{"id":"W3177987872","doi":"10.1109/iccworkshops50388.2021.9473827","title":"Energy Efficient Resource Allocation and Trajectory Design for Multi-UAV-Enabled Wireless Networks","year":2021,"lang":"en","type":"article","venue":"","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Backhaul (telecommunications); Cache; Transmitter power output; Software deployment; Mathematical optimization; Throughput; Resource allocation; Wireless network; Efficient energy use; Optimization problem; Wireless; Convex optimization; Computer network; Regular polygon; Algorithm; Telecommunications; Engineering; Channel (broadcasting)","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":[0.00008019168,0.00007752243,0.000077696,0.0000289771,0.00006843534,0.00003362161,0.0000354609,0.00006425903,0.00001431735],"category_scores_gemma":[0.000004631339,0.00007972436,0.00001912077,0.0001408912,0.000009915878,0.00002536161,0.000008851912,0.0000314731,7.370199e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002848773,"about_ca_system_score_gemma":0.00001150637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006684053,"about_ca_topic_score_gemma":0.00001531443,"domain_scores_codex":[0.9995598,0.00001587063,0.0001179689,0.000141451,0.00004112545,0.0001237899],"domain_scores_gemma":[0.9997036,0.00006095105,0.00001349756,0.000124597,0.0000563087,0.00004097544],"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":[0.000003592947,0.00002177879,0.000004432408,0.00001382565,0.00001083472,1.958225e-7,0.00005214327,0.9885499,0.002197848,0.001753874,0.000999096,0.006392512],"study_design_scores_gemma":[0.0003181957,0.000007045545,0.00006945831,0.000006300823,0.00001200668,0.000001619085,0.00006601498,0.98426,0.009501056,0.000006770005,0.005652647,0.00009892686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004707522,0.0004716462,0.9939291,0.00003224559,0.0000396846,0.0001513341,0.000001214676,0.00015287,0.0005143975],"genre_scores_gemma":[0.8155231,0.0001901221,0.1826594,0.00008734527,0.00007022997,0.000222129,0.00008509384,0.00003855458,0.001124042],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8112697,"threshold_uncertainty_score":0.3251065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01559268243833168,"score_gpt":0.2043944421003216,"score_spread":0.18880175966199,"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."}}