{"id":"https://openalex.org/W4293192639","doi":"https://doi.org/10.1109/lgrs.2022.3162668","title":"Compression Method of NMR Echo Data Obtained From Complex Pore Structure Formation","display_name":"Compression Method of NMR Echo Data Obtained From Complex Pore Structure Formation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293192639","doi":"https://doi.org/10.1109/lgrs.2022.3162668"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3162668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3162668","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040421292","display_name":"Xiangning Meng","orcid":"https://orcid.org/0000-0001-6418-8389"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangning Meng","raw_affiliation_strings":["Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi&#x2019;an Shiyou University, Xi&#x2019;an, Shaanxi, China","an, Shaanxi, China","an Shiyou University, Xi&#x2019"],"affiliations":[{"raw_affiliation_string":"Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi&#x2019;an Shiyou University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I181903023"]},{"raw_affiliation_string":"an, Shaanxi, China","institution_ids":[]},{"raw_affiliation_string":"an Shiyou University, Xi&#x2019","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103075040","display_name":"Hui Jia","orcid":"https://orcid.org/0000-0002-6449-7840"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Jia","raw_affiliation_strings":["Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi&#x2019;an Shiyou University, Xi&#x2019;an, Shaanxi, China","an Shiyou University, Xi&#x2019","an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi&#x2019;an Shiyou University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I181903023"]},{"raw_affiliation_string":"an Shiyou University, Xi&#x2019","institution_ids":["https://openalex.org/I181903023"]},{"raw_affiliation_string":"an, Shaanxi, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101444597","display_name":"Wenxin Tian","orcid":"https://orcid.org/0000-0003-4536-3430"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenxin Tian","raw_affiliation_strings":["Material Equipment Company, China Petroleum Logging Company, Ltd., Langfang, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Material Equipment Company, China Petroleum Logging Company, Ltd., Langfang, Hebei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062185386","display_name":"Weigao Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weigao Yu","raw_affiliation_strings":["Exploration Department, PetroChina Huabei Oilfield Company, Renqiu, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Exploration Department, PetroChina Huabei Oilfield Company, Renqiu, Hebei, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101640642","display_name":"Yang Gao","orcid":"https://orcid.org/0000-0002-9976-5032"},"institutions":[{"id":"https://openalex.org/I4210112595","display_name":"Research Institute of Petroleum Exploration and Development","ror":"https://ror.org/02awe6g05","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210112595","https://openalex.org/I98227222"]},{"id":"https://openalex.org/I4210162687","display_name":"Second Hospital of Liaohe Oilfield","ror":"https://ror.org/018w5ms25","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210162687"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Gao","raw_affiliation_strings":["Research Institute of Petroleum Exploration and Development, PetroChina Liaohe Oilfield Company, Panjin, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Research Institute of Petroleum Exploration and Development, PetroChina Liaohe Oilfield Company, Panjin, Liaoning, China","institution_ids":["https://openalex.org/I4210162687","https://openalex.org/I4210112595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040421292"],"corresponding_institution_ids":["https://openalex.org/I181903023"],"apc_list":null,"apc_paid":null,"fwci":0.3801,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.89468933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12603","display_name":"NMR spectroscopy and applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12603","display_name":"NMR spectroscopy and applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9502000212669373,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9365000128746033,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.8896834850311279},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.7307806015014648},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6105476021766663},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.5748418569564819},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5347862243652344},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.4955357313156128},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.49223414063453674},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.48473021388053894},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4542570114135742},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4456327259540558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43937546014785767},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37969574332237244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36336424946784973},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.30608731508255005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.254965603351593},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.17528662085533142},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.14283156394958496},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08555999398231506},{"id":"https://openalex.org/keywords/computational-chemistry","display_name":"Computational chemistry","score":0.06358623504638672}],"concepts":[{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.8896834850311279},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.7307806015014648},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6105476021766663},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.5748418569564819},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5347862243652344},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.4955357313156128},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.49223414063453674},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.48473021388053894},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4542570114135742},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4456327259540558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43937546014785767},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37969574332237244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36336424946784973},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.30608731508255005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.254965603351593},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.17528662085533142},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.14283156394958496},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08555999398231506},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.06358623504638672}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3162668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3162668","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4707773459","display_name":null,"funder_award_id":"41911530258","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5048860504","display_name":null,"funder_award_id":"2018JQ4002","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G8716473397","display_name":null,"funder_award_id":"41802019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8987697029","display_name":null,"funder_award_id":"42172036","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336567","display_name":"Natural Science Basic Research Program of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W624378077","https://openalex.org/W1977230190","https://openalex.org/W2052420154","https://openalex.org/W2070255659","https://openalex.org/W2135638778","https://openalex.org/W2137346077","https://openalex.org/W2140095548","https://openalex.org/W2158001550","https://openalex.org/W2270097383","https://openalex.org/W2884319406","https://openalex.org/W2896535919","https://openalex.org/W4206407320","https://openalex.org/W6683383647"],"related_works":["https://openalex.org/W2366185040","https://openalex.org/W2027376491","https://openalex.org/W2558026684","https://openalex.org/W2140869420","https://openalex.org/W2958374823","https://openalex.org/W2353199197","https://openalex.org/W2098028537","https://openalex.org/W2382704364","https://openalex.org/W1985034083","https://openalex.org/W2090258569"],"abstract_inverted_index":{"To":[0],"reduce":[1],"the":[2,19,33,67,93,101,114,160,192,206,211,219,229,236],"redundancy":[3],"of":[4,23,58,95,126,144,178],"nuclear":[5],"magnetic":[6],"resonance":[7],"(NMR)":[8],"echo":[9,69,97],"data,":[10],"kernel":[11,42,64,131,134,149,161,188,202,207,212],"principal":[12],"component":[13,86],"analysis":[14,87],"(KPCA)":[15],"is":[16,28,37,77,89,150,171,189,203,233],"used":[17,41],"in":[18,30,120,191,235],"compression.":[20],"The":[21,55,81,123,140,175],"algorithm":[22],"data":[24,70,98],"compression":[25,56,94,124,141,176,221,231],"using":[26],"KPCA":[27,59,110,127,145,154,179,198],"introduced":[29],"detail,":[31],"and":[32,52,79,132,186],"specific":[34],"calculation":[35],"process":[36],"given.":[38],"Four":[39],"commonly":[40],"functions":[43,65],"are":[44,135],"selected:":[45],"Gaussian":[46,130,182],"kernel,":[47,49,51,158,183,185],"linear":[48,148,184],"polynomial":[50,157,201],"exponential":[53,133,187],"kernel.":[54],"effect":[57,232],"based":[60,111,128,146,155,180,199],"on":[61,66,112,129,147,156,181,200],"these":[62],"four":[63,115],"NMR":[68,96],"obtained":[71,99,234],"from":[72,100],"complex":[73,104,195,237],"pore":[74,105,196,238],"structure":[75],"formation":[76,102],"compared":[78],"analyzed.":[80],"study":[82],"found":[83],"that:":[84],"Principal":[85],"(PCA)":[88],"not":[90],"suitable":[91],"for":[92],"with":[103,108,194],"structure.":[106,197],"Compared":[107],"PCA,":[109],"all":[113,136],"kernels":[116],"has":[117],"obvious":[118],"advantages":[119],"computational":[121],"efficiency.":[122],"capabilities":[125],"lower":[137],"than":[138,173],"PCA.":[139,153,174],"capability":[142],"(CA)":[143],"equivalent":[151],"to":[152,205],"when":[159,210],"parameter":[162,213],"<inline-formula>":[163,214],"<tex-math":[164,215],"notation=\"LaTeX\">$\\sigma":[165,216],"\\ge":[166],"2$":[167],"</tex-math></inline-formula>,":[168,218],"its":[169],"CA":[170],"higher":[172],"accuracy":[177,222],"stable":[190],"formations":[193],"sensitive":[204],"parameter,":[208],"only":[209],"=5$":[217],"optimal":[220,230],"can":[223],"be":[224],"obtained.":[225],"At":[226],"this":[227],"time,":[228],"formation.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
