Computing and Information Systems - Research Publications
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ItemNo Preview AvailableDesigning an App for Pregnancy Care for a Culturally and Linguistically Diverse Community(The Association for Computing Machinery, 2017)We report a study to design and evaluate an app to support pregnancy information provided to women through an Australian health service. As part of a larger project to provide prenatal resources for culturally and linguistically diverse groups, this study focused on the design and reception of an app with the local Vietnamese community and health professionals of a particular hospital. Our study had three stages: an initial design workshop with the hospital; prototype design and development; prototype-based interviews with health professionals and focus groups with Vietnamese women. We explore how an app of this sort must be designed for a range of different use scenarios, considering its use by consumers with a multiplicity of differing viewpoints about its nature and purpose in relation to pregnancy care.
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ItemSummarizing Significant Changes in Network Traffic Using Contrast Pattern Mining(Association for Computing Machinery, 2017)Extracting knowledge from the massive volumes of network traffic is an important challenge in network and security management. In particular, network managers require concise reports about significant changes in their network traffic. While most existing techniques focus on summarizing a single traffic dataset, the problem of finding significant differences between multiple datasets is an open challenge. In this paper, we focus on finding important differences between network traffic datasets, and preparing a summarized and interpretable report for security managers. We propose the use of contrast pattern mining, which finds patterns whose support differs significantly from one dataset to another. We show that contrast patterns are highly effective at extracting meaningful changes in traffic data. We also propose several evaluation metrics that reflect the interpretability of patterns for security managers. Our experimental results show that with the proposed unsupervised approach, the vast majority of extracted patterns are pure, i.e., most changes are either attack traffic or normal traffic, but not a mixture of both.
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ItemAdversarially Parameterized Optimization for 3D Human Pose Estimation(IEEE, 2017)We propose Adversarially Parameterized Optimization, a framework for learning low-dimensional feasible parameterizations of human poses and inferring 3D poses from 2D input. We train a Generative Adversarial Network to `imagine' feasible poses, and search this imagination space for a solution that is consistent with observations. The framework requires no scene/observation correspondences and enforces known geometric invariances without dataset augmentation. The algorithm can be configured at run time to take advantage of known values such as intrinsic/extrinsic camera parameters or target height when available without additional training. We demonstrate the framework by inferring 3D human poses from projected joint positions for both single frames and sequences. We show competitive results with extremely simple shallow network architectures and make the code publicly available.
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ItemNo Preview AvailableReal-Time UAV Maneuvering via Automated Planning in Simulations(International Joint Conferences on Artificial Intelligence, 2017-08-19)The automatic generation of realistic behaviour such as tactical intercepts for Unmanned Aerial Vehicles (UAV) in air combat is a challenging problem. State-of-the-art solutions propose hand–crafted algorithms and heuristics whose performance depends heavily on the initial conditions and specific aerodynamic characteristics of the UAVs involved. This demo shows the ability of domain–independent planners, embedded into simulators, to generate on–line, feed–forward, control signals that steer simulated aircraft as best suits the situation
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ItemNo Preview AvailableSession details: Sense Making for Creativity(ACM, 2017-06-22)
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ItemSpontaneous interactions with a virtually embodied intelligent assistant in Minecraft(Association for Computing Machinery (ACM), 2017-05-06)An increasing number of our technological interactions are mediated through virtually embodied characters and software agents powered by machine learning. To understand how users relate to and evaluate these types of interfaces, we designed a Wizard of Oz prototype of an embodied agent in Minecraft that learns from users' actions, and conducted a user study with 18 school-aged Minecraft players. We categorised nine main ways users spontaneously attempted to interact with and teach the agent: four using game controls, and five using natural language text input. This study lays groundwork for a better understanding of human interaction with learning agents in virtual worlds.
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ItemEvaluating Real-Time Gaze Representations to Infer Intentions in Competitive Turn-Based Strategy Games(Association for Computing Machinery, 2017)In this paper, we investigate nine different visual representations of gaze in a competitive digital game setting. We evaluate the ability of spectators to infer a player's intentions in the game for each visual representation. Our results show that spectators have a remarkable ability to infer intent accurately using all nine visualizations, but that visualizations with certain characteristics were more comprehensible and more readily revealed the player's intent. The real-time Heatmap visualization was the most highly preferred by participants and the most effective in revealing intent, due to its ability to balance real-time gaze information with a persistent summary of recent gaze behaviour. Our findings show that eye-tracking visualization can enable playful interactions in competitive games based on players' ability to interpret opponents' attention and intention through gaze information.
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ItemE-Storm: Replication-based State Management in Distributed Stream Processing Systems(IEEE COMPUTER SOC, 2017-01-01)Apache Storm is a fault-tolerant, distributed inmemory computation system for processing large volumes of high-velocity data in real-time. As an integral part of the fault-tolerance mechanism, Storm's state management is achieved by a checkpointing framework, which commits states regularly and recovers lost states from the latest checkpoint. However, this method involves a remote data store for state preservation and access, resulting in significant overheads to the performance of error-free execution.In this paper, we propose E-Storm, a replication-based state management system that actively maintains multiple state backups on different worker nodes. We build a prototype on top of Storm by extending it with monitoring and recovery modules to support inter-task state transfer whenever needed. The experiments carried out on synthetic and real-world streaming applications confirm that E-Storm outperforms the existing checkpointing method in terms of the resulting application performance, obtaining as much as 9.44 times throughput improvement while reducing the application latency down to 9.8%.
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ItemTo be (Me) or Not to Be? Photorealistic Avatars and Older Adults(ACM, 2017)The growth of commercial VR technology has fueled an interest in user embodiment, where a graphical representation of the user, a virtual avatar, enables a more immersive experience and richer interaction. Recent research suggests that older adults are increasingly playing digital games. These factors, combined with the rapidly ageing population, means it is vital that avatar creation software responds to the needs of older adults. Our study seeks to address these needs, by better understanding older adult opinions about virtual avatars that are photorealistic, i.e. bearing likeness to their physical appearances. In our exploratory study, we interviewed six older adults aged between 70 and 80 years and asked them to evaluate 18 photorealistic avatars created with three different commercial avatar creation tools. Results showed that participants were not satisfied with their custom-made avatars due to them missing characteristic features. The results also showed that there was major consensus towards using photorealistic avatars across a range of virtual environments.
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ItemNegotiating stereotypes of older adults through avatars(Association for Computing Machinery (ACM), 2017-11-28)Virtual Avatars can bring opportunities for enjoyment, social participation and exploration of identities. However, the configuration of avatar creation software may marginalise some groups of users due to them reinforcing social stereotypes that privilege youth and beauty, rather than representing the broader variety of human identities. Older adults are one group who may be disadvantaged with respect to avatars as avatar studies have typically focused on younger users. Considering that older populations are growing and that their participation in virtual environments is increasing, it is timely to investigate older adults' preferences in relation to avatars. We conducted a study with 23 participants (70+ years old) to understand the representational requirements of older adults when creating a humanoid virtual avatar. Our findings demonstrate that older adults are negotiating ageing stereotypes when creating a virtual body. These negotiations of body appearances range from: the Actual Avatar that by mirroring the self suggests an acceptance of the ageing body; the Vibrant Avatar that is idealising the physical condition of the self; the Other Avatar, that aims to explore other identities; and the Companion Avatar that creates another persona as company. These findings highlight that older adults have specific representational requirements when designing virtual avatars.