All Outputs (98)

Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21. (2021)
Conference Proceeding
HAJAR, M.S., CHAHINE, M.K., HAMDAN, R. and QDAH, M.S. 2021. Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21. In Proceedings of the 2021 IEEE International conference on communications workshops (ICC workshops 2021), 14-23 June 2021, Montreal, Canada. Piscataway: IEEE [online], 9473639. Available from: https://doi.org/10.1109/ICCWorkshops50388.2021.9473639

Next Generation Wireless Networks (NGWN) aim to provide any service at any time and anywhere with seamless mobility between homogeneous and heterogeneous networks. IEEE defines the IEEE 802.21 standard to facilitate seamless handover, namely, Media I... Read More about Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21..

Visualisation to explain personal health trends in smart homes. (2021)
Presentation / Conference
FORBES, G., MASSIE, S. and CRAW, S. 2021. Visualisation to explain personal health trends in smart homes. Presented at 1st eXplainable artificial intelligence (XAI) in healthcare international workshop 2021 (XAI-Healthcare 2021), 16 June 2021, co-located with 19th Artificial intelligence in medicine (AIME) international conference 2021 (AIME 2021), 15-17 June 2021, [virtual conference]. Hosted on ArXiv [online], article 2109.15125. Available from: https://arxiv.org/abs/2109.15125

An ambient sensor network is installed in Smart Homes to identify low-level events taking place by residents, which are then analysed to generate a profile of activities of daily living. These profiles are compared to both the resident's typical prof... Read More about Visualisation to explain personal health trends in smart homes..

Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing. (2021)
Journal Article
CHEN, R., ZHENG, Z., YU, Y., ZHAO, H., REN, J. and TAN, H.-Z. 2021. Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing. IEEE sensors journal [online], 21(16), article 103048, pages 18222-18236. Available from: https://doi.org/10.1109/JSEN.2021.3085568

Out-of-focus blurring of the QR code is very common in mobile Internet systems, which often causes failure of authentication as a result of a misreading of the information hence adversely affects the operation of the system. To tackle this difficulty... Read More about Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing..

Ethical challenges in argumentation and dialogue in a healthcare context. (2021)
Journal Article
SNAITH, M., NIELSEN, R.Ø., KOTNIS, S.R. and PEASE, A. 2021. Ethical challenges in argumentation and dialogue in a healthcare context. Argument and computation [online], 12(2), pages 249-264. Available from: https://doi.org/10.3233/AAC-200908

As the average age of the population increases, so too do the number of people living with chronic illnesses. With limited resources available, the development of dialogue-based e-health systems that provide justified general health advice offers a c... Read More about Ethical challenges in argumentation and dialogue in a healthcare context..

Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection. (2021)
Journal Article
SUN, H., REN, J., ZHAO, H., YUEN, P. and TSCHANNERL, J. 2022. Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection. IEEE transactions on geoscience and remote sensing [online], 60, article 5506413. Available from: https://doi.org/10.1109/TGRS.2021.3075663

As an important topic in hyperspectral image (HSI) analysis, band selection has attracted increasing attention in the last two decades for dimensionality reduction in HSI. With the great success of deep learning (DL)-based models recently, a robust u... Read More about Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection..

Counterfactual explanations for student outcome prediction with Moodle footprints. (2021)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., NKILSI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Counterfactual explanations for student outcome prediction with Moodle footprints. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 1, pages 1-8. Available from: http://ceur-ws.org/Vol-2894/short1.pdf

Counterfactual explanations focus on “actionable knowledge” to help end-users understand how a machine learning outcome could be changed to one that is more desirable. For this purpose a counterfactual explainer needs to be able to reason with simila... Read More about Counterfactual explanations for student outcome prediction with Moodle footprints..

Non-deterministic solvers and explainable AI through trajectory mining. (2021)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W. and CHRISTIE, L.A. 2021. Non-deterministic solvers and explainable AI through trajectory mining. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 4, pages 75-78. Available from: http://ceur-ws.org/Vol-2894/poster2.pdf

Traditional methods of creating explanations from complex systems involving the use of AI have resulted in a wide variety of tools available to users to generate explanations regarding algorithm and network designs. This however has traditionally bee... Read More about Non-deterministic solvers and explainable AI through trajectory mining..

Similarity and explanation for dynamic telecommunication engineer support. (2021)
Thesis
MARTIN, K. 2021. Similarity and explanation for dynamic telecommunication engineer support. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1447160

Understanding similarity between different examples is a crucial aspect of Case-Based Reasoning (CBR) systems, but learning representations optimised for similarity comparisons can be difficult. CBR systems typically rely on separate algorithms to le... Read More about Similarity and explanation for dynamic telecommunication engineer support..

The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research. (2021)
Thesis
STEPHENS HEMINGWAY, B.H. 2021. The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1603154

The greatest potential application of mathematical models in sport science is to predict future performance of individual athletes in response to training, with sufficient accuracy to assist with planning of training programs and short tapering perio... Read More about The utility of mathematical fitness-fatigue models for assisting with the planning of physical training for sport: from in silico experiments employing synthetic data, lower-bound operational conditions and model estimation, to the development of software resources for future research..

DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre. (2021)
Journal Article
MEKALA, M.S., PATAN, R., ISLAM, S.H., SAMANTA, D., MALLAH, G.A. and CHAUDHRY, S.A. 2021. DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre. Security and communication networks [online], 2021: security, trust and privacy for cloud, fog and Internet of Things, article ID 6688162. Available from: https://doi.org/10.1155/2021/6688162

The heterogeneous resource-required application tasks increase the cloud service provider (CSP) energy cost and revenue by providing demand resources. Enhancing CSP profit and preserving energy cost is a challenging task. Most of the existing approac... Read More about DAWM: cost-aware asset claim analysis approach on big data analytic computation model for cloud data centre..

Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. (2021)
Journal Article
YAN, Y., REN, J., TSCHANNERL, J., ZHAO, H., HARRISON, B. and JACK, F. 2021. Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. IEEE transactions on instrumentation and measurement [online], 70, article 5010715. Available from: https://doi.org/10.1109/TIM.2021.3082274

Quantifying phenolic compound in peated barley malt and discriminating its origin are essential to maintain the aroma of high-quality Scottish whisky during the manufacturing process. The content of the total phenol varies in peated barley malts, whi... Read More about Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning..

ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design. (2021)
Conference Proceeding
ALKUBAISY, D., PIRAS, L., AL-OBEIDALLAH, M.G., COX, K. and MOURATIDIS, H. 2021. ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design. In Ali, R., Kaindl, H. and Maciaszek, L. (eds.) Proceedings of 16th Evaluation of novel approaches to software engineering international conference 2021 (ENASE 2021), 26-27 April 2021, [virtual conference]. Setúbal, Portugal: SciTePress [online], pages 80-91. Available from: https://doi.org/10.5220/0010406100800091

Privacy and security requirements, and their potential conflicts, are increasingly having more and more importance. It is becoming a necessary part to be considered, starting from the very early stages of requirements engineering, and in the entire s... Read More about ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design..

A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. (2021)
Journal Article
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2021. A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. Information fusion [online], 75, pages 55-69. Available from: https://doi.org/10.1016/j.inffus.2021.04.015

Face Recognition is considered one of the most common biometric solutions these days and is widely used across a range of devices for various security purposes. The performance of FR systems has improved by orders of magnitude over the past decade. T... Read More about A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods..

Burst detection-based selective classifier resetting. (2021)
Journal Article
WARES, S., ISAACS, J. and ELYAN, E. 2021. Burst detection-based selective classifier resetting. Journal of information and knowledge management [online], 20(2), article 2150027. Available from: https://doi.org/10.1142/S0219649221500271

Concept drift detection algorithms have historically been faithful to the aged architecture of forcefully resetting the base classifiers for each detected drift. This approach prevents underlying classifiers becoming outdated as the distribution of a... Read More about Burst detection-based selective classifier resetting..

Angles of vision: digital storytelling on the cosmic tide? (2021)
Report
IRONSIDE, R., HEDDLE, D. and MASSIE, S. 2021. Angles of vision: digital storytelling on the cosmic tide? Edinburgh: Royal Society of Edinburgh. Hosted on Orkney Digital Storytelling [online]. Available from: https://www.orkneydigitalstorytelling.com/project-report.html

In this report, a collaboration between Robert Gordon University and the University of the Highlands and Islands Institute for Northern Studies, the authors bring together findings from four workshops hosted as part of the My Orkney Story project.... Read More about Angles of vision: digital storytelling on the cosmic tide?.

Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT). (2021)
Journal Article
MEKALA, M.S., RIZWAN, P. and KHAN, M.S. 2023. Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT). IEEE Internet of Things journal [online], 10(3), pages 2121-2130. Available from: https://doi.org/10.1109/JIOT.2021.3073600

Continues field monitoring and searching sensor data remains an imminent element emphasizes the influence of the Internet of Things (IoT). Most of the existing systems are concede spatial coordinates or semantic keywords to retrieve the entail data,... Read More about Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT)..

Effective detection of cyber attack in a cyber-physical power grid system. (2021)
Conference Proceeding
OTOKWALA, U., PETROVSKI, A. and KALUTARAGE, H. 2021. Effective detection of cyber attack in a cyber-physical power grid system. In Arai, K. (ed) Advances in information and communication: proceedings of Future of information and communication conference (FICC 2021), 29-30 April 2021, Vancouver, Canada. Advances in intelligent systems and computing, 1363. Cham: Springer [online], 1, pages 812-829. Available from: https://doi.org/10.1007/978-3-030-73100-7_57

Advancement in technology and the adoption of smart devices in the operation of power grid systems have made it imperative to ensure adequate protection for the cyber-physical power grid system against cyber-attacks. This is because, contemporary cyb... Read More about Effective detection of cyber attack in a cyber-physical power grid system..

Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. (2021)
Journal Article
ZHU, H., CHEN, W., ZHU, R., ZHANG, L., FU, B. and LU, X. 2021. Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. Proceedings of the Institution of Mechanical Engineers, part C: journal of mechanical engineering science [online], 235(22), pages 5975-5993. Available from: https://doi.org/10.1177/0954406221992798

The coupled dynamic model of the intermediate and tail gearboxes’ spiral bevel gear-oblique tail shaft-laminated membrane coupling was established by employing the hybrid modeling method of finite element and lumped mass. Among them, the dynamic equa... Read More about Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter..

Two layer ensemble of deep learning models for medical image segmentation. [Preprint] (2021)
Working Paper
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2021. Two layer ensemble of deep learning models for medical image segmentation. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2104.04809

In recent years, deep learning has rapidly become a method of choice for the segmentation of medical images. Deep Neural Network (DNN) architectures such as UNet have achieved state-of-the-art results on many medical datasets. To further improve the... Read More about Two layer ensemble of deep learning models for medical image segmentation. [Preprint].

Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. (2021)
Journal Article
CARLOTO, I., JOHNSTON, P., PESTANA, C.J. and LAWTON, L.A. 2021. Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. Science of the total environment [online], 784, article 146956. Available from: https://doi.org/10.1016/j.scitotenv.2021.146956

The presence of harmful algal bloom in many reservoirs around the world, alongside the lack of sanitation law/ordinance regarding cyanotoxin monitoring (particularly in developing countries), create a scenario in which the local population could pote... Read More about Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks..