{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T09:14:57Z","timestamp":1785575697372,"version":"3.56.0"},"reference-count":73,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,8]],"date-time":"2018-03-08T00:00:00Z","timestamp":1520467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Automated segmentation of planar and linear features of point clouds acquired from construction sites is essential for the automatic extraction of building construction elements such as columns, beams and slabs. However, many planar and linear segmentation methods use scene-dependent similarity thresholds that may not provide generalizable solutions for all environments. In addition, outliers exist in construction site point clouds due to data artefacts caused by moving objects, occlusions and dust. To address these concerns, a novel method for robust classification and segmentation of planar and linear features is proposed. First, coplanar and collinear points are classified through a robust principal components analysis procedure. The classified points are then grouped using a new robust clustering method, the robust complete linkage method. A robust method is also proposed to extract the points of flat-slab floors and\/or ceilings independent of the aforementioned stages to improve computational efficiency. The applicability of the proposed method is evaluated in eight datasets acquired from a complex laboratory environment and two construction sites at the University of Calgary. The precision, recall, and accuracy of the segmentation at both construction sites were 96.8%, 97.7% and 95%, respectively. These results demonstrate the suitability of the proposed method for robust segmentation of planar and linear features of contaminated datasets, such as those collected from construction sites.<\/jats:p>","DOI":"10.3390\/s18030819","type":"journal-article","created":{"date-parts":[[2018,3,8]],"date-time":"2018-03-08T12:07:33Z","timestamp":1520510853000},"page":"819","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Robust Segmentation of Planar and Linear Features of Terrestrial Laser Scanner Point Clouds Acquired from Construction Sites"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6825-2691","authenticated-orcid":false,"given":"Reza","family":"Maalek","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Derek","family":"Lichti","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janaka","family":"Ruwanpura","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.autcon.2012.10.005","article-title":"Accuracy assessment of Ultra-Wide Band technology in tracking static resources in indoor construction scenarios","volume":"30","author":"Maalek","year":"2013","journal-title":"Autom. Constr."},{"key":"ref_2","first-page":"04014025","article-title":"Automated progress monitoring using unordered daily construction photographs and IFC-based building information models","volume":"29","author":"Savarese","year":"2012","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.autcon.2015.11.009","article-title":"Accuracy assessment of ultra-wide band technology in locating dynamic resources in indoor scenarios","volume":"63","author":"Maalek","year":"2016","journal-title":"Autom. Constr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1139\/l06-088","article-title":"Predicting construction productivity using situation-based simulation models","volume":"33","author":"Choy","year":"2006","journal-title":"Can. J. Civ. Eng."},{"key":"ref_5","unstructured":"Nunnally, S.W. (2010). Construction Methods and Management, Pearson Education. [8th ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Maalek, R., Ruwanpura, J., and Ranaweera, K. (2014, January 19\u201321). Evaluation of the state-of-the-art automated construction progress monitoring and control systems. Proceedings of the Construction Research Congress: Construction in a Global Network, Atlanta, GA, USA.","DOI":"10.1061\/9780784413517.105"},{"key":"ref_7","unstructured":"Ballast, D.K. (2007). Handbook of Construction Tolerances, John Wiley & Sons."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.aei.2015.05.002","article-title":"Terrestrial laser scanning and continuous wavelet transform for controlling surface flatness in construction\u2014A first investigation","volume":"29","author":"Biotteau","year":"2015","journal-title":"Adv. Eng. Inform."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"S23","DOI":"10.3846\/13923730.2013.795187","article-title":"Combined 3D building surveying techniques\u2013terrestrial laser scanning (TLS) and total station surveying for BIM data management purposes","volume":"19","author":"Mill","year":"2013","journal-title":"J. Civ. Eng. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"163","DOI":"10.5194\/isprsarchives-XL-5-W4-163-2015","article-title":"Advances in multi-sensor scanning and visualization of complex plants: The utmost case of a reactor building","volume":"40","author":"Hullo","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.autcon.2014.05.014","article-title":"The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components","volume":"49","author":"Ahmed","year":"2015","journal-title":"Autom. Constr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.aei.2015.01.001","article-title":"State of research in automatic as-built modelling","volume":"29","author":"Armeni","year":"2015","journal-title":"Adv. Eng. Inform."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.autcon.2012.11.027","article-title":"On site 3D marking for construction activity tracking","volume":"30","author":"Shahi","year":"2013","journal-title":"Autom. Constr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.aei.2015.01.009","article-title":"As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure: A survey","volume":"29","author":"Son","year":"2015","journal-title":"Adv. Eng. Inform."},{"key":"ref_15","first-page":"33","article-title":"Recognizing structure in laser scanner point clouds","volume":"46","author":"Vosselman","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.isprsjprs.2013.12.001","article-title":"An adaptive approach for the segmentation and extraction of planar and linear\/cylindrical features from laser scanning data","volume":"93","author":"Lari","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2015.01.011","article-title":"Octree-based region growing for point cloud segmentation","volume":"104","author":"Vo","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0734-189X(88)80033-1","article-title":"A survey of the Hough transform","volume":"44","author":"Illingworth","year":"1988","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_19","unstructured":"Tarsha-Kurdi, F., Landes, T., and Grussenmeyer, P. (2007, January 12\u201314). Hough-transform and extended ransac algorithms for automatic detection of 3d building roof planes from lidar data. Proceedings of the ISPRS Workshop on Laser Scanning\u2013Silvilaser, Espoo, Finland."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.1016\/j.csda.2007.05.024","article-title":"Principal component analysis for data containing outliers and missing elements","volume":"52","author":"Serneels","year":"2008","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1080\/10618600.2012.672100","article-title":"A deterministic algorithm for robust location and scatter","volume":"21","author":"Hubert","year":"2012","journal-title":"J. Comput. Graph. Stat."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for point-cloud shape detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1700","DOI":"10.1109\/TVCG.2013.74","article-title":"Cylinder detection in large-scale point cloud of pipeline plant","volume":"19","author":"Liu","year":"2013","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JSTARS.2014.2349003","article-title":"A methodology for automated segmentation and reconstruction of urban 3-D buildings from ALS point clouds","volume":"7","author":"Chen","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Poux, F., Neuville, R., Van Wersch, L., Nys, G.A., and Billen, R. (2017). 3D point clouds in archaeology: Advances in acquisition, processing and knowledge integration applied to quasi-planar objects. Geosciences, 7.","DOI":"10.3390\/geosciences7040096"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.isprsjprs.2016.11.008","article-title":"A hierarchical methodology for urban facade parsing from TLS point clouds","volume":"123","author":"Li","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2014.07.004","article-title":"Robust statistical approaches for local planar surface fitting in 3D laser scanning data","volume":"96","author":"Nurunnabi","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_28","first-page":"79","article-title":"Segmentation based robust interpolation\u2014A new approach to laser filtering","volume":"36","author":"Pfeifer","year":"2005","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.inffus.2004.06.004","article-title":"Using the Dempster Shafer method for the fusion of TLS data and multispectral images for building detection","volume":"6","author":"Rottensteiner","year":"2005","journal-title":"Inf. Fusion"},{"key":"ref_30","first-page":"25","article-title":"Automatic extraction of building features from terrestrial laser scanning","volume":"36","author":"Pu","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_31","first-page":"44","article-title":"Classification and segmentation of terrestrial lasers canner point clouds using local variance information","volume":"36","author":"Belton","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.isprsjprs.2016.01.001","article-title":"Octree-based segmentation for terrestrial TLS point cloud data in industrial applications","volume":"113","author":"Su","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.isprsjprs.2005.10.005","article-title":"Segmentation of airborne laser scanning data using a slope adaptive neighborhood","volume":"60","author":"Filin","year":"2006","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","unstructured":"Kim, C., Habib, A., and Mrstik, P. (2007, January 7\u201311). New Approach for Planar Patch Segmentation using Airborne Laser Data. Proceedings of the ASPRS, Tampa, FL, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"55","DOI":"10.5194\/isprsannals-II-5-W2-55-2013","article-title":"Eigenvalue and graph-based object extraction from mobile laser scanning point clouds","volume":"II-5\/W2","author":"Bremer","year":"2013","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2409","DOI":"10.1109\/TGRS.2014.2359951","article-title":"A multiscale and hierarchical feature extraction method for terrestrial laser scanning point cloud classification","volume":"53","author":"Wang","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Kim, C., Habib, A., Pyeon, M., Kwon, G.R., Jung, J., and Heo, J. (2016). Segmentation of planar surfaces from laser scanning data using the magnitude of normal position vector for adaptive neighborhoods. Sensors, 16.","DOI":"10.3390\/s16020140"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Maronna, R.A., Martin, D.R., and Yohai, V.J. (2006). Robust Statistics: Theory and Methods, Wiley.","DOI":"10.1002\/0470010940"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1214\/aos\/1176349264","article-title":"Asymptotics for the Minimum Covariance Determinant Estimator","volume":"21","author":"Butler","year":"1993","journal-title":"Ann. Stat."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1828","DOI":"10.1214\/aos\/1176348891","article-title":"The asymptotics of Rousseeuw\u2019s minimum volume ellipsoid","volume":"20","author":"Davies","year":"1992","journal-title":"Ann. Stat."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1080\/00224065.2008.11917723","article-title":"Monitoring correlation within linear profiles using mixed models","volume":"40","author":"Jensen","year":"2008","journal-title":"J. Qual. Technol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1080\/00401706.1999.10485670","article-title":"A fast algorithm for the Minimum Covariance Determinant estimator","volume":"41","author":"Rousseeuw","year":"1999","journal-title":"Technometrics"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"129","DOI":"10.5194\/isprsannals-II-3-W5-129-2015","article-title":"Robust classification and segmentation of planar and linear features for construction site progress monitoring and structural dimensional compliance control","volume":"II-3\/W5","author":"Maalek","year":"2015","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.autcon.2016.12.002","article-title":"An adaptive approach for the reconstruction and modelling of as-built 3D pipelines from point clouds","volume":"75","author":"Patil","year":"2017","journal-title":"Autom. Constr."},{"key":"ref_45","unstructured":"Wang, J., and Shan, J. (2009, January 9\u201313). Segmentation of LiDAR point clouds for building extraction. Proceedings of the ASPRS Annual Conference, Baltimore, MD, USA."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Teboul, O., Simon, L., Koutsourakis, P., and Paragios, N. (2010, January 13\u201318). Segmentation of building facades using procedural shape priors. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5540068"},{"key":"ref_47","first-page":"248","article-title":"Segmentation of point clouds using smoothness constraint","volume":"36","author":"Rabbani","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_48","unstructured":"Deschaud, J.E., and Goulette, F. (2010, January 17\u201320). A fast and accurate plane detection algorithm for large noisy point clouds using filtered normals and voxel growing. Proceedings of the 3D Processing, Visualization and Transmission Conference, Paris, France."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.cad.2007.10.013","article-title":"A global clustering approach to point cloud simplification with a specified data reduction ratio","volume":"40","author":"Song","year":"2008","journal-title":"Comput.-Aided Des."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1016\/j.cad.2011.04.001","article-title":"Adaptive simplification of point cloud using k-means clustering","volume":"43","author":"Shi","year":"2011","journal-title":"Comput.-Aided Des."},{"key":"ref_51","unstructured":"Haralick, R.M., and Shapiro, L.G. (1992). Computer and Robot Vision, Addison-Wesley."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/0031-3203(80)90002-3","article-title":"Monte Carlo comparisons of selected clustering procedures","volume":"12","author":"Bayne","year":"1980","journal-title":"Pattern Recog."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1207\/s15327906mbr1504_6","article-title":"Detection of biological sex: An empirical test of cluster methods","volume":"15","author":"Golden","year":"1980","journal-title":"Multivariate Behav. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"320","DOI":"10.2307\/2347485","article-title":"Statistical algorithms: Algorithm AS 217. Computation of the dip statistic to test for unimodality","volume":"34","author":"Hartigan","year":"1985","journal-title":"Appl. Stat."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Everitt, B.S., Landau, S., Leese, M., and Stahl, D. (2011). Cluster Analysis, John Wiley & Sons. [5th ed.].","DOI":"10.1002\/9780470977811"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/BF02289588","article-title":"Hierarchical clustering schemes","volume":"32","author":"Johnson","year":"1967","journal-title":"Psychometrika"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Wille, L.T. (2004). The Challenges of Clustering in High Dimensional Data. New Directions in Statistical Physics, Springer.","DOI":"10.1007\/978-3-662-08968-2"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Nurunnabi, A., Belton, D., and West, G. (2014, January 8\u201310). Diagnostics based principal component analysis for robust plane fitting in laser data. Proceedings of the 2013 16th International Conference on Computer and Information Technology (ICCIT), Khulna, Bangladesh.","DOI":"10.1109\/ICCITechn.2014.6997319"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.chemolab.2004.06.003","article-title":"LIBRA: A MATLAB library for robust analysis","volume":"75","author":"Verboven","year":"2005","journal-title":"Chemometr. Intell. Lab. Syst."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s10182-011-0156-3","article-title":"Multivariate process capability using principal component analysis in the presence of measurement errors","volume":"95","author":"Scagliarini","year":"2011","journal-title":"ASTA Adv. Stat. Anal."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1111\/sjos.12083","article-title":"The impact of measurement error on principal component analysis","volume":"41","author":"Hellton","year":"2014","journal-title":"Scand. J. Stat."},{"key":"ref_62","unstructured":"Mikhail, E.M., and Ackermann, F.E. (1976). Observations and Least Squares, Harper and Row."},{"key":"ref_63","unstructured":"Mahalanobis, P.C. (2018, March 06). On the Generalized Distance in Statistics. Available online: http:\/\/bayes.acs.unt.edu:8083\/BayesContent\/class\/Jon\/MiscDocs\/1936_Mahalanobis.pdf."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1109\/TIT.1983.1056714","article-title":"On the shape of a set of points in the plane","volume":"29","author":"Edelsbrunner","year":"1983","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1016\/j.adhoc.2008.12.001","article-title":"Localised alpha-shape computations for boundary recognition in sensor networks","volume":"7","author":"Fayed","year":"2009","journal-title":"Ad Hoc Netw."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Shapira, L., Avidan, S., and Shamir, A. (October, January 29). Mode-detection via median-shift. Proceedings of the 2009 IEEE 12th International Conference on Computer Vision, Kyoto, Japan.","DOI":"10.1109\/ICCV.2009.5459423"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Macher, H., Landes, T., and Grussenmeyer, P. (2017). From point clouds to building information models: 3D semi-automatic econstruction of indoors of existing buildings. Appl. Sci., 7.","DOI":"10.3390\/app7101030"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1080\/01621459.1974.10482962","article-title":"The influence curve and its role in robust estimation","volume":"69","author":"Hampel","year":"1974","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_69","unstructured":"(2018, March 06). Leica HDS6100 TLS Datasheet and Key Performance Specifications. Available online: http:\/\/w3.leica-geosystems.com\/downloads123\/hds\/hds\/HDS6100\/brochures\/Leica_HDS6100_brochure_us.pdf."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.isprsjprs.2011.01.005","article-title":"Scanning geometry: Influencing factor on the quality of terrestrial laser scanning points","volume":"66","author":"Soudarissanane","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_71","first-page":"73","article-title":"Robust statistics for outlier detection","volume":"1","author":"Rousseeuw","year":"2011","journal-title":"Wiley Interdiscip. Rev.: Data Mining Knowl. Discov."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Sprent, P., and Smeeton, N.C. (2016). Applied Nonparametric Statistical Methods, CRC Press.","DOI":"10.1201\/b15842"},{"key":"ref_73","unstructured":"Olsen, D.L., and Denlen, D. (2008). Advanced Data Mining Techniques, Springer."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/3\/819\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:56:17Z","timestamp":1760194577000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/3\/819"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,8]]},"references-count":73,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2018,3]]}},"alternative-id":["s18030819"],"URL":"https:\/\/doi.org\/10.3390\/s18030819","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,8]]}}}