{"id":"https://openalex.org/W33291739","doi":"https://doi.org/10.3390/s20236946","title":"HUBUNGAN ANTARA KADAR HEMOGLOBIN DENGAN KEMAMPUANKOGNITIF DAN PRESTASI BELAJAR REMAJA PUTRI MURIDTIGA SEKOLAH MENENGAH UMUM DI SEMARANG","display_name":"HUBUNGAN ANTARA KADAR HEMOGLOBIN DENGAN KEMAMPUANKOGNITIF DAN PRESTASI BELAJAR REMAJA PUTRI MURIDTIGA SEKOLAH MENENGAH UMUM DI SEMARANG","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W33291739","doi":"https://doi.org/10.3390/s20236946","mag":"33291739"},"language":"en","primary_location":{"id":"mag:33291739","is_oa":false,"landing_page_url":"http://eprints.undip.ac.id/20136/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},"type":"article","indexed_in":[],"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/A5015641811","display_name":"Apoina Kartini","orcid":"https://orcid.org/0000-0003-4845-3730"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Apoina Kartini","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4845-3730","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113018141","display_name":"Suhartono Suhartono","orcid":"https://orcid.org/0000-0002-4194-7220"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suhartono Suhartono","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4194-7220","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110985035","display_name":"Bagoes Widjanarko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bagoes Widjanarko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085694456","display_name":"M. Zen Rahfiludin","orcid":"https://orcid.org/0000-0003-2290-0395"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M.Zen Rahfiludin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00599644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"23","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13602","display_name":"Educational Methods and Media Use","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13602","display_name":"Educational Methods and Media Use","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14495","display_name":"Public Health and Nutrition","score":0.9708999991416931,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T13559","display_name":"Edcuational Technology Systems","score":0.9460999965667725,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hemoglobin","display_name":"Hemoglobin","score":0.47691985964775085},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3845701515674591},{"id":"https://openalex.org/keywords/gynecology","display_name":"Gynecology","score":0.370564341545105},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.31206345558166504},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15668681263923645}],"concepts":[{"id":"https://openalex.org/C2778917026","wikidata":"https://www.wikidata.org/wiki/Q43041","display_name":"Hemoglobin","level":2,"score":0.47691985964775085},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3845701515674591},{"id":"https://openalex.org/C29456083","wikidata":"https://www.wikidata.org/wiki/Q1221899","display_name":"Gynecology","level":1,"score":0.370564341545105},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.31206345558166504},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15668681263923645}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:33291739","is_oa":false,"landing_page_url":"http://eprints.undip.ac.id/20136/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G6173460034","display_name":null,"funder_award_id":"CNOOC-KJ ZDHXJSGG YF 2019-02","funder_id":"https://openalex.org/F4320322143","funder_display_name":"China National Offshore Oil Corporation"}],"funders":[{"id":"https://openalex.org/F4320322143","display_name":"China National Offshore Oil Corporation","ror":"https://ror.org/054dq0621"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,20,25,29,33,37,57,67,74,84,92,108,112,133,138,150,154,163],"field":[2],"of":[3,12,19,24,41,86,96,158,165],"ultrasonic":[4,26,42,58],"nondestructive":[5],"testing":[6],"(NDT),":[7],"robust":[8],"and":[9,22,39,156],"accurate":[10],"detection":[11,43],"defects":[13],"is":[14,62,104,130],"a":[15,77,119],"challenging":[16],"task":[17],"because":[18],"attenuation":[21],"noising":[23],"wave":[27],"from":[28],"structure.":[30],"For":[31],"determining":[32],"reflection":[34],"characteristics":[35],"representing":[36],"position":[38],"amplitude":[40],"signals,":[44],"sparse":[45],"blind":[46,101,147],"deconvolution":[47,75,148],"methods":[48,152],"have":[49],"been":[50],"implemented":[51],"to":[52,72,106,111],"separate":[53],"overlapping":[54,160],"echoes":[55,161],"when":[56],"transducer":[59],"impulse":[60],"response":[61],"unknown.":[63],"This":[64],"letter":[65],"introduces":[66],"\u21131/\u21132":[68],"ratio":[69],"regularization":[70],"function":[71],"model":[73],"as":[76],"nonconvex":[78],"optimization":[79],"problem.":[80],"The":[81,123],"initialization":[82],"influences":[83],"accuracy":[85],"estimation":[87],"and,":[88],"for":[89],"this":[90],"purpose,":[91],"alternating":[93,125],"direction":[94],"method":[95],"multipliers":[97],"(ADMM)":[98],"combined":[99],"with":[100,145],"gain":[102],"calibration":[103],"used":[105],"find":[107],"initial":[109],"approximation":[110],"real":[113],"solution,":[114,135],"given":[115],"multiple":[116],"observations":[117],"in":[118,132,136,162],"joint":[120],"sparsity":[121],"case.":[122],"proximal":[124],"linearized":[126],"minimization":[127],"(PALM)":[128],"algorithm":[129],"embedded":[131],"iterate":[134],"which":[137],"majorize-minimize":[139],"(MM)":[140],"approach":[141],"accelerates":[142],"convergence.":[143],"Compared":[144],"conventional":[146],"algorithms,":[149],"proposed":[151],"demonstrate":[153],"robustness":[155],"capability":[157],"separating":[159],"context":[164],"synthetic":[166],"experiments.":[167]},"counts_by_year":[],"updated_date":"2025-07-27T08:57:57.515327","created_date":"2016-06-24T00:00:00"}
