{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T06:51:49Z","timestamp":1763621509435,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819978540"},{"type":"electronic","value":"9789819978557"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-7855-7_5","type":"book-chapter","created":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:04:33Z","timestamp":1698969873000},"page":"58-69","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Automated Cattle Behavior Classification Using Wearable Sensors and\u00a0Machine Learning Approach"],"prefix":"10.1007","author":[{"given":"Niken Prasasti","family":"Martono","sequence":"first","affiliation":[]},{"given":"Rie","family":"Sawado","sequence":"additional","affiliation":[]},{"given":"Itoko","family":"Nonaka","sequence":"additional","affiliation":[]},{"given":"Fuminori","family":"Terada","sequence":"additional","affiliation":[]},{"given":"Hayato","family":"Ohwada","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,3]]},"reference":[{"key":"5_CR1","doi-asserted-by":"publisher","unstructured":"Antanaitis, R., et al.: Change in rumination behavior parameters around calving in cows with subclinical ketosis diagnosed during 30 days after calving. Animals 13 (2023). https:\/\/doi.org\/10.3390\/ani13040595","DOI":"10.3390\/ani13040595"},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Barwick, J., Lamb, D.W., Dobos, R., Welch, M., Trotter, M.: Categorising sheep activity using a tri-axial accelerometer. Computers and Electronics in Agriculture 145, 289\u2013297 (2018). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0168169917311468","DOI":"10.1016\/j.compag.2018.01.007"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Benaissa, S., et al.: On the use of on-cow accelerometers for the classification of behaviours in dairy barns. Res. Veterinary Sci. 125, 425\u2013433 (2019). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S003452881730423X","DOI":"10.1016\/j.rvsc.2017.10.005"},{"key":"5_CR4","doi-asserted-by":"publisher","unstructured":"Brouwers, S.P., Simmler, M., Savary, P., Scriba, M.F.: Towards a novel method for detecting atypical lying down and standing up behaviors in dairy cows using accelerometers and machine learning. Smart Agric. Technol. 4 (2023). https:\/\/doi.org\/10.1016\/j.atech.2023.100199","DOI":"10.1016\/j.atech.2023.100199"},{"key":"5_CR5","doi-asserted-by":"publisher","unstructured":"Cabezas, J., et al.: Analysis of accelerometer and GPS data for cattle behaviour identification and anomalous events detection. Entropy 24 (2022). https:\/\/doi.org\/10.3390\/e24030336","DOI":"10.3390\/e24030336"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Chang, A.Z., Fogarty, E.S., Moraes, L.E., Garc\u00eda-Guerra, A., Swain, D.L., Trotter, M.G.: Detection of rumination in cattle using an accelerometer ear-tag: a comparison of analytical methods and individual animal and generic models. Comput. Electron. Agric. 192, 106595 (2022). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0168169921006128","DOI":"10.1016\/j.compag.2021.106595"},{"key":"5_CR7","doi-asserted-by":"publisher","unstructured":"Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785\u2013794. KDD \u201916, ACM, New York, NY, USA (2016). https:\/\/doi.org\/10.1145\/2939672.2939785","DOI":"10.1145\/2939672.2939785"},{"issue":"2","key":"5_CR8","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1111\/j.2517-6161.1958.tb00292.x","volume":"20","author":"DR Cox","year":"1958","unstructured":"Cox, D.R.: The regression analysis of binary sequences. J. Roy. Stat. Soc.: Ser. B (Methodol.) 20(2), 215\u2013232 (1958)","journal-title":"J. Roy. Stat. Soc.: Ser. B (Methodol.)"},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Ho, T.K.: Random decision forests. In: Proceedings of 3rd international conference on document analysis and recognition, vol. 1, pp. 278\u2013282. IEEE (1995)","DOI":"10.1109\/ICDAR.1995.598994"},{"key":"5_CR10","doi-asserted-by":"publisher","unstructured":"King, M., LeBlanc, S., Pajor, E., Wright, T., DeVries, T.: Behavior and productivity of cows milked in automated systems before diagnosis of health disorders in early lactation. J. Dairy Sci. 101(5), 4343\u20134356 (2018). https:\/\/doi.org\/10.3168\/jds.2017-13686","DOI":"10.3168\/jds.2017-13686"},{"key":"5_CR11","doi-asserted-by":"publisher","unstructured":"Leliveld, L.M., Riva, E., Mattachini, G., Finzi, A., Lovarelli, D., Provolo, G.: Dairy cow behavior is affected by period, time of day and housing. Animals 12 (2022). https:\/\/doi.org\/10.3390\/ani12040512","DOI":"10.3390\/ani12040512"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Montes, M.E., et al.: Relationship between body temperature and behavior of nonpregnant early-lactation dairy cows (2023)","DOI":"10.3168\/jdsc.2022-0327"},{"key":"5_CR13","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1080\/01652176.2021.1987581","volume":"41","author":"S Paudyal","year":"2021","unstructured":"Paudyal, S.: Using rumination time to manage health and reproduction in dairy cattle: a review. Vet. Q. 41, 292\u2013300 (2021). https:\/\/doi.org\/10.1080\/01652176.2021.1987581","journal-title":"Vet. Q."},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Turner, L., Udal, M., Larson, B., Shearer, S.: Monitoring cattle behavior and pasture use with GPS and GIS (2000)","DOI":"10.4141\/A99-093"},{"key":"5_CR15","doi-asserted-by":"publisher","unstructured":"Weerd, N.D., et al.: Deriving animal behaviour from high-frequency GPS: Tracking cows in open and forested habitat. PLoS ONE 10 (2015). https:\/\/doi.org\/10.1371\/journal.pone.0129030","DOI":"10.1371\/journal.pone.0129030"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Williams, L.R., Fox, D.R., Bishop-Hurley, G.J., Swain, D.L.: Use of radio frequency identification (RFID) technology to record grazing beef cattle water point use. Comput. Electron. Agric. 156, 193\u2013202 (2019). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0168169918306707","DOI":"10.1016\/j.compag.2018.11.025"},{"key":"5_CR17","unstructured":"Wolhuter, R., Petrus, S., Roux, L., Marais, J., Niesler, T.: Automatic classification of sheep behaviour using 3-axis accelerometer data cough detection view project automatic real-time animal behaviour classification view project automatic classification of sheep behaviour using 3-axis accelerometer data (2014). https:\/\/www.researchgate.net\/publication\/319331093"},{"issue":"1","key":"5_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-007-0114-2","volume":"14","author":"X Wu","year":"2008","unstructured":"Wu, X., et al.: Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1), 1\u201337 (2008)","journal-title":"Knowl. Inf. Syst."}],"container-title":["Lecture Notes in Computer Science","Knowledge Management and Acquisition for Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-7855-7_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T08:40:23Z","timestamp":1730450423000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-7855-7_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819978540","9789819978557"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-7855-7_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"3 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PKAW","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim Knowledge Acquisition Workshop","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jakarta","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indonesia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pkaw2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/pkawwebsite.github.io\/2023\/#home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","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":"28","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":"9","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":"2","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":"32% - 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":"3","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":"2.6","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)"}}]}}