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检索条件"任意字段=Conference on Data Analysis and Modeling for Process Control"

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Research on MLD modeling Method of Robot Aluminum Alloy Pulsed TIG Welding process Based on Visual Sensing

Research on MLD Modeling Method of Robot Aluminum Alloy Puls...

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Digital analysis and processing, Intelligent Computation (DAPIC), International conference on

作者： Xiaolan Liu Yan Wang Kunpeng Zhao Rui Hao Liang Zhang Harbin Huade University Harbin Heilongjiang China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

This study focuses on the hybrid logic dynamic (MLD) modeling method of robot aluminum alloy pulse TIG (Tungsten Inert Gas) welding process based on vision sensing. Welding is a key technology in modern manufacturing industry, especially in the application of aluminum alloy materials, and its welding quality control is facing complex challenges. This study aims to improve the automation and intelligence level of welding process by combining robot technology and visual sensing technology. A data acquisition system based on high-precision vision sensor and advanced image processing algorithm is designed, which realizes real-time and accurate acquisition of weld and molten pool information. The weld contour is identified by machine learning algorithm, and the geometric parameters and dynamic change characteristics of weld pool are extracted, and the statistical relationship model between welding parameters and geometric characteristics of weld pool is established. On this basis, the MLD model is constructed, which can describe the continuous and discrete dynamics in the welding process. The experimental results show that MLD model can accurately predict the change trend of weld pool geometric parameters, effectively identify the welding state, and realize accurate control of welding process. This study not only improves the stability of welding quality, but also promotes the further development of aluminum alloy welding technology, which has important practical application value and broad application prospects.

关键词： Visualization Accuracy Machine learning algorithms Welding Heuristic algorithms process control Vision sensors Robot sensing systems Aluminum alloys Real-time systems

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Stones Artificial Lift System: Extending the Boundaries of Subsea Boosting

Stones Artificial Lift System: Extending the Boundaries of S...

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Offshore Technology conference, OTC 2025

作者： Merlino, A. Abels, J. Overstreet, J. Henao, S. Dowdy, B. Pisarev, G. Lupeau, A. Shell Exploration & Production HoustonTX United States EDG Inc HoustonTX United States SLB OneSubsea Bergen Norway SLB HoustonTX United States

ISBN: (纸本)9781959025610

Subsea boosting is now accepted as one of the most competent artificial lift methods to enhance subsea asset productivity. In many scenarios, it is a technical enabler to unlock resources located at a distance or water depth where the reservoir energy is not sufficient to naturally produce and transport the fluids to the surface process facility. The Stones system is currently the world's deepest offshore oil and gas project, operating at a water depth of around 2,900 meters (9,500 feet). The subsea boosting system, which includes two 3-MWsingle-phase pumps (SPPs), was deployed in the Gulf of Mexico in 2019. The system boosts the production of a complex reservoir and has to counterbalance the effect of the significant hydrostatic column to maintain the production delivered through eight wells. The vital role of the subsea boosting system for Stones production requires continuous monitoring of the equipment to ensure a maximum uptime and detect unexpected events. Maintenance of rotating machineryis always required at some point in its lifetime. Predictability is critical to be able to plan costly subsea interventions and minimize the time required to install spare equipment. Simple modeling of the subsea pump envelope provided too little resolution to be able to make adequate assessments, especially as the field conditions changed. The solution came from using data and modeling capabilities along with integrated surface facility surveillance. The objective was to provide the asset with the optimal recommendation for production well assurance to determine when a subsea pump would requirere placement on the basis of performance degradation resulting from solids production and the expected production forecast. The deployment of a condition monitoring system enabled subject matter experts (SMEs) from the operator and supplier to collect, visualize, and analyze critical system operational data together. The connection of production and equipment expertise enabled the SMEs

关键词： Quality control

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NS3-Based Communication Network modeling for Multi-Microgrid Systems: Design and Evaluation

NS3-Based Communication Network Modeling for Multi-Microgrid...

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2025 IEEE Green Technologies conference, GreenTech 2025

作者： Ali, Ola Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798331520182

This paper presents a communication emulation model for enhancing the efficiency of multi-microgrid (MMG) networks, employing Network Simulator 3 (ns3). MMG systems require robust communication frameworks for coordination, particularly under varying traffic conditions. The introduced model accommodates multiple local area networks (LANs) that support efficient communication across multiple autonomous AC microgrids. The developed model facilitates seamless bidirectional information exchange between the microgrids' local controllers and the MMG control center (MMGCC), employing TCP/IP protocol to ensure high data transmission integrity and low latency. A detailed design in C + is demonstrated, including the configuration of the communication nodes, topology, communication links, and quality of service (QoS) analysis. The network performance is rigorously assessed across low and high traffic conditions, with performance metrics such as throughput, delay, and percentage packet loss at each node. Results confirm the effectiveness of the introduced model in sustaining minimal packet loss, high throughput, and low delays under dynamic operating scenarios. These findings establish the developed model as a viable solution for meeting the real-time communication requirements of MMG energy management systems. © 2025 IEEE.

关键词： Transmission control protocol

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analysis of Logistics Service Quality Satisfaction in Fresh E-Commerce Based on KANO-IPA Model 14

Analysis of Logistics Service Quality Satisfaction in Fresh ...

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14th International conference on Logistics and Systems Engineering

作者： Wu, Haifeng Zhang, Ruijun Shi, Hang Wang, Menghao Liu, Yixuan School of Management Wuhan University of Science and Technology Hubei Wuhan430065 China Center of Service Science and Engineering Wuhan University of Science and Technology Hubei Wuhan430065 China

ISBN: (纸本)9798331314347

In the context of fresh food e-commerce platforms, a critical challenge that urgently needs to be addressed in the current e-commerce domain is how to leverage user online review data to conduct in-depth analysis and identify key logistics service quality factors that affect user satisfaction, as well as to uncover underlying expectations, thereby proposing effective optimization strategies. This paper applies the KANO-IPA model to user online reviews on fresh food e-commerce platforms and constructs a satisfaction analysis model for fresh food logistics service quality by integrating methods such as the LSQ and SERVQUAL model references to discover latent needs and enhance satisfaction. Firstly, the BERTTopic model is utilized for topic modeling to construct an attribute-sentiment dictionary. Secondly, attributes are mapped onto the KANO-IPA model to analyze user satisfaction and the importance of different attributes. Finally, an empirical analysis is conducted on fruits and vegetables, aquatic products, and meat products, taking JD Fresh as an example, and targeted optimization strategies are proposed. The research results indicate that attributes such as order response time, employee service attitude, cold chain packaging, and temperature control have significant impacts on user satisfaction, while there is still room for improvement in basic service quality requirements such as delivery accuracy and product integrity. © (2025) by Aussino Academic Publishing House All rights reserved.

关键词： Marketplaces

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FedVC: Virtual Clients for Federated Learning with Imbalanced Label Distribution 24

FedVC: Virtual Clients for Federated Learning with Imbalance...

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3rd International conference on Algorithms, data Mining, and Information Technology, ADMIT 2024

作者： Chen, Zhouguo Chen, Hongda Liu, Shuai Liu, Yongdong Schoolof Computer Science and Engineering Southeast University Jiangsu Nanjing China The 30th Research Institute of China Electronics Technology Group Corporation Sichuan Chengdu China School of Software Engineering Xian Jiaotong University Shaanxi Xian China China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798400718120

Federated Learning (FL) has gained considerable attention for collaborative training in big data analysis, particularly in terms of privacy and communication constraints. Despite its promising advantages, FL faces the challenge of dealing with imbalanced label distribution on edge devices, which complicates the learning task. In literature, numerous studies have attempted to tackle this issue by introducing additional hyperparameters, which can complicate and prolong the process of model training and tuning. This complexity may potentially lead to overfitting and limited performance on new datasets. In this paper, we present a new Federated Learning framework called FedVC, which introduces virtual clients to minimize hyperparameter reliance. FedVC aims to bridge the gap between balanced and imbalanced label distribution. Compared with traditional federated learning frameworks, the proposed FedVC model designs a dynamically balanced dataset by utilizing virtual clients, which is proposed for the first time in this work. These virtual clients determine which part of the data should be used in one single training round and manage backpropagation timing for local real clients. The balanced dataset promotes greater stability in local models, thereby enhancing the overall stability of the training process. The experimental results show that FedVC outperforms classical FedAvg and the compared baseline methods for the data with imbalanced label distribution. Especially, FedVC exhibits more stable and accurate results than alternative approaches in highly heterogeneous settings. The source code is available at https://***/aikedaerC/FedVC. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Development and integration of intelligent auxiliary emergency disposal software for power grid faults

Development and integration of intelligent auxiliary emergen...

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2024 International conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Fang, Jinhu Kong, Dejun Tao, Weilong Wu, Chunyan Hu, Huiyi Wang, Baixiang State Grid Hefei Electric Power Supply Company China Nanjing211106 China Beijing Kedong Electric Power Control System Co. Ltd Beijing100192 China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

Under the current social background of high industrialization and informationization, the challenges faced by power grid as a key infrastructure and the countermeasures. Aiming at the problems of frequent power grid faults, expanding influence scope and low efficiency of traditional disposal methods, this study introduces in detail the overall architecture of intelligent auxiliary emergency disposal software for power grid faults, including the design of front-end, back-end and database. The front end pays attention to user experience and ease of use, the back end is responsible for data processing and algorithm operation, and the database provides data storage and management functions. The software includes real-time monitoring module, fault diagnosis module, emergency treatment module and historical data analysis module, which together constitute a complete software system, aiming at realizing intelligent auxiliary emergency treatment of power grid faults. Python is chosen as the main development language, and PyCharm is used as the development tool to support the efficient development and optimization of software. In the process of software development, Hadoop HDFS and Spark, a distributed storage system, are used to process and analyze massive power grid data to ensure the real-time and accuracy of the data. At the same time, machine learning algorithm is used for fault diagnosis and prediction. Through the integration with SCADA and GIS system, the real-time monitoring, rapid positioning and effective emergency treatment of power grid faults are realized, and the practicability and intelligence level of the software are improved. The performance of the software is tested in detail, and the problems found in the test are optimized to improve the stability of the system and the ability to handle high concurrent requests. © 2025 SPIE.

关键词： Power distribution faults

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Innovative Integration of Pressure Transducers and Advanced Computer Technology for Enhanced Pinch Roll control Systems 3

Innovative Integration of Pressure Transducers and Advanced ...

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3rd International conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Chandrasekar, S. Radha, J. Rithana, A.S. Sharon Benni, S. Gokulkumar, U. Praveen Kumar, R. Kongu Engineering College Tamil Nadu Erode India Nandha Engineering College Tamil Nadu Erode India

ISBN: (纸本)9798331527549

Furnace pinch roller from the analysis of the hot rolling mill unit, it was established that it transforms metal scrap into high quality rolled sheets using furnace pinch roller and metal conveyor belt. The guide and pinch rollers facilitate easy progression and avoid sheet damage during the rolling process mainly through accurate sheet guidance and retention. These rollers are positioned by a hydraulic cylinder that is supplied with a pressure transducer with a pressure limit of 30 bar so as to monitor it on line. The furnace retains working temperatures of 900°C inside and 600°C outside in order to sustain efficient rolling temperatures. This setup acts to improve the accuracy of the metal conversion process and the results obtained from it. But in the existing inductive proximity sensors scale are heat sensitive and an interferometer disturbances positional inaccuracies resulting in recurrent operational interferences and high costs of maintenance. To eliminate such limitations, the research offers improved sensor designs given the harsh conditions of operation. Also, using predictive monitoring systems is adopted to minimize pressures, increase effectiveness, and maintain unchanging Industrial standards. © 2025 IEEE.

关键词： Hot rolling

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15th International conference on Subject-Oriented Business process Management, S-BPM ONE 2024

15th International Conference on Subject-Oriented Business P...

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15th International conference on Subject-Oriented Business process Management, S-BPM ONE 2024

ISBN: (纸本)9783031720406

The proceedings contain 22 papers. The special focus in this conference is on Subject-Oriented Business process Management. The topics include: data Mesh: How to Implement the Paradigm Shift;improving Agile Maturity in data Teams: A Framework for Enhanced Business process Agility;Synergizing data Contracts and BPM to Improve process Interoperability: An analysis of Gaps and Opportunities of data Exchange Agreements in BPM Models;an Aspect-Oriented Extension of the Parallel Activity Specification Schema: A First Draft;how Business process modeling Can Benefit from Rhetorical Structure Theory;modeling of IoT Systems Behavior: A Subject-Oriented Reference Model;Subject-Oriented modeling Workflow control Patterns with PASS;subject- and process-Oriented Comparison of Multi-factor Authentication Methods;S-BPM as an Alternative to BPMN in the Context of Low-Code: Applicability, User Experience and Transformation from S-BPM to BPMN;facilitating the Preparation of Life Cycle Assessment Through Subject-Oriented process modeling: A Methodological Framework;a Framework for Sustainable Web Design in the Era of Digital Transformation;green Thoughts and Creative Spaces: An Experimental Study on Influence of Innovation Labs on Productivity and Sustainability of process Teams;towards Resilient Digital Supply Chains;Walking Away from Omelas: Towards a Comprehensive Model for Successful Adoption of Industry 4.0 Technologies in SMEs;interoperable Product Change Management Within Engineering: A Digital Twin Approach;Next-Generation Business process Management (BPM): A Systematic Literature Review of Cognitive Computing and Improvements in BPM;three Stances in Enterprise System Design;process Orientation in Authorities: Opportunities, Challenges and Best Practices;Which Good Practices Minimize Procedural Problems in IT Workflows Between Authorities?;Meta-prompt Engineering in ChatGPT-4 for AI-Generated BPM Reference Models.

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25th International conference on Intelligent data Engineering and Automated Learning, IDEAL 2024

25th International Conference on Intelligent Data Engineerin...

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25th International conference on Intelligent data Engineering and Automated Learning, IDEAL 2024

ISBN: (纸本)9783031777370

The proceedings contain 92 papers. The special focus in this conference is on Intelligent data Engineering and Automated Learning. The topics include: Model-Based Meta-reinforcement Learning for Hyperparameter Optimization;towards Sustainable Precision: Machine Learning for Laser Micromachining Optimization;association Rules Mining with Auto-encoders;using Contrastive Learning to Map Stylistic Similarities in Narrative Writers;automatic Classification of Signal and Noise in Functional Magnetic Resonance Imaging Scans Using Convolutional Neural Networks;how Resilient are Language Models to Text Perturbations?;emotional Sequential Influence modeling on False Information;CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care data Interoperability;padel Two-Dimensional Tracking Extraction from Monocular Video Recordings;drowsiness Detection Using Vital Sign Sensors and Deep Learning on Smartwatches;Benchmarking Out of the Box Open-Source LLMs for Malware Detection Based on API Calls Sequences;multimodal Visio-Lingual Content analysis to Detect Fake Content on Reddit;MetaLIRS: Meta-learning for Imputation and Regression Selection;pipeline for Semantic Segmentation of Large Railway Point Clouds;preliminary Investigation on Machine Learning and Deep Learning Models for Change of Direction Classification in Running;efficient Radar Scheduling Using Genetic Algorithms and Stochastic Heuristic Initialization;towards a Communication Specification Language for Heterogeneous Service Orchestration Based on process Calculus and Holonic Multi-agent Systems;counterfactual Explanations for Sustainable Tourism Indicators;Tracking Healthy Organs in Medical Scans to Improve Cancer Treatment by Using UW-Madison GI Tract Image Segmentation;low Consumption Models for Disease Diagnosis in Isolated Farms;fast and Scalable Recommendation Retrieval Model with Mixed Attention and Knowledge Distillation;Federated Learning for Vietnamese SMS Spam Detection Using Pre

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5G Real-time data synchronization and safety monitoring for live operation of distribution lines

5G Real-time data synchronization and safety monitoring for ...

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2024 International conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Gao, Hui Li, Ran Luo, Yan Zhang, Shuo Li, Yuying State Grid Henan Electric Power Company Xixia County power supply company 474500 China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

With the rapid development of 5G technology, its unique characteristics of high bandwidth, low latency, and high reliability have brought revolutionary data transmission and monitoring solutions for live working in the power industry. In live operation of distribution lines, 5G technology not only achieves real-time synchronization of equipment status, environmental parameters, and operation progress, ensuring accurate remote monitoring and real-time command, but also significantly improves the safety monitoring level of the operation process through the deep integration of high-definition video monitoring, intelligent analysis and warning, and remote control technology, effectively reducing the risk of operation and the possibility of personnel exposure to high-risk environments. This article proposes an innovative distribution line safety monitoring system based on artificial intelligence (AI) and 5G technology. The system utilizes the high-speed transmission capability of 5G network and combines AI algorithms to perform real-time analysis of massive data, achieving precise monitoring and intelligent warning of job sites. The experimental results show that the system can accurately identify potential safety hazards in the operation, issue warning signals in advance, and provide scientific decision support for operators, thereby greatly improving the safety and efficiency of live working. © 2025 SPIE.

关键词： 5G mobile communication systems

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