1.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of AucklandNZ89 papers
- Commonwealth Scientific and Industrial Research OrganisationAU64 papers
- Swinburne University of TechnologyAU58 papers
- University of ManchesterGB57 papers
- Max Planck Institute for Radio AstronomyDE50 papers
- Centre National de la Recherche ScientifiqueFR46 papers
- ARC Centre of Excellence for Gravitational Wave DiscoveryAU45 papers
- International Centre for Radio Astronomy ResearchAU45 papers
- Curtin UniversityAU42 papers
- Australia Telescope National FacilityAU40 papers
- Korea Astronomy and Space Science InstituteKR36 papers
- The Ohio State UniversityUS36 papers
67 papers · 1 filter
Dynamic hardware system for cascade SVM classification of melanoma
Shereen Afifi, Hamid GholamHosseini, Roopak Sinha
Melanoma is the most dangerous form of skin cancer, which is responsible for the majority of skin cancer-related deaths. Early diagnosis of melanoma can significantly reduce mortal…
Graph-Theoretic Models of Resource Distribution for Cyber-Physical Systems of Disaster-Affected Regions
Kenneth Johnson, Samaneh Madanian, Roopak Sinha
We propose a tool-supported framework to reason about requirements constraining resource distributions and devise strategies for routing essential services in a disaster-affected r…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
The polarization of the drifting sub-pulses from PSR B1919+21
N. Primak, C. Tiburzi, W. van Straten +2
Aims. We aim to expand our understanding of radio wave emission and propagation in the pulsar magnetosphere by studying the polarization of drifting sub-pulses in highly sensitive…
A system on chip for melanoma detection using FPGA-based SVM classifier
Shereen Afifi, Hamid GholamHosseini, Roopak Sinha
Support Vector Machine (SVM) is a robust machine learning model that shows high accuracy with different classification problems, and is widely used for various embedded application…
Semiclassical bifurcations and quantum trajectories: a case study of the open Bose-Hubbard dimer
Andrus Giraldo, Stuart J. Masson, Neil G. R. Broderick +1
We consider the open two-site Bose-Hubbard dimer, a well-known quantum mechanical model that has been realised recently for photons in two coupled photonic crystal nanocavities. Th…
Routing Emergency Vehicles in Arterial Road Networks using Real-time Mixed Criticality Systems*
Subash Humagain, Roopak Sinha
Reducing the response time of Emergency Vehicles (EVs) has an undoubted advantage in saving life and property. Implementing pre-emption can aid in achieving it. EVs get unobstructe…
SVM Classifier on Chip for Melanoma Detection
Shereen Afifi, Hamid GholamHosseini, Roopak Sinha
Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical im…
Janus: A Systems Engineering Approach to the Design of Industrial Cyber-Physical Systems
Dennis Jarvis, Jacqueline Jarvis, Chen-Wei Yang +2
The benefits that arise from the adoption of a systems engineering approach to the design of engineered systems are well understood and documented. However , with software systems,…
The True Role of Active Communicators: An Empirical Study of Jazz Core Developers
Sherlock A. Licorish, Stephen G. MacDonell
Context: Interest in software engineering (SE) methodologies and tools has been complemented in recent years by research efforts oriented towards understanding the human processes…
How do Globally Distributed Agile Teams Self-organise? Initial Insights from a Case Study
Sherlock A. Licorish, Stephen G. MacDonell
Agile software developers are required to self-organize, occupying various informal roles as needed in order to successfully deliver software features. However, previous research h…
Differences in Jazz Project Leaders' Competencies and Behaviors: A Preliminary Empirical Investigation
Sherlock A. Licorish, Stephen G. MacDonell
Studying the human factors that impact on software development, and assigning individuals with specific competencies and qualities to particular software roles, have been shown to…
Towards the Objective Speech Assessment of Smoking Status based on Voice Features: A Review of the Literature
Zhizhong Ma, Chris Bullen, Joanna Ting Wai Chu +3
In smoking cessation clinical research and practice, objective validation of self-reported smoking status is crucial for ensuring the reliability of the primary outcome, that is, s…
Self-organising Roles in Agile Globally Distributed Teams
Sherlock A. Licorish, Stephen G. MacDonell
The ability to self-organise is posited to be a fundamental requirement for successful agile teams. In particular, self-organising teams are said to be crucial in agile globally di…
A Taxonomy of Data Quality Challenges in Empirical Software Engineering
Michael Franklin Bosu, Stephen G. MacDonell
Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for proce…
Adopting Softer Approaches in the Study of Repository Data: A Comparative Analysis
Sherlock A. Licorish, Stephen G. MacDonell
Context: Given the acknowledged need to understand the people processes enacted during software development, software repositories and mailing lists have become a focus for many st…
Packaged Software Implementation Requirements Engineering by Small Software Enterprises
Issam Jebreen, Robert Wellington, Stephen G. MacDonell
Small to medium sized business enterprises (SMEs) generally thrive because they have successfully done something unique within a niche market. For this reason, SMEs may seek to pro…
Towards the statistical construction of hybrid development methods
Paolo Tell, Jil Klünder, Steffen Küpper +6
Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use…
A Critical Evaluation of Failure in a Nearshore Outsourcing Project: What dilemma analysis can tell us
Tony Clear, Bilal Raza, Stephen G. MacDonell
Global Software Engineering (GSE) research contains few examples consciously applying what Glass and colleagues have termed an 'evaluative-critical' approach. In this study we appl…
Data Quality in Empirical Software Engineering: A Targeted Review
Michael Franklin Bosu, Stephen G. MacDonell
Context: The utility of prediction models in empirical software engineering (ESE) is heavily reliant on the quality of the data used in building those models. Several data quality…
What can developers' messages tell us? A psycholinguistic analysis of Jazz teams' attitudes and behavior patterns
Sherlock A. Licorish, Stephen G. MacDonell
Reports that communication and behavioral issues contribute to inadequately performing software teams have fuelled a wealth of research aimed at understanding the human processes e…
The Thousand-Pulsar-Array programme on MeerKAT III: Giant pulse characteristics of PSR J05406919
Marisa Geyer, Maciej Serylak, Federico Abbate +8
PSR J05406919 is the second-most energetic radio pulsar known and resides in the Large Magellanic Cloud. Like the Crab pulsar it is observed to emit giant radio pulses (GPs). We…
Examining and Mitigating Kernel Saturation in Convolutional Neural Networks using Negative Images
Nidhi Gowdra, Roopak Sinha, Stephen MacDonell
Neural saturation in Deep Neural Networks (DNNs) has been studied extensively, but remains relatively unexplored in Convolutional Neural Networks (CNNs). Understanding and alleviat…
Examining convolutional feature extraction using Maximum Entropy (ME) and Signal-to-Noise Ratio (SNR) for image classification
Nidhi Gowdra, Roopak Sinha, Stephen MacDonell
Convolutional Neural Networks (CNNs) specialize in feature extraction rather than function mapping. In doing so they form complex internal hierarchical feature representations, the…