All Outputs (100)

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)..

A user-centred evaluation of DisCERN: discovering counterfactuals for code vulnerability detection and correction. (2023)
Journal Article
WIJEKOON, A. and WIRATUNGA, N. 2023. A user-centred evaluation of DisCERN: discovering counterfactuals for code vulnerability detection and correction. Knowledge-based systems [online], 278, article 110830. Available from: https://doi.org/10.1016/j.knosys.2023.110830

Counterfactual explanations highlight actionable knowledge which helps to understand how a machine learning model outcome could be altered to a more favourable outcome. Understanding actionable corrections in source code analysis can be critical to p... Read More about A user-centred evaluation of DisCERN: discovering counterfactuals for code vulnerability detection and correction..

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..

Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation. (2023)
Journal Article
SUN, G., FU, H., ZHANG, A. and REN, J. 2023. Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation. Cehui xuebao/Acta geodaetica et cartographica sinica [online], 15(7), pages 1148-1163. Available from: https://doi.org/10.11947/j.AGCS.2023.20220542

Hyperspectral remote sensing imagery (HSI) usually contains dozens to hundreds of continuous spectral bands, with the syncretism of spectrum and image, spectral continuity, which can realize fine classification of ground objects and has been widely u... Read More about Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation..

An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. (2023)
Journal Article
LI, J.W., LIN, D., CHE, Y., LV, J.J., CHEN, R.J., WANG, L.J., ZENG, X.X., REN, J.C., ZHAO, H.M. and LU, X. 2023. An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. Frontiers in neuroscience [online], 17, article 1221512. Available from: https://doi.org/10.3389/fnins.2023.1221512

Efficiently recognizing emotions is a critical pursuit in brain–computer interface (BCI), as it has many applications for intelligent healthcare services. In this work, an innovative approach inspired by the genetic code in bioinformatics, which util... Read More about An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method..

Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring. (2023)
Journal Article
ZAKARIYYA, I., KALUTARAGE, H. and AL-KADRI, M.O. 2023. Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring. Computer and security [online], 133, article 103388. Available from: https://doi.org/10.1016/j.cose.2023.103388

The application of Deep Neural Networks (DNNs) for monitoring cyberattacks in Internet of Things (IoT) systems has gained significant attention in recent years. However, achieving optimal detection performance through DNN training has posed challenge... Read More about Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring..

MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings. (2023)
Journal Article
GENG, J., ZHANG, X., YAN, Y., SUN, M., ZHANG, H., ASSAAD, M., REN, J. and LI, X. 2023. MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings. Cognitive computation [online],15(6), pages 2050-2061. Available from: https://doi.org/10.1007/s12559-023-10172-1

The computational modeling and analysis of traditional Chinese painting rely heavily on cognitive classification based on visual perception. This approach is crucial for understanding and identifying artworks created by different artists. However, th... Read More about MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings..

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..

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..

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..

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..

Large kernel spectral and spatial attention networks for hyperspectral image classification. (2023)
Journal Article
SUN, G., PAN, Z., ZHANG, A., JIA, X., REN, J., FU, H. and YAN, K. 2023. Large kernel spectral and spatial attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 61, article 5519915. Available from: https://doi.org/10.1109/tgrs.2023.3292065

Currently, long-range spectral and spatial dependencies have been widely demonstrated to be essential for hyperspectral image (HSI) classification. Due to the transformer superior ability to exploit long-range representations, the transformer-based m... Read More about Large kernel spectral and spatial attention networks for hyperspectral image classification..

Managing group projects in undergraduate computing. (2023)
Presentation / Conference
SCOTT, M.J., ALSHAIGY, B., SIEGEL, A.A. and ZARB, M. 2023. Managing group projects in undergraduate computing. Panel presented at the 28th Annual conference on innovation and technology in computer science education (ITiCSE 2023), 8-12 July 2023, Turku, Finland.

This panel convenes four educators, each from different institutions and each with experience managing group projects. Their expertise spans topics including: peer assessment and peer evaluation; entrepreneurship; transdisciplinarity; internationalis... Read More about Managing group projects in undergraduate computing..

3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. (2023)
Journal Article
ZHANG, H., MEKALA, M.S., YANG, D., ISAACS, J., NAIN, Z., PARK, J.H. and JUNG, H.-Y. 2023. 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration. IEEE transactions on vehicular technology [online], 72(12), pages 15268-15279. Available from: https://doi.org/10.1109/TVT.2023.3291650

The use of edge computing for 3D perception has garnered interest in intelligent transportation systems (ITS) due to its potential to enhance Vehicle-to-Everything (V2X) orchestration through real-time traffic monitoring. The ability to accurately me... Read More about 3D harmonic loss: towards task-consistent and time-friendly 3D object detection on edge for V2X orchestration..

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..

A system dynamics approach to evaluate advanced persistent threat vectors. (2023)
Journal Article
NICHO, M., MCDERMOTT, C.D., FAKHRY, H. and GIRIJA, S. 2023. A system dynamics approach to evaluate advanced persistent threat vectors. International journal of information security and privacy [online], 17(1), pages 1-23. Available from: https://doi.org/10.4018/IJISP.324064

Cyber-attacks targeting high-profile entities are focused, persistent, and employ common vectors with varying levels of sophistication to exploit social-technical vulnerabilities. Advanced persistent threats (APTs) deploy zero-day malware against suc... Read More about A system dynamics approach to evaluate advanced persistent threat vectors..

Exploring students' independent learning and its relationship to mindset and academic performance. (2023)
Presentation / Conference
FORBES-MCKAY, K.E., BREMNER, P. and JOHNSTON, P. 2023. Exploring students' independent learning and its relationship to mindset and academic performance. Presented at the 2023 International higher education teaching and learning annual conference (HETL 2023): re-imagining education: collaboration and compassion, 12-14 June 2023, Aberdeen, UK.

There is increasing interest in the role of independent learning (IL) in higher education (Thomas, 2015). Indeed, several studies demonstrate the impact of IL on students' academic achievement (Difrancesca et al. 2016). Research also suggests that mo... Read More about Exploring students' independent learning and its relationship to mindset and academic performance..