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Extending the "Smart City" Concept to Small-to-Medium Sized Estonian Municipalities: Initiatives and Challenges Faced 19th

Extending the "Smart City" Concept to Small-to-Medium Sized ...

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

作者： Frohlich, Karin Amukugo Soe, Ralf-Martin Maoneke, Pardon Blessings Jain, Karishma Pinomaa, Antti Nieminen, Marko Aalto Univ Espoo Finland Univ Technol Tallinn Estonia Univ Mpumalanga Nelspruit Mpumalanga South Africa Lappeenranta Lahti Univ Technol Lappeenranta Finland

ISBN: (纸本)9783031306938;9783031306945

This study investigated smart city initiatives and challenges faced by small to medium sized municipalities. The literature on smart cities is dominated by findings from large cities yet, both large and small municipalities are expected to contribute towards the fulfillment of the UnitedNation's 17 sustainable development goals. A mixed method was used in which 35 municipalities were engaged. Study findings suggest that rural municipalities are yet to be fully aware of how they can harness the technology and become smart in the way they operate and serve inhabitants. Nonetheless, cities and towns seem to have an idea of what smart city initiatives to consider. Together, Estonian cities, towns and rural municipalities face several challenges in their efforts to assume "smartness" something that needs to be addressed in a pragmatic way. Municipalities face unique challenges;hence, solutions that work for one municipality may not work for another.

关键词： Digital Governance Smart City Smart Village SDGs ICTs

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Security Risk Assessment of Blockchain-Based Patient Health Record Systems 19th

Security Risk Assessment of Blockchain-Based Patient Health ...

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

作者： Al Barghuthi, Nedaa B. Said, Huwida E. Badi, Sulafa M. Girija, Shini Higher Coll Technol Sharjah U Arab Emirates Zayed Univ Dubai U Arab Emirates British Univ Dubai Dubai U Arab Emirates

ISBN: (纸本)9783031306938;9783031306945

Blockchain technology is receiving greater attention for enhancing the security of patient records systems;however, it is not a panacea, as many security risks have been found in these healthcare applications. This study conducts a state-of-the-art analysis of emerging risks in blockchain-based patient health record systems, their severity level, impact, and the corresponding countermeasures against them. In addition, we conclude our observations and indicate how blockchain security vulnerabilities may develop in the future. This study aims to promote more research on blockchain security challenges by offering researchers insights into future security and privacy developments in blockchain-based patient health record systems.

关键词： Blockchain Electronic health records (EHR) Patient health records (PHR) risks impact countermeasures privacy security

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Significance of Eco-Cement Constituents to Its Mechanical Properties, by Machine Learning Algorithms 19th

Significance of Eco-Cement Constituents to Its Mechanical Pr...

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

作者： Anastasi, Natia R. Bakas, Nikolaos P. Neapolis Univ Pafos Dept Civil Engn Sch Architecture Engn Land & Environm Sci 2 Danais Ave CY-8042 Paphos Cyprus

ISBN: (纸本)9783031306938;9783031306945

A novel proposed material for the potential replacement of cement in some of its applications was evaluated. This new material labeled Eco-Cement comprised of Biomass from the dairy and poultry industries, Urea, Cement Kiln Dust, Rice Husk Ash, Sand, and Water and was manufactured in a range of weight ratios. In this work, a comprehensive analysis of the ingredients in varying weight percentages of the novel material was manufactured and the corresponding strength and strains of the material were studied. A variety of concrete pastes using amounts of sought ratios were produced, molded into blocks, and allowed to cure under laboratory conditions. Unconfined compression tests were performed using a deformation control compressive strength machine. The strength and strains were evaluated from the initial zero load step incrementally, until the failure of each specimen. The resulting database was analyzed by utilizing Linear Regression, Random Forests, and the Gradient Boosting machine learning methods. Extensive sensitivity analysis with the machine learning algorithms, reveal certain patterns, which were established with three different methods. Furthermore, we present the analysis of the corresponding literature with Bibliometric techniques.

关键词： Cement Biomass Compressive Strength Machine Learning

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A Catalog of Source Code Metrics - A Tertiary Study 15th

A Catalog of Source Code Metrics - A Tertiary Study

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15th Software Quality Days Conference (SWQD)

作者： Iftikhar, Umar Bin Ali, Nauman Borstler, Jurgen Usman, Muhammad Blekinge Inst Technol Karlskrona Sweden

ISBN: (纸本)9783031314872;9783031314889

Context: A large number of source code metrics are reported in the literature. It is necessary to systematically collect, describe and classify source code metrics to support research and practice. Objective: We aim to utilize existing secondary studies to develop a catalog of source code metrics together with their descriptions. The catalog will also provide information about which units of code (e.g., operators, operands, lines of code, variables, parameters, code blocks, or functions) are used to measure the internal quality attributes and the scope on which they are collected. Method: We conducted a tertiary study to identify secondary studies reporting source code metrics. We have classified the source code metrics according to the measured internal quality attributes, the units of code used in the measures, and the scope at which the source code metrics are collected. Results: From 711 secondary studies, we identified 52 relevant secondary studies. We reported 423 source code metrics together with their descriptions and the internal quality attributes they measure. Source code metrics predominantly incorporate function as a unit of code to measure internal quality attributes. In contrast, several source code metrics use more than one unit of code when measuring internal quality attributes. Nearly 51% of the source code metrics are collected at the class scope, while almost 12% and 15% of source code metrics are collected at module and application levels, respectively. Conclusions: Researchers and practitioners can use the extensive catalog to assess which source code metrics meet their individual needs based on the description and classification scheme presented.

关键词： Internal quality attributes Code measurement Code quality Tertiary study Source code metrics

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A Combined Approach of Process Mining and Rule-Based AI for Study Planning and Monitoring in Higher Education

A Combined Approach of Process Mining and Rule-Based AI for ...

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4th International Conference on Process Mining (ICPM)

作者： Wagner, Miriam Helal, Hayyan Roepke, Rene Judel, Sven Doveren, Jens Goerzen, Sergej Soudmand, Pouya Lakemeyer, Gerhard Schroeder, Ulrik van der Aalst, Wil M. P. Rhein Westfal TH Aachen PADS Aachen Germany Rhein Westfal TH Aachen Knowledge Based Syst Grp Aachen Germany Rhein Westfal TH Aachen Learning Technol Res Grp Aachen Germany

ISBN: (纸本)9783031278143;9783031278150

This paper presents an approach of using methods of process mining and rule-based artificial intelligence to analyze and understand study paths of students based on campus management system data and study program models. Process mining techniques are used to characterize successful study paths, as well as to detect and visualize deviations from expected plans. These insights are combined with recommendations and requirements of the corresponding study programs extracted from examination regulations. Here, event calculus and answer set programming are used to provide models of the study programs which support planning and conformance checking while providing feedback on possible study plan violations. In its combination, process mining and rule-based artificial intelligence are used to support study planning and monitoring by deriving rules and recommendations for guiding students to more suitable study paths with higher success rates. Two applications will be implemented, one for students and one for study program designers.

关键词： Educational Process Mining Conformance checking Rule-based AI Study planning Study monitoring

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On the Potential of Textual Data for Explainable Predictive Process Monitoring

On the Potential of Textual Data for Explainable Predictive ...

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4th International Conference on Process Mining (ICPM)

作者： Warmuth, Christian Leopold, Henrik Univ Potsdam Hasso Plattner Inst Potsdam Germany SAP Signavio Berlin Germany Kuhne Logist Univ Hamburg Germany

ISBN: (纸本)9783031278143;9783031278150

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.

关键词： Predictive process monitoring Explainable Artificial Intelligence (XAI) Natural language processing Machine learning

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Aligning Object-Centric Event Logs with Data-Centric Conceptual Models 24th

Aligning Object-Centric Event Logs with Data-Centric Concept...

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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： Goossens, Alexandre Verbruggen, Charlotte Snoeck, Monique De Smedt, Johannes Vanthienen, Jan Katholieke Univ Leuven Naamsestr 69 B-3000 Leuven Belgium

ISBN: (纸本)9783031342400;9783031342417

Recently, the consideration of data aspects has seen a surge in interest both from the perspective of designing processes as from a model discovery perspective. However, it seems that both research domains (models for design and model discovery) use different conceptualisations of data/object-aware systems. In an ideal situation, when (designed) models are implemented, the resulting information systems are equipped with logging functionalities that allow the rediscovery of the models based on which the information systems were implemented. However, there is a lack of guidelines on how to set up logging. From a logging perspective, logging formats are unclear about the granularity of events: the logging may be done at the level of entire tasks or at the level of the operations on individual objects, or a single log may even contain a mix of events at different granularity levels. The lack of clarity in this matter complicates the correct interpretation of log information. The goal of this paper is therefore to investigate how the concepts of object-centric logging and those for data-aware process modelling may be better aligned. This will facilitate setting up proper logging at system implementation time, and facilitate the connection of discovered models to models-for-design. The investigation resulted in iDOCEM, a metamodel that aligns the DOCEL and the Merode meta-model. Comparing iDOCEM to different other logging meta-models demonstrates that the proposed meta-model is complete enough to capture (more than) existing logging formats.

关键词： conceptual modelling object-centric process logging rtefact-centric process modelling data-aware process modelling object-centric process discovery

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Big Data in the Innovation Process - A Bibliometric Analysis and Discussion 19th

Big Data in the Innovation Process - A Bibliometric Analysis...

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

作者： Yordanova, Zornitsa Univ Natl & World Econ Sofia Bulgaria

ISBN: (纸本)9783031306938;9783031306945

Companies are already using big data to develop innovations and improve efficiency and productivity in many business processes. The innovation process is one of the most important processes at the company level and beyond, as it impacts the company's overall performance and potential. Innovation is a data-intensive process, so the development of new technologies, especially big data, has a significant impact on innovation. The purpose of this research is to examine how big data is currently influencing the innovation process. The current scope of big data in innovation processes is defined by a literature analysis of 110 publications indexed in the Web of Science, Social Science Citation Index. This represents any article that uses both "big data" and "innovation process" in the title, abstract, and author words. In addition to state-of-the-art analysis, we identify topics that have not yet been explored to advance future research in this area and in some clusters, allowing further depth and analysis of the topic.

关键词： Innovation Process Big Data Innovation Management Technology Management Bibliometric Analysis

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Browser Extension for Detection of Fake News and Disinformation 19th

Browser Extension for Detection of Fake News and Disinformat...

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

作者： Hasimi, Lumbardha Poniszewska-Maranda, Aneta Lodz Univ Technol Inst Informat Technol Lodz Poland

ISBN: (纸本)9783031306938;9783031306945

Fake news is information usually used to mislead, manipulate or disinform while reaching a certain audience and going viral in rather a short period. Currently it started to be the bigger and bigger problem in Internet, mass media and in everyday life. The pervasive and wide-spreading effect of fake news content is becoming a serious concern of our era. Considering the emergent need for research in this area, our work aims to observe, analyse and propose a solution to the fake news topic. This work presents an Internet browser extension, aiming to notify the user regarding the credibility of the information and carrying out fake news detection. The system as an extension is designed using JavaScript environment, cloud function configured on Google Cloud platform while using Neural Network Model based on TensorFlow library for predictions process on the credibility of the content. The paper also discusses and presents approaches and models on fake news detection, and subsequently security issues on the system's functionality.

关键词： fake news detection cloud computing browser plugin prediction of text neural networks

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Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs

Clustering Analysis and Frequent Pattern Mining for Process ...

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4th International Conference on Process Mining (ICPM)

作者： Faria Junior, Elio Ribeiro Neubauer, Thais Rodrigues Fantinato, Marcelo Peres, Sarajane Marques Univ Sao Paulo BR-03828000 Sao Paulo SP Brazil Univ Contestado BR-89300000 Mafra SC Brazil

ISBN: (纸本)9783031278143;9783031278150

Object-centric event log is a format for properly organizing information from different views of a business process into an event log. The novelty in such a format is the association of events with objects, which allows different notions of cases to be analyzed. The addition of new features has brought an increase in complexity. Clustering analysis can ease this complexity by enabling the analysis to be guided by process behaviour profiles. However, identifying which features describe the singularity of each profile is a challenge. In this paper, we present an exploratory study in which we mine frequent patterns on top of clustering analysis as a mechanism for profile characterization. In our study, clustering analysis is applied in a trace clustering fashion over a vector representation for a flattened event log extracted from an object-centric event log, using a unique case notion. Then, frequent patterns are discovered in the event sublogs associated with clusters and organized according to that original object-centric event log. The results obtained in preliminary experiments show association rules reveal more evident behaviours in certain profiles. Despite the process underlying each cluster may contain the same elements (activities and transitions), the behaviour trends show the relationships between such elements are supposed to be different. The observations depicted in our analysis make room to search for subtler knowledge about the business process under scrutiny.

关键词： Object-centric event log Process mining Trace clustering Association rules

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