{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T02:10:35Z","timestamp":1773195035409,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T00:00:00Z","timestamp":1564704000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T00:00:00Z","timestamp":1564704000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["71433003"],"award-info":[{"award-number":["71433003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["51669014"],"award-info":[{"award-number":["51669014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Science Fund for Distinguished Young Scholars of Jiangxi Province","award":["2018ACB21029"],"award-info":[{"award-number":["2018ACB21029"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Sign Process Syst"],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1007\/s11265-019-01459-4","type":"journal-article","created":{"date-parts":[[2019,8,2]],"date-time":"2019-08-02T10:47:54Z","timestamp":1564742874000},"page":"1219-1236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Density Peak Clustering Based on Cumulative Nearest Neighbors Degree and Micro Cluster Merging"],"prefix":"10.1007","volume":"91","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5186-3848","authenticated-orcid":false,"given":"Lizhong","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhanfeng","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiye","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,2]]},"reference":[{"issue":"7","key":"1459_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-018-9729-5","volume":"62","author":"Z Cui","year":"2019","unstructured":"Cui, Z., Zhang, J., Wang, Y., Cao, Y., Cai, X., Zhang, W., & Chen, J. (2019). A pigeon-inspired optimization algorithm for many-objective optimization problems[J]. SCIENCE CHINA Information Sciences, 62(7), 070212. \nhttps:\/\/doi.org\/10.1007\/s11432-018-9729-5\n\n.","journal-title":"SCIENCE CHINA Information Sciences"},{"issue":"2","key":"1459_CR2","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/s12293-017-0237-2","volume":"10","author":"M Zhang","year":"2018","unstructured":"Zhang, M., Wang, H., Cui, Z., et al. (2018). Hybrid multi-objective cuckoo search with dynamical local search[J]. Memetic Computing, 10(2), 199\u2013208.","journal-title":"Memetic Computing"},{"key":"1459_CR3","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.jpdc.2016.10.011","volume":"103","author":"Zhihua Cui","year":"2017","unstructured":"Zhihua Cui, Bin Sun, Gaige Wang, et al. A novel oriented cuckoo search algorithm to improve DV-hop performance for cyber-physical systems[J]. Journal of Parallel and Distributed Computing, 2017, 103:42\u201352.","journal-title":"Journal of Parallel and Distributed Computing"},{"issue":"4","key":"1459_CR4","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1504\/IJBIC.2016.078666","volume":"8","author":"X Cai","year":"2016","unstructured":"Cai, X., Gao, X.-z., & Xue, Y. (2016). Improved bat algorithm with optimal forage strategy and random disturbance strategy[J]. International Journal of Bio-inspired Computation, 8(4), 205\u2013214.","journal-title":"International Journal of Bio-inspired Computation"},{"issue":"8","key":"1459_CR5","doi-asserted-by":"publisher","first-page":"3590","DOI":"10.1109\/TII.2017.2780885","volume":"14","author":"K Gai","year":"2018","unstructured":"Gai, K., & Qiu, M. (2018). Blend arithmetic operations on tensor-based fully homomorphic encryption over real numbers[J]. IEEE Transactions on Industrial Informatics, 14(8), 3590\u20133598.","journal-title":"IEEE Transactions on Industrial Informatics"},{"issue":"4","key":"1459_CR6","doi-asserted-by":"publisher","first-page":"3059","DOI":"10.1109\/JIOT.2018.2830340","volume":"5","author":"K Gai","year":"2018","unstructured":"Gai, K., Choo, K. K. R., Qiu, M., & Zhu, L. (2018). Privacy-preserving content-oriented wireless communication in internet-of-things[J]. IEEE Internet of Things Journal, 5(4), 3059\u20133067.","journal-title":"IEEE Internet of Things Journal"},{"key":"1459_CR7","doi-asserted-by":"publisher","unstructured":"Wang, G., Cai, X., Cui, Z., et al. (2017). High performance computing for cyber physical social systems by using evolutionary multi-objective optimization algorithm[J]. IEEE Transactions on Emerging Topics in Computing. \nhttps:\/\/doi.org\/10.1109\/TETC.2017.2703784\n\n.","DOI":"10.1109\/TETC.2017.2703784"},{"key":"1459_CR8","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1016\/j.future.2017.08.004","volume":"87","author":"M Qiu","year":"2018","unstructured":"Qiu, M., Gai, K., & Xiong, Z. (2018). Privacy-preserving wireless communications using bipartite matching in social big data[J]. Future Generation Computer Systems, 87, 772\u2013781.","journal-title":"Future Generation Computer Systems"},{"key":"1459_CR9","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1016\/j.future.2018.08.021","volume":"90","author":"P Wu","year":"2019","unstructured":"Wu, P., Lu, Z., Zhou, Q., Lei, Z., Li, X., Qiu, M., & Hung, P. C. K. (2019). Big data logs analysis based on seq2seq networks for cognitive internet of things[J]. Future Generation Computer Systems, 90, 477\u2013488.","journal-title":"Future Generation Computer Systems"},{"issue":"7","key":"1459_CR10","doi-asserted-by":"publisher","first-page":"3187","DOI":"10.1109\/TII.2018.2822680","volume":"14","author":"Z Cui","year":"2018","unstructured":"Cui, Z., Xue, F., Cai, X., Cao, Y., Wang, G.-g., & Chen, J. (2018). Detection of malicious code variants based on deep learning[J]. IEEE Transactions on Industrial Informatics, 14(7), 3187\u20133196.","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"1459_CR11","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/j.jpdc.2017.12.014","volume":"132","author":"Zhihua Cui","year":"2019","unstructured":"Cui, Z., Cao, Y., Cai, X., Cai, J., & Chen, J. (2017). Optimal LEACH protocol with modified bat algorithm for big data sensing systems in internet of things. Journal of Parallel and Distributed Computing. \nhttps:\/\/doi.org\/10.1016\/j.jpdc.2017.12.014\n\n.","journal-title":"Journal of Parallel and Distributed Computing"},{"key":"1459_CR12","unstructured":"Macqueen, J. (1967). Some methods for classification and analysis of multi variate observations[C]. Proceedings of Berkeley symposium on mathematical statistics &probability, 281\u2013297."},{"issue":"2","key":"1459_CR13","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1023\/A:1009783824328","volume":"1","author":"T Zhang","year":"1997","unstructured":"Zhang, T., Ramakrishnan, R., & Livny, M. (1997). BIRCH: A new data clustering algorithm and its applications [J]. Data Mining and Knowledge Discovery, 1(2), 141\u2013182.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"1459_CR14","unstructured":"Ester M. A. (1996). Density-based algorithm for discovering clusters in large spatial databases with noise[C]. Proceedings of the second ACM international conference on knowledge discovery and data mining, 226\u2013231."},{"issue":"5814","key":"1459_CR15","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1126\/science.1136800","volume":"315","author":"BJ Frey","year":"2007","unstructured":"Frey, B. J., & Dueck, D. (2007). Clustering by passing messages between data points[J]. Science, 315(5814), 972\u2013976.","journal-title":"Science"},{"key":"1459_CR16","unstructured":"Wei, W., Yang, J., & Muntz, R. R. (1997). STING: A statistical information grid approach to spatial data mining[C]. Proceedings of the 23rd international conference on very large data bases, 186\u2013195."},{"issue":"6191","key":"1459_CR17","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez, A., & Laio, A. (2014). Clustering by fast search and find of density peaks[J]. Science, 344(6191), 1492\u20131496.","journal-title":"Science"},{"key":"1459_CR18","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/j.neucom.2019.01.074","volume":"337","author":"M Xu","year":"2019","unstructured":"Xu, M., Li, Y., Li, R., Zou, F., & Gu, X. (2019). EADP: An extended adaptive density peaks clustering for overlapping community detection in social networks[J]. Neurocomputing, 337, 287\u2013302.","journal-title":"Neurocomputing"},{"issue":"3","key":"1459_CR19","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1007\/s00779-018-1112-y","volume":"22","author":"R Mehmood","year":"2018","unstructured":"Mehmood, R., El-Ashram, S., Bie, R., et al. (2018). Effective cancer subtyping by employing density peaks clustering by using gene expression microarray[J]. Personal and Ubiquitous Computing, 22(3), 615\u2013619.","journal-title":"Personal and Ubiquitous Computing"},{"key":"1459_CR20","doi-asserted-by":"publisher","first-page":"38921","DOI":"10.1109\/ACCESS.2018.2853129","volume":"6","author":"E Liao","year":"2018","unstructured":"Liao, E., & Liu, C. (2018). A hierarchical algorithm based on density peaks clustering and ant Colony optimization for traveling salesman problem[J]. IEEE Access, 6, 38921\u201338933.","journal-title":"IEEE Access"},{"key":"1459_CR21","doi-asserted-by":"crossref","unstructured":"Zhang, W., Wang, X., & Zhao, D., et al. (2012). Graph degree linkage: Agglomerative clustering on a directed graph[C]. Proceedings of the European conference on computer vision, 428\u2013441.","DOI":"10.1007\/978-3-642-33718-5_31"},{"key":"1459_CR22","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1016\/j.knosys.2018.06.021","volume":"159","author":"Z Zhou","year":"2018","unstructured":"Zhou, Z., Gangquan, S., Yanbin, Z., et al. (2018). Robust clustering by identifying the veins of clusters based on kernel density estimation[J]. Knowledge-Based Systems, 159, 309\u2013320.","journal-title":"Knowledge-Based Systems"},{"issue":"7","key":"1459_CR23","first-page":"36","volume":"54","author":"X Xue","year":"2018","unstructured":"Xue, X., Gan, S., Peng, H., et al. (2018). Improved density peaks clustering algorithm combining K-nearest neighbors[J]. Computer Engineering and Applications, 54(7), 36\u201343.","journal-title":"Computer Engineering and Applications"},{"key":"1459_CR24","first-page":"1","volume":"12","author":"M Du","year":"2017","unstructured":"Du, M., Ding, S., & Xue, Y. (2017). A robust density peaks clustering algorithm using fuzzy neighborhood[J]. International Journal of Machine Learning & Cybernetics, 12, 1\u201310.","journal-title":"International Journal of Machine Learning & Cybernetics"},{"issue":"8","key":"1459_CR25","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001417500239","volume":"31","author":"W Zang","year":"2017","unstructured":"Zang, W., Ren, L., Zhang, W., & Liu, X. (2017). Automatic density peaks clustering using DNA genetic algorithm optimized data field and Gaussian process[J]. International Journal of Pattern Recognition and Artificial Intelligence, 31(8), 1750023.","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"issue":"9","key":"1459_CR26","first-page":"2511","volume":"38","author":"B Qiu","year":"2018","unstructured":"Qiu, B., & Cheng, L. (2018). A parameter-free clustering algorithm based on Laplace centrality and density peaks. Journal of Computer Applications, 38(9), 2511\u20132514.","journal-title":"Journal of Computer Applications"},{"key":"1459_CR27","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.knosys.2017.07.010","volume":"133","author":"L Yaohui","year":"2017","unstructured":"Yaohui, L., Zhengming, M., & Fang, Y. (2017). Adaptive density peak clustering based on K-nearest neighbors with aggregating strategy [J]. Knowledge-Based Systems, 133, 208\u2013220.","journal-title":"Knowledge-Based Systems"},{"key":"1459_CR28","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.ins.2016.03.011","volume":"354","author":"J Xie","year":"2016","unstructured":"Xie, J., Gao, H., Xie, W., Liu, X., & Grant, P. W. (2016). Robust clustering by detecting density peaks and assigning points based on fuzzy weighted K-nearest neighbors[J]. Information Sciences, 354, 19\u201340.","journal-title":"Information Sciences"},{"key":"1459_CR29","doi-asserted-by":"crossref","unstructured":"Ankerst, M., Breunig, M. M., & Kriegel, H.-P., et al. (1999). Optics: Ordering points to identify the clustering structure[C]. Proceedings of the ACM Sigmod Record, 49\u201360.","DOI":"10.1145\/304181.304187"},{"issue":"1","key":"1459_CR30","first-page":"2837","volume":"11","author":"N Vinh","year":"2010","unstructured":"Vinh, N., Epps, J., & Bailey, J. (2010). Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance [J]. Journal of Machine Learning Research, 11(1), 2837\u20132854.","journal-title":"Journal of Machine Learning Research"},{"issue":"383","key":"1459_CR31","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1080\/01621459.1983.10478008","volume":"78","author":"EB Fowlkes","year":"1983","unstructured":"Fowlkes, E. B., & Mallows, C. L. (1983). A method for comparing two hierarchical Clusterings [J]. Journal of the American Statistical Association, 78(383), 553\u2013569.","journal-title":"Journal of the American Statistical Association"},{"key":"1459_CR32","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.ins.2018.03.031","volume":"450","author":"R Liu","year":"2018","unstructured":"Liu, R., Wang, H., & Yu, X. (2018). Shared-nearest-neighbor-based clustering by fast search and find of density peaks [J]. Information Sciences, 450, 200\u2013226.","journal-title":"Information Sciences"},{"key":"1459_CR33","unstructured":"Jain, A.K., & Law, M.H. (2005). Data clustering: A user\u2019s dilemma[C]. Proceedings of the international conference on pattern recognition and machine intelligence, : 1\u201310."},{"issue":"1","key":"1459_CR34","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.patcog.2007.04.010","volume":"41","author":"H Chang","year":"2008","unstructured":"Chang, H., & Yeung, D.-Y. (2008). Robust path-based spectral clustering[J]. Pattern Recognition, 41(1), 191\u2013203.","journal-title":"Pattern Recognition"},{"issue":"1","key":"1459_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1217299.1217303","volume":"1","author":"A Gionis","year":"2007","unstructured":"Gionis, A., Mannila, H., & Tsaparas, P. (2007). Clustering aggregation[J]. ACM Transactions on Knowledge Discovery from Data, 1(1), 1\u201330.","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"issue":"1","key":"1459_CR36","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/1471-2105-8-3","volume":"8","author":"L Fu","year":"2007","unstructured":"Fu, L., & Medico, E. (2007). FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data[J]. BMC Bioinformatics, 8(1), 3.","journal-title":"BMC Bioinformatics"},{"issue":"9","key":"1459_CR37","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1109\/TPAMI.2002.1033218","volume":"24","author":"CJ Veenman","year":"2002","unstructured":"Veenman, C. J., Reinders, M. J. T., & Backer, E. (2002). A maximum variance cluster algorithm[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9), 1273\u20131280.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"11","key":"1459_CR38","doi-asserted-by":"publisher","first-page":"1875","DOI":"10.1109\/TPAMI.2006.227","volume":"28","author":"P Franti","year":"2006","unstructured":"Franti, P., Virmajoki, O., & Hautamaki, V. (2006). Fast agglomerative clustering using a k-nearest neighbor graph[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(11), 1875\u20131881.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"5","key":"1459_CR39","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1016\/j.patcog.2005.09.012","volume":"39","author":"P Frnti","year":"2006","unstructured":"Frnti, P., & Virmajoki, O. (2006). Iterative shrinking method for clustering problems[J]. Pattern Recognition, 39(5), 761\u2013775.","journal-title":"Pattern Recognition"},{"key":"1459_CR40","unstructured":"Bache, K., & Lichman, M. (2013). UCI machine learning repository. \nhttp:\/\/archive.ics.uci.edu\/ml\n\n. Irvine: University of California."},{"key":"1459_CR41","unstructured":"Street, W. N., Wolberg, W. H., & Mangasarian, O. L. (1993). Nuclear feature extraction for breast tumor diagnosis[C]. Proceedings of the IS&T\/SPIE International Symposium on Electronic Imaging:Science and Technology, 1905, 861\u2013870."},{"key":"1459_CR42","doi-asserted-by":"crossref","unstructured":"Charytanowicz, M., Niewczas, J., Kulczycki, P., et al. (2010). Complete gradient clustering algorithm for features analysis of x-ray images [J]. Advances in Intelligent and Soft Computing, 69, 15-24.","DOI":"10.1007\/978-3-642-13105-9_2"},{"key":"1459_CR43","doi-asserted-by":"crossref","unstructured":"Dias, D. B., Madeo, R. C. B., & Rocha T., et al. (2009). Hand movement recognition for brazilian sign language: A study using distance-based neural networks[C]. Proceedings of the international joint on neural networks, 697\u2013704.","DOI":"10.1109\/IJCNN.2009.5178917"},{"issue":"3","key":"1459_CR44","first-page":"262","volume":"10","author":"VG Sigillito","year":"1989","unstructured":"Sigillito, V. G., Wing, S. P., Hutton, L. V., et al. (1989). Classification of radar returns from the ionosphere using neural networks[J]. Johns Hopkins APL Technical Digest, 10(3), 262\u2013266.","journal-title":"Johns Hopkins APL Technical Digest"},{"key":"1459_CR45","volume-title":"Classification and regression trees[M]","author":"L Breiman","year":"1984","unstructured":"Breiman, L., Friedman, J., Stone, C. J., et al. (1984). Classification and regression trees[M]. Boca Raton: CRC Press."},{"key":"1459_CR46","doi-asserted-by":"publisher","first-page":"2777","DOI":"10.1007\/s00500-017-2748-7","volume":"22","author":"J Ding","year":"2018","unstructured":"Ding, J., He, X., Yuan, J., & Jiang, B. (2018). Automatic clustering based on density peak detection using generalized extreme value distribution[J]. Soft Computing, 22, 2777\u20132796.","journal-title":"Soft Computing"}],"updated-by":[{"DOI":"10.1007\/s11265-019-01495-0","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T00:00:00Z","timestamp":1574121600000}}],"container-title":["Journal of Signal Processing Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-019-01459-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11265-019-01459-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-019-01459-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T09:16:36Z","timestamp":1596273396000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11265-019-01459-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,2]]},"references-count":46,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2019,10]]}},"alternative-id":["1459"],"URL":"https:\/\/doi.org\/10.1007\/s11265-019-01459-4","relation":{"correction":[{"id-type":"doi","id":"10.1007\/s11265-019-01495-0","asserted-by":"object"}]},"ISSN":["1939-8018","1939-8115"],"issn-type":[{"value":"1939-8018","type":"print"},{"value":"1939-8115","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,2]]},"assertion":[{"value":"6 May 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 May 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 August 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2019","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The Publisher regrets an error on the printed front cover of the October 2019 issue. The issue numbers were incorrectly listed as Volume 91, Nos. 10-12, October 2019. The correct number should be: \"Volume 91, No. 10, October 2019\"","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}}]}}