Recent Submissions

  • Real-time relative permeability prediction using deep learning. 

    Arigbe, Ovoke D.; Oyeneyin, Babs; Arana, Ines; Droubi, M. Ghazi
    ARIGBE, O.D., OYENEYIN, M.B., ARANA, I. and GHAZI, M.D. [2018]. Real-time relative permeability prediction using deep learning. Journal of petroleum exploration and production technologies [online], (accepted).
    A review of the existing two and three phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real ...
  • Modelling the generalised median correspondence through an edit distance. 

    Moreno-García, Carlos Francisco; Serratosa, Francesc (Springer https://doi.org/10.1007/978-3-319-97785-0_26, 2018-08-02)
    MORENO-GARCÍA, C.F. and SERRATOSA, F. 2018. Modelling the generalised median correspondence through an edit distance. In Bai, X., Hancock, E., Ho, T., Wilson, R., Biggio, B. and Robles-Kelly, A. (eds.) Lecture notes in computer science, 11004: structural, syntactic and statistical pattern recognition: proceedings of the Joint International Association of Pattern Recognition (IAPR) international workshop on structural and syntactic pattern recognition and statistical techniques in pattern recognition (S+SSPR 2018), 17-19 August 2018, Beijing, China. Cham: Springer [online], pages 271-281. Available from: https://doi.org/10.1007/978-3-319-97785-0_26
    On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural ...
  • Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. 

    Ochei, Laud Charles; Bass, Julian M.; Petrovski, Andrei
    OCHEI, L.C., BASS, J.M. and PETROVSKI, A. [2018]. Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. Journal of cloud computing [online], (accepted).
    A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and ...
  • A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. 

    Ochei, Laud Charles; Petrovski, Andrei; Bass, Julian M. (Inderscience https://doi.org/10.1504/IJCC.2018.095399, 2018-09-20)
    OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2018. A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. International journal of cloud computing [online], 7(3-4), pages 248-281. Available from: https://doi.org/10.1504/IJCC.2018.095399
    Multitenancy allows multiple tenants to access a single instance of a cloud offering. While several approaches exist for implementing multitenancy, little attention has been paid to implementing the required degree of ...
  • Iterated racing algorithm for simulation-optimisation of maintenance planning. 

    Lacroix, Benjamin; McCall, John; Lonchampt, Jérôme (IEEE https://doi.org/10.1109/CEC.2018.8477843, 2018-07-08)
    LACROIX, B., MCCALL, J. and LONCHAMPT, J. 2018. Iterated racing algorithm for simulation-optimisation of maintenance planning. In Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation 2018 (CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. New York: IEEE [online], pages 1-7. Available from: https://doi.org/10.1109/CEC.2018.8477843
    The purpose of this paper is two fold. First, we present a set of benchmark problems for maintenance optimisation called VMELight. This model allows the user to define the number of components in the system to maintain and ...
  • Opinion context extraction for aspect sentiment analysis. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Massie, Stewart; Luhar, Rushi (AAAI Press https://www.aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17859, 2018-06-15)
    BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Opinion context extraction for aspect sentiment analysis. In Proceedings of 12th International Association for the Advancement of Artificial Intelligence (AAAI) conference on web and social media 2018 (ICWSM 2018), 25-28 June 2018, Palo Alto, USA. Palo Alto: AAAI Press [online], pages 564-567. Available from: https://www.aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17859/17051
    Sentiment analysis is the computational study of opinionated text and is becoming increasing important to online commercial applications. However, the majority of current approaches determine sentiment by attempting to ...
  • CFD modelling of pipe erosion due to sand transport. 

    Ogunsesan, Oluwademilade Adekunle; Hossain, Mamdud; Iyi, Draco; Droubi, M. Ghazi (Springer https://doi.org/10.1007/978-981-13-2273-0_22, 2018-08-28)
    OGUNSESAN, O.A., HOSSAIN, M., IYI, D. and DHROUBI, M.G. 2018. CFD modelling of pipe erosion due to sand transport. In Wahab, M.A. (ed.) Numerical modelling in civil engineering, 2: proceedings of the 1st International conference on numerical modelling in engineering (NME 1018); 28-29 August 2018, Ghent, Belgium. Singapore: Springer [online], pages 274-289. Available from: https://doi.org/10.1007/978-981-13-2273-0_22
    Erosion caused by sand particles is a serious problem facing the oil and gas industry. Predicting pipe erosion due to sand transport is a complex process in multiphase flows due to the complex nature of the flow. Existing ...
  • Lexicon induction for interpretable text classification. 

    Clos, Jérémie; Wiratunga, Nirmalie (Springer https://doi.org/10.1007/978-3-319-67008-9_39, 2017-09-02)
    CLOS, J. and WIRATUNGA, N. 2017. Lexicon induction for interpretable text classification. In Kampus, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L. and Karydis, I. (eds). Lecture notes in computer science, 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 [online], pages 498-510. Available from: https://doi.org/10.1007/978-3-319-67008-9_39
    The automated classification of text documents is an active research challenge in document-oriented information systems, helping users browse massive amounts of data, detecting likely authors of unsigned work, or analyzing ...
  • Deep imitation learning with memory for robocup soccer simulation. 

    Hussein, Ahmed; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_3, 2018-07-27)
    HUSSEIN, A., ELYAN, E. and JAYNE, C. 2018. Deep imitation learning with memory for robocup soccer simulation. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. Cham: Springer [online], pages 31-43. Available from: https://doi.org/10.1007/978-3-319-98204-5_3
    Imitation learning is a field that is rapidly gaining attention due to its relevance to many autonomous agent applications. Providing demonstrations of effective behaviour to teach the agent is useful in real world challenges ...
  • Toward video tampering exposure: inferring compression parameters from pixels. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_4, 2018-07-27)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks conference (EANN 2018), 3-5 September 2018, Bristol, UK. Cham: Springer [online], pages 44-57. Available from: https://doi.org/10.1007/978-3-319-98204-5_4
    Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression ...
  • Combining heterogeneous classifiers via granular prototypes. 

    Nguyen, Tien Thanh; Nguyen, Mai Phuong; Pham, Xuan Cuong; Liew, Alan Wee-Chung; Pedrycz, Witold (Elsevier https://doi.org/10.1016/j.asoc.2018.09.021, 2018-09-28)
    NGUYEN, T.T., NGUYEN, M.P., PHAM, X.C., LIEW, A. W.-C. and PEDRYCZ, W. 2018. Combining heterogeneous classifiers via granular prototypes. Applied soft computing [online], 73, pages 795-815. Available from: https://doi.org/10.1016/j.asoc.2018.09.021
    In this study, a novel framework to combine multiple classifiers in an ensemble system is introduced. Here we exploit the concept of information granule to construct granular prototypes for each class on the outputs of an ...
  • Correspondence edit distance to obtain a set of weighted means of graph correspondences. 

    Moreno-García, Carlos Francisco; Serratosa, Francesc; Xiaoyi, Jiang (Elsevier https://doi.org/10.1016/j.patrec.2018.08.027, 2018-08-30)
    MORENO-GARCIA, C.F., SERRATOSA, F. and XIAOYI, J. 2018. Correspondence edit distance to obtain a set of weighted means of graph correspondences. Pattern recognition letters [online], In Press. Available from: https://doi.org/10.1016/j.patrec.2018.08.027
    Given a pair of data structures, such as strings, trees, graphs or sets of points, several correspondences (also referred in literature as labellings, matchings or assignments) can be defined between their local parts. The ...
  • Deep learning based approaches for imitation learning. 

    Hussein, Ahmed (Robert Gordon University School of Computing Science and Digital Media, 2018-05-01)
    HUSSEIN, A. 2018. Deep learning based approaches for imitation learning. Robert Gordon University, PhD thesis.
    Imitation learning refers to an agent's ability to mimic a desired behaviour by learning from observations. The field is rapidly gaining attention due to recent advances in computational and communication capabilities as ...
  • Change detection for activity recognition. 

    Bashir, Sulaimon A. (Robert Gordon University School of Computing Science and Digital Media, 2017-11-01)
    BASHIR, S.A. 2017. Change detection for activity recognition. Robert Gordon University, PhD thesis.
    Activity Recognition is concerned with identifying the physical state of a user at a particular point in time. Activity recognition task requires the training of classification algorithm using the processed sensor data ...
  • Domain-specific lexicon generation for emotion detection from text. 

    Bandhakavi, Anil (Robert Gordon University School of Computing and Digital Media, 2018-01-01)
    BANDHAKAVI, A. 2018. Domain-specific lexicon generation for emotion detection from text. Robert Gordon University, PhD thesis.
    Emotions play a key role in effective and successful human communication. Text is popularly used on the internet and social media websites to express and share emotions, feelings and sentiments. However useful applications ...
  • Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. 

    Ayodele, Mayowa (Robert Gordon University School of Computing and Digital Media, 2018-05-01)
    AYODELE, M. 2018. Effective and efficient estimation of distribution algorithms for permutation and scheduling problems. Robert Gordon University, PhD thesis.
    Estimation of Distribution Algorithm (EDA) is a branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables ...
  • Digital interpretation of sensor-equipment diagrams. 

    Moreno-García, Carlos Francisco (CEUR http://ceur-ws.org/Vol-2151/, 2018-06-27)
    MORENO-GARCÍA, C.F. 2018. Digital interpretation of sensor-equipment diagrams. In Martin, K., Wiratunga, N. and Smith, L.S. (eds.) Proceedings of the Scottish Informatics and Computer Science Alliance (SCISA) workshop on reasoning, learning and explainability (ReaLX 2018), 27 June 2018, Aberdeen, UK. Aberdeen: CEUR [online], Session 2, paper 1. Available from: http://ceur-ws.org/Vol-2151/Paper_s2.pdf
    A sensor-equipment diagram is a type of engineering drawing used in the industrial practice that depicts the interconnectivity between a group of sensors and a portion of an Oil & Gas facility. The interpretation of these ...
  • Zero-shot learning with matching networks for open-ended human activity recognition. 

    Wijekoon, Anjana; Wiratunga, Nirmalie; Sani, Sadiq (CEUR http://ceur-ws.org/Vol-2151/, 2018-06-27)
    WIJEKOON, A., WIRATUNGA, N. and SANI, S. 2018. Zero-shot learning with matching networks for open-ended human activity recognition. In Martin, K., Wiratunga, N. and Smith, L.S. (eds.) Proceedings of the Scottish Informatics and Computer Science Alliance (SCISA) workshop on reasoning, learning and explainability (ReaLX 2018), 27 June 2018, Aberdeen, UK. Aberdeen: CEUR [online], Session 2, paper 4. Available from: http://ceur-ws.org/Vol-2151/Paper_S9.pdf
    A real-world solution for Human Activity Recognition (HAR) should cover a variety of activities. However training a model to cover each and every possible activity is not practical. Instead we need a solution that can adapt ...
  • An analysis of pupil concerns regarding transition into higher education. 

    Zarb, Mark; Siegel, Angela A. (Springer https://doi.org/10.1007/978-3-319-97934-2_1, 2018-08-04)
    ZARB, M. and SIEGEL, A.A. 2018. An analysis of pupil concerns regarding transition into higher education. In Cristea, A., Bittencourt, I.I. and Lima, F. (eds.) Communications in computer and information science, 832. Higher education for all: from challenged to novel technology-enhanced solutions; revised selected papers from the 1st International workshop on social, semantic, adaptive and gamification techniques and technologies for distance learning (HEFA 2017), 20-24 March 2017, Maceió, Brazil. Cham: Springer [online], pages 3-16. Available from: https://doi.org/10.1007/978-3-319-97934-2_1
    Transitioning to higher education is often a stressful experience, with incoming students facing similar issues year after year. This chapter presents two years of data collection regarding the concerns of Computing secondary ...
  • Matching networks for personalised human activity recognition. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (CEUR http://ceur-ws.org/Vol-2142/, 2018-07-13)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2018. Matching networks for personalised human activity recognition. In Bichindaritz, I., Guttmann, C., Herrero, P., Koch, F., Koster, A., Lenz, R., López Ibáñez, B., Marling, C., Martin, C., Montagna, S., Montani, S., Reichert, M., Riaño, D., Schumacher, M.I., ten Teije, A. and Wiratunga, N. (eds.) Proceedings of the 1st Joint workshop on artificial intelligence in health organized as part of the Federated AI meeting (FAIM 2018), co-located with 17th International autonomous agents and multiagent systems conference (AAMAS 2018), 35th International conference on machine learning (ICML 2018), 27th International joint conference on artificial intelligence (IJCAI 2018) and 26th International conference on case-based reasoning (ICCBR 2018), 13-19 July 2018, Stockholm, Sweden. Stockholm: CEUR [online], pages 61-64. Available from: http://ceur-ws.org/Vol-2142/short4.pdf
    Human Activity Recognition (HAR) has many important applications in health care which include management of chronic conditions and patient rehabilitation. An important consideration when training HAR models is whether to ...

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