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All Outputs (127)

Wearable epilepsy seizure monitor user interface evaluation (2020)
Conference Proceeding
Rukasha, T., Woolley, S. I., & Collins, T. (in press). Wearable epilepsy seizure monitor user interface evaluation. . https://doi.org/10.1145/3410530.3414382

Wearable health devices have the potential to incentivize individuals in health-promoting behaviors and to assist in the monitoring of health conditions. Wearable epilepsy seizure monitoring devices are now evolving that can support individuals and t... Read More about Wearable epilepsy seizure monitor user interface evaluation.

Reflections on the Doctoral Consortium (2020)
Conference Proceeding
Flint, T., Sim, G., Bond, R., Woolley, S., Dix, A., & Hall, L. (2020). Reflections on the Doctoral Consortium. . https://doi.org/10.14236/ewic/HCI20DC.2

This paper provides a reflective commentary on the British HCI Doctoral Consortium from the perspective of the Organising Committee. We discuss the approach to holding a Human Computer Interaction Doctoral Consortium in July 2020 and the outcomes. We... Read More about Reflections on the Doctoral Consortium.

A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data (2020)
Conference Proceeding
Kabir, S., & Wagner, C. (2020). A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data. In Information Processing and Management of Uncertainty in Knowledge-Based Systems (603-617). https://doi.org/10.1007/978-3-030-50143-3_48

Recent advances in the literature have leveraged the fuzzy integral (FI), a powerful multi-source aggregation operator, where a fuzzy measure (FM) is used to capture the worth of all combinations of subsets of sources. While in most applications, the... Read More about A Bidirectional Subsethood Based Fuzzy Measure for Aggregation of Interval-Valued Data.

Visualising the Invisible: Augmented Reality and Virtual Reality as Persuasive Technologies for Energy Feedback (2020)
Conference Proceeding
David Fredericks, A., Fan, Z., & Woolley, S. I. (2020). Visualising the Invisible: Augmented Reality and Virtual Reality as Persuasive Technologies for Energy Feedback. . https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00225

In the last fifteen years, the outlook for engaging direct energy feedback as a method of effectively curtailing domestic energy consumption has grown more pessimistic. Continuing studies and reviews suggest the impact of such techniques on consumers... Read More about Visualising the Invisible: Augmented Reality and Virtual Reality as Persuasive Technologies for Energy Feedback.

Seven-Point Checklist with Convolutional Neural Networks for Melanoma Diagnosis (2019)
Conference Proceeding
Alzahrani, S., Al-Nuaimy, W., & Al-Bander, B. (2019). Seven-Point Checklist with Convolutional Neural Networks for Melanoma Diagnosis. . https://doi.org/10.1109/EUVIP47703.2019.8946208

Reliable skin lesion detection is an important pre-requisite for melanoma and other skin diseases diagnosis. Existing melanoma assessment models consider either pattern analysis methods or seven-point checklist criteria to investigate skin lesion. Ho... Read More about Seven-Point Checklist with Convolutional Neural Networks for Melanoma Diagnosis.

A gyro-elastic device for cloaking of elastic waves in micro-structured materials (2019)
Conference Proceeding
Garau, M., Nieves, M., Carta, G., & Brun, M. (2019). A gyro-elastic device for cloaking of elastic waves in micro-structured materials. . https://doi.org/10.1109/MetaMaterials.2019.8900841

The design of a structured gyro-elastic system capable of being used as a cloaking device for a discrete medium is discussed. The efficiency of the gyro-elastic cloak, composed of springs connecting periodically placed masses, attached to gyroscopic... Read More about A gyro-elastic device for cloaking of elastic waves in micro-structured materials.

Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions (2019)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (in press). Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions. . https://doi.org/10.1109/fuzz-ieee.2019.8858862

Discontinuous intervals (DIs) arise in a wide range of contexts, from real world data capture of human opinion to α-cuts of non-convex fuzzy sets. Commonly, for assessing the similarity of DIs, the latter are converted into their continuous form, fol... Read More about Measuring Similarity Between Discontinuous Intervals - Challenges and Solutions.

Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images (2019)
Conference Proceeding
Ibraheem Jabbar, S., Day, C. R., & Chadwick, E. K. (2019). Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE.2019.8858971

Edge detection in Musculoskeletal Ultrasound Imaging readily allows an ultrasound image to be rendered as a binary image. This facilitates automated measurement of geometric parameters, such as muscle thickness, circumference and cross-sectional area... Read More about Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images.

Cross-spectral Periocular Recognition: a Survey (2019)
Conference Proceeding
Behera, S., Mandal, B., & Puhan, N. (2019). Cross-spectral Periocular Recognition: a Survey. In Emerging Research in Electronics, Computer Science and Technology (731–741). https://doi.org/10.1007/978-981-13-5802-9_64

Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the whole fac... Read More about Cross-spectral Periocular Recognition: a Survey.

Problems with Statistical Practice in Software Engineering Research (2019)
Conference Proceeding
Kitchenham, B., Madeyski, L., & Brereton, P. (2019). Problems with Statistical Practice in Software Engineering Research. In EASE '19 Proceedings of the Evaluation and Assessment on Software Engineering (134-143). https://doi.org/10.1145/3319008.3319009

Background Examples of questionable statistical practice, when published in high quality software engineering (SE) journals, may lead to novice researchers adopting incorrect statistical practices. Objective Our goal is to highlight issues contr... Read More about Problems with Statistical Practice in Software Engineering Research.

Measuring and Testing the Scalability of Cloud-based Software Services (2019)
Conference Proceeding
Al-Said Ahmad, A., & Andras, P. (2019). Measuring and Testing the Scalability of Cloud-based Software Services. In 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT) (67-74). https://doi.org/10.1109/ISIICT.2018.8613297

Performance and scalability testing and measurements of cloud-based software services are critically important in the context of rapid growth of cloud computing and supporting the delivery of these services. Cloud-based software services performance... Read More about Measuring and Testing the Scalability of Cloud-based Software Services.

Computational aspects of model acquisition and join geometry for the virtual reconstruction of the atrahasis cuneiform tablet (2018)
Conference Proceeding
Collins, T., Woolley, S., Gehlken, E., & Ch'ng, E. (2018). Computational aspects of model acquisition and join geometry for the virtual reconstruction of the atrahasis cuneiform tablet. . https://doi.org/10.1109/VSMM.2017.8346284

The epic of Atrahasis is one of the most significant pieces of ancient Mesopotamian literature. The account has survived millennia on sets of clay tablets inscribed with cuneiform script; a sophisticated early writing system comprising signs formed f... Read More about Computational aspects of model acquisition and join geometry for the virtual reconstruction of the atrahasis cuneiform tablet.

DeepPCA Based Objective Function for Melanoma Detection (2018)
Conference Proceeding
Sultana, N. N., Puhan, N. B., & Mandal, B. (2018). DeepPCA Based Objective Function for Melanoma Detection. In 2018 International Conference on Information Technology (ICIT). https://doi.org/10.1109/icit.2018.00025

In this paper, we propose an objective function for the convolutional neural network to acquire the variation separability as opposed to the categorical cross entropy which maximizes according to the target labels. This approach is an unsupervised le... Read More about DeepPCA Based Objective Function for Melanoma Detection.

Student Centred Design of a Learning Analytics System (2018)
Conference Proceeding
De Quincey, E., Briggs, C., Kyriacou, T., & Waller, R. (2018). Student Centred Design of a Learning Analytics System. In LAK19: Proceedings of the 9th International Conference on Learning Analytics & Knowledge. https://doi.org/10.1145/3303772.3303793

Current Learning Analytics (LA) systems are primarily designed with University staff members as the target audience; very few are aimed at students, with almost none being developed with direct student involvement and undertaking a comprehensive eval... Read More about Student Centred Design of a Learning Analytics System.

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study (2018)
Conference Proceeding
Abuhlfaia, K., & de Quincey, E. (2018). The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study. . https://doi.org/10.14236/ewic/HCI2018.7

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods... Read More about The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study.

Deep Adaptive Temporal Pooling for Activity Recognition (2018)
Conference Proceeding
Song, S., Cheung, N., Chandrasekhar, V., & Mandal, B. (2018). Deep Adaptive Temporal Pooling for Activity Recognition. . https://doi.org/10.1145/3240508.3240713

Deep neural networks have recently achieved competitive accuracy for human activity recognition. However, there is room for improvement, especially in modeling of long-term temporal importance and determining the activity relevance of different tempo... Read More about Deep Adaptive Temporal Pooling for Activity Recognition.

Fault Detection in Steel-Reinforced Concrete Using Echo State Networks (2018)
Conference Proceeding
Wootton, A. J., Day, C. R., & Haycock, P. W. (2018). Fault Detection in Steel-Reinforced Concrete Using Echo State Networks. In 2018 International Joint Conference on Neural Networks (IJCNN) (1-8). https://doi.org/10.1109/IJCNN.2018.8489761

The cost of maintaining and repairing the world's ageing reinforced concrete infrastructure continues to increase, and is expected to cost the United States economy alone $58 billion by 2020. Consequently, the use of non-destructive testing technolog... Read More about Fault Detection in Steel-Reinforced Concrete Using Echo State Networks.

A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets (2018)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets. In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/fuzz-ieee.2018.8491669

Similarity measures are useful for reasoning about fuzzy sets. Hence, many classical set-theoretic similarity measures have been extended for comparing fuzzy sets. In previous work, a set-theoretic similarity measure considering the bidirectional sub... Read More about A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets.