Recent Submissions

  • Spatial effects of video compression on classification in convolutional neural networks. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (IEEE, 2018-07-08)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Spatial effects of video compression on classification in convolutional neural networks. In Proceedings of the international joint neural networks conference 2018 (IJCNN), 8-13 July 2018, Rio de Janeiro, Brazil.
    A collection of Computer Vision application reuse pre-learned features to analyse video frame-by-frame. Those features are classically learned by Convolutional Neural Networks (CNN) trained on high quality images. However, ...
  • Stokes coordinates. 

    Savoye, Yann (ACM https://doi.org/10.1145/3154353.3154354, 2017-05-15)
    SAVOYE, Y. 2017. Stokes coordinates. In Proceedings of the 33rd computer graphics spring conference, 15-17 May 2017, Mikulov, Czech Republic. New York: ACM [online], article no. 5. Available from: https://doi.org/10.1145/3154353.3154354
    Cage-based structures are reduced subspace deformers enabling non-isometric stretching deformations induced by clothing or muscle bulging. In this paper, we reformulate the cage-based rigging as an incompressible Stokes ...
  • Towards computational dialogue types for BIM collaborative design: an initial study. 

    Toniolo, Alice; Leon, Marianthi (CEUR Workshop Proceedings http://ceur-ws.org/Vol-2012/, 2017-11-16)
    TONIOLO, A. and LEON, M. 2017. Towards computational dialogue types for BIM collaborative design: an initial study. In Bistarelli, S., Giacomin, M. and Pazienza, A. (eds). Proceedings of the 1st advances in argumentation in artificial intelligence workshop (AI^3 2017), 16-17 November 2017, Bari, Italy. Bari: CEUR Workshop Proceedings [online], pages 79-84. Available from: http://ceur-ws.org/Vol-2012/AI3-2017_paper_8.pdf
    Collaborative design is an iterative process of selecting and evaluating solutions under potentially conflicting requirements, a concept central to Building Information Modelling (BIM) implementation. Previous research has ...
  • CSDM: SelfBACK: self-management of low back pain. [Project website] 

    School of Computing and Digital Media (Robert Gordon University http://www.comp.rgu.ac.uk/selfback/, 2016-01-01)
    SCHOOL OF COMPUTING SCIENCE AND DIGITAL MEDIA 2016. CSDM: SelfBACK: self-management of low back pain. Aberdeen: Robert Gordon University [online]. Available from: http://www.comp.rgu.ac.uk/selfback/
  • SelfBACK: a decision support system to improve self-management of non-specific low back pain. [Project website] 

    SelfBACK Project (SelfBACK http://www.selfback.eu/, 2016-01-01)
    SELFBACK PROJECT. 2016. SelfBACK: a decision support system to improve self-management of non-specific low back pain. Norway: SelfBACK [online]. Available from: http://www.selfback.eu/
    This is the official project website for the SelfBack project. The project will run from Jan 2016 – Dec 2020. The aim of the project is to improve self-management of non-specific low back pain through the development of a ...
  • Accuracy of physical activity recognition from a wrist-worn sensor. 

    Cooper, Kay; Sani, Sadiq; Corrigan, Liam; MacDonald, Haley; Prentice, Chris; Vareta, Rob; Massie, Stewart; Wiratunga, Nirmalie (Physiotherapy UK http://www.physiotherapyuk.org.uk/, 2017-11-10)
    COOPER, K., SANI, S., CORRIGAN, L., MACDONALD, H., PRENTICE, C., VARETA, R., MASSIE, S. and WIRATUNGA, N. 2017. Accuracy of physical activity recognition from a wrist-worn sensor. Presented at the Physiotherapy UK conference and trade exhibition 2017: transform lives, maximise independence and empower populations, 10-11 November 2017, Birmingham, UK.
    The EU-funded project 'selfBACK' (http://www.selfback.eu) will utilise continuous objective monitoring of physical activity (PA) by a wrist-mounted wearable, combined with self-monitoring of symptoms and case-based reasoning. ...
  • Simulation and optimisation of the separation process in offshore oil and gas platforms. 

    Veleshki, Stoyan Ivanov (Robert Gordon University School of Computing Science and Digital Media, 2017-10-01)
    VELESHKI, S. 2017. Simulation and optimisation of the separation process in offshore oil and gas platforms. Robert Gordon University, MRes thesis.
    Hydrocarbon separation in offshore oil and gas platforms is the process that transforms extracted crude oil into transportable oil and gas. Temperatures and pressures of the separation system can be adjusted to modify the ...
  • Improving e-learning recommendation by using background knowledge. 

    Mbipom, Blessing; Craw, Susan; Massie, Stewart (Wiley https://doi.org/10.1111/exsy.12265, 2018-01-26)
    MBIPOM, B., CRAW, S. and MASSIE, S. 2018. Improving e-learning recommendation by using background knowledge. Expert systems [online], Early View. Available from: https://doi.org/10.1111/exsy.12265
    There is currently a large amount of e-Learning resources available to learners on the Web. However, learners often have difficulty finding and retrieving relevant materials to support their learning goals because they ...
  • An e-learning recommender that helps learners find the right materials. 

    Mbipom, Blessing; Massie, Stewart; Craw, Susan (Association for the Advancement of Artificial Intelligence, 2018-02-03)
    MBIPOM, B., MASSIE, S. and CRAW, S. [2018]. An e-learning recommender that helps learners find the right materials. To be presented at the 8th educational advances in artificial intelligence 2018 (EAAI-18), 3-4 February 2018, New Orleans, USA, (accepted).
    Learning materials are increasingly available on the Web making them an excellent source of information for building e-Learning recommendation systems. However, learners often have difficulty finding the right materials ...
  • Taxonomic corpus-based concept summary generation for document annotation. 

    Nkisi-Orji, Ikechukwu; Wiratunga, Nirmalie; Hui, Kit-Ying; Heaven, Rachel; Massie, Stewart (Springer https://doi.org/10.1007/978-3-319-67008-9_5, 2017-09-02)
    NKISI-ORJI, I., WIRATUNGA, N., HUI, K.-Y., HEAVEN, R. and MASSIE, S. 2017. Taxonomic corpus-based concept summary generation for document annotation. In Kampus, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L. and Karydis, I. (eds). Lecture notes in computer science [online], 10450, research and advanced technology for digital libraries: proceedings of the 21st international conference on theory and practice of digital libraries (TPDL 2017), 18-21 September 2017, Thessaloniki, Greece. Cham: Springer, pages 49-60. Available from: https://doi.org/10.1007/978-3-319-67008-9_5
    Semantic annotation is an enabling technology which links documents to concepts that unambiguously describe their content. Annotation improves access to document contents for both humans and software agents. However, the ...
  • Evolving ANN-based sensors for a context-aware cyber physical system of an offshore gas turbine. 

    Majdani, Farzan; Petrovski, Andrei; Doolan, Daniel C. (Springer https://doi.org/10.1007/s12530-017-9206-8, 2017-10-27)
    MAJDANI, F., PETROVSKI, A. and DOOLAN, D. 2017. Evolving ANN-based sensors for a context-aware cyber physical system of an offshore gas turbine. Evolving systems [online], OnlineFirst. Available from: https://doi.org/10.1007/s12530-017-9206-8
    An adaptive multi-tiered framework, that can be utilised for designing a context-aware cyber physical system to carry out smart data acquisition and processing, while minimising the amount of necessary human intervention ...
  • Deep imitation learning for 3D navigation tasks. 

    Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina (Springer https://doi.org/10.1007/s00521-017-3241-z, 2017-12-04)
    HUSSEIN, A., ELYAN, E., GABER, M.M. and JAYNE, C. 2018. Deep imitation learning for 3D navigation tasks. Neural computing and applications [online], 29(7), pages 389-404. Available from: https://doi.org/10.1007/s00521-017-3241-z
    Deep learning techniques have shown success in learning from raw high dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, ...
  • Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. 

    McDermott, Christopher D.; Petrovski, Andrei (AIRCC http://airccse.org/journal/ijc2017.html, 2017-07-31)
    MCDERMOTT, C.D. and PETROVSKI, A. 2017. Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. International journal of computer networks and communications [online], 9(4), pages 45-56. Available from: https://doi.org/10.5121/ijcnc.2017.9404
    Wireless Sensor Networks (WSNs) have become a key technology for the IoT and despite the obvious benefits, challenges still exist regarding security. As more devices are connected to the internet, new cyber attacks are ...
  • A framework for unsupervised change detection in activity recognition. 

    Bashir, Sulaimon A.; Petrovski, Andrei; Doolan, Daniel C. (Emerald https://doi.org/10.1108/IJPCC-03-2017-0027, 2017-06-05)
    BASHIR, S.A., PETROVSKI, A. and DOOLAN, D. 2017. A framework for unsupervised change detection in activity recognition. International journal of pervasive computing and communications [online], 13(2), pages 157-175. Available from: https://doi.org/10.1108/IJPCC-03-2017-0027
    Purpose - This purpose of this paper is to develop a change detection technique for activity recognition model. The approach aims to detect changes in the initial accuracy of the model after training and when the model is ...
  • The effect of person order on egress time: a simulation model of evacuation from a Neolithic visitor attraction. 

    Stewart, Arthur D.; Elyan, Eyad; Isaacs, John; McEwen, Leah; Wilson, Lyn (Sage https://doi.org/10.1177/0018720817729608, 2017-09-19)
    STEWART, A., ELYAN, E., ISAACS, J., MCEWEN, L. and WILSON, L. 2017. The effect of person order on egress time: a simulation model of evacuation from a neolithic visitor attraction. Human factors [online], 59(8), pages 1222-1232. Available from: https://doi.org/10.1177/0018720817729608
    Objective: The aim of this study was to model the egress of visitors from a Neolithic visitor attraction. Background: Tourism attracts increasing numbers of elderly and mobility-impaired visitors to our built-environment ...
  • A convolutional Siamese network for developing similarity knowledge in the SelfBACK dataset. 

    Martin, Kyle; Wiratunga, Nirmalie; Sani, Sadiq; Massie, Stewart; Clos, Jérémie (ICCBR (Organisers), 2017-06-26)
    MARTIN, K., WIRATUNGA, N., SANI, S., MASSIE, S. and CLOS, J. 2017. A convolutional Siamese network for developing similarity knowledge in the SelfBACK dataset. Presented at the 25th international case-based reasoning conference (ICCBR 2017): case-based reasoning and deep learning workshop (CBRDL 2017), 26 June 2017, Trondheim, Norway.
    The Siamese Neural Network (SNN) is a neural network architecture capable of learning similarity knowledge between cases in a case base by receiving pairs of cases and analysing the differences between their features to ...
  • Learning deep features for kNN-based human activity recognition. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart (ICCBR (Organisers), 2017-06-26)
    SANI, S., WIRATUNGA, N. and MASSIE, S. 2017. Learning deep features for kNN-based human activity recognition. Presented at the 25th international case-based reasoning conference (ICCBR 2017): case-based reasoning and deep learning workshop (CBRDL 2017), 26-28 June 2017, Trondheim, Norway.
    A CBR approach to Human Activity Recognition (HAR) uses the kNN algorithm to classify sensor data into different activity classes. Different feature representation approaches have been proposed for sensor data for the ...
  • kNN sampling for personalised human recognition. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (Springer https://doi.org/10.1007/978-3-319-61030-6_23, 2017-06-21)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2017. kNN sampling for personalised human recognition. Lecture notes in computer science, 10339, case-based reasoning research and development: proceedings of the 25th international case-based reasoning conference (ICCBR 2017), 26-28 June 2017, Trondheim, Norway. Cham: Springer [online], pages 330-344. Available from: https://doi.org/10.1007/978-3-319-61030-6_23
    The need to adhere to recommended physical activity guidelines for a variety of chronic disorders calls for high precision Human Activity Recognition (HAR) systems. In the SelfBACK system, HAR is used to monitor activity ...
  • Learning deep and shallow features for human activity recognition. 

    Sani, Sadiq; Massie, Stewart; Wiratunga, Nirmalie; Cooper, Kay (Springer https://doi.org/10.1007/978-3-319-63558-3_40, 2017-07-19)
    SANI, S., MASSIE, S., WIRATUNGA, N. and COOPER, K. 2017. Learning deep and shallow features for human activity recognition. Lecture notes in artificial intelligence, 10412: proceedings of the 10th international knowledge science engineering and management conference (KESEM 2017), 19-20 August 2017, Melbourne, Australia. Cham: Springer [online], pages 469-482. Available from: https://doi.org/10.1007/978-3-319-63558-3_40
    selfBACK is an mHealth decision support system used by patients for the self-management of Lower Back Pain. It uses Human Activity Recognition from wearable sensors to monitor user activity in order to measure their adherence ...
  • Architecting the deployment of cloud-hosted services for guaranteeing multitenancy isolation. 

    Ochei, Laud Charles (Robert Gordon University School of Computing Science and Digital Media, 2017-05-01)
    OCHEI, L.C. 2017. Architecting the deployment of cloud-hosted services for guaranteeing multitenancy isolation. Robert Gordon University, PhD thesis.
    In recent years, software tools used for Global Software Development (GSD) processes (e.g., continuous integration, version control and bug tracking) are increasingly being deployed in the cloud to serve multiple users. ...

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