All Outputs (105)

Visualising personas as goal models to find security tensions. (2021)
Journal Article
FAILY, S., IACOB, C., ALI, R. and KI-ARIES, D. 2021. Visualising personas as goal models to find security tensions. Information and computer security [online], 29(5), pages 787-815. Available from: https://doi.org/10.1108/ICS-03-2021-0035

This paper aims to present a tool-supported approach for visualising personas as social goal models, which can subsequently be used to identify security tensions. The authors devised an approach to partially automate the construction of social goal m... Read More about Visualising personas as goal models to find security tensions..

Spectral-spatial self-attention networks for hyperspectral image classification. (2021)
Journal Article
ZHANG, X., SUN, G., JIA, X., WU, L., ZHANG, A., REN, J., FU, H. and YAO, Y. 2022. Spectral-spatial self-attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5512115. Available from: https://doi.org/10.1109/TGRS.2021.3102143

This study presents a spectral-spatial self-attention network (SSSAN) for classification of hyperspectral images (HSIs), which can adaptively integrate local features with long-range dependencies related to the pixel to be classified. Specifically, i... Read More about Spectral-spatial self-attention networks for hyperspectral image classification..

Deep neural networks based error level analysis for lossless image compression based forgery detection. (2021)
Conference Proceeding
SRI, C.G., BANO, S., DEEPIKA, T., KOLA, N. and PRANATHI, Y.L. 2021. Deep neural networks based error level analysis for lossless image compression based forgery detection. In Proceedings of the 2021 International conference on intelligent technologies (CONIT 2021), 25-27 June 2021, Hubli, India. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/CONIT51480.2021.9498357

The proposed model is implemented in deep learning based on counterfeit feature extraction and Error Level Analysis (ELA) techniques. Error level analysis is used to improve the efficiency of distinguishing copy-move images produced by Deep Fake from... Read More about Deep neural networks based error level analysis for lossless image compression based forgery detection..

Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset] (2021)
Dataset
SANDAL, L.F., BACH, K., ØVERÅS, C.K., WIRATUNGA, N., COOPER, K, et al. 2021. Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset]. JAMA internal medicine [online], 181(10), pages 1288-1296. Available from: https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2782459#supplemental-tab

SELFBACK is an evidence-based decision support system that supports self-management of nonspecific low back pain. In specific, SELFBACK provides the user with evidence-based advice on physical activity level, strength/ flexibility exercises, and educ... Read More about Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. [Dataset].

Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. (2021)
Journal Article
ACEVES-MARTINS, A., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(3), pages 544-560. Available from: https://doi.org/10.1093/nutrit/nuab041

Context: Prevalence of overweight and obesity has been rising in the past 3 decades among Mexican children and adolescents. Objective: To systematically review experimental studies evaluating interventions to treat obesity in Mexican children and ado... Read More about Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis..

Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. (2021)
Journal Article
SANDAL, L.F., BACH, K., ØVERÅS, C.K., WIRATUNGA, N., COOPER, K, et al. 2021. Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. JAMA internal medicine [online], 181(10), pages 1288-1296. Available from: https://doi.org/10.1001/jamainternmed.2021.4097

Importance: Lower back pain (LBP) is a prevalent and challenging condition in primary care. The effectiveness of an individually tailored self-management support tool delivered via a smartphone app has not been rigorously tested. Objective: To invest... Read More about Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial..

A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. (2021)
Journal Article
FANG, Z., REN, J., MACLELLAN, C., LI, H., ZHOA, H., HUSSAIN, A. and FORTINO, G. 2022. A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. IEEE transactions on molecular, biological and multi-scale communications [online], 8(1), pages 17-27. Available from: https://doi.org/10.1109/tmbmc.2021.3099367

To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due... Read More about A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images..

一种基于模糊成像机理的QR码图像快速盲复原方法. (2021)
Journal Article
CHEN, R., ZHENG, Z., ZHAO, H., REN, J. and TAN, H. 2021. 一种基于模糊成像机理的QR 码图像快速 盲复原方法. = [Fast blind restoration of QR code images based on blurred imaging mechanism]. Guangzi xuebao/Acta photonica sinica [online], 50(7), article 0710003. Available from: https://doi.org/10.3788/gzxb20215007.0710003

A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots, the circular finder pattern is designed. When the... Read More about 一种基于模糊成像机理的QR码图像快速盲复原方法..

An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. (2021)
Conference Proceeding
JIANG, M. and ZHANG, L. 2021. An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533847. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533847

The generation of desirable video game contents has been a challenge of games level design and production. In this research, we propose a game player flow experience driven interactive latent variable evolution strategy incorporated with a Deep Convo... Read More about An interactive evolution strategy based deep convolutional generative adversarial network for 2D video game level procedural content generation..

Class-decomposition and augmentation for imbalanced data sentiment analysis. (2021)
Conference Proceeding
MORENO-GARCIA, C.F., JAYNE, C. and ELYAN, E. 2021. Class-decomposition and augmentation for imbalanced data sentiment analysis. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533603. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533603

Significant progress has been made in the area of text classification and natural language processing. However, like many other datasets from across different domains, text-based datasets may suffer from class-imbalance. This problem leads to model's... Read More about Class-decomposition and augmentation for imbalanced data sentiment analysis..

Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. (2021)
Conference Proceeding
WALL, C., ZHANG, L., YU, Y. and MISTRY, K. 2021. Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533966. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533966

In recent years, a variety of deep learning techniques and methods have been adopted to provide AI solutions to issues within the medical field, with one specific area being audio-based classification of medical datasets. This research aims to create... Read More about Deep recurrent neural networks with attention mechanisms for respiratory anomaly classification..

Detecting image similarity using SIFT. (2021)
Conference Proceeding
SRI, K.H., MANASA, G.T., REDDY, G.G., BANO, S. and TRINADH, V.B. 2022. Detecting image similarity using SIFT. In Jacob, I.J., Gonzalez-Longatt, F.M., Shanmugam, S.K. and Izonin, I. (eds.) Proceedings of the 2021 International conference on expert clouds and applications (ICOECA 2021), 18-19 February 2021, Bangalore, India. Lecture notes in networks and systems, 209. Singapore: Springer [online], pages 561-575. Available from: https://doi.org/10.1007/978-981-16-2126-0_45

Manually identifying similarity between any images is a difficult task. This study proposes an image similarity detection model. The scale-invariant feature transform (SIFT) algorithm is used to detect similarity between input images, and also to cal... Read More about Detecting image similarity using SIFT..

Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms. (2021)
Presentation / Conference
HAN, K., CHRISTIE, L.A., ZAVOIANU, A.-C. and MCCALL, J. 2021. Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms. Presented at 2021 Genetic and evolutionary computation conference (GECCO 2021), 10-14 July 2021, [virtual conference].

The past five years have seen a rapid development of plans and test pilots aimed at introducing connected and autonomous vehicles (CAVs) in public transport systems around the world. Using a real-world scenario from the Leeds Metropolitan Area as a c... Read More about Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms..

A multi-institutional exploration of the social mobility potential of degree apprenticeships. (2021)
Journal Article
SMITH, S., TAYLOR-SMITH, E., FABIAN, K., ZARB, M., PATERSON, J., BARR, M. and BERG, T. 2021. A multi-institutional exploration of the social mobility potential of degree apprenticeships. Journal of education and work [online], 34(4), pages 488-503. Available from: https://doi.org/10.1080/13639080.2021.1946494

This mixed-method study at six universities asked degree apprentices about their trajectories into the apprenticeship, to better understand the social mobility potential of apprenticeships. The degree apprenticeship offers a route to a degree for app... Read More about A multi-institutional exploration of the social mobility potential of degree apprenticeships..

Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. (2021)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2021. Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem. In Chicano, F. (ed.) GECCO '21: proceedings of 2021 Genetic and evolutionary computation conference companion, 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 1405-1413. Available from: https://doi.org/10.1145/3449726.3463139

Recent work in combinatorial optimisation have demonstrated that neighbouring solutions of a local optima may belong to more favourable attraction basins. In this sense, the perturbation strategy plays a critical role on local search based algorithms... Read More about Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem..

Experiences of piloting the learning by developing action model in a computing science context. (2021)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2021. Experiences of piloting the learning by developing action model in a computing science context. In Gómez Chova, L., López Martínez, A. and Candel Torres, I. (eds.) EDULEARN 21: proceedings of the 13th international conference on Education and new learning technologies 2021 (EDULEARN 2021), 5-6 July 2021, [virtual conference]. Valencia: International Academy of Technology, Education and Development (IATED) [online], pages 3036-3042. To be available from: https://doi.org/10.21125/edulearn.2021

This article describes the piloting of the Learning by Developing (LbD) action model in the UK. The purpose of the pilot is to study how a pedagogical method based on the LbD can be introduced in computing students in the UK. The LbD action model has... Read More about Experiences of piloting the learning by developing action model in a computing science context..

Android mobile malware detection using machine learning: a systematic review. (2021)
Journal Article
SENANAYAKE, J., KALUTARAGE, H. and AL-KADRI, M.O. 2021. Android mobile malware detection using machine learning: a systematic review. Electronics [online], 10(13), article 1606. Available from: https://doi.org/10.3390/electronics10131606

With the increasing use of mobile devices, malware attacks are rising, especially on Android phones, which account for 72.2% of the total market share. Hackers try to attack smartphones with various methods such as credential theft, surveillance, and... Read More about Android mobile malware detection using machine learning: a systematic review..

Fast blind deblurring of QR code images based on adaptive scale control. (2021)
Journal Article
CHEN, R., ZHENG, Z., PAN, J., YU, Y., ZHAO, H. and REN, J. 2022. Fast blind deblurring of QR code images based on adaptive scale control. Mobile networks and applications [online], 26(6), pages 2472-2487. Available from: https://doi.org/10.1007/s11036-021-01780-y

With the development of 5G technology, the short delay requirements of commercialization and large amounts of data change our lifestyle day-to-day. In this background, this paper proposes a fast blind deblurring algorithm for QR code images, which ma... Read More about Fast blind deblurring of QR code images based on adaptive scale control..

Proceedings of the 2021 SICSA explainable artificial intelligence workshop (SICSA XAI 2021) (2021)
Conference Proceeding
MARTIN, K., WIRATUNGA, N. and WIJEKOON, A. (eds.) 2021. Proceedings of the 2021 SICSA explainable artificial intelligence workshop (SICSA XAI 2021), 1 June 2021, Aberdeen, UK. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online]. Available from: https://ceur-ws.org/Vol-2894/

The SICSA Workshop 2021 was designed to present a forum for the dissemination of ideas on domains relating to the explainability of Artificial Intelligence and Machine Learning methods. The event was organised into several themed sessions: Session 1... Read More about Proceedings of the 2021 SICSA explainable artificial intelligence workshop (SICSA XAI 2021).

Face detection with YOLO on edge. (2021)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCIA, C.F. and ZWIEGELAAR, J. 2021. Face detection with YOLO on edge. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Enginering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 284-292. Available from: https://doi.org/10.1007/978-3-030-80568-5_24

Significant progress has been achieved in objects detection applications such as Face Detection. This mainly due to the latest development in deep learning-based approaches and especially in the computer vision domain. However, deploying deep-learnin... Read More about Face detection with YOLO on edge..