{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T17:58:53Z","timestamp":1774547933581,"version":"3.50.1"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61833004"],"award-info":[{"award-number":["61833004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U20A20189"],"award-info":[{"award-number":["U20A20189"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61991401"],"award-info":[{"award-number":["61991401"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenyang Innovation Program in Sciences and Technologies for Young and Middle-aged Scientists","award":["RC190443"],"award-info":[{"award-number":["RC190443"]}]},{"DOI":"10.13039\/501100018617","name":"Liaoning Revitalization Talents Program","doi-asserted-by":"publisher","award":["XLYC1907049"],"award-info":[{"award-number":["XLYC1907049"]}],"id":[{"id":"10.13039\/501100018617","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Automat. Sci. Eng."],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1109\/tase.2021.3124015","type":"journal-article","created":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T22:38:27Z","timestamp":1636583907000},"page":"3471-3482","source":"Crossref","is-referenced-by-count":18,"title":["Semi-Supervised Condition Monitoring and Visualization of Fused Magnesium Furnace"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3537-8620","authenticated-orcid":false,"given":"Shaowen","family":"Lu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yixin","family":"Wen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"The future of manufacturing","author":"Gorajia","year":"2019"},{"key":"ref2","article-title":"Digital twin+industrial internet for smart manufacturing: A case study in the steel industry","author":"Lin","year":"2019","journal-title":"IIC J. Innov."},{"key":"ref3","volume-title":"Industry 4.0 and the Digital Twin: Manufacturing Meets Its Match","year":"2017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-38756-7_4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2873186"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/pr7080537"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.engfailanal.2020.104517"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103277"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3390\/designs3030045"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/COASE.2019.8843166"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.promfg.2017.07.094"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.2514\/1.J055201"},{"key":"ref13","volume-title":"Digital twin: Manufacturing excellence through virtual factory replication","author":"Grieves","year":"2015"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2349479"},{"issue":"9","key":"ref15","first-page":"1","article-title":"Online detection of semi-molten of fused magnesium furnace based on deep convolutional neural network","volume":"23","author":"Lu","year":"2017","journal-title":"Control Decis."},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCA.2019.8899693"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2021.3070512"},{"issue":"9","key":"ref18","first-page":"1565","article-title":"Conditions recognition of fused magnesia furnace based on flame dynamic texture","volume":"36","author":"Zhao","year":"2019","journal-title":"Control Theory Appl."},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3042464"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9780262033589.001.0001"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/279943.279962"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065703001522"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS.2016.0165"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2019.2918562"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2911979"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICPHYS.2018.8390780"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/RWEEK.2018.8473535"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/34.667881"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2012.2230332"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.05.005"},{"issue":"1","key":"ref31","first-page":"233","article-title":"Mid-low resolution vehicle type recognition based on deep feature fusion","volume":"45","author":"Xue","year":"2019","journal-title":"Comput. Eng."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1002\/9780470027318.a8106"},{"issue":"2","key":"ref33","first-page":"153","article-title":"A dynamic flame image segmentation method and its application in video monitoring of fused magnesium furnace process","volume":"40","author":"Lu","year":"2019","journal-title":"J. Northeastern Univ., Natural Sci."},{"key":"ref34","first-page":"529","article-title":"Semi-supervised learning by entropy minimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Grandvalet"},{"key":"ref35","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-4321-0","volume-title":"The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning","author":"Rubinstein","year":"2004"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/38.946629"}],"container-title":["IEEE Transactions on Automation Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8856\/9918179\/09610130.pdf?arnumber=9610130","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T23:44:59Z","timestamp":1705016699000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9610130\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":36,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tase.2021.3124015","relation":{},"ISSN":["1545-5955","1558-3783"],"issn-type":[{"value":"1545-5955","type":"print"},{"value":"1558-3783","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10]]}}}