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All Outputs (328)

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.

Enhancement of Panoramic Musculoskeletal Ultrasound Image Based on Fuzzy Technique (2019)
Conference Proceeding
Ibraheem Jabbar, S., Day, C., & Chadwick, E. K. (2019). Enhancement of Panoramic Musculoskeletal Ultrasound Image Based on Fuzzy Technique. In ICICT '19: Proceedings of the International Conference on Information and Communication Technology (228–232). https://doi.org/10.1145/3321289.3321312

Panoramic Musculoskeletal Ultrasound Images (PMUI) is a developed version of ultrasound images. However, low contrast is a concrete problem which impact negatively on the interpretation of important details of PMUI. Therefore, in this paper a new aut... Read More about Enhancement of Panoramic Musculoskeletal Ultrasound Image Based on Fuzzy Technique.

Early demise from high grade serous ovarian cancer is predictable and likely related to tumour biology (2019)
Conference Proceeding
Hawarden, A., Russell, B., Gee, M., Skayali, F., Edmondson, M., Clamp, A., …Edmondson, R. (2019). Early demise from high grade serous ovarian cancer is predictable and likely related to tumour biology.

Introduction: Despite improvements in median survival for patients with advanced ovarian cancer there remains a cohort of patients who suffer early demise; the reasons for which remain poorly understood. A nested case control study was performed to i... Read More about Early demise from high grade serous ovarian cancer is predictable and likely related to tumour biology.

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.

DUAL PERSPECTIVES ON THE ROLE OF ARTIFICIALLY INTELLIGENT ROBOTIC VIRTUAL AGENTS IN THE TOURISM, TRAVEL AND HOSPITALITY INDUSTRIES (2019)
Conference Proceeding
Ukpabi, D. C., Karjaluoto, H., Olaleye, S. A., & Mogaji, E. (2019). DUAL PERSPECTIVES ON THE ROLE OF ARTIFICIALLY INTELLIGENT ROBOTIC VIRTUAL AGENTS IN THE TOURISM, TRAVEL AND HOSPITALITY INDUSTRIES.

Robotics and artificial intelligence are challenging extant business services and fundamentally impacting business relationships and processes. While studies have elaborately investigated social robotic interactions in medical and health-related doma... Read More about DUAL PERSPECTIVES ON THE ROLE OF ARTIFICIALLY INTELLIGENT ROBOTIC VIRTUAL AGENTS IN THE TOURISM, TRAVEL AND HOSPITALITY INDUSTRIES.

Developing focal construct technology for in vivo diagnosis of osteoporosis (2019)
Conference Proceeding
Greenwood, C., Rogers, K., Wilson, M., Lyburn, I., Evans, P., & Prokopiou, D. (2019). Developing focal construct technology for in vivo diagnosis of osteoporosis. In Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1151/1/012020

Osteoporosis is a prevalent bone disease around the world, characterised by low bone mineral density and increased fracture risk. Currently, the gold standard for identifying osteoporosis and increased fracture risk is through quantification of bone... Read More about Developing focal construct technology for in vivo diagnosis of osteoporosis.

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.

Collagenase Biosensor Based on the Degradation of Peptide Cross-Linked Poly(Ethylene Glycol) Hydrogel Films (2018)
Conference Proceeding
Ahmad, N., Colak, B., Gibbs, M. J., Zhang, D., Becer, C. R., Watkinson, M., …Krause, S. Collagenase Biosensor Based on the Degradation of Peptide Cross-Linked Poly(Ethylene Glycol) Hydrogel Films. . https://doi.org/10.3390/proceedings2130961

Peptide cross-linked poly(ethylene glycol) hydrogel is a promising biomaterial that has been used widely for drug delivery and tissue engineering. However, the use of this material as a biosensor material for the detection of collagenase has not been... Read More about Collagenase Biosensor Based on the Degradation of Peptide Cross-Linked Poly(Ethylene Glycol) Hydrogel Films.

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.

Managing overlap in overviews of reviews: a cross-sectional survey of the published literature between 2015-2017 (2018)
Conference Proceeding
Bajpai, R., Posadzki, P., Soljak, M., & Car, J. (2018). Managing overlap in overviews of reviews: a cross-sectional survey of the published literature between 2015-2017. . https://doi.org/10.1002/14651858.cd201801

Background: Overviews of reviews (or simply 'overviews') have become an increasingly established approach to synthesising research. Overviews are becoming prevalent because they have potential advantages over systematic reviews. However, they impose... Read More about Managing overlap in overviews of reviews: a cross-sectional survey of the published literature between 2015-2017.

Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors (2018)
Conference Proceeding
Oniani, S., Woolley, S. I., Miguel Pires, I., Garcia, N. M., Collins, T., Ledger, S., & Pandyan, A. (2018). Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors.

The aim of this paper is to address the need for reliability assessments of new and updated consumer-grade activity and heart rate monitoring devices. This issue is central to the use of these sensor devices and it is particularly important in their... Read More about Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors.

Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition (2018)
Conference Proceeding
Mandal, B., Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2018). Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition. . https://doi.org/10.1109/ICIP.2018.8451190

In this work, we extract rich representations of crowd behavior from video using a fine-tuned deep convolutional neural residual network. Using spatial partitioning trees we create subclasses within the feature maps from each of the crowd behavior a... Read More about Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition.