{"id":"W4226020401","doi":"10.1109/jsyst.2022.3155786","title":"Joint Trajectory and Power Optimization for Jamming-Aided NOMA-UAV Secure Networks","year":2022,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Jamming; Computer science; Telecommunications link; Scheduling (production processes); Mathematical optimization; Convex optimization; Optimization problem; Transmission (telecommunications); Transmitter power output; Noma; Trajectory optimization; Computer network; Trajectory; Power (physics); Real-time computing; Regular polygon; Transmitter; Algorithm; Telecommunications; Mathematics; Optimal control","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000352009,0.0001156841,0.0001577861,0.0001147978,0.0003891876,0.0001140781,0.00008072515,0.00005697702,0.00006738672],"category_scores_gemma":[0.000005680999,0.0001203139,0.00005411543,0.000146044,0.0000102682,0.0001250632,0.00001125747,0.0002370317,8.598465e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001436969,"about_ca_system_score_gemma":0.00002114514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003972511,"about_ca_topic_score_gemma":0.000001292286,"domain_scores_codex":[0.9991851,0.00004194671,0.0003285313,0.0001167498,0.000140111,0.0001875882],"domain_scores_gemma":[0.9995958,0.00002673117,0.0001060657,0.0001101131,0.00007698021,0.00008435309],"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":[0.000006490753,0.00001037803,0.00003411218,0.00002662343,0.00003246422,0.000001857371,0.0002571033,0.9922717,0.0002268174,0.00007962492,0.006755905,0.0002968739],"study_design_scores_gemma":[0.0004481987,0.00006460781,0.00006397306,0.00001581111,0.0000204634,0.0002832465,0.0002521978,0.9916775,0.00002190899,0.00001442694,0.006995209,0.0001425024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02474654,0.001419687,0.9710736,0.00003906532,0.001851873,0.0004306117,0.000016453,0.00009510908,0.0003270349],"genre_scores_gemma":[0.9948297,0.00009683383,0.004275636,0.00002269186,0.0004286008,0.0001692545,0.0000173336,0.00004636239,0.0001136421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9700831,"threshold_uncertainty_score":0.4906259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008998327847213512,"score_gpt":0.1868790141734902,"score_spread":0.1778806863262767,"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."}}