Recent Submissions

  • FITsense: multi-modal sensors in smart homes to predict falls. 

    Massie, Stewart; Forbes, Glenn; Craw, Susan; Fraser, Lucy; Hamilton, Graeme (Springer http://iccbr18.com/accepted-papers/, 2018-07-09)
    MASSIE, S., FORBES, G., CRAW, S., FRASER, L. and HAMILTON, G. [2018]. FITsense: multi-modal sensors in smart homes to predict falls. In Lecture notes in computer science: Proceedings of the 26th International conference on case-based reasoning (ICCBR-18), 9-12 July 2018, Stockholm, Sweden. Cham: Springer [online], (accepted).
    As people live longer, the increasing average age of the population places additional strains on our health and social services. There are widely recognised benefits to both the individual and society from supporting people ...
  • Monitoring health in smart homes using simple sensors. 

    Massie, Stewart; Forbes, Glenn; Craw, Susan; Fraser, Lucy; Hamilton, Graeme (ICCBR (Organisers), 2018-07-13)
    MASSIE, S., FORBES, G., CRAW, S., FRASER, L. and HAMILTON, G. [2018]. Monitoring health in smart homes using simple sensors. In Proceedings of the 3rd International workshop on knowledge discovery in healthcare data co-located with the 26th International joint conference on artificial intelligence (IJCAI 2018), 13 July 2018, Stockholm, Sweden.
    We consider use of an ambient sensor network, installed in Smart Homes, to identify low level events taking place which can then be analysed to generate a resident's profile of activities of daily living (ADLs). These ADL ...
  • Performance analysis of GA and PBIL variants for real-world location-allocation problems. 

    Ankrah, Reginald; Regnier-Coudert, Olivier; McCall, John; Conway, Anthony; Hardwick, Andrew (IEEE http://www.ecomp.poli.br/~wcci2018/, 2018-07-08)
    ANKRAH, R., REGNIER-COUDERT, O., MCCALL, J., CONWAY, A. and HARDWICK, A. 2018. Performance analysis of GA and PBIL variants for real-world location-allocation problems. To be presented at the IEEE world congress on computational intelligence; IEEE congress on evolutionary computation (IEEE CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
    The Uncapacitated Location-Allocation problem (ULAP) is a major optimisation problem concerning the determination of the optimal location of facilities and the allocation of demand to them. In this paper, we present two ...
  • Case based reasoning as a model for cognitive artificial intelligence. 

    Craw, Susan; Aamodt, Agnar
    CRAW, S. and AAMODT, A. [2018]. Case based reasoning as a model for cognitive artificial intelligence. In Lecture notes in computer science: Proceedings of the 26th International conference on case-based reasoning (ICCBR-18), 9-12 July 2018, Stockholm, Sweden. Cham: Springer, (accepted).
    Cognitive Systems understand the world through learning and experience. Case Based Reasoning (CBR) systems naturally capture knowledge as experiences in memory and they are able to learn new experiences to retain in their ...
  • Personalised human activity recognition using matching networks. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (Springer, 2018-07-09)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. [2018]. Personalised human activity recognition using matching networks. Lecture notes in computer science [online], Proceedings of the 26th international conference on case-based reasoning 2018 (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Cham: Springer [online], (accepted).
    Human Activity Recognition (HAR) is typically modelled as a classification task where sensor data associated with activity labels are used to train a classifier to recognise future occurrences of these activities. An ...
  • Improving kNN for human activity recognition with privileged learning using translation models. 

    Wijekoon, Anjana; Wiratunga, Nirmalie; Sani, Sadiq; Massie, Stewart; Cooper, Kay (Springer, 2018-07-09)
    WIJEKOON, A., WIRATUNGA, N., SANI, S., MASSIE, S. and COOPER, K. [2018]. Improving kNN for human activity recognition with privileged learning using translation models. Lecture notes in computer science [online], Proceedings of the 26th international conference on case-based reasoning 2018 (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Cham: Springer [online], (accepted).
    Multiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is preferred by consumers as it is more convenient and less intrusive. This presents a ...
  • Neural induction of a lexicon for fast and interpretable stance classification. 

    Clos, Jérémie; Wiratunga, Nirmalie (Springer https://doi.org/10.1007/978-3-319-59888-8_16, 2017-05-27)
    CLOS, J. and WIRATUNGA, N. 2017. Neural induction of a lexicon for fast and interpretable stance classification. Lecture notes in computer science, 10318, Proceedings of the 1st international conference on language, data and knowledge (LDK 2017), 19-20 June 2017, Galway, Ireland. Cham: Springer [online], pages 181-193. Available from: https://dx.doi.org/10.1007/978-3-319-59888-8_16
    Large-scale social media classification faces the following two challenges: algorithms can be hard to adapt to Web-scale data, and the predictions that they provide are difficult for humans to understand. Those two challenges ...
  • Generic application of deep learning framework for real-time engineering data analysis. 

    Majdani, Farzan; Petrovski, Andrei; Petrovski, Sergei (IEEE, 2018-07-08)
    MAJDANI, F., PETROVSKI, A. and PETROVSKI, S. 2018. Generic application of deep learning framework for real-time engineering data analysis. Presented at the International joint conference on neural networks 2018 (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
    The need for computer-assisted real-time anomaly detection in engineering data used for condition monitoring is apparent in various applications, including the oil and gas, automotive industries and many other engineering ...
  • Towards situational awareness of botnet activity in the internet of things. 

    McDermott, Christopher D.; Petrovski, Andrei; Majdani, Farzan (IEEE, 2018-06-11)
    MCDERMOTT, C.D., PETROVSKI, A.V. and MAJDANI, F. 2018. Towards situational awareness of botnet activity in the internet of things. Presented at the Cyber situation awareness conference 2018 (Cyber SA 2018): cyber situation awareness as a tool for analysis and insight, 11-12 June 2018, Glasgow, UK.
    An IoT botnet detection model is designed to detect anomalous attack traffic utilised by the mirai botnet malware. The model uses a novel application of Deep Bidirectional Long Short Term Memory based Recurrent Neural ...
  • Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. 

    Vilela, Martin; Oluyemi, Gbenga Folorunso; Petrovski, Andrei (IEEE, 2018-07-08)
    VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2018. Fuzzy data analysis methodology for the assessment of value of information in the oil and gas industry. Presented at the IEEE International fuzzy systems conference 2018 (FUZZ-IEEE 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
    To manage uncertainty in reservoir development projects, the Value of Information is one of the main factors on which the decision is based to determine whether it is necessary to acquire additional data. However, subsurface ...
  • Botnet detection in the internet of things using deep learning approaches. 

    McDermott, Christopher D.; Majdani, Farzan; Petrovski, Andrei (IEEE, 2018-07-08)
    MCDERMOTT, C.D., MAJDANI, F. and PETROVSKI, A.V. 2018. Botnet detection in the internet of things using deep learning approaches. Presented at the International joint conference on neural networks 2018 (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
    The recent growth of the Internet of Things (IoT) has resulted in a rise in IoT based DDoS attacks. This paper presents a solution to the detection of botnet activity within consumer IoT devices and networks. A novel ...
  • Few-shot classifier GAN. 

    Ali-Gombe, Adamu; Elyan, Eyad; Savoye, Yann; Jayne, Chrisina
    ALI-GOMBE, A., ELYAN, E., SAVOYE, Y. and JAYNE, C. 2018. Few-shot classifier GAN. Presented at the International joint conference on neural networks 2018 (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil.
    Fine-grained image classification with a few-shot classifier is a highly challenging open problem at the core of a numerous data labeling applications. In this paper, we present Few-shot Classifier Generative Adversarial ...
  • 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 Presented at the International joint conference on neural networks 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 ...
  • An e-learning recommender that helps learners find the right materials. 

    Mbipom, Blessing; Massie, Stewart; Craw, Susan (Association for the Advancement of Artificial Intelligence https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16253, 2018-02-03)
    MBIPOM, B., MASSIE, S. and CRAW, S. 2018. An e-learning recommender that helps learners find the right materials. In the Proceedings of the 32nd Association of the Advancement of Artificial Intelligence conference (AAAI-18), including the 8th educational advances in artificial intelligence symposium (EAAI-18), 3-4 February 2018, New Orleans, USA. Palo Alto: AAAI Press [online], pages 7928-7933. Available from: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16253
    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 ...
  • A convolutional Siamese network for developing similarity knowledge in the SelfBACK dataset. 

    Martin, Kyle; Wiratunga, Nirmalie; Sani, Sadiq; Massie, Stewart; Clos, Jérémie (ICCBR (Organisers) http://ceur-ws.org/Vol-2028, 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. In Sanchez-Ruiz, A.A. and Kofod-Petersen, A. (eds.) Proceedings of the 25th International case-based reasoning conference (ICCBR 2017): case-based reasoning and deep learning workshop (CBRDL 2017), 26-28 June 2017, Trondheim, Norway. Trondheim: ICCBR [online], pages 85-94. Available from: http://ceur-ws.org/Vol-2028/paper8.pdf
    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) http://ceur-ws.org/Vol-2028/, 2017-06-26)
    SANI, S., WIRATUNGA, N. and MASSIE, S. 2017. Learning deep features for kNN-based human activity recognition. In Sanchez-Ruiz, A.A. and Kofod-Petersen, A. (eds.) Proceedings of the 25th International case-based reasoning conference (ICCBR 2017): case-based reasoning and deep learning workshop (CBRDL 2017), 26-28 June 2017, Trondheim, Norway. Trondheim: ICCBR [online], pages 95-103. Available from: http://ceur-ws.org/Vol-2028/paper9.pdf
    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 ...

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