Computing and Information Systems - Research Publications

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    Understanding Older Adults' Participation in Online Social Activities
    Zhao, W ; Kelly, RM ; Rogerson, MJ ; Waycott, J (Association for Computing Machinery (ACM), 2022-11-07)
    Restrictions arising from the COVID-19 pandemic have limited opportunities for older people to participate in face-to-face organised social activities. Many organisations moved these activities online, but little is known about older adults' experiences of participating in those activities. This paper reports an investigation of older adults' experiences of participating in social activities that they used to attend in-person, but which were moved online because of strict lockdown restrictions. We conducted in-depth interviews with 40 older adults living independently (alone or with others). Findings from a reflexive thematic analysis show that online social activities were important during the pandemic for not only staying connected to other people but also helping older adults stay engaged in meaningful activities, including arts, sports, cultural, and civic events. Online activities provided older adults with opportunities to connect with like-minded people; share care, encouragement, and support; participate in civic agendas; learn knowledge and develop new skills; and experience entertainment, distraction, and mental stimulation. Our participants had diverse perceptions of the transition from in-person to online social activities. Based on the findings, we present a taxonomy of multi-layered meaningful activities for older adults' digital social participation and highlight implications for future technology design.
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    Navigating Online Down Under: International Students’ Digital Journeys in Australia
    Martin, F ; Chang, S ; Gomes, C ; Gomes, C ; Yeoh, B (Rowman & Littlefield, 2018)
    Research focusing on the experiences of international students tends to centre directly on their educational experiences rather than their everyday lives outside study. Moreover, much of this research has concentrated almost exclusively on the various impacts of the physical, geographic mobility of international students as they move from one country to another, with very little exploration of their digital experiences. There also exists extensive research on the social media and information seeking experiences of young people in different regions of the world. Some of this research provides a comparison between different sources of information and uses of social media. However, there has been little research on what happens when young people move between regions or countries. Borrowing Chang and Gomes’ (2017a) concept of the digital journey, where in crossing transnational borders, migrants might also cross digital borders, this chapter provides some concrete examples of the digital experiences of international students as they transition––wholly or partly––to the Australian digital environment. How do international students transition from certain online environments into others that may be completely different, even alien, to what they have previously experienced? Referring to qualitative and quantitative data collected from three separate projects conducted between 2012 and 2017, this chapter shows that in making the digital journey, international students in Australia do not so much quit their original digital comfort zones as widen their digital horizons. Understanding international students’ digital journeys is particularly significant since it has implications for future research in international student well-being and the provision of support services for students.
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    A representation learning framework for detection and characterization of dead versus strain localization zones from pre-to post-failure
    Tordesillas, A ; Zhou, S ; Bailey, J ; Bondell, H (SPRINGER, 2022-08-01)
    Abstract Experiments have long shown that zones of near vanishing deformation, so-called “dead zones”, emerge and coexist with strain localization zones inside deforming granular media. To date, a method that can disentangle these dynamically coupled structures from each other, from pre- to post- failure, is lacking. Here we develop a framework that learns a new representation of the kinematic data, based on the complexity of a grain’s neighborhood structure in the kinematic-state-space, as measured by a recently introduced metric called s-LID. Dead zones (DZ) are first distinguished from strain localization zones (SZ) throughout loading history. Next the coupled dynamics of DZ and SZ are characterized using a range of discriminative features representing: local nonaffine deformation, contact topology and force transmission properties. Data came from discrete element simulations of biaxial compression tests. The deformation is found to be essentially dual in nature. DZ and SZ exhibit distinct yet coupled dynamics, with the separation in dynamics increasing in the lead up to failure. Force congestion and plastic deformation mainly concentrate in SZ. Although the 3-core of the contact network is highly prone to damage in SZ, it is robust to pre-failure microbands but is decimated in the shearband, leaving a fragmented 3-core in DZ at failure. We also show how loading condition and rolling resistance influence SZ and DZ differently, thus casting new light on controls on plasticity from the perspective of emergent deformation structures. Graphic abstract
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    Health Misinformation Across Multiple Digital Ecologies: Qualitative Study of Data From Interviews With International Students
    Bahl, R ; Chang, S ; McKay, D ; Buchanan, G (JMIR PUBLICATIONS, INC, 2022-07-05)
    BACKGROUND: Transient migrants such as international students have received limited support from host country governments throughout the COVID-19 pandemic. An increase in misinformation, resulting in poor health outcomes for individuals, may impact an already vulnerable group. OBJECTIVE: Existing research examines the spread of misinformation. Similarly, there is extensive literature on the health information behavior of international students. However, there is a gap in the literature focusing on international students' interaction with health misinformation. This exploratory research aims to address this gap by examining international students' interaction with health misinformation during the COVID-19 pandemic. METHODS: A total of 11 participants took part in semistructured interviews and a health misinformation-identification exercise via Zoom. The data collected were subjected to qualitative thematic analysis. Multiple rounds of coding, checked by other coders, revealed 2 themes and 6 subthemes. RESULTS: The 2 main themes that emerged were (1) approaches to dealing with health misinformation and (2) how international students navigate across multiple digital ecologies. Results show that international students who draw on multiple digital ecologies for information reliably identify misinformation, suggesting that the use of multiple digital ecologies may have a protective effect against health misinformation. CONCLUSIONS: Findings show that international students encounter health misinformation across multiple digital ecologies, and they also compare information across multiple ecologies. This comparison may support them in identifying health misinformation. Thus, the findings of this study combat narratives of international students' susceptibility to misinformation.
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    Structural landscapes of PPI interfaces
    Rodrigues, CHM ; Pires, DE ; Blundell, TL ; Ascher, DB (OXFORD UNIV PRESS, 2022-06-02)
    Proteins are capable of highly specific interactions and are responsible for a wide range of functions, making them attractive in the pursuit of new therapeutic options. Previous studies focusing on overall geometry of protein-protein interfaces, however, concluded that PPI interfaces were generally flat. More recently, this idea has been challenged by their structural and thermodynamic characterisation, suggesting the existence of concave binding sites that are closer in character to traditional small-molecule binding sites, rather than exhibiting complete flatness. Here, we present a large-scale analysis of binding geometry and physicochemical properties of all protein-protein interfaces available in the Protein Data Bank. In this review, we provide a comprehensive overview of the protein-protein interface landscape, including evidence that even for overall larger, more flat interfaces that utilize discontinuous interacting regions, small and potentially druggable pockets are utilized at binding sites.
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    Real-time road safety optimization through network-level data management
    Muthugama, L ; Xie, H ; Tanin, E ; Karunasekera, S (Springer Science and Business Media LLC, 2022-01-01)
    Abstract With the increasing connectedness of vehicles, real-time spatio-temporal data can be collected from citywide road networks. Innovative data management solutions can process the collected data for the purpose of reducing travel time. However, a majority of the existing solutions have missed the opportunity to better manage the collected data for improving road safety at the network level. We propose an efficient data management framework that uses network-level data to improve road safety for citywide applications. Our framework uses a graph-based data structure to maintain real-time network-level traffic data. Based on the graph, the framework uses a novel technique to generate driving instructions for individual vehicles. By following the instructions, inter-vehicular spacing can be increased, leading to an improvement of road safety. Experimental results show that our framework improves road safety, measured based on the time to collision between vehicles, from the state-of-the-art traffic data management solutions by a large margin while achieving lower travel times compared with the solutions. The framework is also readily deployable for large-scale real-time applications due to its low computation costs.
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    MAPPING THE CHATTER: SPATIAL METAPHORS FOR DYNAMIC TOPIC MODELLING OF SOCIAL MEDIA
    Morandini, L ; Mohammad, AR ; Sinnott, RO (Copernicus GmbH, 2022-08-05)
    Abstract. Topic modelling is a branch of Natural Language Processing (NLP) that deals with the discovery of conversation topics in a given document corpus. In social media, this translates into aggregating social media posts, e.g. tweets, into topics of conversation and observing how these topics evolve over time (hence the “dynamic” adjective). Conveying the results of topic modelling can be challenging since the topics often do not lend themselves naturally to meaningful labelling. The volume of real world (global) social media also means that millions of topics can be ongoing at any given time and the relationships between them can involve hundreds of dimensions and relationships that continually emerge. The popularity of topics is itself subject to change over time and reflect the pulse of what is happening in society at large. In this paper, we propose a spatialization technique based on open-source software that reduces the intrinsic complexity of dynamic topic modelling results to familiar topographic objects, namely: ridges, valleys, and peaks. This offers new possibilities for understanding complex relationships that change over time whilst overcoming issues with traditional topic modelling visualisation approaches such as network graphs.
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    Story points changes in agile iterative development An empirical study and a prediction approach
    Pasuksmit, J ; Thongtanunam, P ; Karunasekera, S (SPRINGER, 2022-11-01)
    Abstract Story Points (SP) are an effort unit that is used to represent the relative effort of a work item. In Agile software development, SP allows a development team to estimate their delivery capacity and facilitate the sprint planning activities. Although Agile embraces changes, SP changes after the sprint planning may negatively impact the sprint plan. To minimize the impact, there is a need to better understand the SP changes and an automated approach to predict the SP changes. Hence, to better understand the SP changes, we examine the prevalence, accuracy, and impact of information changes on SP changes. Through the analyses based on 19,349 work items spread across seven open-source projects, we find that on average, 10% of the work items have SP changes. These work items typically have SP value increased by 58%-100% relative to the initial SP value when they were assigned to a sprint. We also find that the unchanged SP reflect the development time better than the changed SP. Our qualitative analysis shows that the work items with changed SP often have the information changes relating to updating the scope of work. Our empirical results suggest that SP and the scope of work should be reviewed prior or during sprint planning to achieve a reliable sprint plan. Yet, it could be a tedious task to review all work items in the product (or sprint) backlog. Therefore, we develop a classifier to predict whether a work item will have SP changes after being assigned to a sprint. Our classifier achieves an AUC of 0.69-0.8, which is significantly better than the baselines. Our results suggest that to better manage and prepare for the unreliability in SP estimation, the team can leverage our insights and the classifier during the sprint planning. To facilitate future studies, we provide the replication package and the datasets, which are available online.
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    A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers
    Thompson, J ; McClure, R ; Scott, N ; Hellard, M ; Abeysuriya, R ; Vidanaarachchi, R ; Thwaites, J ; Lazarus, J ; Lavis, J ; Michie, S ; Bullen, C ; Prokopenko, M ; Chang, SL ; Cliff, OM ; Zachreson, C ; Blakely, A ; Wilson, T ; Ouakrim, DA ; Sundararajan, V (BMC, 2022-10-08)
    The COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models-developed at rapid pace and often in the absence of complete information-ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.