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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4861-4870 订阅

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Energy Efficiency for manufacturing Using PV, FSC, and Battery-Super Capacitor Design to Enhance Sustainable Clean Energy Load Demand 31st

Energy Efficiency for Manufacturing Using PV, FSC, and Batte...

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31st international conference on Flexible Automation and Intelligent manufacturing, FAIM 2022

作者： Adenuga, Olukorede Tijani Mpofu, Khumbulani Mathenjwa, Thobelani Tshwane University of Technology Staartsartillirie Rd Pretoria West Pretoria0183 South Africa

ISBN: (纸本)9783031183256

Energy efficiency (EE) are recognized globally as a critical solution towards reduction of energy consumption, while the management of global carbon dioxide emission complement climate change. EE initiatives drive is a key factor towards climate change mitigation with variable renewable technologies. The paper aimed to design and simulate photovoltaic (PV), fuel cell stack (FCS) systems, and battery-super capacitor energy storage to enhance sustainable clean energy load demand and provide significant decarbonization potentials. An integration of high volume of data in real-time was obtained and energy mix fraction towards low carbon emission mitigation pathway strategy for grid linked renewables electricity generation was proposed as a solution for the future transport manufacturing energy supplement in South Africa. The interrelationship between energy efficiency and energy intensity variables are envisaged to result in approximately 87.6% of global electricity grid production;electricity energy demand under analysis can reduce the CO2 emissions by 0.098 metric tons and CO2 savings by 99.587 per metric tons. The scope serves as a fundamental guideline for future studies in the future transport manufacturing with provision of clean energy and sufficient capacity to supply the demand for customers within the manufacturing. © 2023, The Author(s).

关键词： Energy efficiency

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A Multiple-Blockchains based Service Monitoring Framework in Edge-Cloud Computing 23

A Multiple-Blockchains based Service Monitoring Framework in...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on data Science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Fu, Hang Wang, Puwei Li, Haoran Zhan, Ying Chen, Jinchuan Du, Xiaoyong Guizhou University of Finance and Economics Guiyang City550025 China School of Information Renmin University of China China Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Beijing100872 China

ISBN: (纸本)9781665494571

In the edge-cloud computing, the applications usually are delivered as services, each of which runs independently and can cooperate to construct the complicated applications. However, it is difficult to monitor the services in the decentralized edge-cloud environment since there usually does not exist the central authorization to guarantee trustiness of the service quality data collected. To address the trust issue, the blockchain techniques have been introduced to the service monitoring. Considering the services usually are distributed on the edge nodes, if we deploy only a blockchain on the edge nodes near to the services, it may have to support both the service registration and monitoring because of the loose-coupling principle. That would influence the performance, even would crash the edge nodes. In this paper, we propose a multiple-blockchains based framework, including a registration blockchain that focuses on the service registration and discovery, and a set of monitoring blockchains that focus on the service invocation and monitoring. The registration blockchain is deployed on the cloud nodes, and the monitoring blockchains are deployed on the edge nodes near to the services for collecting efficiently and precisely the service quality data. Based on the cross-chain technology, we design a cross-chain service discovery between the monitoring blockchain and the registration blockchain for finding the services the requesters need. Finally, we implement the registration and monitoring blockchains based on the blockchain platform Cosmos and conduct a set of experiments to show the effectiveness of the proposed framework. © 2021 IEEE.

关键词： Authorization Cloud computing Smart cities Computer crashes Blockchains Monitoring

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Enhancing Social Media Engagement Sentiment Prediction: A Random Forest and SMOTE-Based Approach with Explainable AI 3rd

Enhancing Social Media Engagement Sentiment Prediction: A Ra...

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3rd international conference on Advances in Computing Research, ACR 2025

作者： Al-Quraishi, Tahsien Zaboon, Waseem Alwan Mahdi, Osama A. Naghavipour, Hadi Aburghif, Hsham School of IT Victorian Institute of Technology Melbourne Australia Mechanical Engineering Department College of Engineering Wasit University Kut Iraq School of IT Melbourne Institute of Technology Melbourne Australia School of Business Victorian Institute of Technology Melbourne Australia

ISBN: (纸本)9783031876462

Understanding and predicting user engagement and behaviour requires sentiment analysis. The main objectives of this study were to enhance the Random Forest (RF) algorithm for sentiment prediction in social media engagement, apply synthetic minority oversampling technique (SMOTE) to address class imbalance in the dataset, and utilise SHapley Additive ExPlanations (SHAP) for model interpretability. Unlike conventional methods targeted at text data, this research incorporates engagement metrics and demography for improved results in prediction accuracy and additional knowledge. This research differs from the existing models, both in its multi-faceted approach, combining RF, demographic metrics, and explainable artificial intelligence (XAI) to boost interpretability and address the limitations of previous models. Our results outperform existing studies in accuracy and provide actionable explanations behind decision-making. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Emotion Recognition

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MUT: Human-in-the-Loop Unit Test Migration 24

MUT: Human-in-the-Loop Unit Test Migration

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44th ACM/IEEE international conference on Software engineering, ICSE 2024

作者： Gao, Yi Hu, Xing Xu, Tongtong Xia, Xin Lo, David Yang, Xiaohu Zhejiang University The State Key Laboratory of Blockchain and Data Security Hangzhou China Huawei Hangzhou China School of Computing and Information Systems Singapore Management University Hangzhou China

ISBN: (纸本)9798400702174

Test migration, which enables the reuse of test cases crafted with knowledge and creativity by testers across various platforms and programming languages, has exhibited effectiveness in mobile app testing. However, unit test migration at the source code level has not garnered adequate attention and exploration. In this paper, we propose a novel cross-language and cross-platform test migration methodology, named MUT, which consists of four modules: code mapping, test case filtering, test case translation, and test case adaptation. MUT initially calculates code mappings to establish associations between source and target projects, and identifies suitable unit tests for migration from the source project. Then, MUT's code translation component generates a syntax tree by parsing the code to be migrated and progressively converts each node in the tree, ultima tely generating the target tests, which are compiled and executed in the target project. Moreover, we develop a web tool to assist developers in test migration. The effectiveness of our approach has been validated on five prevalent functional domain projects within the open-source community. We migrate a total of 550 unit tests and submitted pull requests to augment test code in the target projects on GitHub. By the time of this paper submission, 253 of these tests have already been merged into the projects (including 197 unit tests in the Luliyucoordinate-LeetCode project and 56 unit tests in the Rangerlee-HtmlParser project). Through running these tests, we identify 5 bugs, and 2 functional defects, and submitted corresponding issues to the project. The evaluation substantiates that MUT's test migration is both viable and beneficial across programming languages and different projects. © 2024 ACM.

关键词： Mapping

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Business Ecosystem Management : A Model for the Governance, Auditing and Design of Business Ecosystems

Business Ecosystem Management : A Model for the Governance, ...

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2022 Portland international conference on Management of engineering and Technology, PICMET 2022

作者： Humbeck, P. Loeffler, H.T. Bauernhansl, T. Graduate School of Excellence Advanced Manufacturing Engineering Nobelstr. 12 Stuttgart70569 Germany Trumpf Werkzeugmaschinen GmbH + Co. Kg Johann-Maus-Str. 2 Ditzingen71254 Germany Fraunhofer Institute for Manufacturing Engineering and Automation Ipa Nobelstr. 12 Stuttgart70569 Germany Institute of Industrial Manufacturing and Management Iff Nobelstr. 12 Stuttgart70569 Germany

ISBN: (数字)9781890843410

ISBN: (纸本)9781890843410

Current trends such as the increasing commoditization of hardware and the growing generation of customer benefits through software-based services are forcing companies in the mechanical and plant engineering industry to develop innovative Smart Product-Service systems (PSS) based on new business models. The associated increasing complexity requires the integration of new competencies and resources. This leads to a transformation of individually acting companies to inter-organizational business ecosystems. However, since traditional product-oriented companies in the mechanical and plant engineering industry do not have enough awareness or knowledge about the management of business ecosystems, a management model is required. The goal of this paper is to design a model for the management of business ecosystems within the development of Smart PSS. For this purpose, a comprehensive literature review was conducted in which existing approaches were identified. Subsequently, these were evaluated according to defined criteria and the necessary components were derived, as the basis for the created model. The model should enable orchestrating companies to design, audit and govern the business ecosystem with the help of three modules. The model contains methods for practical application and considers the different characteristics of a business ecosystem over its life cycle. © 2022 PICMET.

关键词： Life cycle

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Detection of Small Screws Using Machine Learning 5

Detection of Small Screws Using Machine Learning

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5th international conference on Information and Communication Technology for Development for Africa, ICT4DA 2023

作者： Ambaye, Getachew Krishnan, Krishna Boldsaikhan, Enkhsaikhan Wichita State University Industrial Systems and Manufacturing Engineering Wichita United States

ISBN: (纸本)9798350328486

Small screws are commonly employed in assenrbling similar or dissimilar components of various industrial or consumer products. In automated assembly lines, detecting and sorting small targets like screws require accurate sensing and machine learning. Identifying the size of the screw is crucial for assembling and disassembling. This study focuses on the detection of small screws captured in images using a recent machine learning platform named You Only Look Once (YOLO) Version 8. This algorithmic platform offers powerful supervised machine-learning engines with highly competitive accuracy and speed. The data set from this study consists of images of small black carbon steel flat head screws. The dataset is divided into training, development, and testing subsets. There are 24 classes of screws with extremely small difference in attributes in their sizes. The dataset is annotated using the Make Sense open-source annotating tool. The results indicate that the machine learning method demonstrates 99.3% mean average precision (mAP). This detection performance is promising in comparison to the results documented by previous studies. © 2023 IEEE.

关键词： Computer vision

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Application of TRIZ theory in optimization design of end tooling for large automotive parts 2

Application of TRIZ theory in optimization design of end too...

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2024 2nd international conference on Materials Science and Intelligent manufacturing, MSIM 2024

作者： Du, Hao-Yu Liu, Shang Wu, Han Guo, Xiao-Xia Wang, Peng-Fei Zhu, Yu-Hang Wang, Yu-Hao School of Mechanical and Electrical Engineering Qiqihar University Heilongjiang Qiqihar China School of Mechanical and Electrical Engineering Harbin Institute of Technology Heilongjiang Harbin China

In the process of automobile final assembly, auxiliary assembly end tooling is often designed on the key stations to ensure the quality and efficiency of the production line. This study applies TRIZ theory and scenario analysis methods to solve the potential fault problems in the design and development stage of end tooling products to provide more reliable and high-quality products or systems. Through Ansys Workbench, the proposed scheme is simulated and optimized to verify the feasibility of the end tooling product design. Implementing this research method will help effectively deal with the challenges faced by heavy lifting in modern industrial production and improve production efficiency and operation safety. © Published under licence by IOP Publishing Ltd.

关键词： Production efficiency

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Collaborating Between the Construction Office and the Construction Site Under Collaborative Contracts

Collaborating Between the Construction Office and the Constr...

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international conference of Sustainable Development and Smart Built Environments, SDSBE 2024

作者： Gharouni Jafari, Kobra Mottee, Lara Whyte, Jennifer School of Project Management Faculty of Engineering University of Sydney SydneyNSW2037 Australia John Grill Institute for Project Leadership Faculty of Engineering University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)9789819640508

During the construction phase, collaboration among project parties involved in the contract is a crucial factor for effectively delivering infrastructure projects. Yet, while researchers have assumed that implementing collaborative contracts will enhance collaboration, practically, there is evidence this is not always the case. This research investigates the challenges and opportunities of collaboration between organizations across the "office" and the "site" through a qualitative study of Australian water infrastructure projects utilizing collaborative contracts. To ensure a more focused approach to data collection and analysis, this research specifically examines the collaboration between clients and contractors among all organizations involved in office-based and onsite practices. By analyzing interviews with experts involved in these projects, the findings reveal three main areas where challenges and opportunities arise in collaboration under collaborative contracts during construction: contract implementation, collaboration competencies, and systems and processes. This research enriches the knowledge body by providing deeper insights into the distinct collaboration challenges and opportunities to address change events. While interviewees generally appreciate the opportunities provided by the contractual framework, they also highlighted specific challenges they faced in this area. However, they primarily struggle with issues related to collaboration competencies and systems and processes across the office and the site. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Construction

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Relation Based knowledge Extraction for Animal Farm Management

Relation Based Knowledge Extraction for Animal Farm Manageme...

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international IEEE conference on Intelligent systems, IS

作者： Boriana Vatchova Yordanka Boneva Alexander Gegov Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria School of Computing University of Portsmouth Portsmouth United Kingdom English Faculty of Engineering Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

This paper presents an application of a knowledge extraction method developed by the authors to animal farm management. The main purpose of the paper is to process information on the relationships between profits and costs in livestock farming. The paper uses expert knowledge as a benchmark approach for knowledge extraction and a fuzzy method for comparative validation. The academic novelty in the paper is the first-time application of the relation based knowledge extraction method to livestock farming.

关键词： Fuzzy logic Costs Benchmark testing Livestock data mining Intelligent systems Farming

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Battery manufacturing knowledge infrastructure requirements for multicriteria optimization based decision support in design of simulation 1

Battery manufacturing knowledge infrastructure requirements ...

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1st international Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science, SeMatS 2024

作者： Horsch, Martin Thomas Romanov, Dmytro Valseth, Eirik Belouettar, Salim López, Luis Eduardo Córdova Glutting, Johanna Janssen, Mathijs A. Klein, Peter Linhart, Andreas Seaton, Michael A. Sødahl, Elin D. Vizcaino, Noel Werth, Stephan Stephan, Simon Todorov, Ilian T. Chiacchiera, Silvia Al Machot, Fadi Norwegian University of Life Sciences Faculty of Science and Technology Postboks 5003 Ås1432 Norway UK Research and Innovation STFC Daresbury Laboratory Computational Chemistry Group DaresburyWA4 4AD United Kingdom Simula Research Laboratory AS Kristian Augusts gate 23 Oslo0164 Norway Luxembourg Institute of Science and Technology Avenue des Hauts-Fourneaux 5 Esch-sur-Alzette4362 Luxembourg Kaiserslautern University of Applied Sciences Faculty of Applied Engineering Sciences Kaiserslautern67659 Germany Fraunhofer Institute for Industrial Mathematics Fraunhoferplatz 1 Kaiserslautern67663 Germany VANEVO GmbH Johann-Hinrich-Engelbart-Weg 2 Oldenburg26131 Germany RPTU Kaiserslautern Department of Mechanical and Process Engineering Postfach 3049 Kaiserslautern67653 Germany

This position paper reports on the requirements analysis within the project Battery Cell Assembly Twin (BatCAT), which develops a digital twin for battery manufacturing. The focus is on the aspects of this work that are at the intersection between semantic web technology and materials science and engineering, specifically, the co-design of the architecture of the semantic interoperability layer and the decision support system (DSS). First, visions and ideas are provided on how the architecture will look, and what technology and previous work it will be based on. Key elements to this include, on the side of the semantic technology, the Meta Object Facility (MOF) with the OntoCommons ecosystem as a meta-metamodel (MOF M3 level), a system of ontologies with OWL EL or RL expressivity as a metamodel (MOF M2 level), and a MOF M1-level model based on OO-LD. On the side of the DSS, answer set programming will be combined with multicriteria optimization (MCO), such that MCO can be applied to model parameterization and design of simulation to make best use of computational resources and data. © 2024 CEUR-WS. All rights reserved.

关键词： Decision support systems

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