{"id":"W2606944528","doi":"10.1007/s10470-017-0969-4","title":"ZigBee-based indoor localization system with the personal dynamic positioning method and modified particle filter estimation","year":2017,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Gaziantep Üniversitesi; Ryerson University","keywords":"Trilateration; Particle filter; Resampling; Computer science; Position (finance); Real-time computing; Wireless sensor network; Algorithm; Computation; Filter (signal processing); Engineering; Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003139189,0.0006322902,0.0006929144,0.0005828264,0.0003643112,0.0005514385,0.0006790176,0.0005898615,0.001216269],"category_scores_gemma":[0.0005069212,0.0003408765,0.0004048688,0.0008975219,0.0001899149,0.0009050856,0.000484274,0.0005621264,0.0006634896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002985041,"about_ca_system_score_gemma":0.000698724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002411963,"about_ca_topic_score_gemma":0.002654133,"domain_scores_codex":[0.9995117,0.00008906676,0.00002804679,0.0001290514,0.0002077223,0.00003444154],"domain_scores_gemma":[0.9997519,0.00003854776,0.00003132369,0.00004192396,0.0001216226,0.0000147396],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000589244,0.0002099366,0.007925322,0.0004828589,0.0002924902,0.0001598393,0.0003097461,0.0604488,0.08325209,0.005356679,0.007786648,0.8331864],"study_design_scores_gemma":[0.0002429554,0.0006485982,0.01660508,0.00007965286,0.0003688971,0.0008413873,0.0001128547,0.8748524,0.07267023,0.003399866,0.03000499,0.0001730852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03318197,0.000739214,0.9564586,0.0001557254,0.0001826315,0.00006641997,0.0001546896,0.003170837,0.005889887],"genre_scores_gemma":[0.7135276,0.0007951272,0.2727289,0.000189223,0.000135717,0.0002283747,0.0006783992,0.000114496,0.01160211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002411963,"threshold_uncertainty_score":0.004795849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0109728929327256,"score_gpt":0.233009755484377,"score_spread":0.2220368625516514,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}