Advances in Conceptual Modeling

ER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings

AvMotoshi Saeki,Leah Wong

Häftad, Engelska, 2024

Del 14932 i serien Lecture Notes in Computer Science

820 kr

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Beskrivning

This book constitutes the refereed proceedings of the workshops held at the 43rd International Conference on Conceptual Modeling, ER 2024, which took place in Pittsburgh, PA, USA, during October 28-31, 2024. The 22 full papers and 1 short paper included in this book were carefully reviewed and selected from 52 submissions. They stem from the following workshops: AISA’2024 - The First International Workshop on AI Services and ApplicationsCMLS2024 - The 5th International Workshop on Conceptual Modeling for Life SciencesEmpER'24 -7th International Workshop on Empirical Methods in Conceptual ModelingQUAMES 2024 - 5th International Workshop on Quality and Measurement of Model-Driven Software DevelopmentJUSMOD24 - 3rd International Workshop on Digital JUStice, Digital Law and Conceptual MODelingLLM4Modeling - 2nd Workshop on Modeling in the Age of Large Language Models

Produktinformation

Utgivningsdatum:2024-10-30
Mått:155 x 235 x 22 mm
Vikt:604 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:378
Förlag:Springer International Publishing AG
ISBN:9783031755989

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Innehållsförteckning

AISA.- The First International Workshop on AI Services and Applications.- Empirical case study of AI Service and Application for people with disabilities.- A Methodological Framework for Designing Human Centered Artificial Intelligence Services.- Beyond One Fits All A Case Study Approach to AI System Design Methods.- GRASPER Leveraging Knowledge Graphs for Predictive Supply Chain Analytics.- An MLOps Framework to Data Driven Modelling of Digital Twins with an Application to Virtual Test Rigs.- Empirical Study on the Use of Artificial General Intelligence Healthcare in the Elderly.- Effects of Perceived Ease of Use and Perceived Usefulness of Technology Acceptance Model on Intention to Continue Using Generative AI Focusing on the Mediating Effect of Satisfaction and Moderating Effect of Innovation Resistance.- Conceptual Modeling for Public AI Systems.- Self-Explanatory Retrieval Augmented Generation for SDG Evidence Identification.- CMLS.- International Workshop on Conceptual Modeling for Life Sciences CMLS.- On the Expressiveness of Petri Nets for Modeling Biological Processes the Case for mRNA Translation and Protein Synthesis.- Enhancing Vaxign DL for Vaccine Candidate Prediction with added ESM Generated Features.- Conceptual Modeling for Polygenic Risk Score Research Improving Domain Understanding and Clinical Utility.- Integrative Ontology of Bipolar Disorder OBD Advancing Bipolar Disorder Research through an Interoperable Ontological Framework.- EmpER.- 7th International Workshop on Empirical Methods in Conceptual Modeling EmpER’24.- How Does UML Look and Sound Using AI to Interpret UML Diagrams through Multimodal Evidence.- Can Large Language Models Learn Conceptual Modeling by Looking at Slide Decks and Pass Graduate Examinations An Empirical Study.- Evaluating a Framework of Conceptual Modelling Research.- Extending Goal Models with Execution Orders An Investigation of the Impact on Comprehensibility.- QUAMES.- 5th International Workshop on Quality and Measurement of Model-Driven Software Development QUAMES 2024.- Towards leveraging gamified code testing for effective model validation.- JUSMOD.- 3rd International Workshop on Digital JUStice digital law and conceptual MODeling JUSMOD24.- Resignifying Compliance between Ontologies and Epistemologies of Law.- Modelling Legal Enforcement with UFOL a Case from Swedish Healthcare.- The eu FAIRnews A Preliminary Exploration of Bridging Disinformation and Digital Justice through FAIR Data Practices in Online News Sources.- Safety Assurances in Autonomous Vessels.- LLM4Modeling.- 2nd Workshop ”Modeling in the Age of Large Language Models” LLM4Modeling.- An LLM Assistant for Characterizing Conceptual Modeling Research Contributions.- AI Assisted Analytics An Automated Approach to Data Visualization.- Combining Natural Language Generation and Graph Algorithms to Explain Causal Maps through Meaningful Paragraphs.