/12.2535742

Border management and security challenges are increasing considerably in recent years. One of the major concerns is counterfeiting and fraudulent use of identity and other travel documents for crossing border controls. This poses serious threats and... Read More about Fluorescence lifetime assisted enhanced security feature in travel documents for border control and security applications..

Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms. (2019)
Conference Proceeding
SABRA, A., FUNG, W.-K. and CHURN, P. 2018. Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms. In Correll, N., Schwager, M. and Otte, M. (eds.) Distributed autonomous robotic systems: proceedings of the 14th International distributed autonomous robotic systems symposium 2018 (DARS 2018), 15-17 October 2018, Boulder, USA. Springer proceedings in advanced robotics, 9. Cham: Springer [online], pages 109-123. Available from: https://doi.org/10.1007/978-3-030-05816-6_8

Localization in large-scale underwater swarm robotic systems has increasingly attracted research and industry communities’ attention. An optimized confidence-based localization algorithm is proposed for improving localization coverage and accuracy by... Read More about Multi-objective optimization of confidence-based localization in large-scale underwater robotic swarms..

Confidence-based underwater localization scheme for large-scale mobile sensor networks. (2018)
Conference Proceeding
SABRA, A., FUNG, W.-K. and RADHAKRISHNA, P. 2018. Confidence-based underwater localization scheme for large-scale mobile sensor networks. In Proceedings of the 2018 Marine Technology Society and Institute of Electrical and Electronics Engineers (MTS/IEEE) OCEANS conference (OCEANS 2018 MTS/IEEE), 22-25 October 2018, Charleston, USA. Piscataway, NJ: IEEE [online], article ID 8604878. Available from: https://doi.org/10.1109/OCEANS.2018.8604878

The absence of Global Positioning System in underwater environment predominates in the challenges of underwater vehicles navigation or sensor nodes tracking. Localization of single or few underwater vehicles has been fostered in recent years. However... Read More about Confidence-based underwater localization scheme for large-scale mobile sensor networks..

Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system. (2017)
Conference Proceeding
SABRA, A. and FUNG, W.-K. 2017. Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system. In Proceedings of OCEANS 2017, 18-21 September 2017, Anchorage, Alaska, USA. New York: IEEE [online], article number 8232185, pages 854-861. Available from: http://ieeexplore.ieee.org/document/8232185

Underwater mobile sensor node localization is a key enabling technology for several subsea missions. A novel scalable underwater localization scheme, called Best Suitable Localization Algorithm (BLSA), is proposed to dynamically fuse multiple positio... Read More about Dynamic localization plan for underwater mobile sensor nodes using fuzzy decision support system..

A pilot study on aeronautical surveillance system for drone delivery using heterogeneous software defined radio framework. (2017)
Conference Proceeding
TERRAZAS GONZALEZ, J.D. and FUNG, W.-K. 2017. A pilot study on aeronautical surveillance system for drone delivery using heterogeneous software defined radio framework. In Shen, Y., Ming, A. and Wu, X. (eds.) Proceedings of the 2017 IEEE international conference on real-time computing and robotics (RCAR 2017), 14-18 July 2017, Okinawa, Japan. New York: IEEE [online], article number 8311912, pages 499-504. Available from: https://doi.org/10.1109/RCAR.2017.8311912

This paper presents a heterogeneous computing framework to interface single board computers (SBC) to (i) distinct type of computing nodes, (ii) distinct operating systems, and (iii) distinct software applications for aeronautical surveillance system... Read More about A pilot study on aeronautical surveillance system for drone delivery using heterogeneous software defined radio framework..

Theoretical investigation of positional influence of FBG sensors for structural health monitoring of offshore structures. (2017)
Conference Proceeding
JOHNY, J., SUMMERS, J., BHAVSAR, K., JOSEPH, G.P., FUNG, W.-K. and PRABHU, R. 2017. Theoretical investigation of positional influence of FBG sensors for structural health monitoring of offshore structures. In Proceedings of OCEANS 2017, 19-22 June 2017, Aberdeen, UK. New York: IEEE [online], article number 8084976, pages 2406-2410. Available from: https://doi.org/10.1109/OCEANSE.2017.8084976

Fibre Bragg Grating (FBG) is a key technology for condition monitoring of different offshore oil and gas structures. FBG sensors are used to sense different physical parameters such as strain, temperature, vibration, etc. This paper investigates the... Read More about Theoretical investigation of positional influence of FBG sensors for structural health monitoring of offshore structures..

Investigation of positioning of FBG sensors for smart monitoring of oil and gas subsea structures. (2016)
Conference Proceeding
JOHNY, J., PRABHU, R., FUNG, W.K. and WATSON, J. 2016. Investigation of positioning of FBG sensors for smart monitoring of oil and gas subsea structures. In Proceedings of the 2016 Marine Technology Society/Institute of Electrical and Electronics Engineers (MTS/IEEE) OCEANS conference: our future is with oceans, 10-13 April 2016, Shanghai, China. Piscataway: IEEE [online], paper ID 7485662. Available from: https://dx.doi.org/10.1109/OCEANSAP.2016.7485662

Condition monitoring of offshore structures is an indispensable task in the oil and gas industry. Fibre Bragg Grating (FBG) is the key technology used down-hole in order to sense different physical parameters such as strain, vibration, etc. This pape... Read More about Investigation of positioning of FBG sensors for smart monitoring of oil and gas subsea structures..