A5030486012- Software Engineering Research
- Advanced Software Engineering Methodologies
- Software Engineering Techniques and Practices
- Scientific Computing and Data Management
- Digital Mental Health Interventions
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
- Big Data and Business Intelligence
- Open Source Software Innovations
- Software System Performance and Reliability
- Usability and User Interface Design
- Advanced Malware Detection Techniques
- Digital Marketing and Social Media
- Mental Health Research Topics
- Software Reliability and Analysis Research
- Service-Oriented Architecture and Web Services
- Mobile Health and mHealth Applications
- Technology Adoption and User Behaviour
- Data Quality and Management
- Data Management and Algorithms
- Simulation Techniques and Applications
- Persona Design and Applications
- Online Learning and Analytics
- Innovative Human-Technology Interaction
- Data Visualization and Analytics
Deakin University
2016-2025
Swinburne University of Technology
2007-2017
The advent of online software distribution channels like Apple Inc.'s App Store and Google Play has offered developers a single, low cost, powerful mechanism. These stores help users discover apps as well leave review. Ratings reviews add value to both the developer potential new by providing crowd-sourced indicator app quality. Hence, for it is important get positive high ratings ensure that an viable future. But, what exactly do say on these stores? And more importantly, experience compels...
Document-based Question-Answering (QA) tasks are crucial for precise information retrieval. While some existing work focus on evaluating large language model's (LLMs) performance retrieving and answering questions from documents, assessing the LLMs QA types that require exact answer selection predefined options numerical extraction is yet to be fully assessed. In this paper, we specifically underexplored context conduct empirical analysis of (GPT-4 GPT-3.5) question types, including...
Software metrics offer us the promise of distilling useful information from vast amounts software in order to track development progress, gain insights into nature software, and identify potential problems. Unfortunately, however, many exhibit highly skewed, non-Gaussian distributions. As a consequence, usual ways interpreting these - for example, terms ldquoaveragerdquo values can be misleading. Many metrics, it turns out, are distributed like wealth with high concentrations selected...
Online software distribution channels such as Apple Inc.'s App Store and Google Play provide a platform for third-party app distribution. These online stores feature public review system, allowing users to express opinions regarding purchased apps. reviews can influence product-purchasing decisions via polarised sentiment (1 5 stars) user expressed opinion. For developers, are user-facing crowd-sourced indicator of quality. Hence, high ratings positive affect the viability an app's...
Usability defects can be found either by formal usability evaluation methods or indirectly during system testing usage. No matter how they are discovered, these must tracked and reported. However, empirical studies indicate that often not clearly fully described. This study aims to identify the state of art in reporting software engineering literature. We conducted a systematic literature review defect drawing from both January 2000 until March 2016. As result, total 57 were identified,...
To identify the factors influencing errors in interpretation of dental radiographs.
Real software systems change and become more complex over time. But which parts remain stable? Common wisdom, for example, states that in a well-designed object-oriented system, the popular class is, less likely it is to from one version next, since changes this are impact its clients. We have studied consecutive releases of several public domain, analyzed number measures indicative size, popularity, complexity classes interfaces. As turns out, distributions these remarkably stable as an...
Introduction Meta-analytical evidence confirms a range of interventions, including mindfulness, physical activity and sleep hygiene, can reduce psychological distress in university students. However, it is unclear which intervention most effective. Artificial intelligence (AI)-driven adaptive trials may be an efficient method to determine what works best for whom. The primary purpose the study rank effectiveness activity, hygiene active control on reducing distress, using multiarm contextual...
Diagnosing and managing seizures presents substantial challenges for clinicians caring patients with epilepsy. Although machine learning (ML) has been proposed automated seizure detection using EEG data, there is little evidence of these technologies being broadly adopted in clinical practice. Moreover, a noticeable lack surveys investigating this topic from the perspective medical practitioners, which limits understanding obstacles development effective detection. Besides issue...
Errors of interpretation radigraphic images, also known as interpretive errors, are a critical concern they can have profound implications for clinical decision making. Different types including errors omission and misdiagnosis, been described in the literature. These lead to unnecessary or harmful treat/or prolonged patient care. Understanding nature contributing factors is important developing solutions minimise errors. By exploring knowledge perceptions dental practitioners, this study...
Reporting usability defects can be a challenging task, especially in convincing the software developers that reported defect actually requires attention. Stronger evidence form of specific details is often needed. However, research to date reporting has not investigated value capturing different information based on type. We surveyed practitioners both open source communities and industrial organizations about their practices better understand needs address issues. Our analysis 147 responses...
Intelligent services are becoming increasingly more pervasive; application developers want to leverage the latest advances in areas such as computer vision provide new and products users, large technology firms enable this via RESTful APIs. While APIs promise an easy-to-integrate on-demand machine intelligence, their current design, documentation developer interface hides much of underlying learning techniques that power them. Such look feel like conventional but abstract away data-driven...
The Hierarchical Navigable Small World (HNSW) algorithm is widely used for approximate nearest neighbor (ANN) search, leveraging the principles of navigable small-world graphs. However, it faces some limitations. first local optima problem, which arises from algorithm's greedy search strategy, selecting neighbors based solely on proximity at each step. This often leads to cluster disconnections. second limitation that HNSW frequently fails achieve logarithmic complexity, particularly in...
Object Tracking is essential for many computer vision applications, such as autonomous navigation, surveillance, and robotics. Unlike Passive (POT), which relies on static camera viewpoints to detect track objects across consecutive frames, Active (AOT) requires a controller agent actively adjust its viewpoint maintain visual contact with moving target in complex environments. Existing AOT solutions are predominantly single-agent-based, struggle dynamic scenarios due limited information...
The widespread use of Multi-layer perceptrons (MLPs) often relies on a fixed activation function (e.g., ReLU, Sigmoid, Tanh) for all nodes within the hidden layers. While effective in many scenarios, this uniformity may limit networks ability to capture complex data patterns. We argue that employing same at every node is suboptimal and propose leveraging different functions each increase flexibility adaptability. To achieve this, we introduce Local Control Networks (LCNs), which leverage...
Decentralized Multi-Agent Reinforcement Learning (Dec-MARL) has emerged as a pivotal approach for addressing complex tasks in dynamic environments. Existing (MARL) methodologies typically assume shared objective among agents and rely on centralized control. However, many real-world scenarios feature with individual goals limited observability of other agents, complicating coordination hindering adaptability. Dec-MARL strategies prioritize either communication or coordination, lacking an...
Background Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet body’s needs. In addition daily challenges that HF poses, acute exacerbations can lead costly hospitalizations and increased mortality. High health care costs burden of have led emerging application new technologies support people living with stay well while in community. However, many digital solutions not involved consumers professionals their design, leading poor adoption....
Next-frame prediction in videos is crucial for applications such as autonomous driving, object tracking, and motion prediction. The primary challenge next-frame lies effectively capturing processing both spatial temporal information from previous video sequences. transformer architecture, known its prowess handling sequence data, has made remarkable progress this domain. However, transformer-based models face notable issues: (a) multi-head self-attention (MHSA) mechanism requires the input...
Neural Architecture Search (NAS) aims to automate the design of deep neural networks. However, existing NAS techniques often focus on maximising accuracy, neglecting model efficiency. This limitation restricts their use in resource-constrained environments like mobile devices and edge computing systems. Moreover, current evaluation metrics prioritise performance over efficiency, lacking a balanced approach for assessing architectures suitable constrained scenarios. To address these...