{"id":"W2728520874","doi":"10.22215/etd/2015-11154","title":"Simulation of Mobile Hydroacoustic Communications in Underwater Acoustic Sensor Networks","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Public Works and Government Services Canada","keywords":"Bit error rate; MATLAB; Underwater; Underwater acoustic communication; Noise (video); Spectral density; Computer science; Mobility model; Electronic engineering; Attenuation; Acoustics; Energy (signal processing); Telecommunications; Engineering; Geography; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002963855,0.0003680377,0.0004630686,0.000364093,0.0004058923,0.0005231784,0.0007875725,0.0007460183,0.001409672],"category_scores_gemma":[0.001412054,0.0002418668,0.000479263,0.0005504146,0.0004541469,0.0006142702,0.0005430111,0.000391803,0.0001735935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006125313,"about_ca_system_score_gemma":0.0006719813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01040052,"about_ca_topic_score_gemma":0.00532829,"domain_scores_codex":[0.9997882,0.00007617826,0.00001155541,0.00002731679,0.00005988151,0.00003691252],"domain_scores_gemma":[0.9993919,0.0003531503,0.00007700748,0.0000317052,0.0001094976,0.0000368182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001389872,0.00001345128,0.0008311595,0.00001363433,0.000007085827,0.00004452387,0.00003606942,0.9941486,0.0006189505,0.002497641,0.0001060235,0.001669038],"study_design_scores_gemma":[0.000003138422,0.000009116867,0.0001169946,0.000002421089,0.000001951497,0.00000678401,0.00001106468,0.9990379,0.000209656,0.0003715941,0.0002276649,0.000001718411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7111415,0.0005355569,0.2664903,0.000565092,0.00007739977,0.000132369,0.0004512307,0.0004718158,0.02013464],"genre_scores_gemma":[0.9635071,0.0003966134,0.03121195,0.00006392573,0.00001392182,0.0001478224,0.0002518863,0.00003998379,0.004366881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01040052,"threshold_uncertainty_score":0.02067995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029911390260953,"score_gpt":0.2911245564868594,"score_spread":0.2608254425842499,"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."}}