{"id":"W3135825682","doi":"10.1109/itsc55140.2022.9922133","title":"Dynamic Resource Management for Providing QoS in Drone Delivery Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Drone; Computer science; Quality of service; Bernoulli's principle; Markov decision process; Queueing theory; Markov process; Dynamic Bayesian network; Resource allocation; Mathematical optimization; Distributed computing; Queue; Real-time computing; Operations research; Computer network; Bayesian probability; Artificial intelligence; Engineering; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005793707,0.000818238,0.0008772459,0.000415164,0.0005337346,0.0009002528,0.001385811,0.0007765079,0.00209244],"category_scores_gemma":[0.001748343,0.0003920704,0.0003449759,0.0004146142,0.0004598356,0.001022452,0.0009828985,0.001170043,0.000296157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001007658,"about_ca_system_score_gemma":0.000904274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008664838,"about_ca_topic_score_gemma":0.006544568,"domain_scores_codex":[0.9996932,0.00006667702,0.00001755496,0.00008790195,0.0000610955,0.00007366501],"domain_scores_gemma":[0.9994805,0.0002723461,0.00007238109,0.00003134554,0.00007717833,0.0000662629],"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":[0.0000745892,0.00004780369,0.0005532418,0.00005648779,0.0000180087,0.00008539046,0.00005842626,0.9510819,0.002614304,0.003592547,0.0009241955,0.04089319],"study_design_scores_gemma":[0.000003903454,0.000006264092,0.00004111006,0.00000197156,0.000001811042,0.00000716272,0.00000771428,0.9987256,0.0001928259,0.0008143108,0.0001954251,0.000001902083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0595994,0.0009688178,0.9351513,0.0003731599,0.00008742291,0.00008447145,0.00007543315,0.0006525833,0.00300731],"genre_scores_gemma":[0.9356936,0.000286228,0.06209628,0.0001328799,0.00004578796,0.0000752515,0.00009061494,0.00005324809,0.001526193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008664838,"threshold_uncertainty_score":0.01722884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820465156832261,"score_gpt":0.2533804109130022,"score_spread":0.2251757593446796,"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."}}