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Automated glaucoma diagnosis using deep learning approach (2017)
Presentation / Conference Contribution
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M. A., & Zheng, Y. (2017, March). Automated glaucoma diagnosis using deep learning approach. Presented at 2017 14th International Multi-Conference on Systems, Signals & Devices (SSD)

Glaucoma is one of the common causes of blindness worldwide. It leads to deterioration in vision and quality of life if it is not cured early. This paper addresses the feasibility of developing an automatic feature learning technique for detecting gl... Read More about Automated glaucoma diagnosis using deep learning approach.

Evaluation of AllergiSense Smartphone Tools for Adrenaline Injection Training (2017)
Journal Article
Hernandez-Munoz, L., Woolley, S., Luyt, D., Stiefel, G., Kirk, K., Makwana, N., Melchior, C., Dawson, T., Wong, G., Collins, T., & Diwakar, L. (2017). Evaluation of AllergiSense Smartphone Tools for Adrenaline Injection Training. IEEE Journal of Biomedical and Health Informatics, 21(1), 272-282. https://doi.org/10.1109/JBHI.2015.2497717

Anaphylaxis is an increasingly prevalent life-threatening allergic condition that requires people with anaphylaxis and their caregivers to be trained in the avoidance of allergen triggers and in the administration of adrenaline autoinjectors. The pro... Read More about Evaluation of AllergiSense Smartphone Tools for Adrenaline Injection Training.

An Ambient Intelligence System for Assisted Living (2017)
Book Chapter
Ortolani. (2017). An Ambient Intelligence System for Assisted Living. In 2017 AEIT International Annual Conference, Cagliari, Italy, 20-22 Sep (1 -6). https://doi.org/10.23919/AEIT.2017.8240559

Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, w... Read More about An Ambient Intelligence System for Assisted Living.

Turning Models Inside Out (2017)
Journal Article
(2017). Turning Models Inside Out. CEUR Workshop Proceedings,

We present an approach for change-based (as opposed to state-based) model persistence that can facilitate highperformance incremental model processing (e.g. validation, transformation) by minimising the cost of change identification when models evolv... Read More about Turning Models Inside Out.

Layer formation in horizontally forced stratified turbulence: connecting exact coherent structures to linear instabilities (2017)
Journal Article
(2017). Layer formation in horizontally forced stratified turbulence: connecting exact coherent structures to linear instabilities. Journal of Fluid Mechanics, 409-437. https://doi.org/10.1017/jfm.2017.661

We consider turbulence in a stratified \u2018Kolmogorov\u2019 flow, driven by horizontal shear in the form of sinusoidal body forcing in the presence of an imposed background linear stable stratification in the third direction. This flow configuratio... Read More about Layer formation in horizontally forced stratified turbulence: connecting exact coherent structures to linear instabilities.

A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., Collins, D. J., & Lam, K. P. (2017, October). A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity. Presented at IEEE International Workshop on Signal Processing Systems, Lorient, France

The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and routinely practised. Voltage sensitive dye imaging (VSDi) is a promising tech... Read More about A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity.

Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover (2017)
Journal Article
Channon. (2017). Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover. Scientific reports, https://doi.org/10.1038/s41598-017-14628-x

The critical mutation rate (CMR) determines the shift between survival-of-the-fittest and survival of individuals with greater mutational robustness (“flattest”). We identify an inverse relationship between CMR and sequence length in an in silico sys... Read More about Critical Mutation Rate has an Exponential Dependence on Population Size for Eukaryotic-length Genomes with Crossover.

Approaches to analysis with infinitesimals following Robinson, Nelson, and others (2017)
Journal Article
Fletcher, P., Hrbacek, K., Kanovei, V., Katz, M. G., Lobry, C., & Sanders, S. (2017). Approaches to analysis with infinitesimals following Robinson, Nelson, and others. Real Analysis Exchange, 1 -59. https://doi.org/10.14321/realanalexch.42.2.0193

This is a survey of several approaches to the framework for working with infinitesimals and infinite numbers, originally developed by Abraham Robinson in the 1960s, and their constructive engagement with the Cantor-Dedekind postulate and the Intended... Read More about Approaches to analysis with infinitesimals following Robinson, Nelson, and others.

Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems (2017)
Presentation / Conference Contribution
Pekaslan, D., Kabir, S., Garibaldi, J. M., & Wagner, C. (2017, November). Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems. Presented at 9th International Joint Conference on Computational Intelligence (IJCCI 2017), Funchal, Madeira, Portugal

Non-singleton Fuzzy Logic Systems have the potential to tackle uncertainty within the design of fuzzy systems. The inference process has a major role in determining results, being partly based on the interaction of input and antecedent fuzzy sets (in... Read More about Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems.