Outputs (134)

Frequency-dependent characteristics of nerve-mediated ATP and acetylcholine release from detrusor smooth muscle (2022)
Journal Article

New Findings: What is the central question of this study? Is the frequency dependence of co-transmitter release from postganglionic nerve fibres different for each transmitter? What is the main finding and its importance? Release of co-transmitters f... Read More about Frequency-dependent characteristics of nerve-mediated ATP and acetylcholine release from detrusor smooth muscle.

A novel deep reinforcement learning-based approach for task-offloading in vehicular networks (2022)
Presentation / Conference Contribution

Next-generation vehicular networks will impose unprecedented computation demand due to the wide adoption of compute-intensive services with stringent latency requirements. Computational capacity of vehicular networks can be enhanced by integration of... Read More about A novel deep reinforcement learning-based approach for task-offloading in vehicular networks.

A novel, scalable social media-based intervention Warna-Warni Waktu to reduce body dissatisfaction among young Indonesian women: Protocol for a parallel randomized controlled trial (2022)
Journal Article

Background: Despite the prevalence of body dissatisfaction among young Indonesian women and its consequential negative impacts, there are currently no evidence-based, culturally appropriate interventions to tackle this issue. Therefore, there is a ne... Read More about A novel, scalable social media-based intervention Warna-Warni Waktu to reduce body dissatisfaction among young Indonesian women: Protocol for a parallel randomized controlled trial.

Insights into the dynamics of ligand-induced dimerisation via mathematical modelling and analysis (2022)
Journal Article

The vascular endothelial growth factor (VEGF) receptor (VEGFR) system plays a role in cancer and many other diseases. It is widely accepted that VEGFR receptors dimerise in response to VEGF binding. However, analysis of these mechanisms and their imp... Read More about Insights into the dynamics of ligand-induced dimerisation via mathematical modelling and analysis.

HyperModels - A framework for GPU accelerated physical modelling sound synthesis (2022)
Presentation / Conference Contribution

Physical modelling sound synthesis methods generate vast and intricate sound spaces that are navigated using meaningful parameters. Numerical based physical modelling nsynthesis methods provide authentic representations of the physics they model. Unf... Read More about HyperModels - A framework for GPU accelerated physical modelling sound synthesis.

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article

In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a par... Read More about Transfer learning for operator selection: A reinforcement learning approach.

An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: Mixed methods feasibility study (2022)
Journal Article

Background: Mobile apps may offer a valuable platform for delivering evidence-based psychological interventions for individuals with atypical appearances, or visible differences, who experience psychosocial appearance concerns such as appearance-base... Read More about An acceptance and commitment therapy prototype mobile program for individuals with a visible difference: Mixed methods feasibility study.

Network maintenance planning via multi-agent reinforcement learning (2022)
Presentation / Conference Contribution

Within this work, the challenge of developing maintenance planning solutions for networked assets is considered. This is challenging due to the very nature of these systems which are often heterogeneous, distributed and have complex co-dependencies b... Read More about Network maintenance planning via multi-agent reinforcement learning.

On the fairness of generative adversarial networks (GANs) (2022)
Presentation / Conference Contribution

Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data and then sample synthetic realistic data. Many applications have emerged, using G... Read More about On the fairness of generative adversarial networks (GANs).