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

共 36972 条记录，以下是321-330 订阅

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A data-flow oriented software architecture for heterogeneous marine data streams 21

A data-flow oriented software architecture for heterogeneous...

引用

21st international conference on Software Architecture (ICSA)

作者： Lima, Keila Nguyen, Ngoc-Thanh Heldal, Rogardt ICristensen, Lars Michael Oyetoyan, Tosin Daniel Pelliccione, Patrizio Knauss, Eric Western Norway Univ Appl Sci Bergen Norway Chalmers Univ Gothenburg Gothenburg Sweden Gran Sasso Sci Inst Laquila Italy

ISBN: (纸本)9798350359176;9798350359169

Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of marine ecosystems and/or climate changes. Various public organizations have collected, managed, and openly shared in-situ marine data in the past decade. Recently, initiatives like the Ocean Decade Corporate data Group have incentivized the sharing of marine data of public interest from private companies aiding in ocean management. However, there is no clear understanding of the impact of data quality in the engineering of systems, as well as on how to manage and exploit the collected data. In this paper, we propose main architectural decisions and a data flow-oriented component and connector view for marine in-situ data streams. Our results are based on a longitudinal empirical software engineering process, and driven by knowledge extracted from the experts in the marine domain from public and private organizations, and challenges identified in the literature. The proposed software architecture is instantiated and exemplified in a prototype implementation.

关键词： architecture architectural decisions IoT

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Edge Computing in Industrial IoT: Enhancing Reliability and Efficiency in Smart manufacturing Environments 3

Edge Computing in Industrial IoT: Enhancing Reliability and ...

引用

3rd international conference for Advancement in Technology, ICONAT 2024

作者： Kalaiselvi, K. Pandi, V.Samuthira Shobana, D. Lakshmi Priya, J. Sushma, G. Demel Abisha, K.S. Saveetha Institute of Medical and Technical Sciences Saveetha College of Liberal Arts and Sciences Department of Data Analytics Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Tamil Nadu Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India Saveetha Engineering College Department of ECE Chennai India CVR College of Engineering Mangalpally Department of CSE Ibrahimpatan India Dhanalakshmi College of Engineering Department of CSE Chennai India

ISBN: (纸本)9798350354171

An whole new way of thinking about Industrial Internet of Things (IIoT) applications has been brought about by the introduction of Edge Computing, especially in smart manufacturing settings. This paper examines the pivotal role of Edge Computing in enhancing both reliability and efficiency in industrial settings. With Edge Computing, the latency issues with standard cloud-based methods are lessened by decentralizing processing resources closer to the data source. The ability to process, analyze, and make decisions in real time on data in close proximity is essential for streamlining operating processes and reducing downtime. Furthermore, Edge Computing enables advanced analytics at the edge, empowering smart manufacturing systems to swiftly adapt to dynamic operational demands. Through case studies and technological insights, this paper illustrates how Edge Computing fosters resilient and efficient smart manufacturing ecosystems, driving innovation and competitiveness in the industrial sector. © 2024 IEEE.

关键词： Smart manufacturing

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Human-Intention Prediction with Visual-Language Model

Human-Intention Prediction with Visual-Language Model

引用

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

作者： Liang, Yongshi Zheng, Pai The Hong Kong Polytechnic University Department of Industrial and Systems Engineering Special Administrative Region Hung Hom Hong Kong

ISBN: (纸本)9798350378658

Human-intention prediction is an important part of human-machine interaction wildly utilized in industrial intelligent systems. In recent years, large language models have expanded to the image task with outstanding performance, leading to an increasing attraction to the application of multimodal Large Language Models. However, the exploration of visual-language models in human-intention prediction is still limited. To address this gap, this paper investigates the effectiveness of visual-language models in predicting human intentions and successfully transfers the knowledge in LLMs to downstream classification tasks. Finally, this paper takes traffic scenarios as an example to validate the feasibility of the video-LLaMA model in predicting pedestrian behavior intentions. © 2024 IEEE.

关键词： Prediction models

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Application of Artificial Intelligence Technology in the Digital Transformation Path of Traditional manufacturing Based on Bayesian Network 24

Application of Artificial Intelligence Technology in the Dig...

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5th international conference on Artificial Intelligence and Computer engineering, ICAICE 2024

作者： Jiang, Xu Peng, Ling Guangdong University of Science and Technology Guangdong Dongguan China

ISBN: (纸本)9798400718007

Driven by the global digital economy, the intelligent transformation of traditional manufacturing has become a critical path to enhancing enterprise competitiveness. This study aims to explore the application of artificial intelligence technology in the intelligent transformation path of traditional manufacturing and analyze its impact mechanisms using a Bayesian network model. Through data mining and modeling of relevant enterprises, the study reveals how AI technology accelerates manufacturing transformation by optimizing production processes, enhancing innovation capabilities, and reducing operational costs. The findings suggest that when introducing AI technology, firms should focus on the synergy between intelligent tools and existing production systems to achieve sustainable innovation and development. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Smart manufacturing

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An Al Powered Exam Proctoring: Comprehensive Monitoring for Integrity

An Al Powered Exam Proctoring: Comprehensive Monitoring for ...

引用

2024 international conference on knowledge engineering and Communication systems, ICKECS 2024

作者： Mewada, Dhruv Gaikwad, Shlok Gharat, Bhavika Kamble, Priyanshu Vidyavardhini's College of Engineering and Technology Dept. of Artificial Intelligence&Data Science Mumbai India

ISBN: (纸本)9798350359688

In recent times, remote learning has experienced significant growth, yet the challenge of conducting academic examinations in a secure manner persists. Various approaches have been adopted by universities, such as collecting assignments susceptible to plagiarism or implementing remote proctoring with manual supervision. As our current lifestyle appears to be transitioning towards a new normal, it becomes imperative to explore effective solutions. This paper introduces a proposed remedy: the development of an AI-based integrated system designed to prevent cheating during examinations. The system not only detects fraudulent activities but also records evidence, ensuring both security and cost-effectiveness. © 2024 IEEE.

关键词： online tests proctoring remote learning

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Optimizing Job Shop Scheduling with Dynamic Arrivals using the Deep SOMs Approach

Optimizing Job Shop Scheduling with Dynamic Arrivals using t...

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2024 international conference on Distributed systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Swathi, Pabbati Margaret Indrani, S. Cynthiya Shukla, Swapnil Sheikameer Batcha, S. Khare, Surbhi R. Devi, S. Rukmani Annamacharya University Department of Cs India Sathyabama Institute of Science and Technology Department of Mathematics Chennai India Kalinga University Department of Mechanical Engineering Chhattisgarh Raipur India Sri Eshwar College of Engineering Department of Electrical and Electronics Engineering Coimbatore India Priyadarshini College of Engineering Department of Information Technology Nagpur India Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Chennai India

ISBN: (纸本)9798350375442

Modern manufacturing companies are more focused on serving the diverse demands of consumers in a timely manner, thanks to the exponential rise of globalization and information technology. Job shop manufacturing is characterized by a focus on small batches and a propensity toward producing a variety of products, which is why it has been an important production method for many industrial manufacturing enterprises. data preprocessing, model training, and feature selection are the three stages that make up this suggested method. Step one is preparing the data to make it more accurate and reliable;step two is changing the data's structure to make it more usable by machine learning algorithms. The concept of feature selection is based on the premise that features connected to individual fitness and its contribution to individuals are important. The use of a Deep SOM persisted throughout training. This novel method outperforms SOM and ELM with an average accuracy of 92.63%. © 2024 IEEE.

关键词： Self organizing maps

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A Low-Code Approach for data View Extraction from engineering Models with GraphQL

A Low-Code Approach for Data View Extraction from Engineerin...

引用

ACM/IEEE international conference on Model Driven engineering Languages and systems (MODELS)

作者： Koren, Istvan Jansen, Nico Michael, Judith Rumpe, Bernhard Boese, Enno Rhein Westfal TH Aachen Proc & Data Sci Aachen Germany Rhein Westfal TH Aachen Software Engn Aachen Germany Rhein Westfal TH Aachen Aachen Germany

ISBN: (纸本)9798350324983

Access to data for analysis and control tasks is at the heart of digitization efforts in the manufacturing industry. While sophisticated modeling languages like SysML describe systems and their components, data often ends up in purpose-built relational and time series databases. To generate value, information must be retrieved and integrated from multiple sources. In this paper, we propose an innovative method for leveraging SysML engineering models and database queries by combining them in a collaborative low-code web environment. First, we make heterogeneous databases available via GraphQL, a state-of-the-art approach for building Web APIs. Then, our web application enables domain experts to exploit containment relations in SysML models to connect diverse data sources. The outcome is an integrated GraphQL API that matches the engineering model structures by resembling views across multiple database sources. The discussed approach incorporates the benefits of data-oriented development and low-code platforms beyond the business automation domain.

关键词： Low-Code data Integration data-Driven Applications manufacturing Industry 4.0 Model-Driven Software engineering SysML engineering Models

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Student learning of engineering systems through simulation-based design using Onshape and Blender 5

Student learning of engineering systems through simulation-b...

引用

5th international conference on Industry 4.0 and Smart manufacturing (ISM)

作者： Verner, Igor Cuperman, Dan Mueller, Matthew Technion Israel Inst Technol IL-3200003 Haifa Israel PTC Inc 121 Seaport Blvd Boston MA 02210 USA

This study examines how the introductory engineering course can engage students in learning Industry 4.0 concepts and enhance their digital technology skills through simulation-based design activities. The students used cloud-based design and simulation tools to resolve a system operation problem. They examined the motion of a digital model of a satellite under micro -gravity conditions and detected its instability (Dzhanibekov effect). Then, they redesigned the model and verified its motion stability through simulation. The experimental setup combined the cloud-based CAD platform Onshape and the simulation software Blender. The students' performances, understanding, and perceptions were evaluated using conventional research tools and the data analytics tools of Onshape. Findings showed that the students successfully performed the workshop assignment, correctly answered the questions about the factors that cause motion instability and appreciated the contribution of the workshop. The study demonstrated the potential of online simulation-based design practices for educating novice engineering students.

关键词： Introductory engineering education simulation-based design cloud based CAD Onshape intermediate axis theorem

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Lean quality inspection and control technology for key components in high-end equipment manufacturing 4

Lean quality inspection and control technology for key compo...

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4th international conference on Testing Technology and Automation engineering, TTAE 2024

作者： Wang, Guangping Xu, Zhipeng Zeng, Longfei Li, Yunpeng Duan, Guijiang Company Ltd. Jingdezhen333001 China School of Mechanical Engineering and Automation Beihang University Beijing100191 China Jingdezhen Research Institute Beihang University Jingdezhen333000 China

ISBN: (数字)9781510686656

ISBN: (纸本)9781510686649

As manufacturing transitions toward digitization, there have been significant changes in the manufacturing process compared to traditional methods. However, quality control methods have not yet undergone a new transformation to adapt to the increasingly intelligent production methods. During the inspection planning phase, due to the transmission of two-dimensional paper-based information, inspection information becomes cluttered and lacks reusability. This leads to identification issues for inspectors regarding the inspection objects, resulting in false positives and missed defects. To prevent losses caused by false positives and missed defects, this article proposes a lean quality inspection and control model for critical components of high-end equipment during the inspection planning phase. The model utilizes the Model-Based Definition (MBD) as the information representation carrier and XML as the data storage and transmission method, bridging accurate data transfer across different systems. This provides model support for the manufacturing industry in improving inspection efficiency and reducing inspection planning costs. © 2024 SPIE.

关键词： Reusability

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data-fusion-based Patent Valuation: Discovering the Market Need (SCA) 36

Data-fusion-based Patent Valuation: Discovering the Market N...

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

作者： Bai, Zonghan Zhang, Ying Zhang, Shuqing College of Computer Science Inner Mongolia University Hohhot China Inner Mongolia Technical College of Construction Hohhot China

ISBN: (纸本)1891706594

As innovation-driven development becomes a global consensus, patent valuation has received increasing attention. However, the study of automatic patent valuation is still in its infancy, and traditional models cannot effectively estimate patent value. Since patent value is inherently linked to market needs, understanding market needs is crucial for patent valuation. Current challenges in patent valuation include: 1) Existing patent valuation models neglect market needs;2) Few disclosed patent value data are available. To solve these issues, we propose a data-fusion-based patent need valuation model to discover the market needs of patents, and calculate the need values of patents. Our model includes 2 modules: 1) Discovering market needs from annual reports and patents of listed companies and constructing a value heterogeneous network;2) Calculating the patent need values. In the experiments, we use our model to automatically extract the market needs, and calculate the need values. © 2024 knowledge systems Institute Graduate School. All rights reserved.

关键词： data fusion

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