bluuebunny/crossref_metadata_2025 huggingface dataset:
Going Nowhere: Oceanic Im/Mobilities in North American Refugee Fiction
Authors: Ganser Alexandra
Published: March 2023

In philosophy and theory, the terms flight and territorialization are tightly connected to Gilles Deleuze and Félix Guattari’s A Thousand Plateaus. Through “lines of flight”—unpredictable routes defying spatial control—they conceptualize the breakup of a hegemonic spatial semantics through the mobility of the nomad. These lines make the paths of “deterritorialization,” contravening normative spatial structures (“striated” space) and producing “smooth space” that escapes structuration and control. Postcolonial critics such as Gayatri Spivak have held Deleuzian philosophy accountable for reaffirming a universal (white male) subject, but rarely debate lines of flight and deterritorialization, which appear somewhat romantic if applied to refugees subjected to involuntarily deterritorialization. In my essay, I ask how literature can perform the work of a conceptual corrective to such blind spots by reading Edwidge Danticat’s 1991 short story “Children of the Sea” and the novel Dogs at the Perimeter by the Chinese-Malaysian Canadian Madeleine Thien (2011). Danticat’s story focuses on the Haitian “boat people” that attempted to reach Florida shores in the 1980s and 1990s, while Thien examines the Cambodian genocide and its consequences for the children that came to Canada as refugees. Both texts, I argue, articulate what Achille Mbembe has called the necropolitics of genocide and demographic control and perform a grueling critique of the necropolitical structures that continue to produce transoceanic death.
“Spoken Nowhere but on the Water”: Amitav Ghosh’s Sea of Poppies and Lost-and-Found Languages of the Indian Ocean World
Authors: Lavery Charne
Published: March 2023

Amitav Ghosh’s fictional oeuvre makes a major contribution to contemporary sea fiction, particularly that written from a non-Eurocentric perspective. HisIbistrilogy, for instance, paints a vivid picture of historical oceanic mobility in the form of ship journeys and littoral interconnections, centered on and in the Indian Ocean world. This chapter explores one aspect of that mobility, a language “spoken only on the water,” a roving dialect that Ghosh both painstakingly and playfully recreates in the first novel of the trilogy,Sea of Poppies. Laskariis a dialect that was spoken among lascar sailors born of, and borne on, the Indian Ocean. This essay examines the ways in which two dominant areas of Ghosh’s experimentation and interest—language and the sea—intersect inSea of Poppies,through a focus onlaskarias a lingua franca of work. It argues that the intersection can be approached in three ways: through the lens of Ghosh’s production of Indian Ocean space, as a language of South-South mobility; through the lens of sailor speech as a vernacular associated particularly with the craft of sail, participating in a tradition of sea fiction that harks back to Conrad and Melville; and, briefly, through the lens of postcolonial ecology, as a language that has been lost and only partially recovered.
South Seas Speculation in Finance and Fiction
Authors: Kennedy Melissa
Published: March 2023

In the Western imaginary, the “south seas” of the Pacific Ocean has always been a speculative space on which both desires and fears are projected. Western images of fantastical, utopian spaces and exotic species ripe for conquest and capitalist extraction have left long legacies, that today continue to impact on issues of land ownership, indigenous agency, and response to ecological devastation. The conceptualization of the “south seas” in Britain’s first financial crisis, the 1720 south sea Bubble and its associated satirical fiction, produced a dominant, overdetermined imaginary of the Pacific that masked its real financial and economic motivations. As this paper’s analysis of the 2017 BBC television seriesTabooargues, this imaginary stubbornly remains 300 years later, enabling unbound speculative investment, extraction, and concealment that are damaging the world economy through offshore finance, and global ecology through reckless pillaging of natural resources.
Precarious Passages: On Migrant Maritime Mobilities, ca. 1907
Authors: Sander Sarah
Published: March 2023

Taking contemporary visual discourse on ‘precarious passages’ as a starting point, Sander’s contribution explores the media and material conditions of migrant maritime mobilities around 1900. In the wake of the second wave of mass migration to the United States, a new kind of steamship was developed that shaped the experience of the passage from the ‘Old’ to the New World: the Grand Ocean Lines. Not unlike today, the parameters of this experience were based on economic and social structures. While the great mass of migrants traveled under unreasonably perilous conditions in the dark and dirty steerage holds of the ship, the upper decks of the ocean liners developed into ‘Grand Hotels,’ offering the first- and second-class passengers luxurious voyages on the very same steamers. Alfred Stieglitz’s famous cubist photograph “The Steerage” (1907) powerfully shows these divergent class conditions. The picture, in which new formal parameters are combined with a clear look at everyday reality on the steamship, thus became one of the most important images of maritime modernity.
High Sea and Sediment: Watermarks in Ilse Aichinger’s Work
Authors: Pelz Annegret
Published: March 2023

This chapter seeks to trace the significance of water and the sea in the work of Austrian author Ilse Aichinger (1921–2016). By looking at both Aichinger’s literary texts (her 1948 novel The Greater Hope, her radio plays “Gare Maritime” and “Auckland” as well as the prose miniature “Flecken”) and her poetological work, the chapter shows how the author uses the sea in order to make sense of the conditions of narrative writing in the postwar period. Taking issue with Anglophone realist seafarer-narrators such as Joseph Conrad, Aichinger instead refers to the sea as an indicator of a rupture in narrative continuity, of a break with realist narration. However, while the sea appears as a destructive flood that threatens meaning and narrative closure, it also harbors the potential for linguistic renewal in her work. For Aichinger, the sea also has autobiographical meaning, indicating salvation: In 1938, her sister was able to escape from the Nazis, crossing the channel to England on a ship as part of a Kindertransport (children’s transport). By turning the “stains” of dried out language into the seeds of new narrative, Aichinger suggests a possibile way, through writing, to counter the threat of forgetting the National Socialist era.
Place-Based Approaches to Food System Resilience: Emerging Trends and Lessons from South Africa
Authors: Losch Bruno , May Julian
Published: March 2023

Food systems have outcomes related to three goals: food and nutrition security; livelihoods and economic inclusion; and environmental sustainability. Place-based approaches help to delineate the adequate territories in which coalitions of actors can address such goals. In the case of food, they facilitate food system resilience through identifying opportunities for adaptation to change and offer risk management to deal with external shocks. In many countries, local authorities and communities were central in the early response to the COVID-19 pandemic. The South African experience is illustrative of their potential roles in a time of crisis. Although South Africa’s provinces have restricted competency for food system governance, the Western Cape Province adopted a pro-active approach and developed from 2014 a food security strategy where it commits to a wide range of interventions. Related and following local debates provided a fertile context which allowed further engagement about ways to improve food governance. It facilitated the emergence of multiple community-led initiatives to address the loss of livelihoods and food insecurity during the crisis. This experience illustrates the potential to produce polycentric forms of governance that can progressively result in collaborative governance; it also reveals how embryonic territorial approaches addressing food system issues can emerge.
Food Security and the Fractured Consensus on Food Resilience: An Analysis of Development Agency Narratives
Authors: Lindgren Karl-Axel , Lang Tim
Published: March 2023

The published narratives on food resilience of 16 development agencies are analysed. Using a rapid appraisal method, their positions and conception of resilience as a factor in food security are scrutinised. The study provides a snapshot of thought in 2020 and 2021. The COVID-19 pandemic, climate change, biodiversity loss and a policy focus on food systems have made resilience prominent in food policy. Firstly, concerns are raised that resilience may follow food security in its plasticity, blunting its critical edge. Secondly, the methods are explained. Thirdly, the findings are presented and organised by agency type. Fourthly, the findings are discussed. A fractured consensus around food resilience is noted. Despite broad agreement that resilience is a useful dimension for food security, there is no mutually agreed systematic conceptualisation or framework. Agencies use different definitions, approaches and measurements in their discourse, with varying levels of complexity. Some agencies adopt resilience as a buzzword, while others make it central to their institutional approach. The chapter concludes that, although resilience is emerging as core concept, its value would be strengthened with interdisciplinary attention paid to how food resilience is measured; unless this occurs, the risk is that resilience will be diluted as it becomes ubiquitous.
Food Systems, Resilience, and Their Implications for Public Action
Authors: Hoddinott John
Published: March 2023

Linking the concepts of food systems and resilience offers the opportunity to strengthen our understanding of these concepts, the potential they hold for more informed policy discussions, and the design and implementation of interventions that will better deliver on food security outcomes. This chapter outlines how these twin concepts can be linked conceptually and empirically. It argues that while we know much about certain elements of the food system, specifically production and consumption, our understanding of the processing and distribution components of the food system are weak. For example, market structure in the processing sector and market integration can contribute to food system resilience, but these are rarely measured at a country level. This makes efforts to measure resilience at the system-level challenging. Understanding what can make a resilient food system has important implications for policy and intervention design. Building resilient food systems requires that policymakers grapple with trade-offs and tensions such as those between the benefits of diversification versus gains from specialization; and how openness to trade reduces vulnerability to domestic shocks to the food system while exposing it to external shocks. How best to manage these will be an important challenge to address.
Food Security Under a Changing Climate: Exploring the Integration of Resilience in Research and Practice
Authors: De Pinto Alessandro , Islam Md Mofakkarul , Katic Pamela
Published: March 2023

Climate change poses significant risks to our food systems, thus jeopardising the food security of millions of people worldwide. The concept of resilience is increasingly being proposed as a framework to find solutions to these challenges. In this chapter, we assess how resilience has been integrated in discussions about climate change and food security by both academics and practitioners. We performed a targeted review of the academic literature on climate change, food security, and resilience and found that despite a growing body of literature on the subject, the pathways through which actions translate into resilience and then into food security remain unclear. An examination of a sample of projects implemented through the Adaptation Fund revealed that many good practices with potential for resilience-building are used but also that suitable indicators and methods to monitor and evaluate resilience and its outcomes are lacking. Based on our findings, we conclude that while the concept of resilience has accompanied and may have favoured a transition towards more integrated approaches and interventions in work related to climate change and food security, further efforts are needed to identify an efficient and rational sequence of interventions to improve food security in response to climate threats.
Gender, Resilience, and Food Systems
Authors: Bryan Elizabeth , Ringler Claudia , Meinzen-Dick Ruth
Published: March 2023

Research on the gender dimensions of resilience highlights differences in the ways that men and women experience disturbances, their resilience capacities, and their preferred responses. This chapter incorporates a food systems lens into a gender and resilience framework to identify key entry points to strengthen women’s and men’s food security and nutrition in the face of multiple, reoccurring shocks and stressors. Drawing on systematic reviews and case studies from the literature, this chapter finds that exposure and sensitivity to disturbances depend largely on gendered roles in food systems, including along agricultural value chains, and the food environments in which men and women live. Increasing women’s resilience capacities—which tend to be lower than men’s—through investments in education, information and financial services, employment opportunities, and women’s agency, can improve food security and nutrition outcomes and increase their contribution to food system resilience. Considering gender differences in needs and preferences in policy and intervention design is, therefore, essential to ensure that investments reach, benefit, and empower women as agents of change for greater resilience.
COVID-19, Household Resilience, and Rural Food Systems: Evidence from Southern and Eastern Africa
Authors: Upton Joanna , Tennant Elizabeth , Fiorella Kathryn J. , Barrett Christopher B.
Published: March 2023

Resilience offers a useful lens for studying how human well-being and agri-food systems absorb and recover from a range of shocks and stressors, including the COVID-19 pandemic. Looking beyond the direct effects of observable shocks to the mechanisms that shape their impacts can guide our understanding of COVID-19 and leverage findings from the pandemic to better understand resilience to future shocks. We develop a conceptual framework for the multiple paths through which observed shocks interact with systemic mechanisms to influence resilience. We illustrate this framework with reference to the pandemic and policy responses as they unfolded in three rural areas in Malawi, Madagascar, and Kenya. Consistent with this framework, we find multiple pathways through which the pandemic affected household food security and resilience. Our findings highlight that, in some settings, the direct effects—in this case severe illness and mortality from SARS-CoV-2—may impact fewer people than the indirect impacts that arise as behaviors, markets, and policies adjust. We illustrate that although COVID-19 is a new shock, its massive, broad-reaching impacts manifest through familiar stressors and uncertainties that frequently burden poor rural populations in much of the low- and middle-income world.
Do You Behave Always the Same?
Authors: Di Federico Gemma , Burattin Andrea
Published: March 2023

Human behavior could be represented in the form of a process. Existing process modeling notations, however, are not able to faithfully represent these very flexible and unstructured processes. Additional non-process aware perspectives should be considered in the representation. Control-flow and data dimensions should be combined to build a robust model which can be used for analysis purposes. The work in this paper proposes a new hybrid model in which these dimensions are combined. An enriched conformance checking approach is described, based on the alignment of imperative and declarative process models, which also supports data dimensions from a statistical viewpoint.
BERMUDA: Participatory Mapping of Domain Activities to Event Data via System Interfaces
Authors: Cosma Vlad P. , Hildebrandt Thomas T. , Gyldenkærne Christopher H. , Slaats Tijs
Published: March 2023

We present a method and prototype tool supporting participatory mapping of domain activities to event data recorded in information systems via the system interfaces. The aim is to facilitate responsible secondary use of event data recorded in information systems, such as process mining and the construction of predictive AI models. Another identified possible benefit is the support for increasing the quality of data by using the mapping to support educating new users in how to register data, thereby increasing the consistency in how domain activities are recorded. We illustrate the method on two cases, one from a job center in a danish municipality and another from a danish hospital using the healthcare platform from Epic.
Predicting Activities of Interest in the Remainder of Customer Journeys Under Online Settings
Authors: Wolters Lisan , Hassani Marwan
Published: March 2023

Customer journey analysis is important for organizations to get to know as much as possible about the main behavior of their customers. This provides the basis to improve the customer experience within their organization. This paper addresses the problem of predicting the occurrence of a certain activity of interest in the remainder of the customer journey that follows the occurrence of another specific activity. For this, we propose the HIAP framework which uses process mining techniques to analyze customer journeys. Different prediction models are researched to investigate which model is most suitable for high importance activity prediction. Furthermore the effect of using a sliding window or landmark model for (re)training a model is investigated. The framework is evaluated using a health insurance real dataset and a benchmark data set. The efficiency and prediction quality results highlight the usefulness of the framework under various realistic online business settings.
On the Potential of Textual Data for Explainable Predictive Process Monitoring
Authors: Warmuth Christian , Leopold Henrik
Published: March 2023

Predictive process monitoring techniques leverage machine learning (ML) to predict future characteristics of a case, such as the process outcome or the remaining run time. Available techniques employ various models and different types of input data to produce accurate predictions. However, from a practical perspective, explainability is another important requirement besides accuracy since predictive process monitoring techniques frequently support decision-making in critical domains. Techniques from the area of explainable artificial intelligence (XAI) aim to provide this capability and create transparency and interpretability for black-box ML models. While several explainable predictive process monitoring techniques exist, none of them leverages textual data. This is surprising since textual data can provide a rich context to a process that numerical features cannot capture. Recognizing this, we use this paper to investigate how the combination of textual and non-textual data can be used for explainable predictive process monitoring and analyze how the incorporation of textual data affects both the predictions and the explainability. Our experiments show that using textual data requires more computation time but can lead to a notable improvement in prediction quality with comparable results for explainability.
Attribute-Based Conformance Diagnosis: Correlating Trace Attributes with Process Conformance
Authors: Grohs Michael , Rehse Jana-Rebecca
Published: March 2023

An important practical capability of conformance checking is that organizations can use it to alleviate potential deviations from the intended process behavior. However, existing techniques only identify these deviations, but do not provide insights on potential explanations, which could help to improve the process. In this paper, we present attribute-based conformance diagnosis (ABCD), a novel approach for correlating process conformance with trace attributes. ABCD builds on existing conformance checking techniques and uses machine learning techniques to find trace attribute values that potentially impact the process conformance. It creates a regression tree to identify those attribute combinations that correlate with higher or lower trace fitness. We evaluate the explanatory power, computational efficiency, and generated insights of ABCD based on publicly available event logs. The evaluation shows that ABCD can find correlations of trace attribute combinations with higher or lower fitness in a sufficiently efficient way, although computation time increases for larger log sizes.
Detecting Surprising Situations in Event Data
Authors: Kohlschmidt Christian , Qafari Mahnaz Sadat , van der Aalst Wil M. P.
Published: March 2023

Process mining is a set of techniques that are used by organizations to understand and improve their operational processes. The first essential step in designing any process reengineering procedure is to find process improvement opportunities. In existing work, it is usually assumed that the set of problematic process instances in which an undesirable outcome occurs is known prior or is easily detectable. So the process enhancement procedure involves finding the root causes and the treatments for the problem in those process instances. For example, the set of problematic instances is considered as those with outlier values or with values smaller/bigger than a given threshold in one of the process features. However, on various occasions, using this approach, many process enhancement opportunities, not captured by these problematic process instances, are missed. To overcome this issue, we formulate finding the process enhancement areas as a context-sensitive anomaly/outlier detection problem. We define a process enhancement area as a set of situations (process instances or prefixes of process instances) where the process performance is surprising. We aim to characterize those situations where process performance is significantly different from what was expected considering its performance in similar situations. To evaluate the validity and relevance of the proposed approach, we have implemented and evaluated it on a real-life event log.
Weighted Violations in Alignment-Based Conformance Checking
Authors: Grüger Joscha , Geyer Tobias , Kuhn Martin , Braun Stephan A. , Bergmann Ralph
Published: March 2023

Conformance checking is a process mining technique that allows verifying the conformance of process instances to a given model. Many conformance checking algorithms provide quantitative information about the conformance of a process instance through metrics such as fitness. Fitness measures to what degree the model allows the behavior observed in the event log. Conventional fitness does not consider the individual severity of deviations. In cases where there are rules that are more important to comply with than others, fitness consequently does not take all factors into account. In the field of medicine, for example, there are guideline recommendations for clinical treatment that have information about their importance and soundness, making it essential to distinguish between them. Therefore, we introduce an alignment-based conformance checking approach that considers the importance of individual specifications and weights violations. The approach is evaluated with real patient data and evidence-based guideline recommendations. Using this approach, it was possible to integrate guideline recommendation metadata into the conformance checking process and to weight violations individually.
Event Log Generation in MIMIC-IV Research Paper
Authors: Cremerius Jonas , Pufahl Luise , Klessascheck Finn , Weske Mathias
Published: March 2023

Public event logs are valuable for process mining research to evaluate process mining artifacts and identify new and promising research directions. Initiatives like the BPI Challenges have provided a series of real-world event logs, including healthcare processes, and have significantly stimulated process mining research. However, the healthcare related logs provide only excerpts of patient visits in hospitals. The Medical Information Mart for Intensive Care (MIMIC)-IV database is a public available relational database that includes data on patient treatment in a tertiary academic medical center in Boston, USA. It provides complex care processes in a hospital from end-to-end. To facilitate the use of MIMIC-IV in process mining and to increase the reproducibility of research with MIMIC, this paper provides a framework consisting of a method, an event hierarchy, and a log extraction tool for extracting useful event logs from the MIMIC-IV database. We demonstrate the framework on a heart failure treatment process, show how logs on different abstraction levels can be generated, and provide configuration files to generate event logs of previous process mining works with MIMIC.
SAMPLE: A Semantic Approach for Multi-perspective Event Log Generation
Authors: Grüger Joscha , Geyer Tobias , Jilg David , Bergmann Ralph
Published: March 2023

Data and process mining techniques can be applied in many areas to gain valuable insights. For many reasons, accessibility to real-world business and medical data is severely limited. However, research, but especially the development of new methods, depends on a sufficient basis of realistic data. Due to the lack of data, this progress is hindered. This applies in particular to domains that use personal data, such as healthcare. With adequate quality, synthetic data can be a solution to this problem. In the procedural field, some approaches have already been presented that generate synthetic data based on a process model. However, only a few have included the data perspective so far. Data semantics, which is crucial for the quality of the generated data, has not yet been considered. Therefore, in this paper we present the multi-perspective event log generation approach SAMPLE that considers the data perspective and, in particular, its semantics. The evaluation of the approach is based on a process model for the treatment of malignant melanoma. As a result, we were able to integrate the semantic of data into the log generation process and identify new challenges.
Discovering Break Behaviours in Process Mining: An Application to Discover Treatment Pathways in ICU of Patients with Acute Coronary Syndrome
Authors: Chen Qifan , Lu Yang , Tam Charmaine S. , Poon Simon K.
Published: March 2023

The inductive miner (IM) can guarantee to return structured process models, but the process behaviours that process trees can represent are limited. Loops in process trees can only be exited after the execution of the “body” part. However, in some cases, it is possible to break a loop structure in the “redo” part. This paper proposes an extension to the process tree notation and the IM to discover and represent break behaviours. We present a case study using a healthcare event log to explore Acute Coronary Syndrome (ACS) patients’ treatment pathways, especially discharge behaviours from ICU, to demonstrate the usability of the proposed approach in real-life. We find that treatment pathways in ICU are routine behaviour, while discharges from ICU are break behaviours. The results show that we can successfully discover break behaviours and obtain the structured and understandable process model with satisfactory fitness, precision and simplicity.
Multi-perspective Identification of Event Groups for Event Abstraction
Authors: Rebmann Adrian , Pfeiffer Peter , Fettke Peter , Aa Han van der
Published: March 2023

In process mining settings, events are often recorded on a low level and cannot be used for meaningful analysis directly. Moreover, the resulting variability in the recorded event sequences leads to complex process models that provide limited insights. To overcome these issues, event abstraction techniques pre-process the event sequences by grouping the recorded low-level events into higher-level activities. However, existing abstraction techniques require elaborate input about high-level activities upfront to achieve acceptable abstraction results. This input is often not available or needs to be constructed, which requires considerable manual effort and domain knowledge. We overcome this by proposing an approach that suggests groups of low-level events for event abstraction. It does not require the user to provide elaborate input upfront, but still allows them to inspect and select groups of events that are related based on their common multi-perspective contexts. To achieve this, our approach learns representations of events that capture their context and automatically identifies and suggests interesting groups of related events. The user can inspect group descriptions and select meaningful groups to abstract the low-level event log.
Deriving Event Logs from Legacy Software Systems
Authors: Breitmayer Marius , Arnold Lisa , Rocca Stephan La , Reichert Manfred
Published: March 2023

The modernization of legacy software systems is one of the key challenges in software industry, which requires comprehensive system analysis. In this context, process mining has proven to be useful for understanding the (business) processes implemented by the legacy software system. However, process mining algorithms are highly dependent on both the quality and existence of suitable event logs. In many scenarios, existing software systems (e.g., legacy applications) do not leverage process engines capable of producing such high-quality event logs, which hampers the application of process mining algorithms. Deriving suitable event log data from legacy software systems, therefore, constitutes a relevant task that fosters data-driven analysis approaches, including process mining, data-based process documentation, and process-centric software migration. This paper presents an approach for deriving event logs from legacy software systems by combining knowledge from source code and corresponding database operations. The goal is to identify relevant business objects as well as to document user and software interactions with them in an event log suitable for process mining.
SAP Signavio Academic Models: A Large Process Model Dataset
Authors: Sola Diana , Warmuth Christian , Schäfer Bernhard , Badakhshan Peyman , Rehse Jana-Rebecca , Kampik Timotheus
Published: March 2023

In this paper, we introduce the SAP Signavio Academic Models (SAP-SAM) dataset, a collection of hundreds of thousands of business models, mainly process models in BPMN notation. The model collection is a subset of the models that were created over the course of roughly a decade on academic.signavio.com, a free-of-charge software-as-a-service platform that researchers, teachers, and students can use to create business (process) models. We provide a preliminary analysis of the model collection, as well as recommendations on how to work with it. In addition, we discuss potential use cases and limitations of the model collection from academic and industry perspectives.
A Virtual Knowledge Graph Based Approach for Object-Centric Event Logs Extraction
Authors: Xiong Jing , Xiao Guohui , Kalayci Tahir Emre , Montali Marco , Gu Zhenzhen , Calvanese Diego
Published: March 2023

Process mining is a family of techniques that support the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream () is the most widely adopted. In , each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion and one event may refer to multiple objects. In particular, the Object-Centric Event Logs () standard has been proposed recently. However, the crucial problem of extracting logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph () approach to access data in relational databases. We have implemented this approach in the system, extending it to support both and standards. We have carried out an experiment with over the Dolibarr system. The evaluation results confirm that can effectively extract logs and the performance is scalable.
Monitoring Constraints in Business Processes Using Object-Centric Constraint Graphs
Authors: Park Gyunam , van der Aalst Wil M. P.
Published: March 2023

Constraint monitoring aims to monitor the violation of constraints in business processes, e.g., an invoice should be cleared within 48 h after the corresponding goods receipt, by analyzing event data. Existing techniques for constraint monitoring assume that a single case notion exists in a business process, e.g., a patient in a healthcare process, and each event is associated with the case notion. However, in reality, business processes are object-centric, i.e., multiple case notions (objects) exist, and an event may be associated with multiple objects. For instance, an Order-To-Cash (O2C) process involves order, item, delivery, etc., and they interact when executing an event, e.g., packing multiple items together for a delivery. The existing techniques produce misleading insights when applied to such object-centric business processes. In this work, we propose an approach to monitoring constraints in object-centric business processes. To this end, we introduce Object-Centric Constraint Graphs (OCCGs) to represent constraints that consider the interaction of objects. Next, we evaluate the constraints represented by OCCGs by analyzing Object-Centric Event Logs (OCELs) that store the interaction of different objects in events. We have implemented a web application to support the proposed approach and conducted two case studies using a real-life SAP ERP system.
Identifying the Steps in an Exploratory Data Analysis: A Process-Oriented Approach
Authors: Daele Seppe Van , Janssenswillen Gert
Published: March 2023

Best practices in (teaching) data literacy, specifically Exploratory Data Analysis, remain an area of tacit knowledge until this day. However, with the increase in the amount of data and its importance in organisations, analysing data is becoming a much-needed skill in today’s society. Within this paper, we describe an empirical experiment that was used to examine the steps taken during an exploratory data analysis, and the order in which these actions were taken. Twenty actions were identified. Participants followed a rather iterative process of working step by step towards the solution. In terms of the practices of novice and advanced data analysts, few relevant differences were yet discovered.
Discovering Students’ Learning Strategies in a Visual Programming MOOC Through Process Mining Techniques
Authors: Rohani Narjes , Gal Kobi , Gallagher Michael , Manataki Areti
Published: March 2023

Understanding students’ learning patterns is key for supporting their learning experience and improving course design. However, this is particularly challenging in courses with large cohorts, which might contain diverse students that exhibit a wide range of behaviours. In this study, we employed a previously developed method, which considers process flow, sequence, and frequency of learning actions, for detecting students’ learning tactics and strategies. With the aim of demonstrating its applicability to a new learning context, we applied the method to a large-scale online visual programming course. Four low-level learning tactics were identified, ranging from project- and video-focused to explorative. Our results also indicate that some students employed all four tactics, some used course assessments to strategize about how to study, while others selected only two or three of all learning tactics. This research demonstrates the applicability and usefulness of process mining for discovering meaningful and distinguishable learning strategies in large courses with thousands of learners.
A Survey on the Application of Process Mining to Smart Spaces Data
Authors: Bertrand Yannis , Van den Abbeele Bram , Veneruso Silvestro , Leotta Francesco , Mecella Massimo , Serral Estefanía
Published: March 2023

During the last years, a number of studies have experimented with applying process mining (PM) techniques to smart spaces data. The general goal has been to automatically model human routines as if they were business processes. However, applying process-oriented techniques to smart spaces data comes with its own set of challenges. This paper surveys existing approaches that apply PM to smart spaces and analyses how they deal with the following challenges identified in the literature: choosing a modelling formalism for human behaviour; bridging the abstraction gap between sensor and event logs; and segmenting logs in traces. The added value of this article lies in providing the research community with a common ground for some important challenges that exist in this field and their respective solutions, and to assist further research efforts by outlining opportunities for future work.
Building User Journey Games from Multi-party Event Logs
Authors: Kobialka Paul , Mannhardt Felix , Tapia Tarifa Silvia Lizeth , Johnsen Einar Broch
Published: March 2023

To improve the user experience, service providers may systematically record and analyse user interactions with a service using event logs. User journeys model these interactions from the user’s perspective. They can be understood as event logs created by two independent parties, the user and the service provider, both controlling their share of actions. We propose multi-party event logs as an extension of event logs with information on the parties, allowing user journeys to be analysed as weighted games between two players. To reduce the size of games for complex user journeys, we identify decision boundaries at which the outcome of the game is determined. Decision boundaries identify subgames that are equivalent to the full game with respect to the final outcome of user journeys. The decision boundary analysis from multi-party event logs has been implemented and evaluated on the BPI Challenge 2017 event log with promising results, and can be connected to existing process mining pipelines.
Discrimination-Aware Process Mining: A Discussion
Authors: Pohl Timo , Qafari Mahnaz Sadat , van der Aalst Wil M. P.
Published: March 2023

Organizations increasingly use process mining techniques to gain insight into their processes. Process mining techniques can be used to monitor and/or enhance processes. However, the impact of processes on the people involved, in terms of unfair discrimination, has not been studied. Another neglected area is the impact of applying process mining techniques on the fairness of processes. In this paper, we overview and categorize the existing fairness concepts in machine learning. Moreover, we summarize the areas where fairness is relevant to process mining and provide an approach to applying existing fairness definitions in process mining. Finally, we present some of the fairness-related challenges in processes.
Electric-field driven nonequilibrium phase transitions in AdS/CFT
Authors: Endo Daisuke , Fukazawa Yuichi , Matsumoto Masataka , Nakamura Shin
Published: March 2023

Abstract

We study phase transitions and critical phenomena in nonequilibrium steady states controlled by an electric field. We employ the D3/D7 model in the presence of a charge density and electric field at finite temperatures. The system undergoes the first-order and the second-order phase transitions under the variation of the electric field in the presence of dissipation. We numerically find that the critical exponents which we define for the nonequilibrium phase transition in this model take the mean-field values.
Decoherence and thermalization of Unruh-DeWitt detector in arbitrary dimensions
Authors: Xu Hao
Published: March 2023

Abstract

We study the decoherence and thermalization of an Unruh-DeWitt detector linearly coupled to the free massless scalar field in flat spacetime with arbitrary dimensions d ≥ 2. The initial state of the detector is chosen to be a pure state consisting of a linear superposition of ground and excited states, and we calculate the time evolution of reduced density matrix of the detector. Using perturbation method, we analytically derive the transition rate of the detector (the rate of change of the diagonal elements in the density matrix) and the decoherence rate (the rate of change of the off-diagonal elements in the density matrix). We find that the results are not the same in odd and even dimensional spacetimes, but the unitarity of the qubit is preserved in both cases. The real part of the decoherence rate is related to the transition rate, while the imaginary part may contain different forms of divergence terms in different dimensions due to the temporal order product operator and the singularities of the Wightman function for quantum field theory. We derive the recurrence formula to obtain the divergence terms in each dimension and analyze the renormalization problem.
Medium-induced radiation with vacuum propagation in the pre-hydrodynamics phase
Authors: Andres Carlota , Apolinário Liliana , Dominguez Fabio , Martinez Marcos Gonzalez , Salgado Carlos A.
Published: March 2023

Abstract

The recent discovery of the potential of jet quenching observables to constrain the initial stages after a heavy-ion collision makes imperative to have a better understanding of the process of medium-induced radiation before the formation of the quark-gluon plasma (QGP) and its impact on observables at high-pT. In this work, we generalize the BDMPS-Z framework for medium-induced radiation to account for additional emissions occurring before the creation of the QGP. For simplicity, we assume that during the pre-hydrodynamics phase the hard parton propagates as in vacuum. This set-up, allows us to isolate the contribution from the additional initial radiation by comparing with the usual scenarios in which the emitter is created inside the medium but with different starting points. Using both a numerical implementation of the fully resummed emission spectrum and the usual analytical approximations, we find that replacing an initial slab of the medium by vacuum yields to a significant reduction of the emission spectrum for low radiated gluon energies, while the high-energy tails remain largely unmodified. Finally, we assess the effect of replacing the initial medium by vacuum propagation on the single-inclusive particle suppression RAA and high-pT azimuthal asymmetry v2. Our findings indicate that considering vacuum propagation prior to hydrodynamization leads to an increase in the v2, thus corroborating the importance of the treatment of jet quenching in the initial stages for the correct description of both observables.
On pentagon identity in Ding-Iohara-Miki algebra
Authors: Zenkevich Yegor
Published: March 2023

Abstract

We notice that the famous pentagon identity for quantum dilogarithm functions and the five-term relation for certain operators related to Macdonald polynomials discovered by Garsia and Mellit can both be understood as specific cases of a general “master pentagon identity” for group-like elements in the Ding-Iohara-Miki (or quantum toroidal, or elliptic Hall) algebra. We prove this curious identity and discuss its implications.
Non-audible acoustic emission characterization of Reticulitermes termites in pine wood
Authors: Suarez Elisabet , Fuentes Yaiza , Gaju-Ricart Miquel , Gallego Antolino
Published: March 2023

This research evaluates and characterizes the acoustic emission activity generated by Reticulitermes termites as recorded by piezoelectric sensors with sensitivity in the ultrasound range (greater than 20 kHz). To this end, the acoustic emission activity was recorded under controlled conditions of temperature and moisture content in three pine wood samples in which termites were artificially inoculated: only soldiers, only workers, or a colony of workers and soldiers. Different traditional parameters of the acoustic emission signals were analyzed, in both the time and frequency domains. This study proved feasible to use acoustic emission to detect the activity of this kind of termites, although it was not possible to distinguish between workers and soldiers. It is also demonstrated that, by using several sensors, one can locate the activity of the insects, a finding of great practical interest for the accurate detection of colonies in real buildings.
Diabetes and climate change: current evidence and implications for people with diabetes, clinicians and policy stakeholders
Authors: Ratter-Rieck Jacqueline M. , Roden Michael , Herder Christian
Published: March 2023

Climate change will be a major challenge for the world’s health systems in the coming decades. Elevated temperatures and increasing frequencies of heat waves, wildfires, heavy precipitation and other weather extremes can affect health in many ways, especially if chronic diseases are already present. Impaired responses to heat stress, including compromised vasodilation and sweating, diabetes-related comorbidities, insulin resistance and chronic low-grade inflammation make people with diabetes particularly vulnerable to environmental risk factors, such as extreme weather events and air pollution. Additionally, multiple pathogens show an increased rate of transmission under conditions of climate change and people with diabetes have an altered immune system, which increases the risk for a worse course of infectious diseases. In this review, we summarise recent studies on the impact of climate-change-associated risk for people with diabetes and discuss which individuals may be specifically prone to these risk conditions due to their clinical features. Knowledge of such high-risk groups will help to develop and implement tailored prevention and management strategies to mitigate the detrimental effect of climate change on the health of people with diabetes.

Graphical abstract