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Position Paper - Hybrid Artificial Intelligence for Realizing a Leadership Assistant for Platform-Based Leadership Consulting 1

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35th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Grivas, Stella Gatziu Imhof, Denis Gachnang, Phillip Univ Appl Sci & Arts Northwestern Switzerland FHN Olten Switzerland

ISBN: (数字)9783031349850

ISBN: (纸本)9783031349843;9783031349850

Digital technologies enable new forms of value creation, value proposition, and value capturing for all kinds of organizations in all kinds of industries. Often, companies strive to digital transform and obtain consultancy services due to missing expert knowledge on how to approach the transformation. Interestingly, research shows that the consulting industry itself shows a high potential for a digital transformation, but platform-based consulting models and self-service consulting models are still underdeveloped. With this position paper, the authors propose an own approach on how to integrate human expert knowledge and machine learning in a novel hybrid artificial intelligence and platform-based consulting model, which not only offers the potential to transform the consultancy industry but also supports organizations in their transformation efforts. The authors take the area of digital leadership consulting to illustrate this.

关键词： Digital Leadership Consulting 4.0 Hybrid Artificial Intelligence Enterprise Modelling Intelligent information Systems

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Designing an API for the Provision of Public Service information Based on CPSV-AP 19th

Designing an API for the Provision of Public Service Informa...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Pappis, Christos Zeginis, Dimitris Tambouris, Efthimios Tarabanis, Konstantinos Hellen Open Univ Patras Greece Ctr Res & Technol Hellas 6th Km Charilaou Thermi Rd Thessaloniki Greece Univ Macedonia Egnatia 156 Thessaloniki 54636 Greece

ISBN: (纸本)9783031306938;9783031306945

The provision of public services (PS) is at the heart of public authority operations as it directly affects citizens' lives and the prosperity of society. Part of PS provision is publishing PS descriptions in online catalogues to inform citizens and promote transparency. The European Union has developed the Core Public Service Vocabulary Application Profile (CPSV-AP) as a PS data model to facilitate PS catalogue creation and promote semantic interoperability. The use of CPSV-AP is increasing within the European Union leading to a number of relevant PS descriptions that are also potentially beneficial for the implementation of the Single Digital Gateway (SDG) regulation. However, the use of heterogeneous, some times not very popular technologies (e.g. RDF) to provide access to such data hinders their further uniform exploitation. Towards this problem definition, Application Programming Interfaces (APIs) can provide a uniform, easily-consumable way of serving such data hiding any heterogeneity of the underlying technologies. The aim of this paper is to design and implement an API to serve data based on CPSV-AP facilitating the implementation of the SDG and the further exploitation of data at added value services and tools e.g. chatbots. The paper describes the requirements, use cases, design choices and implementation details of the API. We anticipate that the proposed API will help towards the further adoption of CPSV-AP by facilitating and homogenizing the consumption of relevant data.

关键词： eGovernment API public service CPSV-AP

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Process Mining for Analyzing Open Questions Computer-Aided Examinations

Process Mining for Analyzing Open Questions Computer-Aided E...

引用

4th International Conference on Process Mining (ICPM)

作者： Bala, Saimir Revoredo, Kate Mendling, Jan Humboldt Univ Berlin Germany

ISBN: (纸本)9783031278143;9783031278150

Computer-based education relies on information systems to support teaching and learning processes. These systems store trace data about the interaction of the learners with their different functionalities. Process mining techniques have been used to evaluate these traces and provide insights to instructors on the behavior of students. However, an analysis of students behavior on solving open-questioned examinations combined with the marks they received is still missing. This analysis can support the instructors not only on improving the design of future edition of the course, but also on improving the structure of online and physical evaluations. In this paper, we use process mining techniques to evaluate the behavioral patterns of students solving computer-based open-ended exams and their correlation with the grades. Our results show patterns of behavior associated to the marks received. We discuss how these results may support the instructor on elaborating future open question examinations.

关键词： Education Process mining Educational process mining Exam process

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Discovering Break Behaviours in Process Mining: An Application to Discover Treatment Pathways in ICU of Patients with Acute Coronary Syndrome

Discovering Break Behaviours in Process Mining: An Applicati...

引用

4th International Conference on Process Mining (ICPM)

作者： Chen, Qifan Lu, Yang Tam, Charmaine S. Poon, Simon K. Univ Sydney Sch Comp Sci Sydney NSW Australia Univ Sydney Northern Clin Sch Sydney NSW Australia

ISBN: (纸本)9783031278143;9783031278150

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.

关键词： Process mining Inductive miner Process trees Healthcare process discovery

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Digital Solutions to What? - WPR as a Model for Public Servants Seeking a Better Grip on Their Local Digitalization Policy 19th

Digital Solutions to What? - WPR as a Model for Public Serva...

引用

19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Heidlund, Marcus Gidlund, Katarina L. Mid Sweden Univ Sundsvall Sweden

ISBN: (纸本)9783031306938;9783031306945

Public-sector digitalization has gained traction over the years, andwith it has come a flood of official documents (policies and grey literature) highlighting what the (digital) future is supposed to look like and proposing a range of digital solutions to inspire action. Such policies and strategic documents propose what will be important in future societies. In this paper, we employ the policy-analysis framework, 'what's the problem represented to be' (WPR), first developed by Bacchi. We conducted aworkshop with a Swedish municipality, inviting key actors towork with the idea of digitalization to re-read their digitalization policy in light of the WPR framework. The purpose of this paper is to investigate what surfaced when the policymakers and public servants used WPR to dissect their own digitalization policy. The results show that the key actors' reflections centred around the value of the policy itself, and the WPR framework seemed to enhance their ability to reflect upon the usability of the policy and the work needed to implement and evaluate it. Furthermore, they pinpointed that the digitalization policy appeared rather naive in terms of contextual factors (lack of recontextualisation on the municipal level) and hindrances (lack of resources to tackle existing hindrances).

关键词： Digitalization e-Government policy analysis WPR

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Next Generation Process Material Tracking and Analytics for the Process Industries Using Machine Learning Algorithms 19th

Next Generation Process Material Tracking and Analytics for ...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Doe, Symon Kassianides, Christoforos Kassianides, Symeon Bakas, Nikos Christodoulou, Christos Hyper Syst Engn Ltd Athalassis Str 36 CY-2201 Nicosia Cyprus Cyprus Inst Computat Based Sci & Technol Res Ctr Konstantinou Kavafi Str 20 CY-2021 Nicosia Cyprus

ISBN: (纸本)9783031306938;9783031306945

Demand for plastics is the key driver for petrochemicals and they are predicted to account for more than a third of the growth in world oil demand by 2030. While Plastics provide substantial benefits to society their production presents detrimental environmental challenges that need immediate attention and intervention. Typical Polymer production is a combination of Continuous and Batch processes which makes high level traceability of raw materials, products, while maintaining the quality of the end-product a big challenge. To address this, we developed HYPPOS software that is based on a mathematical material tracking algorithm that discretises the continuous manufacturing processes into identifiable slices of material and tracks them as they move through the manufacturing stages. HYPPOS continuously collects data in real time from the plant instrumentation and feeds this data to its tracking model. HYPPOS algorithm can associate any parameter with each individual slice of material and uses this to infer the quality of the material providing visibility to the operator at an early stage of the process. Many plants rely on off-line laboratory measurements for the critical quality parameters, rather than having online automated measurement instruments. To address this limitation, Machine learning (ML) algorithms were built to implement soft sensors for the quality prediction using the existing plant instrumentation. The ML algorithms were trained, validated, and tested using historic measurements from the plant using a variety of ML models, comprising Linear and Polynomial Regression (LR, PR), XGBoost (XGB) and Random Forests (RF), as well as Artificial Neural Networks (ANNs). The errors of the predictions have thoroughly been analysed, to identify specific patterns such as heteroscedasticity and bias in the residual errors. Finally, the importance of each feature to the target variable has been assessed, utilizing the p-values of the linear model, XGBoost importance,

关键词： Decision Support Tool Machine Learning Petrochemicals

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Comparing Anomaly Detection and Classification Algorithms: A Case Study in Two Domains 15th

Comparing Anomaly Detection and Classification Algorithms: A...

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15th Software Quality Days Conference (SWQD)

作者： Staron, Miroslaw Herges, Helena Odenstedt Block, Linda Sjodin, Martin Univ Gothenburg Chalmers Gothenburg Sweden Sahlgrens Univ Hosp Gothenburg Sweden Ericsson AB Gothenburg Sweden

ISBN: (纸本)9783031314872;9783031314889

Utilizing large data sets in practical scenarios usually requires identifying, annotating and classifying rare events or anomalies. Although several methods exists, there are two classes of algorithms: anomaly detection algorithms and classification algorithms. Both types of algorithms have different characteristics and in this paper, we set out to compare them on two cases. We use data from a neurointensive care unit and from microwave radio transmissions. We apply Isolation Forest and Random Forest algorithms to find events in the data that occur with a frequency of ca. 1%. The results show that classification algorithms (Random Forest) perform better and can achieve up to 100% accuracy, while the anomaly detection algorithms (Isolation Forest) can achieve only 73% at best. Based on the results, we conclude that it is better to invest in annotating data a priori and use classification algorithms, despite the lower costs of using the anomaly detection algorithms.

关键词： Machine learning neuro-intensive care telecommunication

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Applying a Genetic Algorithm for Test Suite Reduction in Industry 15th

Applying a Genetic Algorithm for Test Suite Reduction in Ind...

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15th Software Quality Days Conference (SWQD)

作者： Stadler, Philipp Ploesch, Reinhold Ramler, Rudolf Johannes Kepler Univ Linz Linz Austria Software Competence Ctr Hagenberg GmbH SCCH Hagenberg Austria

ISBN: (纸本)9783031314872;9783031314889

Time and cost of test execution increases when regression test suites grow over time. Techniques for test suite reduction have been proposed to streamline frequent test execution in continuous integration and to optimize the set of tests without sacrificing coverage and fault detection. In this paper we report on the design of a genetic algorithm to tackle the underlying optimization problem in context of an industry project from a software company developing tools for test automation. The prototypical implementation of the algorithm has been applied to the project's test suite containing several hundred test cases. We achieved an optimal solution with a 28% reduction of test cases. The evaluation of the reduced test suite using higher-level coverage and mutation analyses showed a minimal loss of coverage. The results demonstrated that the genetic algorithm can be successfully applied in industry and the achieved results are able to satisfy the requirements of the studied project. Nevertheless, major challenges have been identified by applying the approach in industry. They are related to the reliable collection of test execution data from previous test runs and dealing with test suites containing tests exhibiting unpredictable side-effects and flakiness.

关键词： software testing test suite optimization test suite minimisation genetic algorithm

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Principles of Universal Conceptual Modeling 24th

Principles of Universal Conceptual Modeling

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24th International Working Conference on business Process Modeling, Development, and Support (BPMDS) / 28th International Working Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD)

作者： Lukyanenko, Roman Parsons, Jeffrey Storey, Veda C. Samuel, Binny M. Pastor, Oscar Univ Virginia Charlottesville VA 22903 USA Mem Univ Newfoundland St John NL A1B 3X5 Canada Georgia State Univ Atlanta GA 30302 USA Univ Cincinnati Cincinnati OH 45040 USA Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9783031342400;9783031342417

The paper proposes a new frontier for conceptual modeling - universal conceptual modeling (UCM) - defined as conceptual modeling that is general-purpose and accessible to anyone. For the purposes of the discussion, we envision a non-existent, hypothetical universal conceptual modeling language, which we call Datish (as in English or Spanish for data). We focus on the need for a universal conceptual data model to explain the expected benefits of UCM. Datish can facilitate the design of many different applications, including relational databases, NoSQL databases, data lakes, and artificial intelligence systems, and enable use by a broad range of users. To pave the way for rigorous development of such a language, we provide a theoretical basis for Datish in the form of a set of universal conceptual modeling principles: flexibility, accessibility, ubiquity, minimalism, primitivism, and modularity. We apply these principles to illustrate their usefulness and to identify future research opportunities.

关键词： Universal Conceptual Modeling Conceptual Modeling Conceptual Modeling Foundations Universal Data Modeling Language Datish

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Concept for an Open Data Ecosystem to Build a Powerful Data Environment 19th

Concept for an Open Data Ecosystem to Build a Powerful Data ...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Hrustek, Larisa Mekovec, Renata Alexopolus, Charalampos Univ Zagreb Fac Org & Informat Pavlinska 2 Varazhdin Croatia Univ Aegean Dept Informat & Commun Syst Engn Karlovassi 83200 Samos Greece

ISBN: (纸本)9783031306938;9783031306945

Today, data is seen as the starting point for change and innovation in business and management processes. Since the goal of an open data ecosystem is for stakeholders to actively create and use data, their needs must be clearly identified and defined. An analysis of the ecosystem's key elements, characteristics, and modes of operation is required to create an environment that efficiently harnesses the full potential in the creation, use, and reuse of data. This paper proposes an approach for developing a conceptual model of the open data ecosystem in a given environment based on the identified key elements and their characteristics. The following key elements of the open data ecosystem are: Stakeholders, Data, Infrastructure, and Policy/Governance. The identified elements require detailed engagement and elaboration within the open data ecosystem. By clearly identifying these elements, a strong and resilient open data ecosystem can be analyzed and built in any industry such as agriculture, transport, education, law, finance and other potential field or specific field in the public sector, contributing to long-term growth and development.

关键词： Ecosystem Approach Open Data Ecosystem Elements Open Data

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