Computing and Information Systems - Research Publications
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ItemNo Preview AvailableFast Parallel Algorithms for Submodular p-Superseparable Maximization(Springer Nature Switzerland, 2023-01-01)
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ItemNo Preview AvailableChainsFormer: A Chain Latency-Aware Resource Provisioning Approach for Microservices Cluster(SPRINGER INTERNATIONAL PUBLISHING AG, 2023)
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ItemNo Preview AvailableEnSpeciVAT: Enhanced SpecieVAT for Cluster Tendency Identification in Graphs(Springer Nature Switzerland, 2023-01-01)
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ItemAgent Miner: An Algorithm for Discovering Agent Systems from Event Data(Springer Nature Switzerland, 2023)Process discovery studies ways to use event data generated by business processes and recorded by IT systems to construct models that describe the processes. Existing discovery algorithms are predominantly concerned with constructing process models that represent the control flow of the processes. Agent system mining argues that business processes often emerge from interactions of autonomous agents and uses event data to construct models of the agents and their interactions. This paper presents and evaluates Agent Miner, an algorithm for discovering models of agents and their interactions from event data composing the system that has executed the processes which generated the input data. The conducted evaluation using our open-source implementation of Agent Miner and publicly available industrial datasets confirms that our algorithm can provide insights into the process participants and their interaction patterns and often discovers models that describe the business processes more faithfully than process models discovered using conventional process discovery algorithms.
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ItemLearning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning(Springer Nature Switzerland, 2023)Increasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain actions (a.k.a. treatments) that workers may execute to lift the probability that a case ends in a positive outcome. For example, in a loan origination process, a possible treatment is to issue multiple loan offers to increase the probability that the customer takes a loan. Each treatment has a cost. Thus, when defining policies for prescribing treatments to cases, managers need to consider the net gain of the treatments. Also, the effect of a treatment varies over time: treating a case earlier may be more effective than later in a case. This paper presents a prescriptive monitoring method that automates this decision-making task. The method combines causal inference and reinforcement learning to learn treatment policies that maximize the net gain. The method leverages a conformal prediction technique to speed up the convergence of the reinforcement learning mechanism by separating cases that are likely to end up in a positive or negative outcome, from uncertain cases. An evaluation on two real-life datasets shows that the proposed method outperforms a state-of-the-art baseline.
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ItemNo Preview AvailableOverview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents(SPRINGER INTERNATIONAL PUBLISHING AG, 2022)
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ItemNo Preview AvailableHand Hygiene Quality Assessment Using Image-to-Image Translation(SPRINGER INTERNATIONAL PUBLISHING AG, 2022)Hand hygiene can reduce the transmission of pathogens and prevent healthcare-associated infections. Ultraviolet (UV) test is an effective tool for evaluating and visualizing hand hygiene quality during medical training. However, due to various hand shapes, sizes, and positions, systematic documentation of the UV test results to summarize frequently untreated areas and validate hand hygiene technique effectiveness is challenging. Previous studies often summarize errors within predefined hand regions, but this only provides low-resolution estimations of hand hygiene quality. Alternatively, previous studies manually translate errors to hand templates, but this lacks standardized observational practices. In this paper, we propose a novel automatic image-to-image translation framework to evaluate hand hygiene quality and document the results in a standardized manner. The framework consists of two models, including an Attention U-Net model to segment hands from the background and simultaneously classify skin surfaces covered with hand disinfectants, and a U-Net-based generator to translate the segmented hands to hand templates. Moreover, due to the lack of publicly available datasets, we conducted a lab study to collect 1218 valid UV test images containing different skin coverage with hand disinfectants. The proposed framework was then evaluated on the collected dataset through five-fold cross-validation. Experimental results show that the proposed framework can accurately assess hand hygiene quality and document UV test results in a standardized manner. The benefit of our work is that it enables systematic documentation of hand hygiene practices, which in turn enables clearer communication and comparisons.
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ItemNo Preview AvailableBallot-Polling Audits of Instant-Runoff Voting Elections with a Dirichlet-Tree Model(Springer International Publishing, 2023-01-01)
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ItemNo Preview AvailableIndex-Based Batch Query Processing Revisited(SPRINGER INTERNATIONAL PUBLISHING AG, 2023)
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ItemNo Preview AvailableCOLLIDER: A Robust Training Framework for Backdoor Data(Springer Nature Switzerland, 2023-01-01)