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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751-760 订阅

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Implementation of Block Chain, IoT and Role-basis data Access Control (RBAC) for Intelligent manufacturing 7

Implementation of Block Chain, IoT and Role-basis Data Acces...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Kaushal, Rajanish Kumar Kumar, S. M. Ravi Chellaiah, Pandeeswaran Pundir, Sumit Maranan, Ramya Krishnaiah, Nallam Chandigarh University Department of Electrical Engineering Mohali Punjab Gharuan India G. Pullaiah College of Engineering And Technology Department of Mechanical Engineering Andhra Pradesh Kurnool518452 India St. Joseph's College of Engineering Department of Computer Science And Engineering Tamil Nandu Chennai600119 India Graphic Era Deemed To Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering SIMATS Department of Research And Innovation Tamil Nadu Chennai India St.Martin's Engineering Department of Information Technology Telangana Secunderabad500100 India

ISBN: (纸本)9798350359299

Various recommendations for predicting the dependability and quality of equipment contribute to the success of intelligent manufacturing systems. Numerous Role basis access control (RBAC) techniques are being investigated for this purpose. data security and administration is another industry concern that is regarded as crucial. To surmount the challenges, The proposed work integrates block chain and Role basis access control (RBAC) to secure system transactions and manage a dataset to combat the forgery dataset. Big data techniques were used to manage and examine the collected dataset. Based on the hybrid prediction technique, the aspect of defect diagnosis prediction was evaluated on-linear Role basis access control (RBAC) techniques which are mainly used for estimating the system's complex background and figuring out its true positive rate. This was done to evaluate the proposed system's quality control. © 2024 IEEE.

关键词： Access control

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A Domain Adaptive Feature Relevance Analysis for Human Activity Recognition using Transfer Learning

A Domain Adaptive Feature Relevance Analysis for Human Activ...

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2023 IEEE international conference on Research Methodologies in knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Preethy Jemima, P. Madhurika, K. Singh, Gobind Pandey, Adarsh Department of Computer science and Engineering SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai India

ISBN: (纸本)9798350305708

Wearable electronics are electronic gadgets designed to be incorporated into clothing, worn on the body, or integrated into other items. These devices collect data, provide information, and perform specific tasks. Human Activity Recognition (HAR) utilizes Transfer Learning algorithms to track movements using sensor data from devices like accelerometers and gyroscopes. HAR finds applications in security, fitness tracking, and health monitoring systems. Utilizing pretrained models and engineered features from these models aids in creating accurate HAR systems. Transfer learning reduces data requirements and simplifies feature engineering, making it a valuable approach for HAR, especially in diverse real-world scenarios. © 2023 IEEE.

关键词： Deep learning Fine-tuning HAR Neural Networks Pre-processing Transfer learning

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Leveraging Trustworthy AI and IIoT for Cost-Efficient Multimodal Quality Control in Metallurgic Additive manufacturing 5

Leveraging Trustworthy AI and IIoT for Cost-Efficient Multim...

引用

5th IEEE international conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Buescher, Jan Zajaczkowski, Jonas Blecking, Christian Baumann, Ingor Mohle, Roman Wagstyl, David Rademacher, Hans-Georg Tillmann, Wolfgang Deuse, Jochen Institute of Production Systems TU-Dortmund Dortmund Germany Institute of Materials Engineering TU-Dortmund Dortmund Germany Kupferverband e.V. Department of Industrial Applications Duesseldorf Germany RIF e.V. Production Systems Dortmund Germany RIF e.V. Materials Engineering Dortmund Germany Centre for Advanced Manufacturing UTS Sydney Sydney Australia

ISBN: (纸本)9798350364743

Ensuring consistent quality in metallurgic Additive manufacturing (AM) processes, such as Cold Gas Spraying (CGS), is a significant challenge due to the inherent process variability in part quality. This study explores the integration of trustworthy Artificial Intelligence (AI) and the Industrial Internet of Things (IIoT) to multimodal quality control, with the goal of increasing in-situ test coverage of manufactured parts and process stability. An open-source software solution for data engineering and analysis was developed using the Design Science Research methodology. Experiments were conducted on a CGS system utilizing CuZn30, a copper-zinc alloy material, as a representative case study. The developed AI models demonstrated high efficiency in identifying quality deviations across multiple quality characteristics, including oxidation, geometric inaccuracies and porosity (F1-Score=0.998). The results suggest that the combination of IIoT-measurement components and AI is a cost-effective way to significantly improve test coverage, enabling the control of multiple quality attributes and process reliability in metallurgical AM using low-cost sensors and open-source software. This research contributes to the advancement of cost-effective quality control systems and provides a case study of how AI can be used to improve the reliability and stability of advanced industrial manufacturing processes with respect to multiple quality characteristics and data modalities, paving the way for mass customization as proposed in the Industry 4.0 vision. © 2024 IEEE.

关键词： Zinc alloys

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Fault analysis and impact weight calculation of marine diesel engine unable to start based on fault tree and analytic hierarchy process 4

Fault analysis and impact weight calculation of marine diese...

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4th international conference on Mechanical engineering, Intelligent manufacturing, and Automation Technology, MEMAT 2023

作者： Li, Zhaoqiang Yang, Haijun Hou, Linli Wang, Lingling Non-Commissioned Officer Department Binzhou Polytechnic 919 Huanghe 12th Road Shandong Binzhou256600 China Training Management Department Binzhou Polytechnic 919 Huanghe 12th Road Shandong Binzhou256600 China Mechanical and Electrical Engineering Department Binzhou Polytechnic 919 Huanghe 12th Road Shandong Binzhou256600 China

ISBN: (纸本)9781510674820

In response to the malfunction of "marine diesel engine unable to start", the possible causes of the malfunction were deduced and a fault tree model was established. On this basis, the fault tree model was transformed into a hierarchical analysis model, and the target layer, criterion layer, and solution layer were constructed. Through expert consultation and data collection, a judgment matrix for each layer was constructed, and the effectiveness of the judgment matrix was verified. The impact weights of each base event on the top event were determined, and targeted suggestions were proposed for the management of marine diesel engine systems. © 2024 SPIE.

关键词： Diesel engines

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From data to Learning: The Scientific Approach to AI-Enhanced Online Course Design 8

From Data to Learning: The Scientific Approach to AI-Enhance...

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

作者： Blagoev, Ivaylo Vassileva, Gergana Monov, Vladimir Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (纸本)9798350313246

This article explores a transformative approach to online education, driven by the integration of Generative Artificial Intelligence (AI). We present a comprehensive methodology for the creation of interactive online courses, emphasizing four essential steps: content generation powered by AI, division of content into manageable knowledge bites, diversification of content types, and the automated design of course screens with interactive elements and visual assets. The journey begins with AI-driven content creation, leveraging advanced algorithms to generate educational materials efficiently. These materials are then segmented into bite-sized, self-contained knowledge bites, following the principles of microlearning. The diverse array of content types within each knowledge bite enhances engagement and comprehensive understanding. © 2023 IEEE.

关键词： Curricula

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Expediting Multiple Projects Timelines with State-of-the-Art Dashboard Management systems to Improving Efficiency and Minimizing Delays 8

Expediting Multiple Projects Timelines with State-of-the-Art...

引用

8th international conference on Information Technology, InCIT 2024

作者： Saputra, Muhardi Pratami, Devi Chaeruddin, Andi Muhammad Fachri Telkom University Department of Infomation System Indonesia Telkom University Department of Industrial Engineering Indonesia Universiti Teknologi Malaysia Faculty of Mechanical Engineering Department of Materials Manufacturing and Industrial Engineering Malaysia

ISBN: (纸本)9798350366303

A program is a collection of interrelated projects, programs, and other related activities that cannot be managed individually. One Higher Education Institution (HEI) was awarded a program worth over USD 3 million to build an education-integrated application that will serve academic and non-academic processes. The program had severe challenges since it required tight monitoring and control due to its enormous project value. This study aims to design a dashboard to reduce delays and enhance efficiency. The solution was achieved by integrating a Dashboard Management System using the waterfall method. It was developed using Google Spreadsheet due to its familiarity and usability aspect compared to other project management systems that require huge investment and knowledge to use. The study shows that the program management dashboard significantly improved overall program efficiency. The program has reached 37.29% schedule acceleration of work completion. It indicates that the simple information system and adopting the formal standard of program management will increase the success of program completion. © 2024 IEEE.

关键词： Efficiency

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Electric Vehicle Fault Battery Analyzer Using Internet of Things

Electric Vehicle Fault Battery Analyzer Using Internet of Th...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Kamatchi Kannan, V. Muniraj, C. Sankarganesh, R. Parimalsundar, E. Thrinath, B.V. Sai Ponmurugan, P. Knowledge Institute of Technology Salem India K.S.R. College of Engineering Tiruchengode India Mohan Babu University Tirupati India Chennai600078 India

ISBN: (纸本)9798331509828

This research work focuses on a comprehensive solution that evaluates and monitors the health of electric vehicle batteries in real time is the Internet of Things (IoT)-based Electric Vehicle (EV) Battery Fault Analyzer. A micro controller, an IoT module, sensors, a cloud platform, and a user interface are all included in the framework to facilitate efficient data collection, investigation, and client alerting. The core components are individual battery cell management and monitoring, a micro controller for data acquisition, and an Internet of Things module for seamless cloud connectivity. A few of the sensors that provide crucial information about the state of the battery include accelerometers, voltage, current, and temperature. After this, data has been securely transmitted, the condition of the battery is evaluated by fault detection algorithms and data analysis processes on a cloud platform. © 2025 IEEE.

关键词： Fault detection

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Enhancing Object Detection with Hybrid dataset in manufacturing Environments: Comparing Federated Learning to Conventional Techniques 1

Enhancing Object Detection with Hybrid dataset in Manufactur...

引用

1st international conference on Innovative engineering Sciences and Technological Research, ICIESTR 2024

作者： Hegiste, Vinit Walunj, Snehal Antony, Jibinraj Legler, Tatjana Ruskowski, Martin Rptu Kaierslautern-Landau Machine Tools and Control Systems Kaiserslautern Germany Kaiserslautern Germany

ISBN: (纸本)9798350348637

Federated Learning (FL) has garnered significant attention in manufacturing for its robust model development and privacy-preserving capabilities. This paper contributes to research focused on the robustness of FL models in object detection, hereby presenting a comparative study with conventional techniques using a hybrid dataset for small object detection. Our findings demonstrate the superior performance of FL over centralized training models and different deep learning techniques when tested on test data recorded in a different environment with a variety of object viewpoints, lighting conditions, cluttered backgrounds, etc. These results highlight the potential of FL in achieving robust global models that perform efficiently even in unseen environments. The study provides valuable insights for deploying resilient object detection models in manufacturing environments. © 2024 IEEE.

关键词： Federated learning

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Branchy-TEE: Deep Learning Security Inference Acceleration Using Trusted Execution Environment 35

Branchy-TEE: Deep Learning Security Inference Acceleration U...

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

作者： Wang, Yulong Deng, Kai Meng, Fanzhi Chen, Zhi Yin, Mingyong Yang, Run Institute of Computer Application China Academy of Engineering Physics Mianyang China School of Cyberspace Science Harbin Institute of Technology Harbin China

Deep Learning as a Service (DLaaS) has become a remarkable trend in modern data-driven online services. Both data holders and service providers need to build on trust in third-party cloud infrastructure platforms. However, once the trust is broken, data holders’ sensitive data and service providers’ intellectual property rights will face significant security and privacy risks. In this paper, we propose a secure and efficient inference framework for deep learning in untrustworthy cloud platforms, termed Branchy-TEE, which aims to protect the confidentiality and integrity of data and models of multiple participating actors throughout the inference process using the Trusted Execution Environment (TEE). Branchy-TEE dynamically loads the inference network into the TEE on-demand based on early-exit mechanism, expecting to break the hardware performance bottleneck of the TEE. Moreover, a joint training method based on knowledge distillation for multi-exit networks is proposed, by flowing"knowledge" from the final exit with high accuracy to the early branch exit with lower accuracy. Finally, the effectiveness and efficiency of Branchy-TEE are verified through extensive experiments in real environments, while achieving an optimal balance between performance and hardware resources. © 2023 knowledge systems Institute Graduate School. All rights reserved.

关键词： Distillation

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Characterizing Complex Network Properties of knowledge Graphs 15

Characterizing Complex Network Properties of Knowledge Graph...

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15th international conference on knowledge engineering and Ontology Development, KEOD 2023 as part of the 15th international Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2023

作者： Rossanez, Anderson da Silva Torres, Ricardo dos Reis, Julio Cesar Institute of Computing University of Campinas SP Campinas Brazil Agricultural Biosystems Engineering Wageningen Data Competence Center Wageningen University & Research Wageningen Netherlands Department of ICT and Natural Sciences Norwegian University of Science and Technology Ålesund Norway

ISBN: (纸本)9789897586712

knowledge Graphs have been established as one the most relevant representations to encode knowledge, with relevant applications in the public and private sectors. One common research direction concerning the analysis of created knowledge graphs relies on the assumption that their intrinsic properties and structure are similar to what is observed in complex networks. However, studies concerning identifying typical complex network structures in knowledge graphs are lacking in the literature. This paper bridges this gap by analyzing commonly and recently used knowledge graphs in the semantic web field, seeking to demonstrate their complex network properties. Evaluation involving DBpedia and Wikidata data confirms the occurrence of intrinsic complex network structures in their respective knowledge graphs. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0).

关键词： Complex networks

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