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Summary of Airfoil Data. United States.\nAchour, Gabriel, Sung, Woong Je, Pinon-Fischer, Olivia J., Mavris, Dimitri N., 2020. Development of a Conditional Generative Adversarial Network for Airfoil Shape Optimization, page 2261.\nBonaiuti, 2010, Parametric design of a waterjet pump by means of inverse design, cfd calculations and experimental analyses, J. Fluids Eng., 132, 10.1115\u002F1.4001005\nBrown, 2019, Design variable analysis and generation for performance-based parametric modeling in architecture, Int. J. Archit. Comput., 17, 36\nBui-Thanh, 2004, Aerodynamic data reconstruction and inverse design using proper orthogonal decomposition, AIAA J., 42, 1505, 10.2514\u002F1.2159\nCao, 2005, Hydrodynamic design of rotodynamic pump impeller for multiphase pumping by combined approach of inverse design and cfd analysis, J. 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Auto-encoding variational bayes. arXiv:1312.6114.\nLee, 2010, System reliability-based design optimization using the mpp-based dimension reduction method, Comput. Methods Appl. Mech. Eng., 41, 823\nLi, 2020, Designing phononic crystal with anticipated band gap through a deep learning based data-driven method, Struct. Multidiscip. Optim., 361\nMirza, 2014\nNarducci, 1995, Sensitivity algorithms for an inverse design problem involving a shock wave, Inverse Probl. Eng., 2, 49, 10.1080\u002F174159795088027593\nNita, 2014, Film cooling hole shape optimization using proper orthogonal decomposition, GT2014\nNita, 2017\nPu, 2016, Variational autoencoder for deep learning of images, labels and captions, 2352\nSohn, 2015, Learning structured output representation using deep conditional generative models, 3483\nSong, 2019, Latent space expanded variational autoencoder for sentence generation, IEEE Access, 7, 144618, 10.1109\u002FACCESS.2019.2944630\nTan, 2020, A deep learning-based method for the design of microstructural materials, Struct. Multidiscip. Optim., 61, 1417, 10.1007\u002Fs00158-019-02424-2\nTolstikhin, Ilya, Bousquet, Olivier, Gelly, Sylvain, Schoelkopf, Bernhard, 2017. Wasserstein auto-encoders. arXiv:1711.01558.\nTortorelli, 1994, Design sensitivity analysis: overview and review, Inverse Probl. Eng., 1, 71, 10.1080\u002F174159794088027573\nXu, 2018, Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications, 187\nYonekura, 2019, Framework for design optimization using deep reinforcement learning, Struct. Multidiscip. Optim., 60, 1709, 10.1007\u002Fs00158-019-02276-w\nYonekura, 2021\nYonekura, 2021, Data-driven design exploration method using conditional variational autoencoder for airfoil design, Struct. Multidiscip. Optim., 64, 613, 10.1007\u002Fs00158-021-02851-0\nYonekura, 2014, A shape parameterization method using principal component analysis in application to shape optimization, J. Mech. Des., 136, 121401, 10.1115\u002F1.4028273\nYu, 2019, Deep learning for determining a near-optimal topological design without any iteration, Struct. Multidiscip. 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PROFIT optimizer (DQP) concepts and implementation course notes. Honeywell Training Document.\nAnonymous, 2002. HYSYS.RTO reference guide. Hyprotech, a subsidiary of Aspen Technology, Inc.\nBillington, P., Krøger, D., 2000. Verification of the process control system for the Åsgard B mono-ethylene-glycol (MEG) regeneration module using HYSYS.plant, dynamic simulation software.” Hyprotech 2000, Amsterdam, The Netherlands.\nDowns, 1993, A plant-wide industrial process control problem, Computers and Chemical Engineering, 17, 245, 10.1016\u002F0098-1354(93)80018-I\nDuvall, 2000, On-line optimization of the Tennessee Eastman challenge problem, Journal of Process Control, 10, 19, 10.1016\u002FS0959-1524(99)00041-4\nForbes, 1996, Design cost: a systematic approach to technology selection for model based real-time optimization, Computers and Chemical Engineering, 20, 717, 10.1016\u002F0098-1354(95)00205-7\nGelb, 1974\nGolshan. M., 2005. Real time optimization of chemical processes. Master thesis, Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran.\nGolshan, 2005, A new approach to real time optimization of the Tennessee Eastman challenge problem, Chemical Engineering Journal, 112, 33, 10.1016\u002Fj.cej.2005.06.005\nHowell, A., Hanson, K., Dhole, V., Sim, W., 2002. Engineering to business: Optimizing asset utilization through process engineering. www.cepmagazine.org, September, CEP, 54–63.\nJavari, M.M., 1999. Plant-wide non-linear control of a chemical process. Master thesis, Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran.\nJokenhovel, 2003, Dynamic optimization of the Tennessee Eastman process using optcontrolcentre, Computers and Chemical Engineering, 27, 1513, 10.1016\u002FS0098-1354(03)00113-3\nLarson, 2001, Self optimizing control of a large scale plant: the Tennessee Eastman process, Industrial and Engineering Chemical Research, 40, 4889, 10.1021\u002Fie000586y\nLee, 1994, Extended Kalman filter based non-linear model predictive control, Industrial and Engineering Chemical Research, 33, 1530, 10.1021\u002Fie00030a013\nLi, 1998, Heuristic random optimization, Computers and Chemical Engineering, 22, 427, 10.1016\u002FS0098-1354(97)00005-7\nMcAvoy, 1994, Base control for the Tennessee Eastman problem, Computers and Chemical Engineering, 18, 383, 10.1016\u002F0098-1354(94)88019-0\nNelder, 1965, A simplex method for function minimization, Computer Journal, 7, 308, 10.1093\u002Fcomjnl\u002F7.4.308\nRao, S.S., 2002. Engineering Optimization, Theory and Practice. New Age International Publishers.\nRicker, 1995, Optimal steady state operation of the Tennessee Eastman challenge process, Computers and Chemical Engineering, 19, 949, 10.1016\u002F0098-1354(94)00043-N\nRicker, 1995, Nonlinear modeling and state estimation for the Tennessee Eastman challenge process, Computers and Chemical Engineering, 19, 983, 10.1016\u002F0098-1354(94)00113-3",{"EN":278},"Stochastic and global real time optimization of Tennessee Eastman challenge problem",{"VOID":280},"10.1016\u002Fj.engappai.2007.04.004","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0952197607000504",[283,300,312],{"id":284,"sortIndex":19,"researcher":18,"roles":285,"affiliations":286,"properties":297},"88c45720-7f75-4136-bbce-3aa763210806",[137],[287],{"id":18,"sortIndex":19,"affiliation":288,"properties":18},{"id":289,"createTime":290,"updateTime":291,"relativeEntities":292,"slug":293,"properties":294,"entityType":55,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"aaf83ad2-b350-4d7c-82a1-c7f380a9af9a","2024-01-20T01:09:06.180+00:00","2025-02-06T18:43:44.619+00:00",[],"Department-of-Chemical-and-Petroleum-Engineering-Sharif-University-of-Technology-Tehran-Iran",{"title":295},{"VI":296},"Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran",{"title":298},{"VI":299},"Masoud Golshan",{"id":301,"sortIndex":201,"researcher":18,"roles":302,"affiliations":303,"properties":309},"4c2efc2d-f549-497d-9df1-65ffb17e2951",[137],[304],{"id":18,"sortIndex":19,"affiliation":305,"properties":18},{"id":289,"createTime":290,"updateTime":291,"relativeEntities":306,"slug":293,"properties":307,"entityType":55,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":308},{"VI":296},{"title":310},{"VI":311},"Mahmoud Reza Pishvaie",{"id":313,"sortIndex":217,"researcher":18,"roles":314,"affiliations":315,"properties":321},"cbb4a868-774f-43d4-be90-b24635c07a45",[137],[316],{"id":18,"sortIndex":19,"affiliation":317,"properties":18},{"id":289,"createTime":290,"updateTime":291,"relativeEntities":318,"slug":293,"properties":319,"entityType":55,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":320},{"VI":296},{"title":322},{"VI":323},"Ramin Bozorgmehry Boozarjomehry",{"url":281,"publisher":325,"properties":347},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":326,"slug":10,"properties":327,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":330,"manageAffiliations":331,"indexDatabases":332,"url":18,"thumbnailPath":18,"statistic":18,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":328,"title":329},{"VOID":13},{"EN":15},[],[],[333,340],{"id":92,"indexDatabase":334,"url":105,"indexYears":106,"academicFieldIds":339,"indexDatabaseRanking":111},{"id":94,"createTime":95,"updateTime":96,"relativeEntities":335,"label":336,"description":337,"key":102,"publicationTags":338,"standard":18},[],{"EN":99,"VI":99},{"EN":99,"VI":101},[104],[108,109,110],{"id":71,"indexDatabase":341,"url":86,"indexYears":18,"academicFieldIds":346,"indexDatabaseRanking":18},{"id":73,"createTime":74,"updateTime":75,"relativeEntities":342,"label":343,"description":344,"key":82,"publicationTags":345,"standard":18},[],{"EN":78,"VI":78},{"VI":80,"EN":81},[84,85],[88,89,90],{"volume":348,"pages":350},{"VOID":349},"21",{"VOID":351},"215-228","2008-03-01",2008,{"id":355,"createTime":356,"updateTime":356,"relativeEntities":357,"slug":18,"properties":358,"entityType":129,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":365,"fullTextUrl":18,"authors":366,"publicationType":152,"publisherRelationship":431,"citationCount":18,"citationInfo":18,"publishDate":459,"publishYear":460,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":18,"openAccess":18,"references":18,"isForceReanalyzing":183},"544aa4a9-0746-4979-bd0e-a53fa7a169f8","2024-01-19T23:58:06.086+00:00",[],{"references":359,"title":361,"doi":363},{"VOID":360},"Akbarinia, 2018, Feedback and surround modulated boundary detection, Int. 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Health Technol. Inform., 108, 253\nPatel, 2012, A review of wearable sensors and systems with application in rehabilitation, J. Neuroeng. Rehabil., 9, 1, 10.1186\u002F1743-0003-9-21\nRDF 1.1 N-Triples, 2014. A line-based syntax for an RDF graph W3C Recommendation, https:\u002F\u002Fwww.w3.org\u002FTR\u002Fn-triples\u002F.\nRienzo, M.D., Rizzo, F., Meriggi, P., Bordoni, B., Brambilla, G., Ferratini, M., Castiglioni, P., 2006. Applications of a textile-based wearable system for vital signs monitoring. In: Engineering in Medicine and Biology Society, 2006. EMBS’06. 28th Annual International Conference of the IEEE, pp. 2223–2226.\nRoy, N., Pallapa, G., Das, S.K., 2007. A middleware framework for ambiguous context mediation in smart healthcare application. In: Wireless and Mobile Computing, Networking and Communications, 2007. WiMOB 2007. 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