{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:41:56Z","timestamp":1767339716189,"version":"3.37.3"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,2,6]],"date-time":"2021-02-06T00:00:00Z","timestamp":1612569600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,6]],"date-time":"2021-02-06T00:00:00Z","timestamp":1612569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1007\/s12652-021-02903-9","type":"journal-article","created":{"date-parts":[[2021,2,9]],"date-time":"2021-02-09T00:50:32Z","timestamp":1612831832000},"page":"313-327","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Optimal school site selection in Urban areas using deep neural networks"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7074-2988","authenticated-orcid":false,"given":"Nimra","family":"Zaheer","sequence":"first","affiliation":[]},{"given":"Saeed-Ul","family":"Hassan","sequence":"additional","affiliation":[]},{"given":"Mohsen","family":"Ali","sequence":"additional","affiliation":[]},{"given":"Mudassir","family":"Shabbir","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,6]]},"reference":[{"key":"2903_CR1","doi-asserted-by":"crossref","unstructured":"Achtert E, B\u00f6hm C, Kr\u00f6ger P, Kunath P, Pryakhin A, Renz M (2006) Efficient reverse k-nearest neighbor search in arbitrary metric spaces. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, SIGMOD \u201906, pages 515\u2013526, New York, NY, USA. ACM","DOI":"10.1145\/1142473.1142531"},{"key":"2903_CR2","doi-asserted-by":"crossref","unstructured":"Achtert E, Kriegel H-P, Kr\u00f6ger P, Renz M, Z\u00fcfle A (2009) Reverse k-nearest neighbor search in dynamic and general metric databases. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT \u201909, pages 886\u2013897, New York, NY, USA. ACM","DOI":"10.1145\/1516360.1516462"},{"key":"2903_CR3","first-page":"1","volume":"2","author":"BH Ahmed","year":"2020","unstructured":"Ahmed BH, Ghabayen AS (2020) Review rating prediction framework using deep learning. J Ambient Intell Hum Comput 2:1\u201310","journal-title":"J Ambient Intell Hum Comput"},{"key":"2903_CR4","doi-asserted-by":"crossref","unstructured":"Aksenova SS, Zhang D, Lu M (2006) Enrollment prediction through data mining. In: 2006 IEEE International Conference on Information Reuse Integration, pages 510\u2013515","DOI":"10.1109\/IRI.2006.252466"},{"key":"2903_CR5","doi-asserted-by":"crossref","unstructured":"Bamrah IS, Girdhar A (2015) Investigation on impact of reservation policy on student enrollment using data mining. In: 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pages 1\u20135","DOI":"10.1109\/ICCIC.2015.7435773"},{"key":"2903_CR6","doi-asserted-by":"crossref","unstructured":"Borah MD, Jindal R, Gupta D, Deka GC (2011) Application of knowledge based decision technique to predict student enrollment decision. In: 2011 International Conference on Recent Trends in Information Systems, pages 180\u2013184","DOI":"10.1109\/ReTIS.2011.6146864"},{"key":"2903_CR7","unstructured":"Cabello S, D\u00edaz-B\u00e1\u00f1ez JM, Langerman S, Seara C, Ventura I (2005) Reverse facility location problems. In: Conference on Computational Geometry"},{"key":"2903_CR8","unstructured":"Castillo VH, Equigua LS, \u00c1lvarez JL, Medina DAM (2013) Projecting school enrolments through an integral flow model. In: 2013 8th Iberian Conference on Information Systems and Technologies (CISTI), pages 1\u20134"},{"issue":"5","key":"2903_CR9","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1007\/s00778-012-0265-y","volume":"21","author":"MA Cheema","year":"2012","unstructured":"Cheema MA, Zhang W, Lin X, Zhang Y (2012) Efficiently processing snapshot and continuous reverse k nearest neighbors queries. VLDB J 21(5):703\u2013728","journal-title":"VLDB J"},{"key":"2903_CR10","first-page":"1","volume":"463\u2013464","author":"J Cui","year":"2018","unstructured":"Cui J, Wang M, Li H, Cai Y (2018) Place your next branch with mile-run: Min-dist location selection over user movement. Inf Sci 463\u2013464:1\u201320","journal-title":"Inf Sci"},{"key":"2903_CR11","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1007\/978-3-319-96890-2_20","volume-title":"Web and big data","author":"X Ding","year":"2018","unstructured":"Ding X, Zhang Y, Chen L, Gao Y, Zheng B (2018) Distributed k-nearest neighbor queries in metric spaces. In: Cai Y, Ishikawa Y, Xu J (eds) Web and big data. Springer International Publishing, Cham, pp 236\u2013252"},{"key":"2903_CR12","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/11535331_10","volume-title":"Advances in spatial and temporal databases","author":"Y Du","year":"2005","unstructured":"Du Y, Zhang D, Xia T (2005) The optimal-location query. In: Bauzer Medeiros C, Egenhofer MJ, Bertino E (eds) Advances in spatial and temporal databases. Springer, Berlin, pp 163\u2013180"},{"issue":"2","key":"2903_CR13","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/s10707-014-0215-5","volume":"19","author":"T Emrich","year":"2015","unstructured":"Emrich T, Kriegel H-P, Kr\u00f6ger P, Niedermayer J, Renz M, Z\u00fcfle A (2015) On reverse-k-nearest-neighbor joins. GeoInformatica 19(2):299\u2013330","journal-title":"GeoInformatica"},{"key":"2903_CR14","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.asoc.2018.05.024","volume":"70","author":"KM Ferreira","year":"2018","unstructured":"Ferreira KM, de Queiroz TA (2018) Two effective simulated annealing algorithms for the location-routing problem. Appl Soft Comput 70:389\u2013422","journal-title":"Appl Soft Comput"},{"issue":"1","key":"2903_CR15","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1007\/BF01840357","volume":"2","author":"S Fortune","year":"1987","unstructured":"Fortune S (1987) A sweepline algorithm for voronoi diagrams. Algorithmica 2(1):153","journal-title":"Algorithmica"},{"issue":"C","key":"2903_CR16","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.ins.2014.11.038","volume":"298","author":"Y Gao","year":"2015","unstructured":"Gao Y, Qi S, Chen L, Zheng B, Li X (2015) On efficient k-optimal-location-selection query processing in metric spaces. Inf Sci 298(C):98\u2013117","journal-title":"Inf Sci"},{"key":"2903_CR17","volume-title":"Deep learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press, Cambridge"},{"key":"2903_CR18","doi-asserted-by":"crossref","unstructured":"Grip RS, Grip ML (2019) Using multiple methods to provide prediction bands of k-12 enrollment projections. Population Research and Policy Review","DOI":"10.1007\/s11113-019-09533-2"},{"issue":"8","key":"2903_CR19","doi-asserted-by":"publisher","first-page":"860","DOI":"10.1016\/j.is.2010.05.002","volume":"35","author":"L Guohui","year":"2010","unstructured":"Guohui L, Yanhong L, Jianjun L, Shu L, Fumin Y (2010) Continuous reverse k nearest neighbor monitoring on moving objects in road networks. Inf Syst 35(8):860\u2013883","journal-title":"Inf Syst"},{"key":"2903_CR20","doi-asserted-by":"crossref","unstructured":"Huang J, Wen Z, Qi J, Zhang R, Chen J, He Z (2011) Top-k most influential locations selection. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM \u201911, pages 2377\u20132380, New York, NY, USA. ACM","DOI":"10.1145\/2063576.2063971"},{"key":"2903_CR21","doi-asserted-by":"crossref","unstructured":"Huang J-S, Chen B-Q, Zeng N-Y, Cao X-C, Li Y (2020) Accurate classification of ecg arrhythmia using mowpt enhanced fast compression deep learning networks. Journal of Ambient Intelligence and Humanized Computing. page inpress","DOI":"10.1007\/s12652-020-02110-y"},{"key":"2903_CR22","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.asoc.2017.10.035","volume":"62","author":"M Karatas","year":"2018","unstructured":"Karatas M, Yak\u0131c\u0131 E (2018) An iterative solution approach to a multi-objective facility location problem. Appl Soft Comput 62:272\u2013287","journal-title":"Appl Soft Comput"},{"issue":"2","key":"2903_CR23","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1145\/335191.335415","volume":"29","author":"F Korn","year":"2000","unstructured":"Korn F, Muthukrishnan S, Muthukrishnan S (2000) Influence sets based on reverse nearest neighbor queries. SIGMOD Rec 29(2):201\u2013212","journal-title":"SIGMOD Rec"},{"key":"2903_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.asoc.2019.02.016","volume":"78","author":"C-M Lai","year":"2019","unstructured":"Lai C-M (2019) Integrating simplified swarm optimization with ahp for solving capacitated military logistic depot location problem. Appl Soft Comput 78:1\u201312","journal-title":"Appl Soft Comput"},{"key":"2903_CR25","doi-asserted-by":"publisher","first-page":"105684","DOI":"10.1016\/j.asoc.2019.105684","volume":"84","author":"C-M Lai","year":"2019","unstructured":"Lai C-M, Chiu C-C, Liu W-C, Yeh W-C (2019) A novel nondominated sorting simplified swarm optimization for multi-stage capacitated facility location problems with multiple quantitative and qualitative objectives. Appl Soft Comput 84:105684","journal-title":"Appl Soft Comput"},{"key":"2903_CR26","doi-asserted-by":"crossref","unstructured":"Li S (2013) A 1.488 approximation algorithm for the uncapacitated facility location problem. Information and Computation 222:45\u201358. 38th International Colloquium on Automata, Languages and Programming (ICALP 2011)","DOI":"10.1016\/j.ic.2012.01.007"},{"key":"2903_CR27","doi-asserted-by":"crossref","unstructured":"Li D, Li H, Wang M, Cui J (2019) k-collective influential facility placement over moving object. In: 2019 20th IEEE International Conference on Mobile Data Management (MDM), pages 191\u2013200","DOI":"10.1109\/MDM.2019.00-57"},{"key":"2903_CR28","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.asoc.2018.10.012","volume":"74","author":"J Liu","year":"2019","unstructured":"Liu J, Liu J (2019) Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems. Appl Soft Comput 74:167\u2013189","journal-title":"Appl Soft Comput"},{"key":"2903_CR29","doi-asserted-by":"crossref","unstructured":"Lu J, Lu Y, Cong G (2011) Reverse spatial and textual k nearest neighbor search. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, pages 349\u2013360","DOI":"10.1145\/1989323.1989361"},{"key":"2903_CR30","doi-asserted-by":"crossref","unstructured":"Mitra S, Saraf P, Sharma R, Bhattacharya A, Ranu S (2019) Netclus: A scalable framework to mine top-k locations for placement of trajectory-aware services. In: Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, CoDS-COMAD \u201919, pages 27\u201335, New York, NY, USA. ACM","DOI":"10.1145\/3297001.3297005"},{"key":"2903_CR31","doi-asserted-by":"publisher","first-page":"105665","DOI":"10.1016\/j.asoc.2019.105665","volume":"83","author":"E Pekel","year":"2019","unstructured":"Pekel E, Kara SS (2019) Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search. Appl Soft Comput 83:105665","journal-title":"Appl Soft Comput"},{"key":"2903_CR32","first-page":"2","volume":"2","author":"S Prakash","year":"2020","unstructured":"Prakash S, Sangeetha K (2020) Deep multilayer and nonlinear kernelized lasso feature learning for healthcare in big data environment. J Ambient Intell Hum Comput 2:2","journal-title":"J Ambient Intell Hum Comput"},{"key":"2903_CR33","doi-asserted-by":"crossref","unstructured":"Qi J, Zhang R, Kulik L, Lin D, Xue Y (2012) The min-dist location selection query. In: 2012 IEEE 28th International Conference on Data Engineering, pages 366\u2013377","DOI":"10.1109\/ICDE.2012.45"},{"issue":"6","key":"2903_CR34","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1007\/s11280-013-0223-7","volume":"17","author":"J Qi","year":"2014","unstructured":"Qi J, Zhang R, Wang Y, Xue AY, Yu G, Kulik L (2014) The min-dist location selection and facility replacement queries. World Wide Web 17(6):1261\u20131293","journal-title":"World Wide Web"},{"key":"2903_CR35","doi-asserted-by":"crossref","unstructured":"Shang S, Yuan B, Deng K, Xie K, Zhou X (2011) Finding the most accessible locations: reverse path nearest neighbor query in road networks. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS \u201911, pages 181\u2013190, New York, NY, USA. ACM","DOI":"10.1145\/2093973.2093999"},{"key":"2903_CR36","unstructured":"Slim A, Hush D, Ojha T, Babbitt T (2018) Predicting student enrollment based on student and college characteristics. In: EDM"},{"key":"2903_CR37","doi-asserted-by":"crossref","unstructured":"Stallings R, Samanta B (2014) Prediction of university enrollment using computational intelligence. In: 2014 IEEE Symposium on Swarm Intelligence, pages 1\u20138","DOI":"10.1109\/SIS.2014.7011816"},{"key":"2903_CR38","unstructured":"Stanoi I, Riedewald M, Agrawal D, Abbadi AE (2001) Discovery of influence sets in frequently updated databases. In: Proceedings of the 27th International Conference on Very Large Data Bases, VLDB \u201901, page 99\u2013108, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc"},{"key":"2903_CR39","doi-asserted-by":"crossref","unstructured":"Sun Y, Zhang R, Xue AY, Qi J, Du X (2016) Reverse nearest neighbor heat maps: A tool for influence exploration. In: 2016 IEEE 32nd International Conference on Data Engineering (ICDE), pages 966\u2013977","DOI":"10.1109\/ICDE.2016.7498305"},{"key":"2903_CR40","doi-asserted-by":"crossref","unstructured":"Wang H, Wang H, Guo J, Feng H (2014) A fuzzy time series forecasting model based on yearly difference of the student enrollment number. In: 2nd International Conference on Soft Computing in Information Communication Technology. Atlantis Press","DOI":"10.2991\/scict-14.2014.41"},{"key":"2903_CR41","doi-asserted-by":"crossref","unstructured":"Wang M, Li H, Cui J, Deng K, Bhowmick SS, Dong Z (2017) Pinocchio: Probabilistic influence-based location selection over moving objects. In: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), pages 21\u201322","DOI":"10.1109\/ICDE.2017.17"},{"key":"2903_CR42","doi-asserted-by":"crossref","unstructured":"Wang Z, Wan Q, Qin Y, Fan S, Xiao Z (2020) Research on intelligent algorithm for alerting vehicle impact based on multi-agent deep reinforcement learning. Journal of Ambient Intelligence and Humanized Computing 1\u201311","DOI":"10.1007\/s12652-020-02198-2"},{"key":"2903_CR43","volume-title":"Theory of the location of industries","author":"A Weber","year":"1929","unstructured":"Weber A, Friedrich CJ (1929) Theory of the location of industries. University of Chicago Press, Reading"},{"key":"2903_CR44","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511921735","volume-title":"The design of approximation algorithms","author":"DP Williamson","year":"2011","unstructured":"Williamson DP, Shmoys DB (2011) The design of approximation algorithms, 1st edn. Cambridge University Press, Cambridge","edition":"1"},{"issue":"1","key":"2903_CR45","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.14778\/1687627.1687754","volume":"2","author":"RC-W Wong","year":"2009","unstructured":"Wong RC-W, \u00d6zsu MT, Yu PS, Fu AW-C, Liu L (2009) Efficient method for maximizing bichromatic reverse nearest neighbor. Proc. VLDB Endow 2(1):1126\u20131137","journal-title":"Proc. VLDB Endow"},{"issue":"6","key":"2903_CR46","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1007\/s00778-011-0230-1","volume":"20","author":"RC-W Wong","year":"2011","unstructured":"Wong RC-W, \u00d6zsu MT, Fu AW-C, Yu PS, Liu L, Liu Y (2011) Maximizing bichromatic reverse nearest neighbor for lp-norm in two- and three-dimensional spaces. VLDB J 20(6):893\u2013919","journal-title":"VLDB J"},{"key":"2903_CR47","unstructured":"Xia T, Zhang D, Kanoulas E, Du Y (2005) On computing top-t most influential spatial sites. In: Proceedings of the 31st International Conference on Very Large Data Bases, VLDB \u201905, pages 946\u2013957. VLDB Endowment"},{"key":"2903_CR48","doi-asserted-by":"crossref","unstructured":"Xiao X, Yao B, Li F (2011) Optimal location queries in road network databases. In: Proceedings of the 2011 IEEE 27th International Conference on Data Engineering, ICDE \u201911, pages 804\u2013815, Washington, DC, USA. IEEE Computer Society","DOI":"10.1109\/ICDE.2011.5767845"},{"issue":"12","key":"2903_CR49","doi-asserted-by":"publisher","first-page":"2796","DOI":"10.1109\/TKDE.2012.160","volume":"25","author":"C Xu","year":"2013","unstructured":"Xu C, Gu Y, Zimmermann R, Lin S, Yu G (2013) Group location selection queries over uncertain objects. IEEE Trans Knowl Data Eng 25(12):2796\u20132808","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2903_CR50","doi-asserted-by":"crossref","unstructured":"Yamunadevi M, Ranjani SS (2020) Efficient segmentation of the lung carcinoma by adaptive fuzzy-glcm (af-glcm) with deep learning based classification. Journal of Ambient Intelligence and Humanized Computing, page inpress","DOI":"10.1007\/s12652-020-01874-7"},{"key":"2903_CR51","doi-asserted-by":"crossref","unstructured":"Yan D, Wong RC-W, Ng W (2011) Efficient methods for finding influential locations with adaptive grids. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM \u201911, pages 1475\u20131484, New York, NY, USA. ACM","DOI":"10.1145\/2063576.2063788"},{"key":"2903_CR52","doi-asserted-by":"crossref","unstructured":"Yang S, Cheema MA, Lin X, Zhang Y (2014) Slice: reviving regions-based pruning for reverse k nearest neighbors queries. In: 2014 IEEE 30th International Conference on Data Engineering, pages 760\u2013771. IEEE","DOI":"10.1109\/ICDE.2014.6816698"},{"issue":"5","key":"2903_CR53","doi-asserted-by":"publisher","first-page":"605","DOI":"10.14778\/2735479.2735492","volume":"8","author":"S Yang","year":"2015","unstructured":"Yang S, Cheema MA, Lin X, Wang W (2015) Reverse k nearest neighbors query processing: experiments and analysis. Proc. VLDB Endow 8(5):605\u2013616","journal-title":"Proc. VLDB Endow"},{"issue":"2","key":"2903_CR54","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/s00778-016-0445-2","volume":"26","author":"S Yang","year":"2017","unstructured":"Yang S, Cheema MA, Lin X, Zhang Y, Zhang W (2017) Reverse k nearest neighbors queries and spatial reverse top-k queries. VLDB J 26(2):151\u2013176","journal-title":"VLDB J"},{"key":"2903_CR55","doi-asserted-by":"crossref","unstructured":"Yilmaz E, Elbasi S, Ferhatosmanoglu H (2017) Predicting optimal facility location without customer locations. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD \u201917, pages 2121\u20132130, New York, NY, USA. ACM","DOI":"10.1145\/3097983.3098198"},{"key":"2903_CR56","unstructured":"Zhang D, Du Y, Xia T, Tao Y (2006) Progressive computation of the min-dist optimal-location query. In: Proceedings of the 32Nd International Conference on Very Large Data Bases, VLDB \u201906, pages 643\u2013654. VLDB Endowment"},{"key":"2903_CR57","doi-asserted-by":"crossref","unstructured":"Zhu J, Liu W, Liu Y, Wang D, Qu S, Duan Y, Yao J (2020) Smart city oriented optimization of residential blocks on intensive urban sensing data based on fuzzy evaluation algorithm. Journal of Ambient Intelligence and Humanized Computing. page inpress","DOI":"10.1007\/s12652-020-02104-w"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-02903-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-021-02903-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-021-02903-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T18:44:52Z","timestamp":1643654692000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-021-02903-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,6]]},"references-count":57,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["2903"],"URL":"https:\/\/doi.org\/10.1007\/s12652-021-02903-9","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2021,2,6]]},"assertion":[{"value":"27 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 February 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}