All Outputs (98)

Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. [Dataset] (2021)
Dataset
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. [Dataset]. Science of the total environment [online], 784, article 146956. Available from: https://www.sciencedirect.com/science/article/pii/S004896972102026X#s0105

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. [Dataset].

VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. (2021)
Conference Proceeding
HAN, K., PHAM, T., VU, T.H., DANG, T., MCCALL, J. and NGUYEN, T.T. 2021. VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. In Nguyen, N.T., Chittayasothorn, S., Niyato, D. and Trawiński, B. (eds.) Intelligent information and database systems: proceedings of the 13th Asian conference on intelligent information and database systems 2021 (ACCIIDS 2021), 7-10 April 2021, [virtual conference]. Lecture Notes in Computer Science, 12672. Cham: Springer [online], pages 168–180. Available from: https://doi.org/10.1007/978-3-030-73280-6_14

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for th... Read More about VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning..

A multimodal corpus of simulated consultations between a patient and multiple healthcare professionals. (2021)
Journal Article
SNAITH, M., CONWAY, N., BEINEMA, T., DE FRANCO, D., PEASE, A., KANTHARAJU, R., JANIER, M., HUIZING, G., PELACHAUD, C. and OP DEN AKKER, H. 2021. A multimodal corpus of simulated consultations between a patient and multiple healthcare professionals. Language resources and evaluation [online], 55(4), pages 1077-1092. Available from: https://doi.org/10.1007/s10579-020-09526-0

Language resources for studying doctor–patient interaction are rare, primarily due to the ethical issues related to recording real medical consultations. Rarer still are resources that involve more than one healthcare professional in consultation wit... Read More about A multimodal corpus of simulated consultations between a patient and multiple healthcare professionals..

Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. (2021)
Journal Article
MEDINA, E.C.G., ESPITIA, V.M.V., SILVA, D.C., DE LAS CUEVAS, S.F.R., HIRATA, M.P., CHEN, A.Z., GONZÁLEZ, J.A.G., BUSTAMANTE-BELLO, R. and MORENO-GARCÍA, C.F. 2021. Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. Applied sciences [online], 11(7), article 2925. Available from: https://doi.org/10.3390/app11072925

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional... Read More about Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems..

Feature selection using enhanced particle swarm optimisation for classification models. (2021)
Journal Article
XIE, H., ZHANG, L., LIM, C.P., YU, Y. and LIU, H. 2021. Feature selection using enhanced particle swarm optimisation for classification models. Sensors [online], 21(5), article 1816. Available from: https://doi.org/10.3390/s21051816

In this research, we propose two Particle Swarm Optimisation (PSO) variants to undertake feature selection tasks. The aim is to overcome two major shortcomings of the original PSO model, i.e., premature convergence and weak exploitation around the ne... Read More about Feature selection using enhanced particle swarm optimisation for classification models..

Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. (2021)
Journal Article
ZHANG, L., LIM, C.P. and YU, Y. 2021. Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. Knowledge-based systems [online], 220, article ID 106918. Available from: https://doi.org/10.1016/j.knosys.2021.106918

Automatic interpretation of human actions from realistic videos attracts increasing research attention owing to its growing demand in real-world deployments such as biometrics, intelligent robotics, and surveillance. In this research, we propose an e... Read More about Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization..

Personalised exercise recognition towards improved self-management of musculoskeletal disorders. (2021)
Thesis
WIJEKOON, A. 2021. Personalised exercise recognition towards improved self-management of musculoskeletal disorders. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1358224

Musculoskeletal Disorders (MSD) have been the primary contributor to the global disease burden, with increased years lived with disability. Such chronic conditions require self-management, typically in the form of maintaining an active lifestyle whil... Read More about Personalised exercise recognition towards improved self-management of musculoskeletal disorders..

Convolutional network based animal recognition using YOLO and darknet. (2021)
Conference Proceeding
REDDY, B.K., BANO, S., REDDY, G.G., KOMMINENI, R. and REDDY, P.Y. 2021. Convolutional network based animal recognition using YOLO and darknet. In Proceedings of the 6th International conference on inventive computation technologies (ICICT 2021), 20-22 January 2021, Coimbatore, India. Piscataway: IEEE [online], pages 1198-1203. Available from: https://doi.org/10.1109/ICICT50816.2021.9358620

In general, the manual detection of animals with their names is a very tedious task. To overcome this challenge, this research work has developed a YOLOV3 model to identify the animal present in the image given by user. The algorithm used in YOLOV3 m... Read More about Convolutional network based animal recognition using YOLO and darknet..

Similarity score of two images using different measures. (2021)
Conference Proceeding
APPANA, V., GUTTIKONDA, T.M., SHREE, D., BANO, S. and KURRA, H. 2021. Similarity score of two images using different measures. In Proceedings of the 6th International conference on inventive computation technologies (ICICT 2021), 20-22 January 2021, Coimbatore, India. Piscataway: IEEE [online], pages 741-746. Available from: https://doi.org/10.1109/ICICT50816.2021.9358789

In the field of computer vision and image processing, image similarity has been a central concern for decades. If you compare two pictures, Image Similarity returns a value that tells you how physically they are close. A quantitative measure of the d... Read More about Similarity score of two images using different measures..

Traditional and contemporary approaches to mathematical fitness-fatigue models in exercise science: a practical guide with resources. Part II. (2021)
Working Paper
SWINTON, P., STEPHENS HEMINGWAY, B., RASCHE, C., PFEIFFER, M. and OGOREK, B. 2021. Traditional and contemporary approaches to mathematical fitness-fatigue models in exercise science: a practical guide with resources. Part II. SportRxiv [online]. Available from: https://doi.org/10.31236/osf.io/5qgc2

The standard fitness-fatigue model (FFM) is known to include several limitations described by the linearity assumption, the independence assumption and the deterministic assumption. These limitations ensure that the modelled response to chronic train... Read More about Traditional and contemporary approaches to mathematical fitness-fatigue models in exercise science: a practical guide with resources. Part II..

Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets. (2021)
Journal Article
SUN, H., LIU, Q., WANG, J., REN, J., WU, Y., ZHAO, H. and LI, H. 2021. Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 2971-2983. Available from: https://doi.org/10.1109/JSTARS.2021.3061496

Detection of the low-altitude and slow-speed small (LSS) targets is one of the most popular research topics in remote sensing. Despite of a few existing approaches, there is still an accuracy gap for satisfying the practical needs. As the LSS targets... Read More about Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets..

Evaluating privacy: determining user privacy expectations on the web. (2021)
Journal Article
PILTON, C., FAILY, S., and HENRIKSEN-BULMER, J. 2021. Evaluating privacy: determining user privacy expectations on the web. Computers and security [online], 105, article 102241. Available from: https://doi.org/10.1016/j.cose.2021.102241

Individuals don’t often have privacy expectations. When asked to consider them, privacy realities were frequently perceived not to meet these expectations. Some websites exploit the trust of individuals by selling, sharing, or analysing their data. W... Read More about Evaluating privacy: determining user privacy expectations on the web..

A new cost function for spatial image steganography based on 2D-SSA and WMF. (2021)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H. and LI, H. 2021. A new cost function for spatial image steganography based on 2D-SSA and WMF. IEEE access [online], 9, pages 30604-30614. Available from: https://doi.org/10.1109/ACCESS.2021.3059690

As an essential tool for secure communications, adaptive steganography aims to communicate secret information with the least security cost. Inspired by the Ranking Priority Profile (RPP), we propose a novel two-step cost function for adaptive stegano... Read More about A new cost function for spatial image steganography based on 2D-SSA and WMF..

LTMS: a lightweight trust management system for wireless medical sensor networks. (2021)
Conference Proceeding
HAJAR, M.S., AL-KADRI, M.O. and KALUTARAGE, H. 2020. LTMS: a lightweight trust management system for wireless medical sensor networks. In Wang, G., Ko, R., Bhuiyan, M.Z.A. and Pan, Y. (eds.). Proceedings of 19th Institute of Electrical and Electronics Engineers (IEEE) Trust, security and privacy in computing and communication international conference 2020 (TrustCom 2020), 29 Dec 2020 - 1 Jan 2021, Guangzhou, China. Piscataway: IEEE [online], pages 1783-1790. Available from: https://doi.org/10.1109/TrustCom50675.2020.00245

Wireless Medical Sensor Networks (WMSNs) offer ubiquitous health applications that enhance patients' quality of life and support national health systems. Detecting internal attacks on WMSNs is still challenging since cryptographic measures can not pr... Read More about LTMS: a lightweight trust management system for wireless medical sensor networks..

Evaluating explainability methods intended for multiple stakeholders. (2021)
Journal Article
MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2021. Evaluating explainability methods intended for multiple stakeholders. KI - Künstliche Intelligenz [online], 35(3-4), pages 397-411. Available from: https://doi.org/10.1007/s13218-020-00702-6

Explanation mechanisms for intelligent systems are typically designed to respond to specific user needs, yet in practice these systems tend to have a wide variety of users. This can present a challenge to organisations looking to satisfy the explanat... Read More about Evaluating explainability methods intended for multiple stakeholders..

A survey on wireless body area networks: architecture, security challenges and research opportunities. (2021)
Journal Article
HAJAR, M.S., AL-KADRI, M.O. and KALUTARAGE, H.K. 2021. A survey on wireless body area networks: architecture, security challenges and research opportunities. Computers and security [online], 104, article ID 102211. Available from: https://doi.org/10.1016/j.cose.2021.102211

In the era of communication technologies, wireless healthcare networks enable innovative applications to enhance the quality of patients’ lives, provide useful monitoring tools for caregivers, and allows timely intervention. However, due to the sensi... Read More about A survey on wireless body area networks: architecture, security challenges and research opportunities..

Particle swarm optimization for automatically evolving convolutional neural networks for image classification. (2021)
Journal Article
LAWRENCE, T., ZHANG, L., LIM, C.P. and PHILLIPS, E.-J. 2021. Particle swarm optimization for automatically evolving convolutional neural networks for image classification. IEEE access [online], 9, pages 14369-14386. Available from: https://doi.org/10.1109/ACCESS.2021.3052489

Designing Convolutional Neural Networks from scratch is a time-consuming process that requires specialist expertise. While automated architecture generation algorithms have been proposed, the underlying search strategies generally are computationally... Read More about Particle swarm optimization for automatically evolving convolutional neural networks for image classification..

Resource efficient boosting method for IoT security monitoring. (2021)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O. and KALUTARAGE, H. 2021. Resource efficient boosting method for IoT security monitoring. In Proceedings of 18th Institute of Electrical and Electronics Engineers (IEEE) Consumer communications and networking conference 2021 (CCNC 2021), 9-12 January 2021, [virtual conference]. Piscataway: IEEE [online], article 9369620. Available from: https://doi.org/10.1109/ccnc49032.2021.9369620

Machine learning (ML) methods are widely proposed for security monitoring of Internet of Things (IoT). However, these methods can be computationally expensive for resource constraint IoT devices. This paper proposes an optimized resource efficient ML... Read More about Resource efficient boosting method for IoT security monitoring..