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检索条件"任意字段=International Conference on Data and Knowledge Systems for Manufacturing and Engineering"

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CAiSE-DC 2024 - Proceedings of the Doctoral Consortium Papers Presented at the 36th international conference on Advanced Information systems engineering

CAiSE-DC 2024 - Proceedings of the Doctoral Consortium Paper...

引用

Doctoral Consortium Papers Presented at the 36th international conference on Advanced Information systems engineering, CAiSE-DC 2024

The proceedings contain 8 papers. The topics discussed include: from adoption to endurance: exploring the dynamics of general-purpose AI adoption across time and contexts;intelligent perception systems for multi-modal data processing in industrial application contexts;a conceptual modeling-based journey into variant interpretation: from unpacking to operationalization;a methodological approach to model-driven software development for quality assurance in metaverse environments;integrating LLMs with knowledge graphs-enhanced task-oriented dialogue systems;translating polygenic risk score research to a clinical setting;comparable and repeatable information security level evaluation;and selecting adequate machine learning methods for human-computer interaction data sets: guidelines and a conceptual structure.

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Educational Applications of Big data and Learning Analytics in Personalized E-Learning 8

Educational Applications of Big Data and Learning Analytics ...

引用

8th international conference on Big data, knowledge and Control systems engineering, BdKCSE 2023

作者： Ivanova, Tatyana Terzieva, Valentina Ivanova, Malinka Technical College of Sofia Technical University of Sofia Sofia Bulgaria Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Faculty of Applied Mathematics and Informatics Technical Department of Informatics Bulgaria

ISBN: (纸本)9798350313246

There is plenty of research on the use of Big educational data, learning analytics, semantics-based knowledge modeling, and other innovative technologies within an educational environment for improving learning and tutoring. Each of these research fields is very wide and complex, and different researchers usually concentrate their work only on one or two of them and on the related subfields. The authors believe that high-quality personalized learning requires the integration of all these technologies into one intelligent educational system. Hence, the paper proposes an integrated model for combining big data learning analytics, and intelligent technologies for personalized learning and discusses the role of these technologies in achieving a more efficient learning process and interoperability between e-learning systems. © 2023 IEEE.

关键词： data mining

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Exploring the Organizational Factors Hindering the HR Analytics Adoption in manufacturing Industries 11

Exploring the Organizational Factors Hindering the HR Analyt...

引用

11th international conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Mahendran, C. Krithika, M. Saveetha School of Engineering Simats Hr Business Partner- Bonfiglioli & Research Associate Tamil Nadu Chennai India Saveetha School of Engineering Simats Chennai India

ISBN: (纸本)9798350350357

This study examines HR analytics implementation barriers in Chennai's manufacturing sector and offers solutions. A literature review of HR analytics adoption and implementation studies, demographic data, and correlation analysis between HR analytics adoption and organizational factors are included. The goal is to understand HR analytics' challenges and solutions for Chennai's manufacturing industries. This suggests HR analytics adoption rises with Organizational Factors. This suggests that HR Analytics adoption rises with organizational Factors. This shows the importance of improving organizational factors to promote HR Analytics adoption and implementation in Chennai's manufacturing industries. This study concludes that HR analytics could benefit Chennai's manufacturing sector but faces data issues, cultural barriers, skill gaps, change resistance, budget constraints, and legacy systems. Studies on manufacturing firms' HR analytics implementation challenges and successes are reviewed in the literature. The demographic profile analysis shows the surveyed population's gender, age, marital status, manufacturing experience, and HR analytics duration. Organizational Factors and HR Analytics Adoption have a significant positive correlation, emphasizing the importance of addressing them to promote HR analytics adoption. This information shows the challenges and opportunities of implementing HR analytics in Chennai's manufacturing industries and provides valuable insights for organization's looking to improve workforce management and decision-making. © 2024 IEEE.

关键词： Decision making

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Industrialization of Site Operations Planning and Management: A BIM-Based Decision Support System 20th

Industrialization of Site Operations Planning and Management...

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20th international conference on Product Lifecycle Management: Leveraging Digital Twins, Circular Economy, and knowledge Management for Sustainable Innovation (PLM)

作者： Blampain, Felix Bricogne, Matthieu Eynard, Benoit Bricogne, Celine Pinon, Sebastien Univ Technol Compiegne F-60203 Compiegne France Spie Batignolles F-92000 Nanterre France

ISBN: (纸本)9783031625800;9783031625787;9783031625770

Construction industry faces many challenges as socio-economical needs evolve and Building Information Modeling (BIM) disrupts practices. BIM processes and solutions are mainly suited for the design stage of a project and experts are currentlyworking to bridge the gap with the construction stage. Improving on BIM practices could be done by creating a more industrialized way of handling construction operations by learning from other industrial fields. This could help to manage quality, delay, and cost more precisely, while considering new indicators (e.g.: GHG emissions). BIM could be improved by developing a construction stage specific data structure inspired by Product Lifecycle Management (PLM) systems. This requires to dynamically manage data for different stakeholders before and during the operations. This paper presents a conceptual data framework to develop a BIM-based decision support system to plan and manage construction operations. A 4D digital mock-up is gradually enriched to support construction processes studies resulting in a As Planned view of the building. Process engineering work is carried through iterative loops and supported by knowledge-based indicators. A cross-disciplinary workflow allows the use of new production methods (e.g.: off-site modular construction). An As Built view of the mock-up is concurrently created as operations advance and changes occur, feeding back the knowledge-based indicators.

关键词： Building Information Modelling Product Lifecycle Management knowledge-Based engineering Enterprise Information System

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Analyzing data Professional Salaries Exploring Trends and Predictive Insights 8

Analyzing Data Professional Salaries Exploring Trends and Pr...

引用

8th international conference on Big data, knowledge and Control systems engineering, BdKCSE 2023

作者： Niknejad, Naghmeh Kianiani, Marzieh Puthiyapurayil, Nafeesath Parappurath Khan, Talha Ali University of Europe for Applied Sciences Department of Business Berlin Germany

ISBN: (纸本)9798350313246

Many university students lack clear goals at the start of their academic journey, leading to a lack of motivation and active engagement in the classroom. This often results in difficulties understanding lectures, poor exam performance, and a failure to acquire essential skills. Despite this, finding a suitable job with a decent salary after graduation, particularly in data science, poses a significant challenge for university students. To enhance the motivation of data science students, we have obtained the data Science Salaries 2023 dataset from the Kaggle website for exploring data science salaries through Exploratory data Analysis (EDA). Furthermore, this study aims to uncover hidden patterns and extract valuable insights to predict the success factors for higher salaries by applying Linear Regression, KNN Regression, and Decision Tree Regression Models. The findings of this study could assist both university students and data scientists in comprehending the factors contributing to higher salaries, thereby enriching their knowledge for future career endeavours. © 2023 IEEE.

关键词： data visualization

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OMNIMOD: Automating Ontology Modularization for Digital Library data Using CIDOC-CRM as Use Case 20

OMNIMOD: Automating Ontology Modularization for Digital Libr...

引用

20th international conference on Web Information systems and Technologies, WEBIST 2024

作者： Biagioni, Giulia New Babylon Anna van Buerenplein 41a Den Haag Netherlands

ISBN: (纸本)9789897587184

This paper introduces OMNIMOD, a new method designed to modularize ontologies, RDF-based structures that organize knowledge within specialized domains. By simplifying complex information into manageable components, OMNIMOD enhances the analysis, understandability, and navigation of large ontological frameworks while also extending its functionality to include the modularization of associated data records, known as instance data. The method has been developed based on theoretical insights gathered from Cognitive Load Theory (CLT) and has been successfully tested and applied to CIDOC-CRM (Conceptual Reference Model of the international Committee for Documentation), the ISO standard for describing data related to cultural heritage materials. The accompanying Python functions, developed for OMNIMOD and provided in the corpus of the text, empower readers to adapt and utilize OMNIMOD according to their specific needs. Copyright © 2024 by SCITEPRESS.

关键词： ISO Standards

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AiFashion: Multi-Modal and Multi-Dimensional Large Model Based on Self-Trained Customer Digital-Twin for Fashion Design and manufacturing

AiFashion: Multi-Modal and Multi-Dimensional Large Model Bas...

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2024 international conference on Automation in manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Yuan, Zhaolin Ding, Haoran Li, Ming Li, Li Huang, George Q. Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong University of Hong Kong Department of Industrial and Manufacturing Systems Engineering Hong Kong Hong Kong School of Fashion and Textiles Hong Kong Polytechnic University Hong Kong Hong Kong

ISBN: (纸本)9798350378658

This paper presents the concept design and tech-nical roadmap of a novel AI-driven fashion design and clothing manufacturing platform, called AiFashion. The vision of AiFashion is enabling every customer to wear personalized and customized clothes at low costs and with shorter waiting times. By integrating advanced information techniques such as Digital Twins, Generative AI, and Large Language Models. AiFashion can revolutionize the entire lifecycle of fashion designing and clothing manufacturing. Compared with existing AI-Assisted fashion tools, AiFashion is characterized by its self-Training nature, customization, interactivity, and lifecycle orientation in the garment industry. The first module of AiFashion, Chat Customer, effectively captures multi-modal customer profiles, including shallow body parameters and underlying preferences. The second module, Chat Tailor is a fashion designer based on Generative AI, which automatically generates the most suitable clothes satisfying multi-dimensional demands such as occasion, weather, and budget. To efficiently produce customized and highly distinctive clothing designed by Chat Tailor in clothing factories, the third module, Chat manufacturing, leverages its absorbed professional knowledge in task planning and resource scheduling by chatting with managers, supervisors, and operators in factories. This paper gives brief implementation plans for each module in AiFashion. © 2024 IEEE.

关键词： Budget control

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A detection and classification algorithm of underground cable targets using ground penetrating radar based on YOLOv5 3

A detection and classification algorithm of underground cabl...

引用

3rd international conference on Electronic Information engineering, Big data, and Computer Technology, EIBDCT 2024

作者： Wei, Yuancheng School of Electrical and Electronic Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781510680449

Ground Penetrating Radar (GPR) offers the benefits of non-destructive testing (NDT) and high efficiency, making it extensively employed for subsurface material detection. However, conventional GPR image interpretation heavily relies on researchers' experiential knowledge, which will lead to reduced detection efficiency and more recognition errors. To address these challenges, this study proposes a new technology to achieve GPR detection in high efficiency. By enhancing the network structure of YOLOv5 through incorporating attention mechanisms, data augmentation techniques, and other approaches, we aim to mitigate issues related to false detections and missed identifications during real-time GPR-based localization of directly buried underground cables. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Ground penetrating radar systems

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On improving the identification of lumped parameter systems with symmetric mass, damping and stiffness matrices 31

On improving the identification of lumped parameter systems ...

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31st international conference on Noise and Vibration engineering, ISMA 2024 and 10th international conference on Uncertainty in Structural Dynamics, USD 2024

作者： Feng, N. Hahn, E.J. Yu, M. Shandong University School of Mechanical Engineering China The University of NSW School of Mechanical and Manufacturing Engineering Australia NSW Department of Education Australia

ISBN: (纸本)9789082893175

Earlier work has shown that satisfactory identification of a six degrees of freedom (DOF) lumped parameter system represented by symmetric mass, damping and stiffness matrices and using vibration response measurements as input data, has so far proved elusive. This paper develops a modified modal analysis identification approach wherein a two-dimensional search procedure is used to help identify the system eigenvalues;and compares the accuracy of the identification of a simple two DOF obtained using this modified modal approach with the earlier one. A direct identification approach wherein one identifies the matrix elements directly without resorting to modal analysis is also included in the comparison. The modified modal approach was found to best identify the system damping while the direct approach proved to be the worst. Whether the newly introduced identification approaches can satisfactorily identify a six DOF still needs to be investigated. © 2024 Proceedings of ISMA 2024 - international conference on Noise and Vibration engineering and USD 2024 - international conference on Uncertainty in Structural Dynamics. All rights reserved.

关键词： Stiffness matrix

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1st international Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information systems, HybridAIMS, 1st Workshop on knowledge Graphs for Semantics-Driven systems engineering, KG4SDSE, Blockchain and Decentralized Governance Design for Information systems, BC4IS and DGD, associated with the 35th international conference on Advanced Information systems engineering, CAiSE 2023

1st International Workshop on Hybrid Artificial Intelligence...

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1st international Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information systems, HybridAIMS, 1st Workshop on knowledge Graphs for Semantics-Driven systems engineering, KG4SDSE, Blockchain and Decentralized Governance Design for Information systems, BC4IS and DGD, associated with the 35th international conference on Advanced Information systems engineering, CAiSE 2023

ISBN: (纸本)9783031349843

The proceedings contain 19 papers. The special focus in this conference is on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information systems. The topics include: A Linked data Based Advanced Credit Rationale;interactive Machine Learning of knowledge Graph-Based Explainable Process Analysis;a Weighted knowledge Graph for Representing the Results of a Systematic Literature Review;knowledge engineering Formalizing DECENT Meta Model;using knowledge Graphs for Record Linkage: Challenges and Opportunities;employing knowledge Graphs for Capturing Semantic Aspects of Robotic Process Automation;Regulation-Friendly Privacy-Preserving Blockchain Based on zk-SNARK;blockchain Governance Design a Computer Science Perspective;The MEV Saga: Can Regulation Illuminate the Dark Forest?;enriching Enterprise Architecture Models with Healthcare Domain knowledge;supporting Reuse of Business Process Models by Semantic Annotation;position Paper - Hybrid Artificial Intelligence for Realizing a Leadership Assistant for Platform-Based Leadership Consulting;developing a Maturity Assessment Tool to Enable the Management of Artificial Intelligence for Organizations;mapping Time-Series data on Process Patterns to Generate Synthetic data;Towards Crisis Response and Intervention Using knowledge Graphs - CRISP Case Study;The RAI Way: A Technical Analysis and Design Method for Building Enterprise Semantic Layers;Towards Recommendations for knowledge-Graph-Based Requirements Management in Construction: A Report on the EU DigiChecks Project.

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