{"id":"W3098328330","doi":"10.22215/etd/2020-14287","title":"Improving the Performance of Video Processing on Hadoop Clusters","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; SPARK (programming language); Big data; Data processing; Video processing; Data-intensive computing; Database; Real-time computing; Data mining; 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":[0.002447529,0.001021885,0.0006552343,0.001000586,0.001689492,0.002231049,0.002118913,0.0005338111,0.001947815],"category_scores_gemma":[0.007691314,0.000397882,0.0005625595,0.001523932,0.0004839985,0.002559731,0.001315088,0.00144066,0.001215258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001732218,"about_ca_system_score_gemma":0.002915675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01067565,"about_ca_topic_score_gemma":0.008730445,"domain_scores_codex":[0.9976758,0.0003077046,0.000126359,0.0004203156,0.001081719,0.0003881949],"domain_scores_gemma":[0.9956391,0.001000536,0.0001002023,0.0006531518,0.002222527,0.0003844573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001909332,0.0009736173,0.00924472,0.000843112,0.0002577626,0.0005321466,0.001136084,0.2144707,0.1136251,0.01359712,0.08500612,0.5584042],"study_design_scores_gemma":[0.0001532793,0.0003293273,0.0052062,0.00006085341,0.00006173042,0.0001264232,0.0006617354,0.8761071,0.08635232,0.008188807,0.02265935,0.00009285109],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4616729,0.0025559,0.4332698,0.002733608,0.00164548,0.001056877,0.001858581,0.03974454,0.0554624],"genre_scores_gemma":[0.700205,0.00105189,0.2865333,0.0003097366,0.0001518552,0.0003280561,0.002883064,0.001360392,0.007176731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01067565,"threshold_uncertainty_score":0.021227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02077544453054981,"score_gpt":0.2845855546082132,"score_spread":0.2638101100776634,"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."}}