{"id":"W2010194014","doi":"10.4028/www.scientific.net/amm.347-350.327","title":"Ultrasonic Phased Array Industrial Imaging with Sub-Nyquist Sampling Rate","year":2013,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China; fRI Research","keywords":"Phased array; Nyquist–Shannon sampling theorem; Sampling (signal processing); Nyquist rate; SIGNAL (programming language); Phased-array optics; Nyquist frequency; Ultrasonic sensor; Acoustics; Electronic engineering; Transducer; Phased array ultrasonics; Noise (video); Computer science; Engineering; Physics; Telecommunications; Computer vision; Bandwidth (computing)","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":[0.0007361008,0.000503629,0.0004976378,0.0004802125,0.0001950215,0.0005171139,0.0005789986,0.0006133725,0.0009842737],"category_scores_gemma":[0.002147469,0.0002391595,0.0003810092,0.0007021711,0.0005391663,0.001344626,0.0004462099,0.0007996461,0.0003956612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005419651,"about_ca_system_score_gemma":0.0004522624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001035553,"about_ca_topic_score_gemma":0.0009190325,"domain_scores_codex":[0.9991505,0.0001750983,0.00003882265,0.0001264182,0.0004656264,0.0000435712],"domain_scores_gemma":[0.9993308,0.0002757196,0.00007965534,0.0001414765,0.0001503704,0.00002205865],"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":[0.0005784878,0.0001163721,0.00283695,0.0004631366,0.00007762494,0.0002347848,0.0003447448,0.1809569,0.1935854,0.143337,0.003208185,0.4742603],"study_design_scores_gemma":[0.00001643484,0.0000933358,0.0004851713,0.00001068812,0.00001234807,0.0001901655,0.00001770291,0.9578013,0.02792669,0.008649136,0.004777442,0.00001960637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005223474,0.0001876515,0.993237,0.00008218735,0.00002348858,0.00001367801,0.0000259391,0.0001894354,0.001017247],"genre_scores_gemma":[0.3578043,0.0009822197,0.6373051,0.000162954,0.000100634,0.0001338195,0.0002460698,0.00007987332,0.003185087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001035553,"threshold_uncertainty_score":0.003932297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707251744446414,"score_gpt":0.2023617789958101,"score_spread":0.185289261551346,"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."}}