01977nam 2200493Ia 450 991069535090332120061010153535.0(CKB)5470000002369242(OCoLC)72471057(EXLCZ)99547000000236924220061010d2005 ua 0engurbz|---|||||txtrdacontentcrdamediacrrdacarrierPilot willingness to take off into marginal weather[electronic resource] final report /William KnechtWashington, DC :Office of Aerospace Medicine, Federal Aviation Administration ;Ft. Belvior, VA :Available through the Defense Technical Information Center ;Springfield, VA :National Technical Information Service,2005.i, 9, 1, 3 pages digital, PDF fileTitle from title screen (viewed on Oct. 10, 2006)."August 2005.""DOT/FAA/AM-05/15."Includes bibliographic references (page 7).Pt. 2, Antecedent overfitting with forward stepwise logistic regressionPilot willingness to take off into marginal weather Meteorology in aeronauticsAir pilotsPsychologyLogistic regression analysisData processingStatisticsRisk assessmentStatistics.lcgftMeteorology in aeronautics.Air pilotsPsychology.Logistic regression analysisData processingRisk assessment.Knecht William267712United States.Office of Aerospace Medicine.United States.Federal Aviation Administration.Civil Aerospace Medical Institute.GPOGPOBOOK9910695350903321Pilot willingness to take off into marginal weather3423805UNINA04515nam 22005775 450 991098469480332120250228115235.09789819635061981963506310.1007/978-981-96-3506-1(CKB)37726369000041(MiAaPQ)EBC31927409(Au-PeEL)EBL31927409(DE-He213)978-981-96-3506-1(OCoLC)1505736100(EXLCZ)993772636900004120250228d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierEvolutionary Multi-Criterion Optimization 13th International Conference, EMO 2025, Canberra, ACT, Australia, March 4–7, 2025, Proceedings, Part I /edited by Hemant Singh, Tapabrata Ray, Joshua Knowles, Xiaodong Li, Juergen Branke, Bing Wang, Akira Oyama1st ed. 2025.Singapore :Springer Nature Singapore :Imprint: Springer,2025.1 online resource (498 pages)Lecture Notes in Computer Science,1611-3349 ;155129789819635054 9819635055 -- Algorithm design. -- Towards an Efficient Innovation Path Seeking Algorithm Using Directed Domination. -- An MaOEA/Local Search Hybrid Based on a Fast, Stochastic BFGS Using Achievement Scalarizing Search Directions. -- Selective evaluations for expediting multi-objective bilevel optimization. -- MOAISDX: A New Multi-objective Artificial Immune System based on Decomposition. -- PAES-25: Local Search, Archiving and Multi/Many-objective PseudoBoolean Functions. -- Weights-Guided Random Bit Climber for Binary Many-objective Optimization. -- Bilevel Optimization-based Decomposition for Solving Single and Multi objective Optimization Problems. -- A Study on Optimistic & Pessimistic Pareto-fronts in Multi objective Bilevel Optimization via ?-Perturbation. -- Cumulative Step Size Adaptation for Adaptive SEMO in Integer Space. -- Adaptive Normal-Boundary Intersection Directions for Evolutionary Many objective Optimization with Complex Pareto Fronts. -- Encodings for Multi-Objective Free-Form Coverage Path Planning. -- VBEA: Voting-Based Evolutionary Algorithm for Multi-Objective Planning. -- Enhancing NSGA-II with a Knee Point for Constrained Multi-objective Optimization. -- Benchmarking. -- Single and Multi-Objective Optimization Benchmark Problems Focusing on Human-Powered Aircraft Design. -- An Extension of the Welded Beam Problem that Includes Multiple Interactng Design Concepts. -- Extended Results on Analytical Hypervolume Indicator Calculation of Linear and Quadratic Pareto Fronts. -- MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOH profiler. -- Applications. -- Multi-Objective Sequential Decision Making for Holistic Supply Chain Optimization. -- Interactive evolutionary re optimization for ground fish survey planning. -- A Multi-Objective Competitive Co-Evolutionary Framework with Progressive Shrinking for Wargame Scenarios. -- -- Impact of Environmental Changes on Optimized Robotics Collective Motion for Multi-Objective Coverage Tasks.This two-volume set LNCS 15512-15513 constitutes the proceedings of the 13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025, held in Canberra, ACT, Australia, in March 2025. The 38 full papers and 2 extended abstracts presented in this book were carefully reviewed and selected from 63 submissions. The papers are divided into the following topical sections: Part I : Algorithm design; Benchmarking; Applications. Part II : Algorithm analysis; Surrogates and machine learning; Multi-criteria decision support.Lecture Notes in Computer Science,1611-3349 ;15512Artificial intelligenceArtificial IntelligenceArtificial intelligence.Artificial Intelligence.006.3Singh Hemant1790150Ray Tapabrata1763711Knowles Joshua1790151Li Xiaodong1790152Branke Juergen1790153Wang Bing1217580Oyama Akira1790154MiAaPQMiAaPQMiAaPQBOOK9910984694803321Evolutionary Multi-Criterion Optimization4326244UNINA01146nam0 22002891i 450 UON0019579920231205103233.53620030730f1980 |0itac50 baengGB|||| 1||||Ghosts of the gothicAustin, Eliot and LawrenceJudith WiltPrincetonPrinceton university1980xii, 307 p.23 cm.AUSTIN JANEUONC040584FIELIOT GEORGEUONC038285FILAWRENCE DAVID HERBERTUONC039601FIUSPrincetonUONL000074820.09Letteratura inglese e in antico inglese. Storia, descrizione, studi critici21WILTJudithUONV115566450830Princeton University PressUONV245813650ITSOL20250530RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00195799SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI Angl IV C 0428 SI LO 38800 5 0428 BuonoGhosts of the gothic146541UNIOR