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An evaluation model for information security strategies in healthcare data systems (2018)
Thesis
Almutiq, M. M. An evaluation model for information security strategies in healthcare data systems. (Thesis). Keele University. https://keele-repository.worktribe.com/output/412314

This thesis presents a newly developed evaluation model, EMISHD (An "Evaluation Model for Information Security Strategies in Healthcare Data Systems") which can address the specific requirements of information security in healthcare sector. Based on... Read More about An evaluation model for information security strategies in healthcare data systems.

Detection of suspicious URLs in online social networks using supervised machine learning algorithms (2018)
Thesis
Al-Janabi, M. F. Z. Detection of suspicious URLs in online social networks using supervised machine learning algorithms. (Thesis). Keele University. https://keele-repository.worktribe.com/output/412294

This thesis proposes the use of several supervised machine learning classification models that were built to detect the distribution of malicious content in OSNs. The main focus was on ensemble learning algorithms such as Random Forest, gradient boos... Read More about Detection of suspicious URLs in online social networks using supervised machine learning algorithms.

A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference (2018)
Journal Article
Misirli. (2018). A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference. ACS synthetic biology, 2812-2823. https://doi.org/10.1021/acssynbio.8b00201

A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in an... Read More about A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference.

Harmonizing semantic annotations for computational models in biology (2018)
Journal Article
Misirli. (2018). Harmonizing semantic annotations for computational models in biology. Briefings in bioinformatics, bby087 - bby087. https://doi.org/10.1093/bib/bby087

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for... Read More about Harmonizing semantic annotations for computational models in biology.

Student Centred Design of a Learning Analytics System (2018)
Presentation / Conference Contribution
De Quincey, E., Briggs, C., Kyriacou, T., & Waller, R. (2019, March). Student Centred Design of a Learning Analytics System. Presented at 9th International Conference on Learning Analytics and Knowledge (LAK19), Tempe, Arizona

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)
Presentation / Conference Contribution
Abuhlfaia, K., & de Quincey, E. (2018, July). The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study. Presented at BCS, The Chartered Institute for IT (ACM Proceedings) 32nd Human Computer Interaction Conference, Belfast

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)
Presentation / Conference Contribution
Song, S., Cheung, N.-M., Chandrasekhar, V., & Mandal, B. (2018, October). Deep Adaptive Temporal Pooling for Activity Recognition. Presented at MM '18: ACM Multimedia Conference, Seoul Republic of Korea

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)
Presentation / Conference Contribution
Wootton, A. J., Day, C. R., & Haycock, P. W. (2018, July). Fault Detection in Steel-Reinforced Concrete Using Echo State Networks

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.

Social Learning in Repeated Cooperation Games in Uncertain Environments (2018)
Journal Article
(2018). Social Learning in Repeated Cooperation Games in Uncertain Environments. Cognitive Systems Research, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some ca ses potential cooperatio... Read More about Social Learning in Repeated Cooperation Games in Uncertain Environments.

Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition (2018)
Presentation / Conference Contribution
Mandal, B., Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2018, October). Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition. Presented at 2018 IEEE International Conference on Image Processing, Athens

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.

Reproducibility of Studies on Text Mining for Citation Screening in Systematic Reviews: Evaluation and Checklist (2018)
Journal Article
(2018). Reproducibility of Studies on Text Mining for Citation Screening in Systematic Reviews: Evaluation and Checklist. Journal of Biomedical Informatics, 1-13. https://doi.org/10.1016/j.jbi.2017.07.010

CONTEXT:
Independent validation of published scientific results through study replication is a pre-condition for accepting the validity of such results. In computation research, full replication is often unrealistic for independent results validatio... Read More about Reproducibility of Studies on Text Mining for Citation Screening in Systematic Reviews: Evaluation and Checklist.

Asymptotic analysis of an anti-plane dynamic problem for a three-layered strongly inhomogeneous laminate (2018)
Journal Article
Prikazchikova, L., Ece Aydın, Y., Erbaş, B., & Kaplunov, J. (2018). Asymptotic analysis of an anti-plane dynamic problem for a three-layered strongly inhomogeneous laminate. Mathematics and Mechanics of Solids, 25(1), 3-16. https://doi.org/10.1177/1081286518790804

Anti-plane dynamic shear of a strongly inhomogeneous dynamic laminate with traction-free faces is
analysed. Two types of contrast are considered, including those for composite structures with stiff thick or thin outer layers. In both cases, the valu... Read More about Asymptotic analysis of an anti-plane dynamic problem for a three-layered strongly inhomogeneous laminate.

The Effect of Pose on the distribution of Edge Gradients in Omnidirectional Images (2018)
Presentation / Conference Contribution
Jarvis, D., & Kyriacou, T. (2018, July). The Effect of Pose on the distribution of Edge Gradients in Omnidirectional Images. Presented at 19th Annual Conference, TAROS 2018, Bristol, UK

Images from omnidirectional cameras are used frequently in applications involving artificial intelligence and robotics as a source of rich information about the surroundings. A useful feature that can be extracted from these images is the distributio... Read More about The Effect of Pose on the distribution of Edge Gradients in Omnidirectional Images.

Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments (2018)
Journal Article
(2018). Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments. Artificial Life, 404-411. https://doi.org/10.1162/isal_a_00078

Cooperation among selfish individuals provides the fundamentals for social organization among animals and humans. Cooperation games capture this behavior at an abstract level and provide the tools for the analysis of the evolution of cooperation. Her... Read More about Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments.

Evolving Robust, Deliberate Motion Planning With a Shallow Convolutional Neural Network (2018)
Journal Article
Channon. (2018). Evolving Robust, Deliberate Motion Planning With a Shallow Convolutional Neural Network. https://doi.org/10.1162/isal_a_00099

Deep Convolutional Neural Networks (ConvNets) have seen great success on machine learning tasks in recent years but have shown difficulty with tasks that require long-term deliberative planning. Whereas, purpose-built hybrid network architectures hav... Read More about Evolving Robust, Deliberate Motion Planning With a Shallow Convolutional Neural Network.

Tiebreaks and Diversity: Isolating Effects in Lexicase Selection (2018)
Journal Article
(2018). Tiebreaks and Diversity: Isolating Effects in Lexicase Selection. https://doi.org/10.1162/isal_a_00109

A primary goal of evolutionary robotics (ER) is generalized control. That is, a robot controller should be capable of solving a variety of tasks in a domain, rather than only addressing specific instances of a task. Prior work has shown that Lexicase... Read More about Tiebreaks and Diversity: Isolating Effects in Lexicase Selection.

Measuring the Scalability of Cloud-based Software Services (2018)
Presentation / Conference Contribution
Al-Said Ahmad, A., & Andras, P. (2018, July). Measuring the Scalability of Cloud-based Software Services. Presented at 2018 IEEE World Congress on Services, San Francisco

Measuring and testing the performance of cloud-based software services is critically important in the context of rapid growth of cloud computing. Scalability, elasticity and efficiency are interrelated aspects of performance of cloud-based software s... Read More about Measuring the Scalability of Cloud-based Software Services.

Quantifying textual similarities across scientific researchcommunities (2018)
Thesis
Duffee, B. Quantifying textual similarities across scientific researchcommunities. (Thesis). Keele University. https://keele-repository.worktribe.com/output/411459

There are well-established approaches of text mining collections of documents and for understanding the network of citations between academic papers. Few studies have examined the textual content of the papers that constitute a citation network. A do... Read More about Quantifying textual similarities across scientific researchcommunities.