05651nam 22007573u 450 991013959630332120230725053500.01-118-13834-11-119-20472-01-283-27299-797866132729971-118-13836-8(CKB)2550000000054329(EBL)693734(OCoLC)772096323(SSID)ssj0000539963(PQKBManifestationID)11373240(PQKBTitleCode)TC0000539963(PQKBWorkID)10581259(PQKB)11271659(MiAaPQ)EBC693734(EXLCZ)99255000000005432920130418d2011|||| u|| |engur|n|---|||||txtccrPension Finance[electronic resource] Putting the Risks and Costs of Defined Benefit Plans Back Under Your ControlNew York Wiley20111 online resource (338 p.)Wiley Finance ;v.708Description based upon print version of record.1-118-10636-9 Pension Finance : Putting the Risks and Costs of Defined Benefit Plans Back under Your Control; Contents; List of Figures; List of Propositions; Foreword; Preface; Acknowledgments; CHAPTER 1 Achieving Long Term Health for Pension Plans Using Improved Managerial Accounting Tools; Perspectives on DB Plans; What Is Economic or Market Value Accounting?; What the Following Chapters Provide; CHAPTER 2 Today's Conventional Pension Finance Practices; Why Managers Need to Adopt the Economic Accounting Perspective; Where Are We Today?; The Accounting Always Follows the EconomicsHistorical Context: The Actuaries' Contribution to the Existence of PensionsConclusion; CHAPTER 3 Measuring Meaningful Present Values; What Is the Right Discount Rate to Use?; The Liability-Matching Portfolio: General Perspective; Risk-Free Rate vs. Expected Return on Assets; "If We Can Earn 7.5 Percent Per Year Over The Long Term": Happy and Unhappy Asset Return Distributions; The Employer's Experience; The Discount Rate Is in Fact the Same on Both Sides of the Full Economic Balance Sheet, But That Doesn't Mean That the Liability Changes Its Value with Changes in Investment Strategy!GASB's White Paper and Public Employee Fund Discount RatesConclusion: Discount Rates; Appendix: Are There Market Values for Pension Plans?; CHAPTER 4 The Full Economic Liability: The Off-Book Starting Point for Management of Pension Costs; The Liability: Inherently an Economic Entity; A Newly Formed Pension Plan; Multiple Correct Measures of the Accrued Portion of the Liability but Only One PARENT Measure; Building a Pension Budget Identity; CHAPTER 5 Core Principles of Pension Accounting: The Full Economic Liability Meets Accrual Accounting and Normal Costs; Full Economic Normal CostEnter the Matching Principle: Normal Costs Accruing Over TimeNormal Costs and Retirees, Active Employees, and Future Employees; Allocating Pension Costs to Current Employees; Payment Patterns Other Than Level Payments; Illustrating Normal Costs and Accrued and Total Liabilities over Time; Comparing Normal Cost Methods; Normal Costs and Contributions: Multiple Measures?; Normal Cost and Agreed Levels of Benefit Security: An Accrual Method Not Reliant on the Matching Principle; Balance Sheet with Accruals of an Economic Measure of Periodic Normal CostUpdating the Beginning-Period Pension Budget IdentitySummary of Discussion of Normal Costs; Appendix: Computing Level Payment Contributions and Normal Costs with a Handheld Calculator in Order to Gain Understanding of the Nature of the Problem; CHAPTER 6 Credit Risk and the Discount Rate; Two Useful Views of the Liability's Value; Termination and Default Risk; Conclusion; CHAPTER 7 Paying for the Plan; Pension Expense and Contributions; Other Components of Pension Expense in Addition to Normal Cost; Distinguishing Economic from Conventional Supplemental Costs; Strict Economic Pension ExpenseEconomic Pension Expense in an Accrual System Praise for PENSION FINANCE ""Pension Finance is a comprehensive, integrated, and self-contained offering on the structure, management, and oversight of defined benefit pension plans, carefully composed by a prime observer and practitioner in the defined benefit pension world. . . an important and most needed contribution to defined benefit pension knowledge. Whether a prime academic researcher, experienced public policymaker, seasoned private-sector practitioner, or novice student of retirement finance, the reader is in for a treat: bon appetit!""-Robert C. Merton, MIT ""This book iWiley FinancePension trusts --ManagementPensions --FinancePensions managementPensionsFinancePension trustsManagementBusiness & EconomicsHILCCLabor & Workers' EconomicsHILCCPension trusts --Management.Pensions --Finance.Pensions management.PensionsFinancePension trustsManagementBusiness & EconomicsLabor & Workers' Economics331.25/24331.2524Waring M. Barton998854AU-PeELAU-PeELAU-PeELBOOK9910139596303321Pension Finance2291405UNINA07257nam 22007093u 450 991079228030332120231110223745.01-118-84873-X(CKB)2560000000147408(EBL)1659273(SSID)ssj0001212511(PQKBManifestationID)11788048(PQKBTitleCode)TC0001212511(PQKBWorkID)11210777(PQKB)11568791(Au-PeEL)EBL7104138(CaSebORM)9781118848739(MiAaPQ)EBC1659273(MiAaPQ)EBC7104138(EXLCZ)99256000000014740820140407d2014|||| u|| |engur|n|---|||||txtccrA Practical Introduction to Computer Vision with OpenCV1st editionHoboken Wiley20141 online resource (235 p.)New York Academy of Sciences Description based upon print version of record.1-118-84845-4 Includes bibliographical references and index.A Practical Introduction to Computer Vision with OpenCV; Contents; Preface; 1 Introduction; 1.1 A Difficult Problem; 1.2 The Human Vision System; 1.3 Practical Applications of Computer Vision; 1.4 The Future of Computer Vision; 1.5 Material in This Textbook; 1.6 Going Further with Computer Vision; 2 Images; 2.1 Cameras; 2.1.1 The Simple Pinhole Camera Model; 2.2 Images; 2.2.1 Sampling; 2.2.2 Quantisation; 2.3 Colour Images; 2.3.1 Red-Green-Blue (RGB) Images; 2.3.2 Cyan-Magenta-Yellow (CMY) Images; 2.3.3 YUV Images; 2.3.4 Hue Luminance Saturation (HLS) Images; 2.3.5 Other Colour Spaces2.3.6 Some Colour Applications2.4 Noise; 2.4.1 Types of Noise; 2.4.2 Noise Models; 2.4.3 Noise Generation; 2.4.4 Noise Evaluation; 2.5 Smoothing; 2.5.1 Image Averaging; 2.5.2 Local Averaging and Gaussian Smoothing; 2.5.3 Rotating Mask; 2.5.4 Median Filter; 3 Histograms; 3.1 1D Histograms; 3.1.1 Histogram Smoothing; 3.1.2 Colour Histograms; 3.2 3D Histograms; 3.3 Histogram/Image Equalisation; 3.4 Histogram Comparison; 3.5 Back-projection; 3.6 k-means Clustering; 4 Binary Vision; 4.1 Thresholding; 4.1.1 Thresholding Problems; 4.2 Threshold Detection Methods; 4.2.1 Bimodal Histogram Analysis4.2.2 Optimal Thresholding4.2.3 Otsu Thresholding; 4.3 Variations on Thresholding; 4.3.1 Adaptive Thresholding; 4.3.2 Band Thresholding; 4.3.3 Semi-thresholding; 4.3.4 Multispectral Thresholding; 4.4 Mathematical Morphology; 4.4.1 Dilation; 4.4.2 Erosion; 4.4.3 Opening and Closing; 4.4.4 Grey-scale and Colour Morphology; 4.5 Connectivity; 4.5.1 Connectedness: Paradoxes and Solutions; 4.5.2 Connected Components Analysis; 5 Geometric Transformations; 5.1 Problem Specification and Algorithm; 5.2 Affine Transformations; 5.2.1 Known Affine Transformations; 5.2.2 Unknown Affine Transformations5.3 Perspective Transformations5.4 Specification of More Complex Transformations; 5.5 Interpolation; 5.5.1 Nearest Neighbour Interpolation; 5.5.2 Bilinear Interpolation; 5.5.3 Bi-Cubic Interpolation; 5.6 Modelling and Removing Distortion from Cameras; 5.6.1 Camera Distortions; 5.6.2 Camera Calibration and Removing Distortion; 6 Edges; 6.1 Edge Detection; 6.1.1 First Derivative Edge Detectors; 6.1.2 Second Derivative Edge Detectors; 6.1.3 Multispectral Edge Detection; 6.1.4 Image Sharpening; 6.2 Contour Segmentation; 6.2.1 Basic Representations of Edge Data; 6.2.2 Border Detection6.2.3 Extracting Line Segment Representations of Edge Contours6.3 Hough Transform; 6.3.1 Hough for Lines; 6.3.2 Hough for Circles; 6.3.3 Generalised Hough; 7 Features; 7.1 Moravec Corner Detection; 7.2 Harris Corner Detection; 7.3 FAST Corner Detection; 7.4 SIFT; 7.4.1 Scale Space Extrema Detection; 7.4.2 Accurate Keypoint Location; 7.4.3 Keypoint Orientation Assignment; 7.4.4 Keypoint Descriptor; 7.4.5 Matching Keypoints; 7.4.6 Recognition; 7.5 Other Detectors; 7.5.1 Minimum Eigenvalues; 7.5.2 SURF; 8 Recognition; 8.1 Template Matching; 8.1.1 Applications; 8.1.2 Template Matching Algorithm8.1.3 Matching MetricsExplains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard. OpenCV libraries Computer Vision is a rapidly expanding area and it is becoming progressively easier for developers to make use of this field due to the ready availability of high quality libraries (such as OpenCV 2). This text is intended to facilitate the practical use of computer vision with the goal being to bridge the gap between the theory and the practical implementation of computer vision. The book will explain how to use the relevant OpenCV library routines and will be accompanied by a full working program including the code snippets from the text. This textbook is a heavily illustrated, practical introduction to an exciting field, the applications of which are becoming almost ubiquitous. We are now surrounded by cameras, for example cameras on computers & tablets/ cameras built into our mobile phones/ cameras in games consoles; cameras imaging difficult modalities (such as ultrasound, X-ray, MRI) in hospitals, and surveillance cameras. This book is concerned with helping the next generation of computer developers to make use of all these images in order to develop systems which are more intuitive and interact with us in more intelligent ways. Explains the theory behind basic computer vision and provides a bridge from the theory to practical implementation using the industry standard. OpenCV libraries offers an introduction to computer vision, with enough theory to make clear how the various algorithms work but with an emphasis on practical programming issues. Provides enough material for a one semester course in computer vision at senior undergraduate and Masters levels. Includes the basics of cameras and images and image processing to remove noise, before moving on to topics such as image histogramming; binary imaging; video processing to detect and model moving objects; geometric operations & camera models; edge detection; features detection; recognition in images. Contains a large number of vision application problems to provide students with the opportunity to solve real problems. Images or videos for these problems are provided in the resources associated with this book.New York Academy of Sciences Computer visionComputer programsComputer visionEngineering & Applied SciencesHILCCApplied PhysicsHILCCComputer visionComputer programsComputer visionEngineering & Applied SciencesApplied Physics006.3/7006.37COM016000bisacshDawson-Howe Kenneth1575073Dawson-Howe KennethAU-PeELAU-PeELAU-PeELBOOK9910792280303321A Practical Introduction to Computer Vision with OpenCV3851755UNINA