{"id":"W4390989433","doi":"10.5267/j.ijdns.2023.12.008","title":"A novel four-wing chaotic system with multiple equilibriums: Dynamical analysis, multistability, circuit simulation and pseudo random number generator (PRNG) based on the voice encryption","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lyapunov exponent; Chaotic; Attractor; Multistability; Encryption; Computer science; Secure communication; Pseudorandom number generator; Random number generation; Control theory (sociology); Synchronization of chaos; CHAOS (operating system); Statistical physics; Mathematics; Algorithm; Nonlinear system; Physics; Mathematical analysis; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009546114,0.0001904745,0.0002244044,0.0001885068,0.0002916427,0.0002498637,0.0002788786,0.0004057569,0.0007538545],"category_scores_gemma":[0.0001934705,0.0001055302,0.0002779329,0.0001545585,0.00033474,0.0003604284,0.0002302504,0.0002146109,0.00008789522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002032238,"about_ca_system_score_gemma":0.0002098479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009537389,"about_ca_topic_score_gemma":0.0006868342,"domain_scores_codex":[0.9999386,0.00001779467,0.000003861713,0.00001230362,0.00002021437,0.000007225853],"domain_scores_gemma":[0.9999405,0.00002022108,0.00001327634,0.000008633216,0.00001173166,0.000005701747],"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":[0.000207685,0.00008586198,0.005175881,0.0003573083,0.0001160566,0.002754248,0.0006686781,0.5713606,0.2720602,0.1009783,0.001435558,0.04479952],"study_design_scores_gemma":[0.00001198178,0.00006061347,0.000575575,0.000006205581,0.000009600519,0.0002908068,0.00001966636,0.9865438,0.007364284,0.003641728,0.001458405,0.00001736405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4003485,0.0007577039,0.5852437,0.0004882044,0.0001299599,0.0001279465,0.00009454603,0.0004591792,0.01235031],"genre_scores_gemma":[0.9611433,0.0001682124,0.03626562,0.00002606559,0.000008395637,0.0000455439,0.00002630492,0.0000112936,0.002305328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009537389,"threshold_uncertainty_score":0.002521873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03805137503845807,"score_gpt":0.2967420376343025,"score_spread":0.2586906625958444,"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."}}