{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T03:01:16Z","timestamp":1770519676299,"version":"3.49.0"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030336165","type":"print"},{"value":"9783030336172","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-33617-2_29","type":"book-chapter","created":{"date-parts":[[2019,11,7]],"date-time":"2019-11-07T00:04:05Z","timestamp":1573085045000},"page":"280-290","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Time Series Display for Knowledge Discovery on Selective Laser Melting Machines"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6610-9581","authenticated-orcid":false,"given":"Ram\u00f3n","family":"Moreno","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4385-6197","authenticated-orcid":false,"given":"Juan Carlos","family":"Pereira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5539-8587","authenticated-orcid":false,"given":"Alex","family":"L\u00f3pez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asif","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prasha","family":"Pahlevannejad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,10,18]]},"reference":[{"key":"29_CR1","doi-asserted-by":"crossref","unstructured":"Gokalp, M.O., Kayabay, K., Akyol, M.A., Eren, P.E., Ko\u00e7yi\u011fit, A.: Big data for industry 4.0: a conceptual framework. In: 2016 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 431\u2013434, December (2016)","DOI":"10.1109\/CSCI.2016.0088"},{"key":"29_CR2","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/MIE.2017.2649104","volume":"11","author":"M Wollschlaeger","year":"2017","unstructured":"Wollschlaeger, M., Sauter, T., Jasperneite, J.: The future of industrial communication: automation networks in the era of the internet of things and industry 4.0. IEEE Ind. Electron. Mag. 11, 17\u201327 (2017)","journal-title":"IEEE Ind. Electron. Mag."},{"issue":"12","key":"29_CR3","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1016\/j.jmatprotec.2010.05.010","volume":"210","author":"I Yadroitsev","year":"2010","unstructured":"Yadroitsev, I., Gusarov, A., Yadroitsava, I., Smurov, I.: Single track formation in selective laser melting of metal powders. J. Mat. Process. Technol. 210(12), 1624\u20131631 (2010)","journal-title":"J. Mat. Process. Technol."},{"key":"29_CR4","doi-asserted-by":"publisher","first-page":"1917","DOI":"10.1007\/s11665-014-0958-z","volume":"23","author":"WE Frazier","year":"2014","unstructured":"Frazier, W.E.: Metal additive manufacturing: a review. J. Mat. Eng. Perform. 23, 1917\u20131928 (2014)","journal-title":"J. Mat. Eng. Perform."},{"key":"29_CR5","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.is.2015.04.007","volume":"53","author":"S Aghabozorgi","year":"2015","unstructured":"Aghabozorgi, S., Shirkhorshidi, A.S., Wah, T.Y.: Time-series clustering - a decade review. Inf. Syst. 53, 16\u201338 (2015)","journal-title":"Inf. Syst."},{"key":"29_CR6","doi-asserted-by":"crossref","unstructured":"Ben Ayed, A., Ben Halima, M., Alimi, A.M.: Survey on clustering methods: towards fuzzy clustering for big data, pp. 331\u2013336. IEEE, August (2014)","DOI":"10.1109\/SOCPAR.2014.7008028"},{"key":"29_CR7","doi-asserted-by":"publisher","first-page":"1525","DOI":"10.1007\/s11222-016-9702-x","volume":"27","author":"M DeYoreo","year":"2017","unstructured":"DeYoreo, M., Kottas, A.: A bayesian nonparametric markovian model for non-stationary time series. Stat. Comput. 27, 1525\u20131538 (2017)","journal-title":"Stat. Comput."},{"key":"29_CR8","first-page":"1","volume":"19","author":"IM Wagner-Muns","year":"2017","unstructured":"Wagner-Muns, I.M., Guardiola, I.G., Samaranayke, V.A., Kayani, W.I.: A functional data analysis approach to traffic volume forecasting. IEEE Trans. Intell. Transport. Syst. 19, 1\u201311 (2017)","journal-title":"IEEE Trans. Intell. Transport. Syst."},{"key":"29_CR9","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/TNN.2005.845141","volume":"16","author":"R Xu","year":"2005","unstructured":"Xu, R., Wunsch, D.: Survey of clustering algorithms. IEEE Trans. Neural Netw. 16, 645\u2013678 (2005)","journal-title":"IEEE Trans. Neural Netw."},{"key":"29_CR10","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1016\/B978-0-444-53868-0.50008-3","volume-title":"Developments in Environmental Modelling","author":"P Legendre","year":"2012","unstructured":"Legendre, P., Legendre, L.: Chapter 8 - cluster analysis, in numerical ecology. In: Legendre, P., Legendre, L. (eds.) Developments in Environmental Modelling, vol. 24, pp. 337\u2013424. Elsevier, Amsterdam (2012). https:\/\/doi.org\/10.1016\/B978-0-444-53868-0.50008-3"},{"issue":"301","key":"29_CR11","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","volume":"58","author":"JH Ward Jr","year":"1963","unstructured":"Ward Jr., J.H.: Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58(301), 236\u2013244 (1963)","journal-title":"J. Am. Stat. Assoc."},{"key":"29_CR12","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1007\/s00357-014-9161-z","volume":"31","author":"F Murtagh","year":"2014","unstructured":"Murtagh, F., Legendre, P.: Ward\u2019s hierarchical agglomerative clustering method: which algorithms implement ward\u2019s criterion? J. Classif. 31, 274\u2013295 (2014)","journal-title":"J. Classif."}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2019"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-33617-2_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T15:31:25Z","timestamp":1709825485000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-33617-2_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030336165","9783030336172"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-33617-2_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"18 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDEAL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Data Engineering and Automated Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Manchester","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ideal2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.confercare.manchester.ac.uk\/events\/ideal2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"149","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"94","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"63% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}