{"id":"W1486524747","doi":"10.1109/ccece.2015.7129166","title":"Optimization of control parameters using averaging of handover indicator and received power for minimizing ping-pong handover in LTE","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Handover; Computer science; Power (physics); Control theory (sociology); Degradation (telecommunications); Transceiver; Power control; Real-time computing; Term (time); SIGNAL (programming language); Control (management); Computer network; Wireless; Telecommunications; Artificial intelligence","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":[0.000369559,0.0004873703,0.0003122009,0.0002612573,0.0002028059,0.0003976193,0.0003869626,0.0002433618,0.0002911379],"category_scores_gemma":[0.0009862577,0.0001427021,0.0001572586,0.00019488,0.0002377821,0.000362152,0.0002538254,0.0002508728,0.00005713128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002621808,"about_ca_system_score_gemma":0.0003407648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001467243,"about_ca_topic_score_gemma":0.001522834,"domain_scores_codex":[0.9997751,0.00004384495,0.00001533178,0.00005544287,0.00007885945,0.00003134037],"domain_scores_gemma":[0.9997403,0.0001103079,0.00005583421,0.00001911625,0.00006464516,0.000009850626],"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":[0.0001551779,0.0001356266,0.002441989,0.00006414411,0.00005311013,0.00004776232,0.00008334275,0.7261885,0.05246263,0.001976065,0.00041757,0.2159741],"study_design_scores_gemma":[0.000008040129,0.0001054907,0.001466919,0.00000352556,0.00001435968,0.0000225223,0.00001077892,0.9906837,0.007114137,0.0003306621,0.000232948,0.00000700586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1304699,0.0003215034,0.8672546,0.00004821904,0.00002124419,0.00002622041,0.00001261326,0.0003390539,0.001506723],"genre_scores_gemma":[0.9686133,0.00005596426,0.03095028,0.00001589867,0.00001232052,0.00002096034,0.00001148622,0.00002002582,0.0002997439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001467243,"threshold_uncertainty_score":0.002917349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207289928367532,"score_gpt":0.2379696580673432,"score_spread":0.21724066523059,"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."}}