All Outputs (1024)

Solutions for innovation transfer between countries with different legislative, regulatory and funding regimes: case studies from rural passenger transport projects. (2023)
Conference Proceeding
GRAY, D., MESJAR, L. and IRONSIDE, L. 2023. Solutions for innovation transfer between countries with different legislative, regulatory and funding regimes: case studies from rural passenger transport projects. In ETC conference papers 2023: proceedings of the 51st European transport conference (ETC 2023), 6-8 September 2023, Milan, Italy. Henley-in-Arden: AET [online], abstract number 8143. Available from: https://tinyurl.com/3b6tku6v

European programmes such as Interreg are predicated on the principles of demonstration and adoption of innovation, transfer of best practice between jurisdictions, and transnational cooperation to address shared challenges. However, governance, fundi... Read More about Solutions for innovation transfer between countries with different legislative, regulatory and funding regimes: case studies from rural passenger transport projects..

Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. (2023)
Conference Proceeding
MUTHUKRISHNAN, R., KANNAN, S., PRABHU, R., ZHAO, Y., BHOWMICK, P. and HASAN, M.J. 2023. Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. In Proceedings of the 2023 Network, multimedia and information technology international conference (NMITCON 2023), 1-2 September 2023, Bengaluru, India. Piscataway: IEEE [online], article number 10275983. Available from: https://doi.org/10.1109/NMITCON58196.2023.10275983

A da Vinci robot endoscopic-camera gives surgeons a magnified 2D view of the operating area, but additional time is required to detect and estimate the location of the surgical-instrument during an operation. The main focus and novelty of this resear... Read More about Tracking and estimation of surgical instrument position and angle in surgical robot using vision system..

Transformation products of microcystin-RR with reactive species produced by radiolysis of water. (2023)
Conference Proceeding
ILIAKOPOULOUS, S., TRIANTIS, T., ANTONOPOULOU, M., EDWARDS, C., LINDA, L., KISKIA, A. and KALOUDIS, T. 2023. Transformation products of microcystin-RR with reactive species produced by radiolysis of water. In Proceedings of the 18th International conference on environmental science and technology 2023 (CEST2023), 30 August - 2 September 2023, Athens, Greece. Athens: COSMOS SA [online], paper ID cest2023_00012. Available from: https://doi.org/10.30955/gnc2023.00012

Microcystins (MCs) are potent cyclic-peptide toxins produced by cyanobacteria during freshwater bloom episodes. They can severely impact drinking water supplies and recreational waters. More than 300 MCs are known today, which are toxic, mainly by in... Read More about Transformation products of microcystin-RR with reactive species produced by radiolysis of water..

HEALER2: a framework for secure data lake towards healthcare digital transformation efforts in low and middle-income countries. (2023)
Conference Proceeding
YENG, P.K., DIEKUU, J.-B., ABOMHARA, M., ELHADJ, B., YAKUBU, M.A., OPPONG, I.N., FAUZI, M.A., YANG, B. and EL-GASSAR, R. 2023. HEALER2: a framework for secure data lake towards healthcare digital transformation efforts in low and middle-income countries. In Singh Jat, D., Bhunu Shava, F., Tripathi, M., Gajrani, J., Nehra, A. and Jain, A. (eds.) Proceedings of the 2023 International conference on Emerging trends in networks and computer communications (ETNCC 2023), 16-18 August 2023, Windhoek, Namibia ; [virtual event]. Piscataway: IEEE [online], pages 31-39. Available from: https://doi.org/10.1109/ETNCC59188.2023.10284959

Low and middle-income countries are vigorously digitizing their operations in the healthcare sector as steps in the digital transformation journey. However, some of the basic principles in information security are being skipped. This has a tendency t... Read More about HEALER2: a framework for secure data lake towards healthcare digital transformation efforts in low and middle-income countries..

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..

Modeling and simulation of heterojunction solar cell; determination of optimal values. (2023)
Conference Proceeding
LAWAL, S.M., FOUGH, N., SELLAMI, N. and MUHAMMAD-SUKKI, F. 2023. Modeling and simulation of heterojunction solar cell: determination of optimal values. 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 10198061. Available from: https://doi.org/10.1109/NEWCAS57931.2023.10198061

A heterojunction solar cell of ZnSe/ZnO/CIGS/Si structure has been simulated in order to determine the optimal values. The performed modeling and Simulation is used to get an idea and identify the optimal values that can be use in the manufacturing p... Read More about Modeling and simulation of heterojunction solar cell; determination of optimal values..

Modelling and analysis of vortex-induced vibrations for flexible cylinders conveying two-phase slug flows. (2023)
Conference Proceeding
MEENAKUMARI, H.N.R., ZANGANEH, H. and HOSSAIN, M. 2023. Modelling and analysis of vortex-induced vibrations for flexible cylinders conveying two-phase slug flows. In Qiu, H., Zhang, Y. and Iasiello, M. (eds.) Proceedings of the 9th World congress on Mechanical, chemical and material engineering. Orléans, ON, Canada: Avestia [online], paper no. ICMIE 138. Available from: https://doi.org/10.11159/icmie23.138

Hydrocarbon flows in a marine riser may appear in multiple phases with varying flow patterns, among which, slug flows are known to exhibit complex flow characteristics due to fluctuations in multiphase mass, velocities, and pressure changes. This flo... Read More about Modelling and analysis of vortex-induced vibrations for flexible cylinders conveying two-phase slug flows..

Unmasking the imposters: task-specific feature learning for face presentation attack detection. (2023)
Conference Proceeding
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2023. Unmasking the imposters: task-specific feature learning for face presentation attack detection. In Proceedings of the 2023 International joint conference on neural networks (IJCNN2023), 18-23 June 2023, Gold Coast, Australia. Piscataway: IEEE [online], 10191953. Available from: https://doi.org/10.1109/IJCNN54540.2023.10191953

Presentation attacks pose a threat to the reliability of face recognition systems. A photograph, a video, or a mask representing an authorised user can be used to circumvent the face recognition system. Recent research has demonstrated high accuracy... Read More about Unmasking the imposters: task-specific feature learning for face presentation attack detection..

CBR driven interactive explainable AI. (2023)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., MARTIN, K., CORSAR, D., NKISI-ORJI, I., PALIHAWADANA, C., BRIDGE, D., PRADEEP, P., AGUDO, B.D. and CARO-MARTÍNEZ, M. 2023. CBR driven interactive explainable AI. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages169-184. Available from: https://doi.org/10.1007/978-3-031-40177-0_11

Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Numerous explanation techniques (explainers) exist in the literature, and recent findings suggest that addressing multiple user needs requi... Read More about CBR driven interactive explainable AI..

Failure-driven transformational case reuse of explanation strategies in CloodCBR. (2023)
Conference Proceeding
NKISI-ORJI, I., PALIHAWADANA, C., WIRATUNGA, N., WIJEKOON, A. and CORSAR, D. 2023. Failure-driven transformational case reuse of explanation strategies in CloodCBR. In Massie, S. and Chakraborti, S. (eds.) Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023 (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages 279-293. Available from: https://doi.org/10.1007/978-3-031-40177-0_18

In this paper, we propose a novel approach to improve problem-solving efficiency through the reuse of case solutions. Specifically, we introduce the concept of failure-driven transformational case reuse of explanation strategies, which involves trans... Read More about Failure-driven transformational case reuse of explanation strategies in CloodCBR..

Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023). (2023)
Conference Proceeding
MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science, 14141. Cham: Springer [online]. Available from: https://doi.org/10.1007/978-3-031-40177-0

This volume contains the papers presented at the 31st International Conference on Case-Based Reasoning (ICCBR 2023), which was held on July 17–20, 2023, at Robert Gordon University in Aberdeen, Scotland, UK. ICCBR is the premier annual meeting of the... Read More about Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023)..

Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis. (2023)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2023. Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis. In GECCO’23 companion: proceedings of the 2023 Genetic and evolutionary computation conference companion, 15-19 July 2023, Lisbon, Portugal. New York: ACM [online], pages 1648-1656. Available from: https://doi.org/10.1145/3583133.3596353

In the field of Explainable AI, population-based search metaheuristics are of growing interest as they become more widely used in critical applications. The ability to relate key information regarding algorithm behaviour and drivers of solution quali... Read More about Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis..

CBR assisted context-aware surface realisation for data-to-text generation. (2023)
Conference Proceeding
UPADHYAY, A. and MASSIE, S. 2023. CBR assisted context-aware surface realisation for data-to-text generation. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages 34-49. Available from: https://doi.org/10.1007/978-3-031-40177-0_3

Current state-of-the-art neural systems for Data-to-Text Generation (D2T) struggle to generate content from past events with interesting insights. This is because these systems have limited access to historic data and can also hallucinate inaccurate... Read More about CBR assisted context-aware surface realisation for data-to-text generation..

The current and future role of visual question answering in eXplainable artificial intelligence. (2023)
Conference Proceeding
CARO-MARTINEZ, M., WIJEKOON, A., DIAZ-AGUDO, B. and RECIO-GARCIA, J.A. 2023. The current and future role of visual question answering in eXplainable artificial intelligence. In Malburg, L. and Verma, D. (eds.) Workshop proceedings of the 31st International conference on case-based reasoning (ICCBR-WS 2023), 17 July 2023, Aberdeen, UK. CEUR workshop proceedings, 3438. Aachen: CEUR-WS [online], pages 172-183. Available from: https://ceur-ws.org/Vol-3438/paper_13.pdf

Over the last few years, we have seen how the interest of the computer science research community on eXplainable Artificial Intelligence has grown in leaps and bounds. The reason behind this rise is the use of Artificial Intelligence in many daily li... Read More about The current and future role of visual question answering in eXplainable artificial intelligence..

AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics. (2023)
Conference Proceeding
PIRIE, C., WIRATUNGA, N., WIJEKOON, A. and MORENO-GARCIA, C.F. 2023. AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics. In Malburg, L. and Verma, D. (eds.) Workshop proceedings of the 31st International conference on case-based reasoning (ICCBR-WS 2023), 17 July 2023, Aberdeen, UK. CEUR workshop proceedings, 3438. Aachen: CEUR-WS [online], pages 184-199. Available from: https://ceur-ws.org/Vol-3438/paper_14.pdf

As deep learning models become increasingly complex, practitioners are relying more on post hoc explanation methods to understand the decisions of black-box learners. However, there is growing concern about the reliability of feature attribution expl... Read More about AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics..

Android code vulnerabilities early detection using AI-powered ACVED plugin. (2023)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and PIRAS, L. 2023. Android code vulnerabilities early detection using AI-powered ACVED plugin. In Atluri, V. and Ferrara, A.L. (eds.) Data and applications security and privacy XXXVII; proceedings of the 37th annual IFIP WG (International Federation for Information Processing Working Group) 11.3 Data and applications security and privacy 2023 (DBSec 2023), 19-21 July 2023, Sophia-Antipolis, France. Lecture notes in computer science (LNCS), 13942. Cham: Springer [online], pages 339-357. Available from: https://doi.org/10.1007/978-3-031-37586-6_20

During Android application development, ensuring adequate security is a crucial and intricate aspect. However, many applications are released without adequate security measures due to the lack of vulnerability identification and code verification at... Read More about Android code vulnerabilities early detection using AI-powered ACVED plugin..

Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. (2023)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PIRAS, L. and PETROVSKI, A. 2023. Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. In De Capitani di Vimercati, S. and Samarati, P. (eds.) Proceedings of the 20th International conference on security and cryptography, 10-12 July 2023, Rome, Italy, volume 1. Setúbal: SciTePress [online], pages 659-666. Available from: https://doi.org/10.5220/0012060400003555

Ensuring the security of Android applications is a vital and intricate aspect requiring careful consideration during development. Unfortunately, many apps are published without sufficient security measures, possibly due to a lack of early vulnerabili... Read More about Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models..

Machine learning for risk stratification of diabetic foot ulcers using biomarkers. (2023)
Conference Proceeding
MARTIN, K., UPHADYAY, A., WIJEKOON, A., WIRATUNGA, N. and MASSIE, S. [2023]. Machine learning for risk stratification of diabetic foot ulcers using biomarkers. To be presented at the 2023 International conference on computational science (ICCS 2023): computing at the cutting edge of science, 3-5 July 2023, Prague, Czech Republic: [virtual event].

Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient's health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ul... Read More about Machine learning for risk stratification of diabetic foot ulcers using biomarkers..

Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. (2023)
Conference Proceeding
TORAL-QUIJAS, L.A., ELYAN, E., MORENO-GARCÍA, C.F. and STANDER, J. 2023. Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. In Iliadis, L, Maglogiannis, I., Alonso, S., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 24th International conference on engineering applications of neural networks (EAAAI/EANN 2023), 14-17 June 2023, León, Spain. Communications in computer and information science, 1826. Cham: Springer [online], pages 217-226. Available from: https://doi.org/10.1007/978-3-031-34204-2_19

Inspecting circumferential welds in caissons is a critical task for ensuring the safety and reliability of structures in the offshore industry. However, identifying and classifying different types of circumferential welds can be challenging in subsea... Read More about Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections..

Towards autonomous developmental artificial intelligence: case study for explainable AI. (2023)
Conference Proceeding
STARKEY, A. and EZENKWU, C.P. 2023. Towards autonomous developmental artificial intelligence: case study for explainable AI. In Maglogiannis, I., Iliadis, L., MacIntyre, J. and Dominguez, M. (eds.) Artificial intelligence applications and innovations: proceedings of the 19th IFIP (International Federation for Information Processing) WG 12.5 Artificial intelligence applications and innovations international conference (AIAI 2023), 14-17 June 2023, León, Spain. IFIP advances in information and communication technology, 676. Cham: Springer [online], pages 94-105. Available from: https://doi.org/10.1007/978-3-031-34107-6_8

State-of-the-art autonomous AI algorithms such as reinforcement learning and deep learning techniques suffer from high computational complexity, poor explainability ability, and a limited capacity for incremental adaptive learning. In response to the... Read More about Towards autonomous developmental artificial intelligence: case study for explainable AI..