Computing and Information Systems - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 2410
  • Item
    No Preview Available
    AI-augmented Business Process Management Systems: A Research Manifesto
    Dumas, M ; Fournier, F ; Limonad, L ; Marrella, A ; Montali, M ; Rehse, J-R ; Accorsi, R ; Calvanese, D ; De Giacomo, G ; Fahland, D ; Gal, A ; La Rosa, M ; Voelzer, H ; Weber, I (ASSOC COMPUTING MACHINERY, 2023-03)
    AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics.
  • Item
    No Preview Available
    Near-infrared Imaging for Information Embedding and Extraction with Layered Structures
    Jiang, W ; Yu, D ; Wang, C ; Sarsenbayeva, Z ; van Berkel, N ; Goncalves, J ; Kostakos, V (ASSOC COMPUTING MACHINERY, 2023-02-01)
    Non-invasive inspection and imaging techniques are used to acquire non-visible information embedded in samples. Typical applications include medical imaging, defect evaluation, and electronics testing. However, existing methods have specific limitations, including safety risks (e.g., X-ray), equipment costs (e.g., optical tomography), personnel training (e.g., ultrasonography), and material constraints (e.g., terahertz spectroscopy). Such constraints make these approaches impractical for everyday scenarios. In this article, we present a method that is low-cost and practical for non-invasive inspection in everyday settings. Our prototype incorporates a miniaturized near-infrared spectroscopy scanner driven by a computer-controlled 2D-plotter. Our work presents a method to optimize content embedding, as well as a wavelength selection algorithm to extract content without human supervision. We show that our method can successfully extract occluded text through a paper stack of up to 16 pages. In addition, we present a deep-learning-based image enhancement model that can further improve the image quality and simultaneously decompose overlapping content. Finally, we demonstrate how our method can be generalized to different inks and other layered materials beyond paper. Our approach enables a wide range of content embedding applications, including chipless information embedding, physical secret sharing, 3D print evaluations, and steganography.
  • Item
    No Preview Available
    CoLocateMe: Aggregation-Based, Energy, Performance and Cost Aware VM Placement and Consolidation in Heterogeneous IaaS Clouds
    Zakarya, M ; Gillam, L ; Salah, K ; Rana, O ; Tirunagari, S ; Buyya, R (IEEE COMPUTER SOC, 2023-03-01)
  • Item
    No Preview Available
    AWARE-Light: a smartphone tool for experience sampling and digital phenotyping
    van Berkel, N ; D’Alfonso, S ; Kurnia Susanto, R ; Ferreira, D ; Kostakos, V (Springer Science and Business Media LLC, 2023-04-01)
  • Item
    No Preview Available
    Social media information governance in multi-level organizations: How humanitarian organizations accrue social capital
    Fischer-Preßler, D ; Marx, J ; Bunker, D ; Stieglitz, S ; Fischbach, K (Elsevier BV, 2023-11-01)
  • Item
    No Preview Available
    Width-based search for multi agent privacy-preserving planning
    Gerevini, AE ; Lipovetzky, N ; Percassi, F ; Saetti, A ; Serina, I (Elsevier BV, 2023-05-01)
    In multi-agent planning, preserving the agents' privacy has become an increasingly popular research topic. For preserving the agents' privacy, agents jointly compute a plan that achieves mutual goals by keeping certain information private to the individual agents. Unfortunately, this can severely restrict the accuracy of the heuristic functions used while searching for solutions. It has been recently shown that, for centralized planning, blind search algorithms such as width-based search can solve instances of many existing domains in low polynomial time when they feature atomic goals. Moreover, the performance of goal-oriented search can be improved by combining it with width-based search. In this paper, we investigate the usage of width-based search in the context of (decentralised) collaborative multi-agent privacy-preserving planning, addressing the challenges related to the agents' privacy and performance. In particular, we show that width-based search is a very effective approach over several benchmark domains, even when the search is driven by heuristics that roughly estimate the distance from goal states, computed without using the private information of other involved agents. Moreover, we show that the use of width-based techniques can significantly reduce the number of messages transmitted among the agents, better preserving their privacy and improving their performance. An experimental study presented in the paper analyses the effectiveness of our techniques, and compares them with the state-of-the-art of collaborative multi-agent planning.
  • Item
  • Item
    Thumbnail Image
    Correction to: Coexisiting type 1 diabetes and celiac disease is associated with lower Hba1c when compared to type 1 diabetes alone: data from the Australasian Diabetes Data Network (ADDN) registry.
    James, S ; Perry, L ; Lowe, J ; Donaghue, KC ; Pham-Short, A ; Craig, ME ; ADDN Study Group, (Springer Science and Business Media LLC, 2023-09-02)
  • Item
    Thumbnail Image
    Use of thermal imaging to measure the quality of hand hygiene.
    Wang, C ; Jiang, W ; Yang, K ; Sarsenbayeva, Z ; Tag, B ; Dingler, T ; Goncalves, J ; Kostakos, V (Elsevier BV, 2023-09)
    OBJECTIVES: Hand hygiene has long been promoted as the most effective way to prevent the transmission of infection. However, due to low compliance and low quality of hand hygiene reported in previous studies, constant monitoring of hand hygiene compliance and quality among healthcare workers is crucial. This study investigated the feasibility of using a thermal camera with an RGB camera to detect hand coverage of alcohol-based formulation, thereby monitoring the quality of hand rubbing. METHODS: In total, 32 participants were recruited to participate in this study. Participants were required to perform four types of hand rubbing to achieve different coverage of the alcohol-based formulation. After each task, participants' hands were photographed under a thermal camera and an RGB camera, while an ultraviolet (UV) test was used to provide the ground truth of hand coverage of alcohol-based formulation. U-Net was used to segment areas exposed to alcohol-based formulation from thermal images, and system performance was evaluated by comparing differences in coverage between thermal images and UV images in terms of accuracy and Dice coefficient. RESULTS: This system found promising results in terms of accuracy (93.5%) and Dice coefficient (87.1%) when observations took place 10 s after hand rubbing. At 60 s after hand rubbing, accuracy and Dice coefficient were 92.4% and 85.7%. CONCLUSIONS: Thermal imaging has potential for accurate, constant and systematic monitoring of the quality of hand hygiene.
  • Item
    Thumbnail Image
    Same graph, different data: A usability study of a student-facing dashboard based on self-regulated learning theory
    de Barba, P ; Araujo Oliveira, E ; Hu, X ; Wilson, S ; Arthars, N ; Wardak, D ; Yeoman, P ; Kalman, E ; Liu, DYT (Australasian Society for Computers in Learning in Tertiary Education (ASCILITE), 2022)
    Student-facing learning analytics dashboards have the potential to reconnect students with their purpose for learning, reminding them of their goals and promoting reflection about their learning journey. However, far less is known about the specifics of the relationship between different types of visualisations and data presented in dashboards and their impact on students’ motivation. In this study, we used a Human-Centred Design method across three iterations to (1) understand how students prioritise similar visualisations when presenting different data (2) examine how they interact with these, and (3) propose a dashboard design that would accommodate students’ different motivational needs. In the first iteration, 26 participants ranked their preferred visualisations using paper prototypes; in the second iteration, a digital wireframe was created based on the results from the first iteration to conduct user tests with two participants; and in the third iteration, a high-fidelity prototype was created to reflect findings from the previous iterations. Overall, findings showed that students mostly valued setting goals and monitoring their progress from a multiple goals approach, and were reluctant about comparing their performance with peers due to concerns related to promoting unproductive competition amongst peers and data privacy. Implications for educators and learning designers are discussed.