Concurrent Engineering-Research and Applications最新文献

筛选
英文 中文
Deep learning based fusion model for COVID-19 diagnosis and classification using computed tomography images 基于深度学习的计算机断层图像诊断与分类融合模型
4区 工程技术
Concurrent Engineering-Research and Applications Pub Date : 2021-06-09 DOI: 10.1177/1063293X211021435
R.T.Subhalakshmi, S. Balamurugan, S. Sasikala
{"title":"Deep learning based fusion model for COVID-19 diagnosis and classification using computed tomography images","authors":"R.T.Subhalakshmi, S. Balamurugan, S. Sasikala","doi":"10.1177/1063293X211021435","DOIUrl":"https://doi.org/10.1177/1063293X211021435","url":null,"abstract":"Recently, the COVID-19 pandemic becomes increased in a drastic way, with the availability of a limited quantity of rapid testing kits. Therefore, automated COVID-19 diagnosis models are essential to identify the existence of disease from radiological images. Earlier studies have focused on the development of Artificial Intelligence (AI) techniques using X-ray images on COVID-19 diagnosis. This paper aims to develop a Deep Learning Based MultiModal Fusion technique called DLMMF for COVID-19 diagnosis and classification from Computed Tomography (CT) images. The proposed DLMMF model operates on three main processes namely Weiner Filtering (WF) based pre-processing, feature extraction and classification. The proposed model incorporates the fusion of deep features using VGG16 and Inception v4 models. Finally, Gaussian Naïve Bayes (GNB) based classifier is applied for identifying and classifying the test CT images into distinct class labels. The experimental validation of the DLMMF model takes place using open-source COVID-CT dataset, which comprises a total of 760 CT images. The experimental outcome defined the superior performance with the maximum sensitivity of 96.53%, specificity of 95.81%, accuracy of 96.81% and F-score of 96.73%.","PeriodicalId":55213,"journal":{"name":"Concurrent Engineering-Research and Applications","volume":"7 1","pages":"116 - 127"},"PeriodicalIF":0.0,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79475373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Using formal methods to scope performance challenges for Smart Manufacturing Systems: focus on agility. 使用形式化方法确定智能制造系统性能挑战的范围:关注敏捷性。
4区 工程技术
Concurrent Engineering-Research and Applications Pub Date : 2015-12-01 DOI: 10.1177/1063293X15603217
Kiwook Jung, K C Morris, Kevin W Lyons, Swee Leong, Hyunbo Cho
{"title":"Using formal methods to scope performance challenges for Smart Manufacturing Systems: focus on agility.","authors":"Kiwook Jung, K C Morris, Kevin W Lyons, Swee Leong, Hyunbo Cho","doi":"10.1177/1063293X15603217","DOIUrl":"10.1177/1063293X15603217","url":null,"abstract":"<p><p>Smart Manufacturing Systems (SMS) need to be agile to adapt to new situations by using detailed, precise, and appropriate data for intelligent decision-making. The intricacy of the relationship of strategic goals to operational performance across the many levels of a manufacturing system inhibits the realization of SMS. This paper proposes a method for identifying what aspects of a manufacturing system should be addressed to respond to changing strategic goals. The method uses standard modeling techniques in specifying a manufacturing system and the relationship between strategic goals and operational performance metrics. Two existing reference models related to manufacturing operations are represented formally and harmonized to support the proposed method. The method is illustrated for a single scenario using agility as a strategic goal. By replicating the proposed method for other strategic goals and with multiple scenarios, a comprehensive set of performance challenges can be identified.</p>","PeriodicalId":55213,"journal":{"name":"Concurrent Engineering-Research and Applications","volume":"23 4","pages":"343-354"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4850556/pdf/nihms763031.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34451933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信