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

共 37040 条记录，以下是651-660 订阅

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The Implementation of Preventive Maintenance in a Product-Service System (PSS) Business Model 32nd

The Implementation of Preventive Maintenance in a Product-Se...

引用

32nd international conference on Flexible Automation and Intelligent manufacturing

作者： Kuroki, Alisson Cardoso, Valdir H. Oliveira Neto, Geraldo C. Amorim, Marlene FEI Univ BR-01525000 Sao Paulo SP Brazil Aveiro Univ P-3810193 Aveiro Portugal

ISBN: (纸本)9783031381645;9783031381652

The commoditization initiatives triggered inmanufacturing companies the concern with the rigidity of their offers, and the appeal of their offers to their customers, leading to servitization strategies. This research highlights the importance of preventive maintenance, and builds on the extraction and processing of data for a PSS business model. data from https://*** was used to analyze the performance of a production process with three products with differentiated levels of quality. data analysis was of exploratory nature using descriptive statistics and Pearson's correlation through, using Python via Google Collaboratory. The main failures were exposed allowing the elaboration of a preventive maintenance plan. Through multivariate statistical analyses, we demonstrate that in a PSS business model, having machine suppliers at your disposal that combine the sale of the item with the provision of predictive maintenance services is a differential that will help to make assertive a preventive d skillful decision, avoiding maintenance unnecessary and waste of time.

关键词： Business Intelligence Big data Analytics Servitization Fault Identification

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Research On Palmprint Recognition Based On Mechanism And data 24

Research On Palmprint Recognition Based On Mechanism And Dat...

引用

2024 international conference on Computer Vision and Deep Learning, CVDL 2024

作者： Chen, Rongyuan Tang, Yangfan Zhong, Yanrong Shi, Yuanxing Huang, Shaonian Shen, Lizhi Hunan University of Technology and Business School of Intelligent Engineering and Intelligent Manufacturing China Shaodong Public Security Bureau China Hunan University of Technology and Business China Fujian Rural Credit Union China

ISBN: (纸本)9798400718199

Among the existing palmprint recognition technologies, traditional methods cannot adaptively extract multi-level features of palmprint images to better represent image information, and methods based on deep learning fail to make full use of prior knowledge existing in palmprint images. To solve this problem, A palmprint recognition method was proposed based on fusion mechanism and data, and constructs a palmprint recognition data model based on deep learning. The prior knowledge in palmprint images is extracted and added to the data model as mechanism knowledge to improve the model's ability to discriminate palmprint features. The multi-direction Gabor filter is used to optimize the prediction results and improve the recognition performance. The experimental results show that the recognition accuracy of the proposed method on CASIA palmprint database is 99.41%, which is better than the existing mainstream methods. © 2024 ACM.

关键词： Gabor filters

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Research on the Construction of knowledge QA System Driven by Large Language Model: One Case Study of Power Transformer Domain 7

Research on the Construction of Knowledge QA System Driven b...

引用

7th international conference on data Science and Information Technology, DSIT 2024

作者： Xu, Hao Kang, Zhenyuan Zhang, Yan Jin, Zhenqiang Wang, Mulan Ge, Linlin Lu, Haihua Management Nanjing University School of Management Engineering Nanjing Institute of Technology School of Information Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering Shen Guorong College Nanjing China Nanjing Institute of Technology School of Management Engineering Nanjing China Jiangsu Power Transmission & Transformation Co. Ltd Nanjing China Nanjing Institute of Technology School of Industrial Center Nanjing China

ISBN: (纸本)9798350384093

The QA system can provide various professionals with fast and accurate knowledge support, significantly improving work efficiency. The introduction of LLMs has further enhanced the accuracy and efficiency of QA systems. A QA system based on LLMs for power transformers can effectively improve the efficiency of fault diagnosis and the resolution of technical issues in the power transformer domain. This study first proposes an automatic dataset construction method for QA based on LLMs, through which a QA dataset of basic knowledge about power transformers is obtained. This dataset then performs low-rank adaptive fine-tuning on the LLM. Subsequently, an external knowledge base covering fundamental knowledge and fault cases of power transformers is built. Finally, with the aid of prompt texts, knowledge responses were generated by RAG in combination with the fine-tuned LLM. Experimental results show that compared with the QA systems driven by general LLMs, the method proposed in this paper generates more concise and professional responses, thus promoting, to some extent, the application of LLMs in the power domain. © 2024 IEEE.

关键词： Distribution transformers

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international conference on Production and Industrial engineering, CPIE 2023

International Conference on Production and Industrial Engine...

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international conference on Production and Industrial engineering, CPIE 2023

ISBN: (纸本)9789819974443

The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial engineering. The topics include: A Comprehensive Overview on Additive manufacturing Processes: Materials, Applications, and Challenges;an Overview of the Untapped Potential of Soft Robotic Arms with Integration of Machining Tools;life Cycle Assessment of Abrasive Flow Machining of 3D Printed Parts: A Comparative Analysis;Modelling and Simulation of Wire DED Additive manufacturing Process;an Overview of the Recent Advances in Additive manufacturing, and Its Scope for the Benefit of Research and Development in Commercial Vehicle Industries;design and Development of Customized Helmet for Military Personnel;additive manufacturing and Sustainability: The Mediating Role of Supply Chain;leverage of Metal 3D Printing Technology in the Automotive Industry;digital Twins of Hybrid Additive and Subtractive manufacturing systems–A Review;exploring Sustainable manufacturing: A Comprehensive Review of Literature and Practices;performance Analysis of 3D Printed Impellers for Portable Vacuum Cleaner;3D Printed Electronics: Role of Materials and Processes;electrochemical Micromachining: A Review on Principles, Processes, and Applications;friction and Wear Characteristics of Engine Oil Through Four-Ball Tester;recent Trends in 4th Industrial Revolution for A Sustainable Future–A Review;AI Control of EMG Sensor data for 3D Printed Prosthesis Hand.

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Impacts of Accelerator Cohort Composition on Startup Performance

Impacts of Accelerator Cohort Composition on Startup Perform...

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2023 Portland international conference on Management of engineering and Technology, PICMET 2023

作者： Han, JungYun Eesley, Charles National Taiwan University College of Management Taipei Taiwan Stanford University Department of Management Science & Engineering Stanford United States

ISBN: (纸本)9781890843434

How does cohort composition affect the outcomes of accelerator participants? Literature on inter-firm and peer learning in entrepreneurship, provides mixed predictions: seeking diverse knowledge and being different vs. pursuing fast learning via similar peers. To reconcile the arguments, we investigate the key contingencies, types of knowledge transferred (market knowledge vs. technology) and the unique nature of competition in each knowledge type. Using data from accelerators and their participants during 2005-2018, we find an inverted-U-shaped relationship between market knowledge similarity in a cohort and post-accelerator performance and a positive relationship between technology similarity and performance. Our study reveals a peer learning mechanism in accelerators and provides a nuanced understanding of the effect of knowledge diversity on startup performance. © 2023 PICMET (Portland international Center for Management of engineering and Technology(.

关键词： Commerce

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Semantic Enrichment of Textual data Through knowledge Extraction 5th

Semantic Enrichment of Textual Data Through Knowledge Extrac...

引用

5th international conference on data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Nanda Devi, D.R. Kasu, Harshitha Line, Meghana Roshni, N. Shreya, P. G. Narayanamma Institute of Technology and Science Telangana Hyderabad India

ISBN: (纸本)9789819780426

A vast web of information i.e. knowledge forms the backbone of intelligent systems. Unstructured data poses challenges in terms of information retrieval, scalability and semantic ambiguity. Possible solutions for many tasks including question answering system, recommendation and information retrieval rely on structured information. The existing representations of knowledge are time consuming. Representation of knowledge in the form of a knowledge graph helps to retrieve information along with relations. It helps to represent entities and relations with high reusability, and reliability. This paper focuses on efficient information retrieval through extraction of entities and relations for the construction of a knowledge graph. An efficient representation of knowledge captures information dynamically and keeps re-purposing itself to provide new insights and inferences which is a key to analyze big data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： knowledge graph

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Research on assembly sequence planning method based on artificial neural networks

Research on assembly sequence planning method based on artif...

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2023 international conference on Computer Graphics, Artificial Intelligence, and data Processing, ICCAID 2023

作者： Zhang, Jing Feng, Shaowei Chai, Kai College of Naval Architecture and Ocean Naval University of Engineering Wuhan430033 China

ISBN: (纸本)9781510677685

Assembly sequence planning is acknowledged as a pivotal aspect of the assembly process, playing a vital role in the realization of production automation and the assembly and disassembly of equipment. It is a current research focal point within both national and international realms of Computer Integrated manufacturing systems (CIMS) and equipment maintenance domains. This paper introduces and executes a neural network-based methodology for automated assembly sequence planning. The proposed method initially employs assembly interconnection matrices, assembly graphs, and penalty matrices to delineate the preferential relationships and assembly costs among components. Thereafter, it utilizes a Backpropagation (BP) neural network to resolve the optimal product assembly sequence adhering to these constraints. The efficacy of this method provides a substantive contribution to the automation of assembly sequences and is potentially beneficial for optimizing complex assembly tasks in industrial applications. Future work may extend towards refining this approach and testing its adaptability across various manufacturing scenarios. © 2024 SPIE.

关键词： Neural networks

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Vulnerability Detection Based on Adapter Tuning and Enhanced Feature Learning 36

Vulnerability Detection Based on Adapter Tuning and Enhanced...

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36th international conference on Software engineering and knowledge engineering, SEKE 2024

作者： Luo, Hui Lu, Lu Liang, Zhihong Suo, Siliang School of Computer Science and Engineering South China University of Technology Guangzhou China Pazhou Laboratory Guangzhou China PengCheng Laboratory Shenzhen China Electric Power Research Institute CSG Guangdong Guangzhou China Guangdong Provincial Key Laboratory of Power System Network Security Guangdong Guangzhou China

ISBN: (纸本)1891706594

Pre-trained code models have achieved promising results in the vulnerability detection field. The prevailing approach is to adapt these models with vulnerability datasets using inefficient full-model fine-tuning. These pre-trained models primarily capture the semantic features of code, while neglecting its structural characteristics. To address these issues, this paper proposes a vulnerability detection method with adapter tuning and enhanced feature learning. First, adapter modules are introduced to UniXcoder and tune only the parameters in the adapters to extract semantic features. This significantly reduces the number of training parameters and better adapts the model to downstream tasks. Then, structural features, including control and data flow information, are extracted from the Program Dependence Graph (PDG) to compensate for the limitations of pre-trained models that rely solely on semantic features. Finally, the semantic and structural features are integrated to train the detection model. The experimental results demonstrate that our proposed method outperforms state-of-the-art approaches and is highly efficient in terms of both training parameters and training data. © 2024 knowledge systems Institute Graduate School. All rights reserved.

关键词： data flow graphs

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FOODIE: A data-centric Sifting Framework for Social Media Analytics 35

FOODIE: A Data-centric Sifting Framework for Social Media An...

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35th international conference on Software engineering and knowledge engineering, SEKE 2023

作者： Agarwal, Dolly Al Imran, Abdullah Perera, Kasun S. Ai Palette Pte Ltd Singapore

There has been a great deal of research conducted in the past on utilizing social media analytics to derive consumer insights and understand their behaviors. However, when such studies are applied to real-world data in an industrial use-case, the results are often found to be incorrect and erroneous. This is a major barrier for companies that provide social media analytics-based solutions to customer-centric industries such as Food and Beverage (FnB). One of the key causes of this barrier is the failure to appropriately process and curate raw social data prior to analytics. In this study, we discuss the challenges we encountered when dealing with social data throughout our industrial experience and propose a standard solution - FOODIE. This is a framework specifically designed for the FnB industry to process social conversation data accurately and in a standard manner prior to perform various downstream tasks on it. The three stages of this paradigm are preparation, sifting, and evaluation. Through this framework, we have reduced the data to error ratio from 8.76% to 0.01% which is quite significant given the volume of the data. While this framework is designed for the FnB space, it can be customized to suit the needs of various other industries. © 2023 knowledge systems Institute Graduate School. All rights reserved.

关键词： Machine learning

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Ambidexterity and High-Performance Work systems: The Roles of knowledge Sharing, Leadership Style, and Social Media 5

Ambidexterity and High-Performance Work Systems: The Roles o...

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5th international conference on Artificial Intelligence and data Sciences, AiDAS 2024

作者： Saide, Saide Ningsi, Nurfitria Muwardi, Didi Jelita, Dian Antasari, Nita Universitas Islam Negeri Sultan Syarif Kasim Riau Faculty of Science and Technology Department of Information Systems Pekanbaru Indonesia Pro Knowledge Pekanbaru28293 Indonesia Universitas Pahlawan Tuanku Tambusai Dept. Informatics Engineering Kampar Indonesia Universitas Sembilanbelas November Kolaka Faculty of Information Technology Department of Information Systems Sulawesi Tenggara93561 Indonesia Riau University Department of Agribusiness Pekanbaru28293 Indonesia Pendidikan Agama Islam Fakultas Tarbiyah dan Tadris Universitas Islam Negeri Fatmawati Sukarno Bengkulu Bengkulu38223 Indonesia

ISBN: (纸本)9798331528553

Research on knowledge sharing, participative leadership, and exploitation-exploration has demonstrated its influence on high-performance work systems (HPWS) and the quality of employee performance. In the context of employee ambidexterity, which encompasses both exploitation and exploration innovations, there is a notable gap in research directly addressing these two aspects. data were collected from target employees using an offline questionnaire-based survey, yielding 56 valid responses. This study aims to determine the extent and significance of the supporting variables on employee ambidexterity. Using structural equation modeling, the findings reveal that participative leadership has a positive and significant effect on HPWS and the quality of employee performance. Additionally, exploration has a positive and significant effect on HPWS. The results of this study suggest strategies for enhancing the competitive quality of employee performance, including participative leadership, knowledge sharing, and exploration innovation. © 2024 IEEE.

关键词： Personnel rating

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