close
1.

図書
図書
1. Guidelines for chemical reactivity evaluation and application to process design
American Institute of Chemical Engineers. Center for Chemical Process Safety
出版情報: New York : Center for Chemical Process Safety of the American Institute of Chemical Engineers, c1995  xxvii, 210 p. ; 24 cm
所蔵情報: loading…
目次情報: 続きを見る
List of Tables
List of Figures
Preface
Acknowledgments
Glossary
List of Symbols
Introduction / Chapter 1：
General / 1.1：
Chemical Reactivity / 1.2：
Detonations, Deflagrations, and Runaways / 1.3：
Assessment and Testing Strategies / 1.4：
Identification of Hazardous Chemical Reactivity / Chapter 2：
Summary/Strategy / 2.1：
Hazard Identification Strategy / 2.1.1：
Exothermic Reactions / 2.1.3：
Experimental Thermal and Reactivity Measurements / 2.1.4：
Test Strategies / 2.1.5：
Overview of Thermal Stability Test methods / 2.1.6：
Examples of Interpretation and Application of Test Data / 2.1.7：
Technical Section / 2.2：
Identification of High Energy Substances / 2.2.2：
Hazard Prediction by Thermodynamic Calculations / 2.2.3：
Oxygen Balance / 2.2.3.1：
Calculation of the Reaction Enthalpy / 2.2.3.2：
Application of Computer Programs / 2.2.3.3：
Instability/Incompatibility Factors / 2.2.4：
Factors Influencing Stability / 2.2.4.1：
Redox Systems / 2.2.4.2：
Reactions with Water / 2.2.4.3：
Reactions between Halogenated Hydrocarbons and Metals / 2.2.4.4：
Practical Testing / 2.3：
Screening Tests / 2.3.1：
Thermal Analysis / 2.3.1.1：
Isoperibolic Calorimetry / 2.3.1.2：
Thermal Stability and Runaway Testing / 2.3.2：
Isothermal Storage Tests / 2.3.2.1：
Dewar Flask Testing and Adiabatic Storage Tests / 2.3.2.2：
Accelerating Rate Calorimeter (ARC) / 2.3.2.3：
Stability Tests for Powders / 2.3.2.4：
Explosibility Testing / 2.3.3：
.Detonation Testing / 2.3.3.1：
Deflagration Testing and Autoclave Testing / 2.3.3.2：
Mechanical Sensitivity Testing / 2.3.3.3：
Sensitivity to heating Under Confinement / 2.3.3.4：
Reactivity Testing / 2.3.4：
Pyrophoric Properties / 2.3.4.1：
Reactivity with Water / 2.3.4.2：
Oxidizing Properties / 2.3.4.3：
Flammability Testing / 2.3.5：
Chemical Reactivity Considerations in Process/Reactor Design and Operation / Chapter 3：
Thermal Hazards: Identification and Analysis / 3.1：
Cause, Definition, and Prevention of a Runaway / 3.1.1.1：
Some Simple Rules for Inherent Safety / 3.1.1.2：
Strategy for Inherent Safety in Design and Operation / 3.1.1.3：
Equipment to be Used for the Analysis of Hazards / 3.1.1.4：
Reactor, Heat and Mass Balance Considerations / 3.2：
Heat and Mass Balances, Kinetics, and Reaction Stability / 3.2.1：
Adiabatic Temperature Rise / 3.2.1.1：
The Reaction / 3.2.1.2：
Reaction Rate / 3.2.1.3：
Reaction Rate Constant / 3.2.1.4：
Concentration of Reactants / 3.2.1.5：
Effect of Surrounding Temperature on Stability / 3.2.1.6：
Effect of Agitation and Surface Fouling on Stability / 3.2.1.7：
Mass Balance / 3.2.1.8：
Choice of Reactor / 3.2.2：
Heat Transfer / 3.2.3：
Heat Transfer in Nonagitated Vessels / 3.2.3.1：
Heat Transfer in Agitated Vessels / 3.2.3.2：
Acquisition and Use of Process Design data / 3.3：
Bench-Scale Equipment for Batch/Tank Reactors / 3.3.1：
Reaction Calorimeter (RC1) / 3.3.2.1：
Contalab / 3.3.2.2：
CPA ThermoMetric Instruments / 3.3.2.3：
Quantitative Reaction Calorimeter / 3.3.2.4：
Specialized Rectors / 3.3.2.5：
Vent Size Package (VSP) / 3.3.2.6：
Reactive System Screening Tool (RSST) / 3.3.2.7：
Process Safety for Reactive Systems / 3.3.3：
Test Plan / 3.3.3.1：
System Under Investigation / 3.3.3.2：
Test Results / 3.3.3.3：
Malfunction and Process Deviation Testing / 3.3.3.4：
Pressure Effect / 3.3.3.5：
Results from the ARC, RSST, and VSP / 3.3.3.6：
Scale-up and Pilot Plants / 3.3.4：
General Remarks / 3.3.4.1：
Chemical Kinetics. 3 / 3.3.4.2：
List of Tables
List of Figures
Preface
2.

図書
図書
2. Spatial data analysis in the social and environmental sciences. 1st pbk. ed (: pbk)
Robert Haining
出版情報: Cambridge [England] ; New York : Cambridge University Press, 1993, c1990  xxi, 409 p. ; 23 cm
所蔵情報: loading…
目次情報: 続きを見る
List of tables and displays
Preface
Acknowledgements
Introduction to issues in the analysis of spatially referenced data / Part A：
Introduction / 1：
Notes
Issues in analysing spatial data / 2：
Spatial data: sources, forms and storage / 2.1：
Sources: quality and quantity / 2.1.1：
Forms and attributes / 2.1.2：
Data storage / 2.1.3：
Spatial data analysis / 2.2：
The importance of space in the social and environmental sciences / 2.2.1：
Measurement error / 2.2.1 (a)：
Continuity effects and spatial heterogeneity / 2.2.1 (b)：
Spatial processes / 2.2.1 (c)：
Types of analytical problems / 2.2.2：
Problems in spatial data analysis / 2.3：
Conceptual models and inference frameworks for spatial data / 2.3.1：
Modelling spatial variation / 2.3.2：
Statistical modelling of spatial data / 2.3.3：
Dependency in spatial data / 2.3.3 (a)：
Spatial heterogeneity: regional subdivisions and parameter variation / 2.3.3 (b)：
Spatial distribution of data points and boundary effects / 2.3.3 (c)：
Assessing model fit / 2.3.3 (d)：
Distributions / 2.3.3 (e)：
Extreme data values / 2.3.3 (f)：
Model sensitivity to the areal system / 2.3.3 (g)：
Size-variance relationships in homogeneous aggregates / 2.3.3 (h)：
A statistical framework for spatial data analysis / 2.4：
Data adaptive modelling / 2.4.1：
Robust and resistant parameter estimation / 2.4.2：
Robust estimation of the centre of a symmetric distribution / 2.4.2 (a)：
Robust estimation of regression parameters / 2.4.2 (b)：
Parametric models for spatial variation / Part B：
Statistical models for spatial populations / 3：
Models for spatial populations: preliminary considerations / 3.1：
Spatial stationarity and isotropy / 3.1.1：
Second order (weak) stationarity and isotropy / 3.1.1 (a)：
Second order (weak) stationarity and isotropy of differences from the mean / 3.1.1 (b)：
Second order (weak) stationarity and isotropy of increments / 3.1.1 (c)：
Order relationships in one and two dimensions / 3.1.2：
Population models for continuous random variables / 3.2：
Models for the mean of a spatial population / 3.2.1：
Trend surface models / 3.2.1 (a)：
Regression model / 3.2.1 (b)：
Models for second order or stochastic variation of a spatial population / 3.2.2：
Interaction models for V of a MVN distribution / 3.2.2 (a)：
Interaction models for other multivariate distributions / 3.2.2 (b)：
Direct specification of V / 3.2.2 (c)：
Intrinsic random functions / 3.2.2 (d)：
Population models for discrete random variables / 3.3：
Boundary models for spatial populations / 3.4：
Edge structures, weighting schemes and the dispersion matrix / 3.5：
Conclusions: issues in representing spatial variation / 3.6：
Simulating spatial models / Appendix：
Statistical analysis of spatial populations / 4：
Model selection / 4.1：
Statistical inference with interaction schemes / 4.2：
Parameter estimation: maximum likelihood (ML) methods / 4.2.1：
[mu] unknown; V known / 4.2.1 (a)：
[mu] known; V unknown / 4.2.1 (b)：
[mu] and V unknown / 4.2.1 (c)：
Models with non-constant variance / 4.2.1 (d)：
Parameter estimation: other methods / 4.2.2：
Ordinary least squares and pseudo-likelihood estimators / 4.2.2 (a)：
Coding estimators / 4.2.2 (b)：
Moment estimators / 4.2.2 (c)：
Parameter estimation: discrete valued interaction models / 4.2.3：
Properties of ML estimators / 4.2.4：
Large sample properties / 4.2.4 (a)：
Small sample properties / 4.2.4 (b)：
A note on boundary effects / 4.2.4 (c)：
Hypothesis testing for interaction schemes / 4.2.5：
Likelihood ratio tests / 4.2.5 (a)：
Lagrange multiplier tests / 4.2.5 (b)：
Statistical inference with covariance functions and intrinsic random functions / 4.3：
Parameter estimation: maximum likelihood methods / 4.3.1：
Properties of estimators and hypothesis testing / 4.3.2：
Validation in spatial models / 4.4：
The consequences of ignoring spatial correlation in estimating the mean / 4.5：
Spatial data collection and preliminary analysis / Part C：
Sampling spatial populations / 5：
Spatial sampling designs / 5.1：
Point sampling / 5.2.1：
Quadrat and area sampling / 5.2.2：
Sampling spatial surfaces: estimating the mean / 5.3：
Fixed populations with trend or periodicity / 5.3.1：
Populations with second order variation / 5.3.2：
Results for one-dimensional series / 5.3.2 (a)：
Results for two-dimensional surfaces / 5.3.2 (b)：
Standard errors for confidence intervals and selecting sample size / 5.3.3：
Sampling spatial surfaces: second order variation / 5.4：
Kriging / 5.4.1：
Scales of variation / 5.4.2：
Sampling applications / 5.5：
Concluding comments / 5.6：
Preliminary analysis of spatial data / 6：
Preliminary data analysis: distributional properties and spatial arrangement / 6.1：
Univariate data analysis / 6.1.1：
General distributional properties / 6.1.1 (a)：
Spatial outliers / 6.1.1 (b)：
Spatial trends / 6.1.1 (c)：
Second order non-stationarity / 6.1.1 (d)：
Regional subdivisions / 6.1.1 (e)：
Multivariate data analysis / 6.1.2：
Data transformations / 6.1.3：
Preliminary data analysis: detecting spatial pattern, testing for spatial autocorrelation / 6.2：
Available test statistics / 6.2.1：
Constructing a test / 6.2.2：
Interpretation / 6.2.3：
Choosing a test / 6.2.4：
Describing spatial variation: robust estimation of spatial variation / 6.3：
Robust estimators of the semi-variogram / 6.3.1：
Robust estimation of covariances / 6.3.2：
Concluding remarks / 6.4：
Modelling spatial data / Part D：
Analysing univariate data sets / 7：
Describing spatial variation / 7.1：
Non-stationary mean, stationary second order variation: trend surface models with correlated errors / 7.1.1：
Non-stationary mean, stationary increments: semi-variogram models and polynomial generalised covariance functions / 7.1.2：
Discrete data / 7.1.3：
Interpolation and estimating missing values / 7.2：
Ad hoc and cartographic techniques / 7.2.1：
Distribution based techniques / 7.2.2：
Sequential approaches (sampling a continuous surface) / 7.2.2 (a)：
Simultaneous approaches / 7.2.2 (b)：
Extensions / 7.2.3：
Obtaining areal properties / 7.2.3 (a)：
Reconciling data sets on different areal frameworks / 7.2.3 (b)：
Categorical data / 7.2.3 (c)：
Other information for interpolation / 7.2.3 (d)：
Analysing multivariate data sets / 8：
Measures of spatial correlation and spatial association / 8.1：
Correlation measures / 8.1.1：
Measures of association / 8.1.2：
Regression modelling / 8.2：
Problems due to the assumptions of least squares not being satisfied / 8.2.1：
Problems of model specification and analysis / 8.2.2：
Model discrimination / 8.2.2 (a)：
Specifying W / 8.2.2 (b)：
Parameter estimation and inference / 8.2.2 (c)：
Model evaluation / 8.2.2 (d)：
Interpretation problems / 8.2.3：
Problems due to data characteristics / 8.2.4：
Numerical problems / 8.2.5：
Regression applications / 8.3：
Model diagnostics and model revision (a) new explanatory variables / Example 8.1：
Model diagnostics and model revision (b) developing a spatial regression model / Example 8.2：
Regression modelling with census variables: Glasgow health data / Example 8.3：
Identifying spatial interaction and heterogeneity: Sheffield petrol price data / Example 8.4：
Robust estimation of the parameters of interaction schemes
Postscript
Glossary
References
Index
List of tables and displays
Preface
Acknowledgements
3.

図書
図書
3. Graphical models for machine learning and digital communication
Brendan J. Frey
出版情報: Cambridge, Mass : The MIT Press, c1998  xiii, 195 p. ; 24 cm
シリーズ名: Adaptive computation and machine learning
所蔵情報: loading…
目次情報: 続きを見る
Preface
Introduction / 1：
A probabilistic perspective / 1.1：
Pattern classification / 1.1.1：
Unsupervised learning / 1.1.2：
Data compression / 1.1.3：
Channel coding / 1.1.4：
Probabilistic inference / 1.1.5：
Graphical models: Factor graphs, Markov random fields and Bayesian belief networks / 1.2：
Factor graphs / 1.2.1：
Markov random fields / 1.2.2：
Bayesian networks / 1.2.3：
Ancestral simulation in Bayesian networks / 1.2.4：
Dependency separation in Bayesian networks / 1.2.5：
Example 1: Recursive convolutional codes and turbocodes / 1.2.6：
Parameterized Bayesian networks / 1.2.7：
Example 2: The bars problem / 1.2.8：
Organization of this book / 1.3：
Probabilistic Inference in Graphical Models / 2：
Exact inference using probability propagation (the sum-product algorithm) / 2.1：
The generalized forward-backward algorithm / 2.1.1：
The burglar alarm problem / 2.1.2：
Probability propagation (the sum-product algorithm) / 2.1.3：
Grouping and duplicating variables in Bayesian networks / 2.1.4：
Exact inference in multiply-connected networks is NP-hard / 2.1.5：
Monte Carlo inference: Gibbs sampling and slice sampling / 2.2：
Inference by ancestral simulation in Bayesian networks / 2.2.1：
Gibbs sampling / 2.2.2：
Gibbs sampling for the burglar alarm problem / 2.2.3：
Slice sampling for continuous variables / 2.2.4：
Variational inference / 2.3：
Choosing the distance measure / 2.3.1：
Choosing the form of the variational distribution / 2.3.2：
Variational inference for the burglar alarm problem / 2.3.3：
Bounds and extended representations / 2.3.4：
Helmholtz machines / 2.4：
Factorial recognition networks / 2.4.1：
Nonfactorial recognition networks / 2.4.2：
The stochastic Helmholtz machine / 2.4.3：
A recognition network that solves the burglar alarm problem / 2.4.4：
Pattern Classification / 3：
Bayesian networks for pattern classification / 3.1：
Autoregressive networks / 3.2：
The logistic autoregressive network / 3.2.1：
MAP estimation for autoregressive networks / 3.2.2：
Scaled priors in logistic autoregressive networks / 3.2.3：
Ensembles of autoregressive networks / 3.2.4：
Estimating latent variable models using the EM algorithm / 3.3：
The expectation maximization (EM) algorithm / 3.3.1：
The generalized expectation maximization algorithm / 3.3.2：
Multiple-cause networks / 3.4：
Estimation by iterative probability propagation / 3.4.1：
Estimation by Gibbs sampling / 3.4.2：
Generalized EM using variational inference / 3.4.3：
Hierarchical networks / 3.4.4：
Ensembles of networks / 3.4.6：
Classification of handwritten digits / 3.5：
Logistic autoregressive classifiers: LARC-1,ELARC-1 / 3.5.1：
The Gibbs machine: GM-1 / 3.5.2：
The mean field Bayesian network: MFBN-1 / 3.5.3：
Stochastic Helmholtz machines: SHM-1, SHM-2, ESHM-1 / 3.5.4：
The classification and regression tree: CART-1 / 3.5.5：
The naive Bayes classifier: NBAYESC-1 / 3.5.6：
The k-nearest neighbor classifier: KNN-CLASS-1 / 3.5.7：
Results / 3.5.8：
Unsupervised Learning / 4：
Extracting structure from images using the wake-sleep algorithm / 4.1：
Wake-sleep parameter estimation / 4.1.1：
Automatic clean-up of noisy images / 4.1.2：
Wake-sleep estimation without positive parameter constraints / 4.1.3：
How hard is the bars problem? / 4.1.4：
Simultaneous extraction of continuous and categorical structure / 4.2：
Continuous sigmoidal Bayesian networks / 4.2.1：
Inference using slice sampling / 4.2.2：
Parameter estimation using slice sampling / 4.2.3：
Nonlinear Gaussian Bayesian networks (NLGBNs) / 4.3：
The model / 4.3.1：
Variational inference and learning / 4.3.2：
Results on the continuous stereo disparity problem / 4.3.3：
Pattern classification using the variational bound / 4.3.4：
Data Compression / 5：
Fast compression with Bayesian networks / 5.1：
Communicating extra information through the codeword choice / 5.2：
Example: A simple mixture model / 5.2.1：
The optimal bits-back coding rate / 5.2.2：
Suboptimal bits-back coding / 5.2.3：
Relationship to maximum likelihood estimation / 5.3：
The "bits-back" coding algorithm / 5.4：
The bits-back coding algorithm with feedback / 5.4.1：
Queue drought in feedback encoders / 5.4.2：
Experimental results / 5.5：
Bits-back coding with a multiple-cause model / 5.5.1：
Compressing handwritten digits / 5.5.2：
Integrating over model parameters using bits-back coding / 5.6：
Channel Coding / 6：
Review: Simplifying the playing field / 6.1：
Additive white Gaussian noise (AWGN) / 6.1.1：
Capacity of an AWGN channel / 6.1.2：
Signal constellations / 6.1.3：
Linear binary codes can get us to capacity / 6.1.4：
Bit error rate (BER) and signal-to-noise ratio (Eb/N0) / 6.1.5：
Capacity of an AWGN channel with binary signalling / 6.1.6：
Achievable BER for an AWGN channel with binary signalling / 6.1.7：
Graphical models for error correction: Turbocodes, low-density parity-check codes and more / 6.2：
Hamming codes / 6.2.1：
Convolutional codes / 6.2.2：
Decoding convolutional codes by probability propagation / 6.2.3：
Turbocodes: parallel concatenated convolutional codes / 6.2.4：
Serially-concatenated convolutional codes, low-density parity-check codes, and product codes / 6.2.5：
"A code by any other network would not decode as sweetly" / 6.3：
Trellis-constrained codes (TCCs) / 6.4：
Homogeneous trellis-constrained codes / 6.4.1：
Ring-connected trellis-constrained codes / 6.4.2：
Decoding complexity of iterative decoders / 6.5：
Parallel iterative decoding / 6.6：
Concurrent turbodecoding / 6.6.1：
Speeding up iterative decoding by detecting variables early / 6.6.2：
Early detection / 6.7.1：
Early detection for turbocodes: Trellis splicing / 6.7.2：
Future Research Directions / 6.7.3：
Modularity and abstraction / 7.1：
Faster inference and learning / 7.2：
Scaling up to the brain / 7.3：
Improving model structures / 7.4：
Iterative decoding / 7.5：
Iterative decoding in the real world / 7.6：
Unification / 7.7：
References
Index
Preface
Introduction / 1：
A probabilistic perspective / 1.1：
4.

図書
図書
4. Complexity and approximation : combinatorial optimization problems and their approximability properties
G. Ausiello ... [et al.]
出版情報: Berlin : Springer, c1999  xix, 524 p. ; 25 cm.
所蔵情報: loading…
目次情報: 続きを見る
The Complexity of Optimization Problems / 1：
Analysis of algorithms and complexity of problems / 1.1：
Complexity analysis of computer programs / 1.1.1：
Upper and lower bounds on the complexity of problems / 1.1.2：
Complexity classes of decision problems / 1.2：
The class NP / 1.2.1：
Reducibility among problems / 1.3：
Karp and Turing reducibility / 1.3.1：
NP-complete problems / 1.3.2：
Complexity of optimization problems / 1.4：
Optimization problems / 1.4.1：
PO and NPO problems / 1.4.2：
NP-hard optimization problems / 1.4.3：
Optimization problems and evaluation problems / 1.4.4：
Exercises / 1.5：
Bibliographical notes / 1.6：
Design Techniques for Approximation Algorithms / 2：
The greedy method / 2.1：
Greedy algorithm for the knapsack problem / 2.1.1：
Greedy algorithm for the independent set problem / 2.1.2：
Greedy algorithm for the salesperson problem / 2.1.3：
Sequential algorithms for partitioning problems / 2.2：
Scheduling jobs on identical machines / 2.2.1：
Sequential algorithms for bin packing / 2.2.2：
Sequential algorithms for the graph coloring problem / 2.2.3：
Local search / 2.3：
Local search algorithms for the cut problem / 2.3.1：
Local search algorithms for the salesperson problem / 2.3.2：
Linear programming based algorithms / 2.4：
Rounding the solution of a linear program / 2.4.1：
Primal-dual algorithms / 2.4.2：
Dynamic programming / 2.5：
Randomized algorithms / 2.6：
Approaches to the approximate solution of problems / 2.7：
Performance guarantee: chapters 3 and 4 / 2.7.1：
Randomized algorithms: chapter 5 / 2.7.2：
Probabilistic analysis: chapter 9 / 2.7.3：
Heuristics: chapter 10 / 2.7.4：
Final remarks / 2.7.5：
Approximation Classes / 2.8：
Approximate solutions with guaranteed performance / 3.1：
Absolute approximation / 3.1.1：
Relative approximation / 3.1.2：
Approximability and non-approximability of TSP / 3.1.3：
Limits to approximability: The gap technique / 3.1.4：
Polynomial-time approximation schemes / 3.2：
The class PTAS / 3.2.1：
APX versus PTAS / 3.2.2：
Fully polynomial-time approximation schemes / 3.3：
The class FPTAS / 3.3.1：
The variable partitioning technique / 3.3.2：
Negative results for the class FPTAS / 3.3.3：
Strong NP-completeness and pseudo-polynomiality / 3.3.4：
Input-Dependent and Asymptotic Approximation / 3.4：
Between APX and NPO / 4.1：
Approximating the set cover problem / 4.1.1：
Approximating the graph coloring problem / 4.1.2：
Approximating the minimum multi-cut problem / 4.1.3：
Between APX and PTAS / 4.2：
Approximating the edge coloring problem / 4.2.1：
Approximating the bin packing problem / 4.2.2：
Approximation through Randomization / 4.3：
Randomized algorithms for weighted vertex cover / 5.1：
Randomized algorithms for weighted satisfiability / 5.2：
A new randomized approximation algorithm / 5.2.1：
A 4/3-approximation randomized algorithm / 5.2.2：
Algorithms based on semidefinite programming / 5.3：
Improved algorithms for weighted 2-satisfiability / 5.3.1：
The method of the conditional probabilities / 5.4：
NP, PCP and Non-approximability Results / 5.5：
Formal complexity theory / 6.1：
Turing machines / 6.1.1：
Deterministic Turing machines / 6.1.2：
Nondeterministic Turing machines / 6.1.3：
Time and space complexity / 6.1.4：
NP-completeness and Cook-Levin theorem / 6.1.5：
Oracles / 6.2：
Oracle Turing machines / 6.2.1：
The PCP model / 6.3：
Membership proofs / 6.3.1：
Probabilistic Turing machines / 6.3.2：
Verifiers and PCP / 6.3.3：
A different view of NP / 6.3.4：
Using PCP to prove non-approximability results / 6.4：
The maximum satisfiability problem / 6.4.1：
The maximum clique problem / 6.4.2：
The PCP theorem / 6.5：
Transparent long proofs / 7.1：
Linear functions / 7.1.1：
Arithmetization / 7.1.2：
The first PCP result / 7.1.3：
Almost transparent short proofs / 7.2：
Low-degree polynomials / 7.2.1：
Arithmetization (revisited) / 7.2.2：
The second PCP result / 7.2.3：
The final proof / 7.3：
Normal form verifiers / 7.3.1：
The composition lemma / 7.3.2：
Approximation Preserving Reductions / 7.4：
The World of NPO Problems / 8.1：
AP-reducibility / 8.2：
Complete problems / 8.2.1：
NPO-completeness / 8.3：
Other NPO-complete problems / 8.3.1：
Completeness in exp-APX / 8.3.2：
APX-completeness / 8.4：
Other APX-complete problems / 8.4.1：
Probabilistic analysis of approximation algorithms / 8.5：
Introduction / 9.1：
Goals of probabilistic analysis / 9.1.1：
Techniques forthe probabilistic analysis of algorithms / 9.2：
Conditioning in the analysis of algorithms / 9.2.1：
The first and the second moment methods / 9.2.2：
Convergence of random variables / 9.2.3：
Probabilistic analysis and multiprocessor scheduling / 9.3：
Probabilistic analysis and bin packing / 9.4：
Probabilistic analysis and maximum clique / 9.5：
Probabilistic analysis and graph coloring / 9.6：
Probabilistic analysis and Euclidean TSP / 9.7：
Heuristic methods / 9.8：
Types of heuristics / 10.1：
Construction heuristics / 10.2：
Local search heuristics / 10.3：
Fixed-depth local search heuristics / 10.3.1：
Variable-depth local search heuristics / 10.3.2：
Heuristics based on local search / 10.4：
Simulated annealing / 10.4.1：
Genetic algorithms / 10.4.2：
Tabu search / 10.4.3：
Mathematical preliminaries / 10.5：
Sets / A.1：
Sequences, tuples and matrices / A.1.1：
Functions and relations / A.2：
Graphs / A.3：
Strings and languages / A.4：
Booleanlogic / A.5：
Probability / A.6：
Random variables / A.6.1：
Linear programming / A.7：
Two famous formulas / A.8：
A List of NP Optimization Problems / B：
Bibliography
Index
The Complexity of Optimization Problems / 1：
Analysis of algorithms and complexity of problems / 1.1：
Complexity analysis of computer programs / 1.1.1：
5.

図書
図書
5. Kinematics of human motion
Vladimir M. Zatsiorsky
出版情報: Champaign, Ill. : Human Kinetics, c1998  xi, 419 p. ; 24 cm
所蔵情報: loading…
目次情報: 続きを見る
Preface
Acknowledgments
Notations and Conventions
Kinematic Geometry of Human Motion: Body Position and Displacement / Chapter 1：
Defining body location / 1.1：
The coordinate method / 1.1.1：
Cartesian versus oblique coordinates / 1.1.2：
Defining body orientation / 1.2：
Fixation of a local system with a rigid body / 1.2.1：
Fixation of a somatic system with a human body / 1.2.2：
Indirect method of defining body orientation / 1.2.3：
What is ""body rotation""? / 1.2.4：
Describing position and displacement / 1.2.5：
Advantages and disadvantages of the various angular conventions / 1.2.6：
Determining body position from experimental recordings / 1.2.7：
Three-dimensional representation of human movement: Eye movement / 1.3：
Eye orientation / 1.3.1：
Motions actually made by the human eye (Donders' law and Listing's law) / 1.3.2：
Rotation surfaces. The laws obeyed by the pointing head and arm movements / 1.3.3：
Summary / 1.4：
Questions for Review / 1.5：
Bibliography / 1.6：
Kinematic Geometry of Human Motion: Body Posture / Chapter 2：
Joint configuration / 2.1：
Technical and somatic systems / 2.1.1：
The clinical reference system / 2.1.2：
Globographic representation / 2.1.3：
Segment coordinate systems / 2.1.4：
Joint rotation convention / 2.1.5：
Kinematic chains / 2.2：
Degrees of freedom. Mobility of kinematic chains / 2.2.1：
Open kinematic chains: The end-effector mobility / 2.2.2：
Kinematics models and mobility of the human body / 2.2.3：
Constraints on human movements / 2.2.4：
Position analysis of kinematic chains / 2.2.5：
Biological solutions to kinematic problems / 2.3：
Internal representation of the immediate extrapersonal space / 2.3.1：
Internal representation of the body posture / 2.3.2：
Differential Kinematics of Human Movement / 2.4：
Velocity of a kinematic chain / 3.1：
Planar movement / 3.1.1：
Motion in three dimensions / 3.1.2：
Acceleration of a kinematic chain / 3.2：
Acceleration of a planar two-link chain / 3.2.1：
Acceleration of a two-link chain in three dimensions / 3.2.2：
Acceleration of a multi-link chain / 3.2.3：
Jerk and snap / 3.2.4：
Biological solutions to the problems of differential kinematics: Control of movement velocity / 3.3：
Control of approach: The tau hypothesis / 3.3.1：
Control of velocity in reaching movement / 3.3.2：
Joint Geometry and Joint Kinematics / 3.4：
Intrajoint kinematics / 4.1：
Articular surfaces and types of joints / 4.1.1：
Movement of articular surfaces / 4.1.2：
Geometry and algebra of intra-articular motion / 4.1.3：
Ligaments and joint motion: A joint as a mechanical linkage / 4.1.4：
Centers and axes of rotation / 4.2：
Planar joint movement / 4.2.1：
Three-dimensional joint movement / 4.2.2：
Kinematics of Individual Joints / 4.3：
Nominal joint axes / 5.1：
The joints of the foot / 5.2：
Metatarsophalangeal joints. The foot as a two-speed construction / 5.2.1：
The joints of the midfoot / 5.2.2：
The ankle joint complex / 5.3：
The talocrural joint / 5.3.1：
The subtalar joint / 5.3.2：
The knee / 5.4：
The tibiofemoral joint / 5.4.1：
The patellofemoral joint / 5.4.2：
The hip joint and the pelvic girdle / 5.5：
The spine / 5.6：
Movement in synarthroses / 5.6.1：
The lumbar and thoracic spine / 5.6.2：
The cervical region: Head and neck movement / 5.6.3：
The rib cage / 5.6.4：
The shoulder complex / 5.7：
Individual joints / 5.7.1：
Movement of the shoulder complex: The scapulohumeral rhythm / 5.7.2：
The elbow complex / 5.8：
Flexion and extension / 5.8.1：
Supination and pronation / 5.8.2：
The wrist / 5.9：
The joints of the hand / 5.10：
The joints of the thumb / 5.10.1：
The joints of the fingers / 5.10.2：
The temporomandibular joint / 5.11：
Glossary / 5.12：
Index
About the Author"
Preface
Acknowledgments
Notations and Conventions
6.

図書
図書
6. Vision science : photons to phenomenology
Stephen E. Palmer
出版情報: Cambridge, MA : MIT Press, c1999  xxii, 810 p., [8] p. of plates ; 26 cm
所蔵情報: loading…
目次情報: 続きを見る
Brief Contents
Contents
Preface
Organization of the Book
Foundations
Spatial Vision
Visual Dynamics
Tailoring the Book to Different Needs
Acknowledgments
An Introduction to Vision Science / Part I：
Visual Perception / 1.1：
Defining Visual Perception / 1.1.1：
The Evolutionary Utility of Vision / 1.1.2：
Perception as a Constructive Act / 1.1.3：
Perception as Modeling the Environment / 1.1.4：
Perception as Apprehension of Meaning / 1.1.5：
Optical Information / 1.2：
The Behavior of Light / 1.2.1：
The Formation of Images / 1.2.2：
Vision as an "Inverse" Problem / 1.2.3：
Visual Systems / 1.3：
The Human Eye / 1.3.1：
The Retina / 1.3.2：
Visual Cortex / 1.3.3：
Theoretical Approaches / 2：
Classical Theories of Vision / 2.1：
Structuralism / 2.1.1：
Gestaltism / 2.1.2：
Ecological Optics / 2.1.3：
Constructivism / 2.1.4：
A Brief History of Information Processing / 2.2：
Computer Vision / 2.2.1：
Information Processing Psychology / 2.2.2：
Biological Information Processing / 2.2.3：
Information Processing Theory / 2.3：
The Computer Metaphor / 2.3.1：
Three Levels of Information Processing / 2.3.2：
Three Assumptions of Information Processing / 2.3.3：
Representation / 2.3.4：
Processes / 2.3.5：
Four Stages of Visual Perception / 2.4：
The Retinal Image / 2.4.1：
The Image-Based Stage / 2.4.2：
The Surface-Based Stage / 2.4.3：
The Object-Based Stage / 2.4.4：
The Category-Based Stage / 2.4.5：
Color Vision: A Microcosm of Vision Science / 3：
The Computational Description of Color Perception / 3.1：
The Physical Description of Light / 3.1.1：
The Psychological Description of Color / 3.1.2：
The Psychophysical Correspondence / 3.1.3：
Image-Based Color Processing / 3.2：
Basic Phenomena / 3.2.1：
Theories of Color Vision / 3.2.2：
Physiological Mechanisms / 3.2.3：
Development of Color Vision / 3.2.4：
Surface-Based Color Processing / 3.3：
Lightness Constancy / 3.3.1：
Chromatic Color Constancy / 3.3.2：
Color Naming / 3.4：
Focal Colors and Prototypes / 3.4.2：
A Fuzzy-Logical Model of Color Naming / 3.4.3：
Processing Image Structure / Part II：
Retinal and Geniculate Cells / 4.1：
Striate Cortex / 4.1.2：
Striate Architecture / 4.1.3：
Development of Receptive Fields / 4.1.4：
Psychophysical Channels / 4.2：
Spatial Frequency Theory / 4.2.1：
Physiology of Spatial Frequency Channels / 4.2.2：
Computational Approaches / 4.3：
Marr's Primal Sketches / 4.3.1：
Edge Detection / 4.3.2：
Alternative Computational Theories / 4.3.3：
A Theoretical Synthesis / 4.3.4：
Visual Pathways / 4.4：
Physiologlcal Evidence / 4.4.1：
Perceptual Evidence / 4.4.2：
Perceiving Surfaces Oriented in Depth / 5：
The Problem of Depth Perception / 5.1：
Heuristic Assumptions / 5.1.1：
Marr's 2.5-D Sketch / 5.1.2：
Ocular Information / 5.2：
Accormmodation / 5.2.1：
Convergence / 5.2.2：
Stereoscopic Information / 5.3：
Binocular Disparity / 5.3.1：
The Correspondence Problem / 5.3.2：
Computational Theories / 5.3.3：
Vertical Disparity / 5.3.4：
Da Vinci Stereopsis / 5.3.6：
Dynamic Information / 5.4：
Motion Parallax / 5.4.1：
Optic Flow Caused by a Moving Observer / 5.4.2：
Optic Flow Caused by Moving Objects / 5.4.3：
Accretion/Deletion of Texture / 5.4.4：
Pictorial Information / 5.5：
Perspective Projection / 5.5.1：
Convergence of Parallel Lines / 5.5.2：
Position Relative to the Horizon of a Surface / 5.5.3：
Relative Size / 5.5.4：
Familiar Size / 5.5.5：
Texture Gradients / 5.5.6：
Edge Interpretation / 5.5.7：
Shading Information / 5.5.8：
Aerial Perspective / 5.5.9：
Integrating Information Sources / 5.5.10：
Development of Depth Perception / 5.6：
Organizing Objects and Scenes / 5.6.1：
Perceptual Grouping / 6.1：
The Classical Principles of Grouping / 6.1.1：
New Principles of Grouping / 6.1.2：
Measuring Grouping Effects Quantitatively / 6.1.3：
Is Grouping an Early or Late Process? / 6.1.4：
Past Experience / 6.1.5：
Region Analysis / 6.2：
Uniform Connectedness / 6.2.1：
Region Segmentation / 6.2.2：
Texture Segregation / 6.2.3：
Figure/Ground Organization / 6.3：
Principles of Figure/Ground Organization / 6.3.1：
Ecological Considerations / 6.3.2：
Effects of Meaningfulness / 6.3.3：
The Problem of Holes / 6.3.4：
Visual Interpolation / 6.4：
Visual Completion / 6.4.1：
Illusory Contours / 6.4.2：
Perceived Transparency / 6.4.3：
Figural Scission / 6.4.4：
The Principle of Nonaccidentalness / 6.4.5：
Multistability / 6.5：
Connectionist Network Models / 6.5.1：
Neural Fatigue / 6.5.2：
Eye Fixations / 6.5.3：
The Role of Instructions / 6.5.4：
Development of Perceptual Organization / 6.6：
The Habituation Paradigm / 6.6.1：
The Development of Grouping / 6.6.2：
Perceiving Object Properties and Parts / 7：
Size / 7.1：
Size Constancy / 7.1.1：
Size Illusions / 7.1.2：
Shape / 7.2：
Shape Constancy / 7.2.1：
Shape Illusions / 7.2.2：
Orientation / 7.3：
Orientation Constancy / 7.3.1：
Orientation Illusions / 7.3.2：
Position / 7.4：
Perception of Direction / 7.4.1：
Position Constancy / 7.4.2：
Position Illusions / 7.4.3：
Perceptual Adaptation / 7.5：
Parts / 7.6：
Evidence for Perception of Parts / 7.6.1：
Part Segmentation / 7.6.2：
Global and Local Processing / 7.6.3：
Representing Shape and Structure / 8：
Shape Equivalence / 8.1：
Defining Objective Shape / 8.1.1：
Invariant Features / 8.1.2：
Transformational Alignment / 8.1.3：
Object-Centered Reference Frames / 8.1.4：
Theories of Shape Representation / 8.2：
Templates / 8.2.1：
Fourier Spectra / 8.2.2：
Features and Dimensions / 8.2.3：
Structural Descriptions / 8.2.4：
Figural Goodness and Pragnanz / 8.3：
Theories of Figural Goodness / 8.3.1：
Structural Information Theory / 8.3.2：
Perceiving Function and Category / 9：
The Perception of Function / 9.1：
Direct Perception of Affordances / 9.1.1：
Indirect Perception of Function by Categorization / 9.1.2：
Phenomena of Perceptual Categorization / 9.2：
Categorical Hierarchies / 9.2.1：
Perspective Viewing Conditions / 9.2.2：
Part Structure / 9.2.3：
Contextual Effects / 9.2.4：
Visual Agnosia / 9.2.5：
Theories of Object Categorization / 9.3：
Recognition by Components Theory / 9.3.1：
Accounting for Empirical Phenomena / 9.3.2：
Viewpoint-Specific Theories / 9.3.3：
Identifying Letters and Words / 9.4：
Identifying Letters / 9.4.1：
Identifying Words and Letters Within Words / 9.4.2：
The Interactive Activation Model / 9.4.3：
Perceiving Motion and Events / Part III：
Image Motion / 10.1：
The Computational Problem of Motion / 10.1.1：
Continuous Motion / 10.1.2：
Apparent Motion / 10.1.3：
Object Motion / 10.1.4：
Perceiving Object Velocity / 10.2.1：
Depth and Motion / 10.2.2：
Long-Range Apparent Motion / 10.2.3：
Dynamic Perceptual Organization / 10.2.4：
Self-Motion and Optic Flow / 10.3：
Induced Motion of the Self / 10.3.1：
Perceiving Self-Motion / 10.3.2：
Understanding Events / 10.4：
Biological Motion / 10.4.1：
Perceiving Causation / 10.4.2：
Intuitive Physics / 10.4.3：
Visual Selection: Eye Movements And Attention / 11：
Eye Movements / 11.1：
Types Of Eye Movements / 11.1.1：
The Physiology Of The Oculomotor System / 11.1.2：
Saccaadic Exploration Of The Visual Environment / 11.1.3：
Visual Attention / 11.2：
Early Versus Late Selection / 11.2.1：
Costs and Benefits of Attention / 11.2.2：
Theories of Spatial Attention / 11.2.3：
Selective Attention to Properties / 11.2.4：
Distributed versus Focused Attention / 11.2.5：
Feature Integration Theory / 11.2.6：
The Physiology of Attention / 11.2.7：
Attention and Eye Movements / 11.2.8：
Visual Memory and Imagery / 12：
Visual Memory / 12.1：
Three Memory Systems / 12.1.1：
Iconic Memory / 12.1.2：
Visual Short-Term Memory / 12.1.3：
Visual Long-Term Memory / 12.1.4：
Memory Dynamics / 12.1.5：
Visual Imagery / 12.2：
The Analog/Propositional Debate / 12.2.1：
Mental Transformtions / 12.2.2：
Image Inspection / 12.2.3：
Kosslyn's Model of Imagery / 12.2.4：
The Relation of Imagery to Perception / 12.2.5：
Visual Awareness / 13：
Philosophical Foundations / 13.1：
The Mind-Body Problem / 13.1.1：
The Problem of Other Minds / 13.1.2：
Neuropsychology of Visual Awareness / 13.2：
Split-Brain Patients / 13.2.1：
Blindsight / 13.2.2：
Unconscious Processing in Neglect and Balint's Syndrome / 13.2.3：
Unconscious Face Recognition in Prosopagnosia / 13.2.4：
Visual Awareness in Normal Observers / 13.3：
Perceptual Defense / 13.3.1：
Subliminal Perception / 13.3.2：
Inattentional Blindsight / 13.3.3：
Theories of Consciousness / 13.4：
Functional Architecture Theories / 13.4.1：
Biological Theories / 13.4.2：
Consciousness and the Limits of Science / 13.4.3：
Psychophysical Methods / Appendix A：
Measuring Thresholds / A.1：
Method of Adjustment / A.1.1：
Method of Limits / A.1.2：
Method of Constant Stimuli / A.1.3：
The Theoretical Status of Thresholds / A.1.4：
Signal Detection Theory / A.2：
Response Bias / A.2.1：
The Signal Detection Paradigm / A.2.2：
The Theory of Signal Detectability / A.2.3：
Difference Thresholds / A.3：
Just Noticeable Differences / A.3.1：
Weber's Law / A.3.2：
Psychophysical Scaling / A.4：
Fechner's Law / A.4.1：
Stevens's Law / A.4.2：
Suggestions for Futher Reading
Connectionist Modeling / Appendix B：
Network Behavior / B.1：
Unit Behavior / B.1.1：
System Architecture / B.1.2：
Systemic Behavior / B.1.3：
Connectionist Learning Algorithms / B.2：
Back Propagation / B.2.1：
Gradient Descent / B.2.2：
Color Technology / Appendix C：
Additive versus Subtractive Color Mixture / C.1：
Adding versus Multiplying Spectra / C.1.1：
Maxwell's Color Triangle / C.1.2：
C.I.E. Color Space / C.1.3：
Subtractive Color Mixture Space? / C.1.4：
Color Television / C.2：
Paints and Dyes / C.3：
Subtractive Combination of Paints / C.3.1：
Additive Combination of Paints / C.3.2：
Color Photography / C.4：
Color Printing / C.5：
Suggestions for Further Reading
Glossary
References
Name Index
Subject Index
Brief Contents
Contents
Preface
7.

図書
図書
7. The economics of contracts : a primer
Bernard Salanié
出版情報: Cambridge, Mass. : MIT Press, c1997  viii, 223 p. ; 24 cm
所蔵情報: loading…
目次情報: 続きを見る
Foreword to the Second Edition
Foreword to the First Edition
Introduction / 1：
The Great Families of Models / 1.1：
The Principal-Agent Model / 1.2：
Overview of the Book / 1.3：
References
Adverse Selection: General Theory / 2：
Mechanism Design / 2.1：
General Mechanisms / 2.1.1：
Application to Adverse Selection Models / 2.1.2：
A Discrete Model of Price Discrimination / 2.2：
The Consumer / 2.2.1：
The Seller / 2.2.2：
The First-Best: Perfect Discrimination / 2.2.3：
Imperfect Information / 2.2.4：
The Standard Model / 2.3：
Analysis of the Incentive Constraints / 2.3.1：
Solving the Model / 2.3.2：
Exercises
Adverse Selection: Examples and Extensions / 3：
Examples of Applications / 3.1：
Regulating a Firm / 3.1.1：
Optimal Taxation / 3.1.2：
The Insurer as a Monopolist / 3.1.3：
Extensions / 3.2：
Perfect Competition in Contracts / 3.2.1：
Multiple Principals / 3.2.2：
The Theory of Auctions / 3.2.3：
Collusion / 3.2.4：
Risk-Averse Agents / 3.2.5：
Multidimensional Characteristics / 3.2.6：
Bilateral Private Information / 3.2.7：
Type-Dependent Reservation Utilities / 3.2.8：
Auditing the Agent / 3.2.9：
Signaling Models / 4：
The Market for Secondhand Cars / 4.1：
Costly Signals / 4.2：
Separating Equilibria / 4.2.1：
Pooling Equilibria / 4.2.2：
The Selection of an Equilibrium / 4.2.3：
Costless Signals / 4.3：
A Simple Example / 4.3.1：
The General Model / 4.3.2：
Other Examples / 4.4：
The Informed Principal / 4.5：
Moral Hazard / 5：
The Agent's Program / 5.1：
The Principal's Program / 5.2.2：
Properties of the Optimal Contract / 5.2.3：
Informativeness and Second-Best Loss / 5.3：
A Continuum of Actions / 5.3.2：
The Limited Liability Model / 5.3.3：
An Infinity of Outcomes / 5.3.4：
The Multisignal Case / 5.3.5：
Imperfect Performance Measurement / 5.3.6：
Models with Several Agents / 5.3.7：
Models with Several Principals / 5.3.8：
The Robustness of Contracts / 5.3.9：
The Multitask Model / 5.3.10：
Insurance / 5.4：
Wage Determination / 5.4.2：
The Dynamics of Complete Contracts / 6：
Commitment and Renegotiation / 6.1：
Strategic Commitment / 6.2：
Adverse Selection / 6.3：
Full Commitment / 6.3.1：
Long-Term Commitment / 6.3.2：
No Commitment / 6.3.3：
Short-Term Commitment / 6.3.4：
Conclusion / 6.3.5：
Renegotiation after Effort / 6.4：
Convergence to the First-Best / 6.4.2：
Finitely Repeated Moral Hazard / 6.4.3：
Incomplete Contracts / 7：
Property Rights, Holdup, and Underinvestment / 7.1：
The Buyer-Seller Model / 7.1.1：
The Complete Contract / 7.1.2：
Incomplete Contracts and Property Rights / 7.1.3：
The Irrelevance Theorems / 7.2：
Restoring Efficient Investment Incentives / 7.2.1：
Using Mechanism Design / 7.2.2：
Concluding Remarks / 7.3：
Some Empirical Work / 8：
Dealing with Unobserved Heterogeneity / 8.1：
Auctions / 8.2：
Tests of Asymmetric Information in Insurance Markets / 8.3：
Some Noncooperative Game Theory / Appendix：
Games of Perfect Information / A.1：
Nash Equilibrium / A.1.1：
Subgame-Perfect Equilibrium / A.1.2：
Games of Incomplete Information / A.2：
Bayesian Equilibrium / A.2.1：
Perfect Bayesian Equilibrium / A.2.2：
Refinements of Perfect Bayesian Equilibrium / A.2.3：
Name Index
Subject Index
Foreword to the Second Edition
Foreword to the First Edition
Introduction / 1：
8.

図書
図書
8. Cluster beam synthesis of nanostructured materials
Paolo Milani, Salvatore Iannotta
出版情報: New York : Springer, c1999  viii, 190 p. ; 24 cm
シリーズ名: Springer series in cluster physics
所蔵情報: loading…
目次情報: 続きを見る
Introduction / 1：
Molecular Beams and Cluster Nucleation / 2：
Molecular Beams / 2.1：
Continuous Effusive Beams / 2.1.1：
Continuous Supersonic Beams / 2.1.2：
Pulsed Beams / 2.1.3：
Nucleation and Aggregation Processes / 2.2：
Classical Theory / 2.2.1：
Homogeneous Nucleation by Monomer Addition / 2.2.2：
Homogeneous Nucleation by Aggregation / 2.2.3：
Nucleation of Clusters in Beams / 2.2.4：
Semi-empirical Approach to Clustering in Free Jets / 2.2.5：
Cluster Sources / 3：
Vaporization Methods / 3.1：
Joule Heating / 3.1.1：
Plasma Generation for Cluster Production / 3.1.2：
Laser Vaporization / 3.1.3：
Glow and Arc Discharges / 3.1.4：
Continuous Sources / 3.2：
Effusive Joule-Heated Gas Aggregation Sources / 3.2.1：
Magnetron Plasma Sources / 3.2.2：
Supersonic Sources / 3.2.3：
Pulsed Sources / 3.3：
Pulsed Valves / 3.3.1：
Laser Vaporization Sources / 3.3.2：
Arc Pulsed Sources / 3.3.3：
Characterization and Manipulation of Cluster Beams / 4：
Mass Spectrometry / 4.1：
Quadrupole Mass Spectrometry / 4.1.1：
Time-of-Flight Mass Spectrometry / 4.1.2：
Retarding Potential Mass Spectrometry / 4.1.3：
Detection Methods / 4.2：
Ionization of Clusters / 4.2.1：
Charged Cluster Detection / 4.2.2：
Cluster Beam Characterization / 4.2.3：
Cluster Selection and Manipulation / 4.3：
Size and Energy Selection / 4.3.1：
Quadrupole Filter / 4.3.2：
Separation of Gas Mixtures in Supersonic Beams / 4.3.3：
Thin Film Deposition and Surface Modification by Cluster Beams / 5：
Kinetic Energy Regimes / 5.1：
Diffusion and Coalescence of Clusters on Surfaces / 5.2：
Low-Energy Deposition / 5.3：
Cluster Networks and Porous Films / 5.3.1：
Composite Nanocrystalline Materials / 5.3.2：
High-Energy Deposition / 5.4：
Implantation, Sputtering, Etching / 5.4.1：
Thin Film Formation / 5.4.2：
Outlook and Perspectives / 6：
Cluster Beam Processing of Surfaces / 6.1：
Nanostructured Materials Synthesis / 6.2：
Perspectives / 6.3：
Appendix
References
Introduction / 1：
Molecular Beams and Cluster Nucleation / 2：
Molecular Beams / 2.1：
9.

図書
図書
9. Parallel database techniques
[edited by] Mahdi Abdelguerfi, Kam-Fai Wong
出版情報: Los Alamitos, CA : IEEE Computer Society, c1998  vii, 222 p. ; 26 cm
所蔵情報: loading…
目次情報: 続きを見る
Introduction / 1：
Background / 1.1：
Parallel Database Systems / 1.2：
Computation Model / 1.2.1：
Engineering Model / 1.2.2：
About this Manuscript / 1.3：
Bibliography
Request Manager / I：
Designing an Optimizer for Parallel Relational Systems / 2：
Overall Design Issues / 2.1：
Design a Simple Parallel Execution Model / 2.2.1：
The Two-Phase Approach / 2.2.2：
Parallelizing is Adding Information! / 2.2.3：
Two-Phase versus Parallel Approaches / 2.2.4：
Parallelization / 2.3：
Kinds of Parallelism / 2.3.1：
Specifying Parallel Execution / 2.3.2：
Search Space / 2.4：
Slicing Hash Join Trees / 2.4.1：
Search Space Size / 2.4.2：
Heuristics / 2.4.3：
The Two-Phase Heuristics / 2.4.4：
Cost Model / 2.5：
Exceptions to the Principle of Optimality / 2.5.1：
Resources / 2.5.2：
Skew and Size Model / 2.5.3：
The Cost Function / 2.5.4：
Search Strategies / 2.6：
Deterministic Search Strategies / 2.6.1：
Randomized Strategies / 2.6.2：
Conclusion / 2.7：
New Approaches to Parallel Join Utilizing Page Connectivity Information / 3：
The Environment and a Motivating Example / 3.1：
The Methodology / 3.3：
Definition of Parameters / 3.3.1：
The Balancing Algorithm / 3.3.2：
Schedules for Reading Join Components and Data Pages / 3.3.3：
Performance Analysis / 3.4：
The Evaluation Method / 3.4.1：
Evaluation Results / 3.4.2：
Concluding Remarks and Future Work / 3.5：
A Performance Evaluation Tool for Parallel Database Systems / 4：
Performance Evaluation Methods / 4.1：
Analytical Modeling / 4.2.1：
Benchmarks / 4.2.2：
Observations / 4.2.3：
The Software Testpilot / 4.3：
The Experiment Specification / 4.3.1：
The Performance Assessment Cycle / 4.3.2：
The System Interface / 4.3.3：
The Software Testpilot and Oracle/Ncube / 4.4：
Database System Performance Assessment / 4.4.1：
The Oracle/Ncube Interface / 4.4.2：
Preliminary Results / 4.5：
Load Placement in Distributed High-Performance Database Systems / 4.6：
Investigated System / 5.1：
System Architecture / 5.2.1：
Load Scenarios / 5.2.2：
Trace Analysis / 5.2.3：
Load Setup / 5.2.4：
Load Placement Strategies Investigated / 5.3：
Scheduling Strategies for Transactions / 5.4：
Simulation Results / 5.5：
Influence of Scheduling / 5.5.1：
Evaluation of the Load Placement Strategies / 5.5.2：
Lessons Learned / 5.5.3：
Decision Parameters Used / 5.5.4：
Conclusion and Open Issues / 5.6：
Parallel Machine Architecture / II：
Modeling Recovery in Client-Server Database Systems / 6：
Uniprocessor Recovery and Formal Approach to Modeling Recovery / 6.1：
Basic Formal Concepts / 6.2.1：
Logging Mechanisms / 6.2.2：
Runtime Policies for Ensuring Correctness / 6.2.3：
Data Structures Maintained for Efficient Recovery / 6.2.4：
Restart Recovery--The ARIES Approach / 6.2.5：
LSN Sequencing Techniques for Multinode Systems / 6.3：
Recovery in Client-Server Database Systems / 6.4：
Client-Server EXODUS (ESM-CS) / 6.4.1：
Client-Server ARIES (ARIES/CSA) / 6.4.2：
Shared Nothing Clients with Disks (CD) / 6.4.3：
Summary of Recovery Approaches in Client-Server Architectures / 6.4.4：
Parallel Strategies for a Petabyte Multimedia Database Computer / 6.5：
Multimedia Data Warehouse, Databases, and Applications / 7.1：
Three Waves of Multimedia Database Development / 7.2.1：
National Medical Practice Knowledge Bank Application / 7.2.2：
Massively Parallel Architecture, Infrastructure, and Technology / 7.3：
Parallelism / 7.3.1：
Teradata-MM Architecture, Framework, and New Concepts / 7.4：
Teradata-MM Architecture / 7.4.1：
Key New Concepts / 7.4.2：
SQL3 / 7.4.3：
Federated Coordinator / 7.4.4：
Teradata Multimedia Object Server / 7.4.5：
Parallel UDF Execution Analysis / 7.5：
UDF Optimizations / 7.5.1：
PRAGMA Facility / 7.5.2：
UDF Value Persistence Facility / 7.5.3：
Spatial Indices for Content-Based Querying / 7.5.4：
The MEDUSA Project / 7.6：
Indexing and Data Partitioning / 8.1：
Standard Systems / 8.2.1：
Grid Files / 8.2.2：
Dynamic Load Balancing / 8.3：
Data Access Frequency / 8.3.1：
Data Distribution / 8.3.2：
Query Partitioning / 8.3.3：
The MEDUSA Architecture / 8.4：
Software / 8.4.2：
Grid File Implementation / 8.4.3：
Load Balancing Strategy / 8.4.4：
MEDUSA Performance Results / 8.5：
Test Configuration / 8.5.1：
Transaction Throughput / 8.5.2：
Speedup / 8.5.3：
Load Balancing Test Results / 8.5.4：
Conclusions / 8.6：
Partitioned Data Store / III：
System Software of the Super Database Computer SDC-II / 9：
Architectural Overview of the SDC-II / 9.1：
Design and Organization of the SDC-II System Software / 9.3：
Parallel Execution Model / 9.3.1：
I/O Model and Buffer Management Strategy for Bulk Data Transfer / 9.3.2：
Process Model and Efficient Flow Control Mechanism / 9.3.3：
Structure of the System Software Components / 9.3.4：
Evaluation of the SDC-II System / 9.4：
Details of a Sample Query Processing / 9.4.1：
Comparison with Commercial Systems / 9.4.2：
Data Placement in Parallel Database Systems / 9.5：
Overview of Data Placement Strategies / 10.1：
Declustering and Redistribution / 10.2.1：
Placement / 10.2.2：
Effects of Data Placement / 10.3：
STEADY and TPC-C / 10.3.1：
Dependence on Number of Processing Elements / 10.3.2：
Dependence on Database Size / 10.3.3：
Contributors / 10.4：
Introduction / 1：
Background / 1.1：
Parallel Database Systems / 1.2：
10.

図書
図書
10. The software project manager's handbook : principles that work at work
Dwayne Phillips
出版情報: Los Alamitos, Calif. : IEEE Computer Society, c1998  xvi, 387 p. ; 26 cm
所蔵情報: loading…
目次情報: 続きを見る
Preface
Elements of Effective Software Management / Part 1：
What Makes a Good Software Manager? / Chapter 1：
People perspective / 1.1：
Business perspective / 1.2：
Process perspective / 1.3：
Successful process techniques / 1.3.1：
Best practices / 1.3.2：
Management "secrets" / 1.3.3：
Key thoughts in this chapter / 1.4：
References
Four Basics that Work / Chapter 2：
People, process, and product / 2.1：
People / 2.1.1：
Process / 2.1.2：
Product / 2.1.3：
Balancing the 3Ps / 2.1.4：
Visibility / 2.2：
Basic visibility techniques / 2.2.1：
Using the techniques / 2.2.2：
Configuration management / 2.3：
The CM plan / 2.3.1：
Basic baselines / 2.3.2：
Activities / 2.3.3：
CM people / 2.3.4：
CM sketch / 2.3.5：
Standards / 2.4：
What Doesn't Work and Why / 2.5：
When the 3Ps are out of balance / 3.1：
When there's not enough visibility / 3.2：
When configuration management is missing or abused / 3.3：
When standards are dismissed / 3.4：
Managing a Project Day by Day / 3.5：
Balancing the 3Ps to create a good environment / 4.1：
Emotional safety / 4.1.1：
Emphasis on team empowerment / 4.1.2：
High degree of personal interaction / 4.1.3：
Good balance of work and rest / 4.1.4：
Structure that promotes success / 4.1.5：
Visibility: Project control in a simple equation / 4.2：
Collecting status / 4.2.1：
Collection guidelines / 4.2.2：
Making status visible and undistorted / 4.2.3：
Analyzing the situation / 4.2.4：
Taking action / 4.2.5：
Making and communicating decisions / 4.2.6：
Making a decision visible / 4.2.7：
Keeping the environment good / 4.2.8：
Managing an external supplier / 4.2.9：
CM: Managing baselines with milestones / 4.3：
Looking to standards for help / 4.4：
The Development Life-Cycle: Early Stages / 4.5：
Requirements / Chapter 5：
Balancing the 3Ps: Requirements gathering and analysis / 5.1：
Selecting the requirements engineer / 5.1.1：
Interviewing customers / 5.1.2：
Conducting group meetings / 5.1.3：
Diffusing tense situations / 5.1.4：
Evolving requirements / 5.1.5：
Requirements vs. design / 5.1.6：
Visibility: Making requirements known / 5.2：
An overview of techniques / 5.2.1：
Joint Application Development / 5.2.2：
Design by Walking Around / 5.2.3：
System Storyboarding Technique / 5.2.4：
Concept of operations / 5.2.5：
Mind maps / 5.2.6：
Gilb charts / 5.2.7：
Method 315 / 5.2.8：
Rapid prototyping / 5.2.9：
Software diagrams / 5.2.10：
The software requirements specification / 5.2.11：
Database support / 5.2.12：
Using CM / 5.3：
Using standards / 5.4：
Planning / 5.5：
Elements of a good plan / 6.1：
Balancing the 3Ps: Selecting the process / 6.2：
Prototyping / 6.2.1：
Rapid application development / 6.2.2：
Microsoft process / 6.2.3：
Spiral process / 6.2.4：
Process improvement mechanisms / 6.2.5：
Making the project visible: Planning techniques / 6.3：
Project context / 6.3.1：
Creating a task network / 6.3.2：
Cards on the wall planning / 6.3.3：
Making the project visible: Estimating techniques / 6.4：
Rayleigh model / 6.4.1：
PSP's Probe / 6.4.2：
A technique for simple estimation / 6.4.3：
Judging an estimate / 6.4.4：
Tailoring techniques to the process model / 6.4.5：
All-in-one military and commercial standards / 6.5：
Documenting the plan / 6.6.2：
Risk Management / 6.7：
A task overview / 7.1：
Balancing the 3Ps: Uncertainty and choice / 7.2：
Risk identification / 7.2.1：
Risk planning / 7.2.2：
Risk control / 7.2.3：
Risk monitoring / 7.2.4：
Risk directing and staffing / 7.2.5：
Making risk visible / 7.3：
Risk estimating / 7.3.1：
Risk evaluation / 7.3.2：
Risk analysis products / 7.3.3：
The Development Life-Cycle: Middle to Late Stages / 7.4：
Design / Chapter 8：
The challenges of the 3Ps / 8.1：
Managing creativity / 8.1.1：
Reducing design frustration / 8.1.2：
Evaluating and selecting from design alternatives / 8.1.3：
Visibility--Expressing the design / 8.2：
Words / 8.2.1：
Pictures / 8.2.2：
Configuration control boards / 8.3：
Design documents / 8.3.2：
Tracing requirements / 8.3.3：
Standards: Writing the SDD / 8.4：
Contents / 8.4.1：
Organization / 8.4.2：
Integration and Testing / 8.5：
Some I&T myths / 9.1：
Managing the 3Ps: People / 9.2：
Managing the 3Ps: Process / 9.3：
Common testing problems / 9.3.1：
IDEA / 9.3.2：
Verification and validation / 9.3.3：
Visibility: Testing techniques and details / 9.4：
Elements of effective testing / 9.4.1：
Black box testing / 9.4.2：
White box testing / 9.4.3：
Combining white box and black box testing / 9.4.4：
Integration testing / 9.4.5：
Acceptance testing / 9.4.6：
Regression testing / 9.4.7：
Cleanroom testing / 9.4.8：
How testing relates to other activities / 9.5：
Controlling test artifacts / 9.5.2：
Using the requirements traceability matrix / 9.5.3：
Standards: Documenting the test plan / 9.6：
Software Maintenance / 9.7：
What is maintenance? / 10.1：
Maintenance or development? / 10.1.1：
Maintenance activities / 10.1.2：
Why use configuration management? / 10.1.3：
Why is it so expensive and difficult? / 10.1.4：
Balancing the 3Ps: Managing the maintainers / 10.2：
Balancing the 3Ps: Managing the process / 10.3：
Balancing the 3Ps: Making the most of the product / 10.4：
Visibility: Understanding the maintenance stages / 10.5：
Identification and classification / 10.5.1：
Analysis / 10.5.2：
Implementation / 10.5.3：
System test / 10.5.5：
Acceptance test / 10.5.6：
Delivery / 10.5.7：
Keeping baselines straight / 10.6：
Managing releases / 10.6.2：
Pacing the process / 10.6.3：
Applying the Principles / 10.7：
Cookbook / Chapter 11：
Essentials / 11.1：
Use journals and decision records / 11.1.1：
Perform all CM activities / 11.1.2：
Manage day by day / 11.1.3：
Use standards / 11.1.4：
Conduct post-mortems / 11.1.5：
OPT: A waterfall project / 11.2：
Context / 11.2.1：
Project details / 11.2.2：
System upgrade: An evolutionary project / 11.3：
CTRan: A spiral project / 11.3.1：
Risks / 11.4.1：
Quadrants of the spiral / 11.4.3：
Cycles of the spiral / 11.4.5：
Appendices / 11.5：
Documents for the OPT Project / Appendix A：
OPT Executive Sponsor Memorandum
OPT Project Context Document
OPT Configuration Management Plan
OPT Concept of Operations
OPT Software Requirements Specification
OPT Software Project Management Plan
OPT Software Design Description
Configuration Management / Appendix B：
Will the Real CM please stand up? / B.1：
The main ingredients / B.2：
Baselines / B.3：
Basics / B.3.1：
Applying baselines in a waterfall project / B.3.2：
Applying baselines in a non-waterfall project / B.3.3：
Documenting baselines / B.3.4：
Baseline contents / B.3.5：
Interface control documents / B.3.6：
CM Activities / B.4：
Identification / B.4.1：
Control / B.4.2：
Auditing / B.4.3：
Status accounting / B.4.4：
CM staff / B.5：
Project manager / B.5.3：
CM plan / B.6：
A CM sketch / B.7：
Summary / B.8：
Structured Analysis and Design / Appendix C：
Structured analysis / C.1：
Environmental model / C.1.2：
Preliminary behavioral model / C.1.3：
Final behavioral model / C.1.4：
Finished essential model / C.1.5：
Structured design / C.2：
User implementation model / C.2.1：
Systems implementation model / C.2.2：
Program implementation model / C.2.3：
Annotated Bibliography / Appendix D：
Index
About the Author
Preface
Elements of Effective Software Management / Part 1：
What Makes a Good Software Manager? / Chapter 1：
文献の複写および貸借の依頼を行う
 文献複写・貸借依頼