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All Outputs (1084)

CIA security for internet of vehicles and blockchain-AI integration. (2024)
Journal Article
HAI, T., AKSOY, M., IWENDI, C., IBEKE, E. and MOHAN, S. 2024. CIA security for internet of vehicles and blockchain-AI integration. Journal of grid computing [online], 22(2), article number 43. Available from: https://doi.org/10.1007/s10723-024-09757-3

The lack of data security and the hazardous nature of the Internet of Vehicles (IoV), in the absence of networking settings, have prevented the openness and self-organization of the vehicle networks of IoV cars. The lapses originating in the areas of... Read More about CIA security for internet of vehicles and blockchain-AI integration..

Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI. (2024)
Journal Article
SENANAYAKE, J., KALUTARAGE, H., PETROVSKI, A., PIRAS, L. and AL-KADRI, M.O. 2024. Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI. Journal of information security and applications [online], 82, article number 103741. Available from: https://doi.org/10.1016/j.jisa.2024.103741

Ensuring strict adherence to security during the phases of Android app development is essential, primarily due to the prevalent issue of apps being released without adequate security measures in place. While a few automated tools are employed to redu... Read More about Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI..

Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers. (2024)
Journal Article
HAYNES, S.C., JOHNSTON, P. and ELYAN, E. 2024. Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers. Multimedia tools and applications [online], Latest Articles. Available from: https://doi.org/10.1007/s11042-024-18543-y

The generalisability of deep neural network classifiers is emerging as one of the most important challenges of our time. The recent COVID-19 pandemic led to a surge of deep learning publications that proposed novel models for the detection of COVID-1... Read More about Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers..

Steps towards a philosophy of computing education. [Discussion paper]. (2024)
Conference Proceeding
MCDERMOTT, R., DANIELS, M. and FREZZA, S.T. 2024. Steps towards a philosophy of computer education. [Discussion paper]. In Mühling, A. and Jormanainen, I. (eds.) Proceedings of the 23rd Koli calling international conference on computing education research 2023, 13-18 November 2024, Koli, Finland. New York: ACM [online], article 20. Available from: https://doi.org/10.1145/3631802.3631817

Is it meaningful to talk about the philosophy of computing education? What is its subject matter and methods? Is it different from, or a subfield of, the philosophy of science education or the philosophy of technology education or the philosophy of e... Read More about Steps towards a philosophy of computing education. [Discussion paper]..

Two-layer ensemble of deep learning models for medical image segmentation. [Article] (2024)
Journal Article
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2024. Two-layer ensemble of deep learning models for medical image segmentation. Cognitive computation [online], In Press. Available from: https://doi.org/10.1007/s12559-024-10257-5

One of the most important areas in medical image analysis is segmentation, in which raw image data is partitioned into structured and meaningful regions to gain further insights. By using Deep Neural Networks (DNN), AI-based automated segmentation al... Read More about Two-layer ensemble of deep learning models for medical image segmentation. [Article].

Detection-driven exposure-correction network for nighttime drone-view object detection. (2024)
Journal Article
XI, Y., JIA, W., MIAO, Q., FENG, J., REN, J. and LUO, H. 2024. Detection-driven exposure-correction network for nighttime drone-view object detection. IEEE transactions on geoscience and remote sensing [online], 62, article number 5605014. Available from: https://doi.org/10.1109/TGRS.2024.3351134

Drone-view object detection (DroneDet) models typically suffer a significant performance drop when applied to nighttime scenes. Existing solutions attempt to employ an exposure-adjustment module to reveal objects hidden in dark regions before detecti... Read More about Detection-driven exposure-correction network for nighttime drone-view object detection..

Feature aggregation and region-aware learning for detection of splicing forgery. (2024)
Journal Article
XU, Y., ZHENG, J., REN, J. and FANG, A. 2024. Feature aggregation and region-aware learning for detection of splicing forgery. IEEE signal processing letters [online], 31, pages 696-700. Available from: https://doi.org/10.1109/LSP.2023.3348689

Detection of image splicing forgery become an increasingly difficult task due to the scale variations of the forged areas and the covered traces of manipulation from post-processing techniques. Most existing methods fail to jointly multi-scale local... Read More about Feature aggregation and region-aware learning for detection of splicing forgery..

A weighted ensemble of regression methods for gross error identification problem. (2023)
Conference Proceeding
DOBOS, D., DANG, T., NGUYEN, T.T., MCCALL, J., WILSON, A., CORBETT, H. and STOCKTON, P. 2023. A weighted ensemble of regression methods for gross error identification problem. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Symposium series on computational intelligence (SSCI 2023), 5-8 December 2023, Mexico City, Mexico. Piscataway: IEEE [online], pages 413-420. Available from: https://doi.org/10.1109/SSCI52147.2023.10371882

In this study, we proposed a new ensemble method to predict the magnitude of gross errors (GEs) on measurement data obtained from the hydrocarbon and stream processing industries. Our proposed model consists of an ensemble of regressors (EoR) obtaine... Read More about A weighted ensemble of regression methods for gross error identification problem..

What is Skill? (and why does it matter?). (2023)
Conference Proceeding
MCDERMOTT, R. and DANIELS, M. 2023. What is skill? (and why does it matter?). In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343520. Available from: https://doi.org/10.1109/FIE58773.2023.10343520

This Research-to-Practice Full Paper seeks to investigate the concept of Skill within a Competency Framework, such as that described by the CC2020 document. The notion of skill is fundamental to modern educational discourse. As educators, we strive,... Read More about What is Skill? (and why does it matter?)..

In search of a philosophy of computing education. (2023)
Conference Proceeding
MCDERMOTT, R., DANIELS,M. and FREZZA, S. 2023. In search of a philosophy of computing eduction. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343513. Available from: https://doi.org/10.1109/FIE58773.2023.10343513

In this paper, we present a preliminary description of the field of inquiry encompassed by the philosophy of computing education. We first attempt to identify a general framework for investigating characteristic questions of a philosophical nature th... Read More about In search of a philosophy of computing education..

On the role of dialogue models in the age of large language models. (2023)
Conference Proceeding
WELLS, S. and SNAITH, M. 2023. On the role of dialogue models in the age of large language models. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Proceedings of the 23rd Workshop on computational models of natural argument (CMNA 2023), 3 December 2023, [virtual event]. CEUR workshop proceedings, 3614. Aachen: CEUR-WS [online], pages 49-51. Available from: https://ceur-ws.org/Vol-3614/abstract2.pdf

We argue that Machine learning, in particular the currently prevalent generation of Large Language Models (LLMs), can work constructively with existing normative models of dialogue as exemplified by dialogue games, specifically their computational ap... Read More about On the role of dialogue models in the age of large language models..

Evaluating a pass/fail grading model in first year undergraduate computing. (2023)
Conference Proceeding
ZARB, M., MCDERMOTT, R., MARTIN, K., YOUNG, T. and MCGOWAN, J. 2023. Evaluating a pass/fail grading model in first year undergraduate computing. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023), 18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article 10343276. Available from: https://doi.org/10.1109/FIE58773.2023.10343276

This Innovative Practice Full Paper investigates the implications of implementing a Pass/Fail marking scheme within the undergraduate curriculum, specifically across first year computing modules in a Scottish Higher Education Institution. The motivat... Read More about Evaluating a pass/fail grading model in first year undergraduate computing..

Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. (2023)
Conference Proceeding
LINTILÄ, T. 2023. Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 15th International conference on education and new learning technologies (EDULEARN 2023), 3-5 July 2023, Palma, Spain. Valencia: IATED [online], pages 2121-2129. Available from: https://doi.org/10.21125/edulearn.2023.0638

This article describes research in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computer science students in Finland and Great Britain. The study has been conducted as action research, and it... Read More about Lecturers' and clients' experiences of using learning by developing action model with project-based computing science study modules in Finland and the UK..

A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. (2023)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2023. A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs. In Chova, L.G., Martínez. C.G. and Lees, J. (eds.) Proceedings of the 17th International technology, education and development conference (INTED 2023), 6-8 March 2023, Valencia, Spain. Valencia: IATED [online], pages 3261-3269. Available from: https://doi.org/10.21125/inted.2023.0897

This article describes a study in which the Learning by Developing (LbD) action model has been used as a teaching and learning method for computing students in Finland and the United Kingdom. The study has been carried out as action research, and the... Read More about A research on the use of learning by developing action model in computing studies in Finland and the UK HEIs..

MicroConceptBERT: concept-relation based document information extraction framework. (2023)
Conference Proceeding
SILVA, K., SILVA, T. and NANAYAKKARA, G. 2023. MicroConceptBERT: concept-relation based document information extraction framework. In Proceedings of the 7th SLAAI (Sri Lanka Association for Artificial Intelligence) International conference on artificial intelligence 2023 (SLAAI-ICAI 2023), 23-24 November 2023, Kelaniya, Sri Lanka. Piscataway: IEEE [online], article number 10365022. Available from: https://doi.org/10.1109...ICAI59257.2023.10365022

Extracting information from documents is a crucial task in natural language processing research. Existing information extraction methodologies often focus on specific domains, such as medicine, education or finance, and are limited by language constr... Read More about MicroConceptBERT: concept-relation based document information extraction framework..

Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. (2023)
Conference Proceeding
JOHNSTON, P., ZARB, M. and MORENO-GARCIA, C.F. 2023. Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Frontiers in education conference (FIE 2023),18-21 October 2023, College Station, TX, USA. Piscataway: IEEE [online], article number 10343048. Available from: https://doi.org/10.1109/fie58773.2023.10343048

This paper presents an experience report of online attendance and associated behavioural patterns during a module in the first complete semester undertaken fully online in the autumn of 2020, and the corresponding module deliveries in 2021 and 2022.... Read More about Student interaction with a virtual learning environment: an empirical study of online engagement behaviours during and since the time of COVID-19..

SecHealth: enhancing EHR security in digital health transformation. (2023)
Conference Proceeding
YENG, P., FAUZI, M.A., YANG, B., DIEKUU, J.-B., NIMBE, P., HOLIK, F., KHATIWADA, P., FAHMI, A. and SUN, L. 2023. SecHealth: enhancing EHR security in digital health transformation. In Widasari, E.R. and Adikara, P.P. (eds.) SIET '23: proceedings of the 8th International conference on sustainable information engineering and technology (SIET '23), 24-25 October 2023, Bali, Indonesia. New York: ACM [online], pages 538-544. Available from: https://doi.org/10.1145/3626641.3627214

In the contemporary wave of digital transformation, the implementation of electronic health records (EHRs) has become a pivotal undertaking for numerous nations. However, amidst this technological advancement, a critical facet deserving heightened at... Read More about SecHealth: enhancing EHR security in digital health transformation..

Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance. (2023)
Journal Article
FORBES-MCKAY, K.E., BREMNER, P.A.M., JOHNSTON, P. and AIR, C. [2024]. Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance. Journal of applied research in higher education [online], EarlyCite. Available from: https://doi.org/10.1108/jarhe-06-2023-0253

This study addresses gaps in the existing literature on students' understanding of Independent Learning (IL), whilst exploring the link between levels of IL, growth mindset, motivated strategies for learning and academic performance. Three hundred an... Read More about Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance..

C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics. (2023)
Journal Article
SRIVASTAVA, G., MEKALA, M.S., HAJAR, M.S. and KALUTARAGE, H. 2023. C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics. IEEE transactions on consumer electronics [online], Early Access. Available from: https://doi.org/10.1109/TCE.2023.3342635

The Medical Internet of Things (MIoT) facilitates extensive connections between cyber and physical "things" allowing for effective data fusion and remote patient diagnosis and monitoring. However, there is a risk of incorrect diagnosis when data is t... Read More about C-NEST: cloudlet based privacy preserving multidimensional data stream approach for healthcare electronics..

Fault detection and localisation in LV distribution networks using a smart meter data-driven digital twin. (2023)
Journal Article
NUMAIR, M., ABOUSHADY, A.A., ARRAÑO-VARGAS, F., FARRAG, M.E. and ELYAN, E. 2023. Fault detection and localisation in LV distribution networks using a smart meter data-driven digital twin. Energies [online], 16(23), 7850. Available from: https://doi.org/10.3390/en16237850

Modern solutions for precise fault localisation in Low Voltage (LV) Distribution Networks (DNs) often rely on costly tools such as the micro-Phasor Measurement Unit (𝜇 PMU), which is potentially impractical for the large number of nodes in LVDNs. Thi... Read More about Fault detection and localisation in LV distribution networks using a smart meter data-driven digital twin..