Neural computation and particle accelerators : research, technology and applications / / Emmerich Chabot and Horace D'Arras, editors

• Pubblicazione: New York, : Nova Science Publishers, c2010
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (433 pages)
• Disciplina: 006.3/2
• Soggetto topico: Neural computers; Particle accelerators
• Altri autori: ChabotEmmerich D'ArrasHorace
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- NEURAL COMPUTATION AND PARTICLE ACCELERATORS: RESEARCH, TECHNOLOGY AND APPLICATIONS -- NEURAL COMPUTATION AND PARTICLE ACCELERATORS: RESEARCH, TECHNOLOGY AND APPLICATIONS -- CONTENTS -- PREFACE -- Chapter 1 MAGNETIC FRINGE FIELDS AND INTERFERENCE IN HIGH-INTENSITY ACCELERATORS -- Abstract -- I. Introduction -- II. Magnet Modeling -- A. Overview of Simulation Codes -- B. A Modeling Example -- III. 3D Field Multipole Expansion -- A. Review of Theory -- B. Expansion Techniques -- C. On-Axis Gradients -- D. A 5th-Order Representation -- E. Higher-Order Effects -- IV. Particle Optics in a Single Quad -- A. Simulation Model and 3D Mulipole Expansion -- B. Form Factor Theory on Magnetic Fringe Field -- C. Linear Transfer Matrices from the Trajectory Equations -- D. Lens Parameters and Hard Edge Models -- E. Third-Order Aberrations -- F. Particle Optics In 30Q44 -- V. Magnetic Interference between Two Magnets -- A. Change in Linear Focusing Function -- B. Magnetic Interference as a First-Order Perturbation -- C. Hard Edge Models for a Perturbed Quad -- VI. Particle Optics in Quad Doublet Assembly -- A. Two-Dimensional Field Parameters -- B. Magnetic Fringe and Interference -- C. Linear Transfer Matrices and Hard Edge Models -- D. Third-Order Aberrations -- E. Verification of Particle Trajectories -- VII. Particle Tracking in Beam Lines -- A. SNS Ring Injection and Beam Losses in Its Dump Line -- B. Injection Constraints -- (a) Closed Orbit Bump and Good Injection -- (b) Transport of Waste Beams Through IDSM -- C. 3D Modeling of Injection Waste Beam Dump Line -- (a) Simulation Models -- (b) Magnets and Fields on Beam Line -- (c) Initial Conditions of Test Particles -- D. 3D Particle Trajectories through IDSM -- E. Remedies -- (a) H--Proton Particle Losses in the Y-Direction in IDSM -- (b) H0-Proton Particle Losses in the X-Direction in IDSM. ; (c) Modification of a Spare IDSM -- F. Experimental Verifications -- VIII. Conclusion -- Acknowledgments -- References -- Chapter 2 TRANSPORT CALCULATIONS AND ACCELERATOR EXPERIMENTS NEEDED FOR RADIATION RISK ASSESSMENT IN SPACE -- Abstract -- 1. Introduction -- 2. Reduction of the Radiation Exposure -- 3. Particle and Heavy Ion Transport Codes -- 3.1. Deterministic Codes -- 3.2. Monte Carlo Codes -- 4. Particle and Heavy Ion Accelerators -- 5. Accelerator Experiments Needed for Validation of Transport Codes -- 6. Summary and Conclusions -- References -- Chapter 3 TRANSPORT OF ION-THERAPY BEAMS IN ROTATING GANTRIES -- Abstract -- Introduction -- Milestones, Current Status and Trends -- Development of Ion Gantries -- Summary of the Relevant Beam Transport Concepts -- Equations of Motion -- Single-Particle Transport Formalism -- Beam-Envelopes Transport Formalism -- Formulation of the Problem -- Rotator-Based Matching Techniques -- Principle of the Rotator-Matching -- Rotator Lattices -- Demonstration of the Rotator Action -- Matching the Dispersion Function -- Analysis of Ion-Optical Properties of the Rotator Lattices -- Matching Techniques without the Rotator - The Sigma-Matrix Matching -- Demonstration of the Sigma-Matrix Matching -- Matching the Dispersion Function -- Application Restrictions of the Sigma-Matrix Matching Technique -- Conclusion -- Acknowledgment -- References -- Chapter 4 INVESTIGATION OF SURFACE TREATMENTS OF NIOBIUM FLAT SAMPLES AND SRF CAVITIES BY GAS CLUSTER ION BEAM TECHNIQUE FOR PARTICLE ACCELERATORS -- Abstract -- 1. Introduction -- 2. Brief History of GCIB and Its Application to Nb -- 3. Working Principal of GCIB -- 4. Suppression of Field Emission by GCIB Treatments -- 5. Modifications of Morphology of Nb Surfaces by GCIB -- 6. Modifications of Surface Oxide Layer Structure by GCIB. ; 7. GCIB Treatments on Nb Single Cell Cavities -- 8. Summary and Perspective -- Acknowledgment -- References -- Chapter 5 THE ROLES OF CHLOROPLAST PROTEASES IN THE ASSEMBLY AND TURNOVER OF LIGHT-HARVESTING COMPLEX -- Abstract -- Introduction -- Classification, Structure and Functions of LHC proteins -- Chloroplast Import -- Stromal Processing Peptidase -- PreP1 and PreP2 -- Assembly of LHC Proteins -- Two Hypotheses -- EGY1 -- Degradation of LHC Proteins -- Lysosomal-Like Vacuole -- FtsHs -- Clps -- Perspectives -- Acknowledgements -- References -- Chapter 6 DESIGN OF HIGH POWER NEUTRON SOURCES FOR NUCLEAR TECHNOLOGY APPLICATIONS BY MEANS OF PARTICLE ACCELERATORS -- Abstract -- Introduction -- Application of Neutron Sources -- General Classification of Neutron Sources -- Low Intensity Neutron Sources -- High Intensity Neutron Sources -- High Power Neutron Sources -- Overview of Neutron Source Design -- Neutron Production -- Radiological Assessments -- Thermal-Hydraulics -- Mechanical Analysis -- Materials -- Conclusion -- References -- Chapter 7 SUBDURAL INTERICTAL EEG ANALYSIS FOR EXTRACTING DISCRIMINATING FEATURES TOWARDS ELECTRODE CLASSIFICATION USING ARTIFICIAL NEURAL NETWORKS -- Abstract -- 1. Introduction -- 2. Methods -- 2.1. Participants -- 2.2. Recording System -- 2.3. Algorithm Development Process -- Step 1- Filtering the Input EEG Data -- Step 2- Extraction of Features from the EEG Data -- Step 3- Implementation of Regression Lines for each Electrode and Parameter -- Step 4- Implementation of an Artificial Neural Network for Linear Classification -- Step 5- Selection of the Best Classifiers -- 3. Results -- 3.1. Detailed Results for Patient #1 -- 3.2. Compilation of Results for All Cases -- 4. Discussion -- 5. Conclusion -- Acknowledgments -- References. ; Chapter 8 A NEW METHOD FOR PREPARING SUBMICRON AND NANO-SIZED AROMATIC POLYAMIDE PARTICLES WITH VARIOUS MORPHOLOGIES AND CHARACTERISTIC FEATURES -- Abstract -- 1. Introduction -- 2. Experiment -- 2.1. Materials -- 2.2. Preparation -- 2.3. Characterization -- 3. Results and Discussion -- 3.1. Volume of Water Added -- 3.2. Ultrasonic Frequency -- 3.3. Mixing Manner -- 3.4. Characteristics of Aromatic Polyamide Particles -- 4. Conclusion -- References -- Chapter 9 SURFACE TREATMENTS OF NIOBIUM SUPERCONDUTING RADIO FREQUENCY CAVITIES BY ELECTROPOLISHING FOR PARTICLE ACCELERATORS* -- Reference -- Chapter10FRICTIONALCOOLINGOFAPARTICLEBEAM -- Abstract -- 1.Introduction -- 2.PhaseSpaceTransformationbyFrictionalForces -- 3.SelectedEnergyRegimes -- 4.MultipleScattering -- 5.TransformationwithSimultaneousAcceleratingForce -- 6.TheFirstFrictional-CoolingExperimentwithMuons -- 6.1.ExperimentalArrangement -- 6.2.Results -- References -- Chapter11MODELSELECTIONFORGAUSSIANMIXTUREMODELINATWO-PHASEPROCEDURE:AFURTHERCOMPARATIVESTUDY -- Abstract -- 1.Introduction -- 2.GaussianMixtureModelandMLLearning -- 3.Two-phaseProcedureandTypicalModelSelectionCriteria -- 3.1.Two-phaseProcedure -- 3.2.SeveralTypicalModelSelectionCriteria -- 3.3.BYYModelSelectionCriterionforSmallSampleSize -- 3.4.ComparativeExperimentsonCriteriainTwo-PhaseImplementation -- 3.4.1.OnSimulatedData -- 3.4.2.OnRealWorldData -- 4.ThreeDataSmoothingScaleUpdatingFormulaeforBYY-S -- 4.1.ThreeFormulaetoUpdatetheDataSmoothingScaleh2 -- 4.2.ComparativeExperimentsonThreeUpdatingFormulae -- 4.2.1.OnSimulatedData -- 4.2.2.OnRealWorldData -- 5.ConcludingRemarks -- Acknowledgment -- References -- Chapter12PRINCIPLEOFALASER-DRIVENCHARGED-PARTICLEACCELERATOR -- Abstract -- Acknowledgment -- References -- Chapter13TOPOLOGICALOPTIMIZATIONOFARTIFICIALNEURALNETWORKSUSINGAPATTERNSEARCHMETHOD -- Abstract -- 1.Introduction. ; 2.ArtificialNeuralNetworks -- 3.TopologicalOptimization -- 3.1.GeneralizedPatternSearchMethod -- 3.2.EvolutionaryStrategy -- 4.FormulationofModelProblem -- 5.OptimalNetworkTopology -- 6.DynamicApplication -- 6.1.MathematicalModel -- 6.2.Results -- 7.Conclusion -- Acknowledgments -- References -- Chapter14APPROXIMATEJOINTMATRIXDIAGONALIZATIONBYRIEMANNIAN-GRADIENT-BASEDOPTIMIZATIONOVERTHEUNITARYGROUP(WITHAPPLICATIONTONEURALMULTICHANNELBLINDDECONVOLUTION) -- Abstract -- 1.Introduction -- 2.JointDiagonalizationbyRiemannian-Gradient-BasedOpti-mizationovertheUnitaryGroupofMatrices -- 2.1.JointComplex-ValuedMatrixDiagonalizationbyUnitaryTransformCastasanOptimizationProblem -- 2.2.OptimizationovertheUnitaryGroupofMatricesbyaRiemannian-Gradient-BasedSteppingMethod -- 2.3.OptimalStepsizeScheduleSelection -- 3.MultichannelBlindDeconvolutionbyNeuralBlindSepara-tionintheTime/Frequency-Domain -- 3.1.MultichannelBlindDeconvolutionandBlindSignalSeparationintheTime/Frequency-Domain -- 3.2.NeuralBlindSignalSeparationintheComplexDomainbyJointEigen-matricesDiagonalization -- 3.3.ApproximateJointDiagonalizationofScaledEigenmatrices -- 4.NumericalResultsandDiscussions -- 4.1.ExperimentalSettingandNumericalIssues -- 4.2.ExperimentsonTwoSourceSignals -- 4.3.ExperimentsonFourSourceSignals -- 5.Conclusion -- Acknowledgments -- A.Appendix:CalculationoftheEuclideanGradientoftheCostFunction(2) -- B.Appendix:CalculationoftheCoefficientsinExpansion(9) -- References -- Chapter15SPIKETIMINGDEPENDENTPLASTICITY:AROUTETOROBUSTNESSINHARDWAREANDALGORITHMS -- Abstract -- 1.Introduction -- 1.1.HebbianLearningandSpikeTimingDependentPlasticity -- 1.2.Depth-from-MotionAlgorithm -- 1.3.Summary -- 2.AnEarlyVisualDepth-from-MotionModelMediatedbySTDP -- 2.1.Introduction -- 2.2.Model -- 2.2.1.SpikingNeuronalModel -- 2.2.2.AVisionAlgorithmUsingSpikes -- 2.2.3.Adaptation -- 2.3.SimulationResults. ; 2.4.Conclusion.
• Titolo autorizzato: Neural computation and particle accelerators
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910813769403321
• Lo trovi qui: Univ. Federico II
• Serie: Neuroscience research progress series.