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1. 東京工業大学名誉教授伊賀健一研究論文・講演集 : 1964年～2001年
伊賀, 健一(1940-)
出版情報: [東京] : [東京工業大学], 2001.10  DVD1枚 ; 12cm
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2.

図書
図書
2. Solid particle erosion : occurrence, prediction and control
Ilmar Kleis, Priit Kulu
出版情報: London : Springer, c2008  xii, 206 p ; 24 cm
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Notation
Experimental Study of Erosion Characteristics / 1：
Laboratory Equipment Used in Erosion Research / 1.1：
Dependence of Erosion on Particle Velocity / 1.2：
Dependence of Erosion on Impact Angle / 1.3：
Dependence of Erosion on Particle Size / 1.4：
Influence of Particle Concentration / 1.5：
Effect of Abrasive Mixtures and Liquid Additives on Erosion / 1.6：
Effect of Mixtures of Uniform Granularity / 1.6.1：
Effect of Fine-grained Solid Additives on Abrasion / 1.6.2：
Abrasion by Industrial Dusts / 1.6.3：
Effect of Liquid Additives / 1.6.4：
Influence of Temperature on Erosion / 1.7：
Erosion of Surface by Grazing Particles / 1.8：
References / 1.9：
Research into the Physical Mechanism of Erosion / 2：
Changes in the Macro-and Microgeometry of a Wearing Surface / 2.1：
Stress Distribution and Structural Changes in Target Material Surface Layer / 2.2：
Fragmentation of Abrasive Particles and Adhesion of the Latter to the Surface / 2.3：
Development of Theories of Collision and Erosion / 2.4：
Hypothesis of a Constant Specific Energy; Dynamic Hardness / 3.1：
Experimental and Theoretical Determination of the Coefficient of Restitution / 3.2：
Analytical Determination of Indentation Load in Terms of Impact Energy / 3.3：
Mathematical Models for Force Calculation / 3.3.1：
Comparison of Calculated and Experimental Results / 3.3.2：
Conclusions / 3.3.3：
Theoretical Treatment of Erosion / 3.4：
A Short Survey of Erosion Theory / 3.4.1：
Erosion by Plastic Contact / 3.4.2：
Energetic Erosion Theory / 3.4.2.1：
Verification and Modification of Energetic Erosion Theory / 3.4.2.2：
Erosion by Brittle Behaviour / 3.4.3：
Modelling of Wear / 3.4.3.1：
Verification of the Model / 3.4.3.2：
Calculation of Erosive Wear of Composite Materials / 3.4.4：
Prediction of Relative Erosion Resistance / 3.5：
Erosion Resistance of Powder Materials and Coatings / 3.6：
Groups and Properties of Wear Resistant Materials and Coatings / 4.1：
Erosion Resistance of Advanced Ceramic Materials and Coatings / 4.2：
Erosion Resistance of Ceramic-Metal Composites and Coatings at Room Temperature / 4.3：
Erosion of Ceramic-Metal Composites / 4.3.1：
Erosion of Coatings / 4.3.2：
Erosion Resistance of Ceramic-Metal Materials and Coatings at Elevated Temperatures / 4.4：
Criteria for Erosive Wear Resistant Material and Coating Selection / 4.4.1：
Tribological Criteria / 4.5.1：
Structural Criteria / 4.5.2：
Qualitative Criteria / 4.5.3：
Improvement of Erosion Resistance of Industrial Equipment / 4.6：
Fans and Exhausters / 5.1：
Influence of Geometrical Parameters of the Rotor on the Erosion Rate / 5.1.1：
Design Methods for Reducing Erosion of Rotors / 5.1.2：
Disintegrators / 5.2：
Use of Disintegrators in the Building Industry / 5.2.1：
Disintegrator as a Machine for Treatment of Different Materials by Collision / 5.2.2：
Application of Wear Resistant Materials and Coatings in Disintegrators / 5.2.3：
Improvement of Disintegrator Design / 5.2.4：
Cyclones for Ash Separation / 5.3：
Cyclone Working Conditions / 5.3.1：
Determination of the Impact Parameters of Erosive Particles / 5.3.2：
Drying Line Equipment at Peat-Briquette Works / 5.4：
Disintegrator as a Device for Milling of Mineral Ores / 5.5：
Materials to be Studied / 5.5.1：
Grindability and Abrasivity of Mineral Materials and Ores / 5.5.2：
Prediction of Relative Erosion Resistance of the Grinding Media / 5.5.3：
Index / 5.6：
Notation
Experimental Study of Erosion Characteristics / 1：
Laboratory Equipment Used in Erosion Research / 1.1：
3.

図書
図書
3. Advanced techniques for assessment surface topography : development of a basis for 3D surface texture standards "surfstand" (: pbk.)
Liam Blunt, Xiangqian Jiang
出版情報: London : Kogan Page Science, c2003  vi, 355 p. ; 30 cm
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Introduction: The History and Current State of 3D Surface Characterisation / Liam Blunt1.：
Characterisation / Part 1：
Numerical Parameters for Characterisation of Topography / Xiangqian Jiang2.：
Novel Areal Characterisation Techniques / Paul J. Scott3.：
Advanced Gaussian Filters / Stefan Brinkman ; Horst Bodschwinna4.：
Multi-scalar Filtration Methodologies / 5.：
Instrumentation / Part 2：
Calibration Procedures for Stylus and Optical Instrumentation / Jean Francois Ville6.：
Calibration Procedures for Atomic Force Microscopes / Anders Kuhle7.：
Case Studies / Part 3：
The Interrelationship of 3D Surface Characterisation Techniques with Standardised 2D Techniques / Robert Ohlsson ; Bengt Goran Rosen ; John Westberg8.：
Applications of Numerical Parameters and Filtration / 9.：
Functionality and Characterisation of Textured Sheet Steel Products / Micheal Vermeulen ; Henrik Hobleke10.：
Characterisation of Automotive Engine Bore Performance using 3D Surface Metrology / 11.：
Future Developments / Part 4：
Surface Texture Knowledge Support--ISM / 12.：
Future Developments in Surface Metrology / 13.：
Index
Introduction: The History and Current State of 3D Surface Characterisation / Liam Blunt1.：
Characterisation / Part 1：
Numerical Parameters for Characterisation of Topography / Xiangqian Jiang2.：
4.

図書
図書
4. Information modeling and relational databases. 2nd ed.
Terry Halpin, Tony Morgan
出版情報: Burlington : Morgan Kaufman Publishers, c2008  xxvi, 943 p. ; 24 cm
シリーズ名: The Morgan Kaufmann series in data management systems
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Introduction / 1：
Information Modeling / 1.1：
Modeling Approaches / 1.2：
Some Historical Background / 1.3：
The Relevant Skills / 1.4：
Summary / 1.5：
Information Levels and Frameworks / 2：
Four Information Levels / 2.1：
The Conceptual Level / 2.2：
Database Design Example / 2.3：
Development Frameworks / 2.4：
Conceptual Modeling: First Steps / 2.5：
Conceptual Modeling Language Criteria / 3.1：
Conceptual Schema Design Procedure / 3.2：
CSDP Step 1: From Examples to Elementary Facts / 3.3：
CSDP Step 2: Draw Fact Types, and Populate / 3.4：
CSDP Step 3: Trim Schema / 3.5：
Note Basic Derivations
Uniqueness Constraints / 3.6：
Arity Check / 4.1 CSDP Step 4: Uniqueness Constraints：
Mandatory Roles / 4.2 Uniqueness Constraints on Unaries and Binaries：
Introduction to CSDP Step 5 / 5.1：
Mandatory and Optional Roles / 5.2：
Reference Schemes / 5.3：
Case Study: A Compact Disc Retailer / 5.4：
Logical Derivation Check / 5.5：
Value, Set-Comparison and Subtype Constraints / 5.6：
CSDP Step 6: Value, Set-Comparison and Subtype constraints / 6.1：
Basic Set Theory / 6.2：
Value Constraints and Independent Objects / 6.3：
Subset, Equality, and Exclusion Constraints / 6.4：
Subtyping / 6.5：
Generalization of Object Types / 6.6：
Other Constraints and Final Checks / 6.7：
CSDP Step 7: Other Constraints and Final Checks / 7.1：
Occurrence Frequencies / 7.2：
Ring Constraints / 7.3：
Other Constraints and Rules / 7.4：
Final Checks / 7.5：
Entity Relationship Modeling / 7.6：
Overview of ER / 8.1：
Barker notation / 8.2：
Information Engineering notation / 8.3：
IDEF1X / 8.4：
Mapping from ORM to ER / 8.5：
Data Modeling in UML / 8.6：
Object-Orientation / 9.1：
Attributes / 9.3：
Associations / 9.4：
Set-Comparison constraints / 9.5：
Other Constraints and Derivation Rules / 9.6：
Mapping from ORM to UML / 9.8：
Advanced Modeling Issues / 9.9：
Join Constraints / 10.1：
Deontic Rules / 10.2：
Temporality / 10.3：
Collection Types / 10.4：
Nominalization and Objectification / 10.5：
Open/Closed World Semantics / 10.6：
Higher-Order Types / 10.7：
Relational Mapping / 10.8：
Implementing a Conceptual Schema / 11.1：
Relational Schemas / 11.2：
Relational Mapping Procedure / 11.3：
Advanced Mapping Aspects / 11.4：
Data Manipulation with Relational Languages / 11.5：
Relational Algebra / 12.1：
Relational Database Systems / 12.2：
SQL: Historical and Structural Overview / 12.3：
SQL: Identifiers and Data Types / 12.4：
SQL: Choosing Columns, Rows, and Order / 12.5：
SQL: Joins / 12.6：
SQL: In, Between, Like, and Null Operators / 12.7：
SQL: Union and Simple Subqueries / 12.8：
SQL: Scalar Operators and Bag Functions / 12.9：
SQL: Grouping / 12.10：
SQL: Correlated and Existential Subqueries / 12.11：
SQL: Recursive Queries / 12.12：
SQL: Updating Table Populations / 12.13：
SQL: Other Useful Constructs / 12.14：
Using Other Database Objects / 12.15：
SQL: Data Definition / 13.1：
SQL: User Defined Functions / 13.2：
SQL: Views and Computed Columns / 13.3：
SQL: Triggers / 13.4：
SQL: Stored Procedures / 13.5：
SQL: Indexes / 13.6：
Other Objects / 13.7：
Exploiting 3GLs / 13.8：
Exploiting XML / 13.9：
Security and Meta-Data / 13.10：
Concurrency / 13.11：
Schema Transformations / 13.12：
Schema Equivalence and Optimization / 14.1：
Predicate Specialization and Generalization / 14.2：
Nesting, Coreferencing, and Flattening / 14.3：
Other Transformations / 14.4：
Introduction / 1：
Information Modeling / 1.1：
Modeling Approaches / 1.2：
5.

図書
図書
5. Process analysis and improvement : tools and techniques
Marvin S. Seppanen, Sameer Kumar, Charu Chandra
出版情報: New York : McGraw-Hill/Irwin, c2005  xvii, 366 p. ; 26 cm.
シリーズ名: The Irwin/McGraw-Hill series in operations and decision sciences
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Introduction to Process Analysis and Improvement / Chapter 1：
Process Analysis and Improvement Using Visio / Chapter 2：
Applications Using Visio / Chapter 3：
Data Management and Analysis Using Excel / Chapter 4：
Applications Using Excel / Chapter 5：
Process Simulation Using Arena / Chapter 6：
Applications Using Arena / Chapter 7：
Visual Basic for Applications: Computer Based Tools Integration / Chapter 8：
Process Analysis and Improvement Application: Customer Service Center / Chapter 9：
Process Analysis and Improvement / Chapter 10：
Student Process Analysis and Improvement Projects / Chapter 11：
Future of Computer Based Tools for Process Analysis and Improvement / Chapter 12：
Introduction to Process Analysis and Improvement / Chapter 1：
Process Analysis and Improvement Using Visio / Chapter 2：
Applications Using Visio / Chapter 3：
6.

図書
図書
6. Nanoscience and nanotechnology on quantum particles : 15-17 December 2003 Tokyo Institute of Technology
RLNR, Tokyo Institute of Technology
出版情報: Tokyo : [Tokyo Institute of Technology], [2003]  x, 79 p ; 30 cm
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7.

図書
図書
7. Selected nonlinear matrix equations (: pbk)
Sandra Fital-Akelbek
出版情報: Saarbrücken : VDM, c2009  vi, 130 p. ; 22 cm
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8.

図書
図書
8. Data analysis and graphics using R : an example-based approach
John Maindonald and John Braun
出版情報: Cambridge, UK : Cambridge University Press, 2003  xxiii, 362 p., [4] p. of plates ; 26 cm
シリーズ名: Cambridge series on statistical and probabilistic mathematics
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目次情報: 続きを見る
Preface
A Chapter by Chapter Summary
A Brief Introduction to R / 1：
A Short R Session / 1.1：
R must be installed! / 1.1.1：
Using the console (or command line) window / 1.1.2：
Reading data from a file / 1.1.3：
Entry of data at the command line / 1.1.4：
Online help / 1.1.5：
Quitting R / 1.1.6：
The Uses of R / 1.2：
The R Language / 1.3：
R objects / 1.3.1：
Retaining objects between sessions / 1.3.2：
Vectors in R / 1.4：
Concatenation--joining vector objects / 1.4.1：
Subsets of vectors / 1.4.2：
Patterned data / 1.4.3：
Missing values / 1.4.4：
Factors / 1.4.5：
Data Frames / 1.5：
Variable names / 1.5.1：
Applying a function to the columns of a data frame / 1.5.2：
Data frames and matrices / 1.5.3：
Identification of rows that include missing values / 1.5.4：
R Packages / 1.6：
Data sets that accompany R packages / 1.6.1：
Looping / 1.7：
R Graphics / 1.8：
The function plot () and allied functions / 1.8.1：
Identification and location on the figure region / 1.8.2：
Plotting mathematical symbols / 1.8.3：
Row by column layouts of plots / 1.8.4：
Graphs--additional notes / 1.8.5：
Additional Points on the Use of R in This Book / 1.9：
Further Reading / 1.10：
Exercises / 1.11：
Styles of Data Analysis / 2：
Revealing Views of the Data / 2.1：
Views of a single sample / 2.1.1：
Patterns in grouped data / 2.1.2：
Patterns in bivariate data--the scatterplot / 2.1.3：
Multiple variables and times / 2.1.4：
Lattice (trellis style) graphics / 2.1.5：
What to look for in plots / 2.1.6：
Data Summary / 2.2：
Mean and median / 2.2.1：
Standard deviation and inter-quartile range / 2.2.2：
Correlation / 2.2.3：
Statistical Analysis Strategies / 2.3：
Helpful and unhelpful questions / 2.3.1：
Planning the formal analysis / 2.3.2：
Changes to the intended plan of analysis / 2.3.3：
Recap / 2.4：
Statistical Models / 2.5：
Regularities / 3.1：
Mathematical models / 3.1.1：
Models that include a random component / 3.1.2：
Smooth and rough / 3.1.3：
The construction and use of models / 3.1.4：
Model formulae / 3.1.5：
Distributions: Models for the Random Component / 3.2：
Discrete distributions / 3.2.1：
Continuous distributions / 3.2.2：
The Uses of Random Numbers / 3.3：
Simulation / 3.3.1：
Sampling from populations / 3.3.2：
Model Assumptions / 3.4：
Random sampling assumptions--independence / 3.4.1：
Checks for normality / 3.4.2：
Checking other model assumptions / 3.4.3：
Are non-parametric methods the answer? / 3.4.4：
Why models matter--adding across contingency tables / 3.4.5：
An Introduction to Formal Inference / 3.5：
Standard Errors / 4.1：
Population parameters and sample statistics / 4.1.1：
Assessing accuracy--the standard error / 4.1.2：
Standard errors for differences of means / 4.1.3：
The standard error of the median / 4.1.4：
Resampling to estimate standard errors: bootstrapping / 4.1.5：
Calculations Involving Standard Errors: the t-Distribution / 4.2：
Confidence Intervals and Hypothesis Tests / 4.3：
One- and two-sample intervals and tests for means / 4.3.1：
Confidence intervals and tests for proportions / 4.3.2：
Confidence intervals for the correlation / 4.3.3：
Contingency Tables / 4.4：
Rare and endangered plant species / 4.4.1：
Additional notes / 4.4.2：
One-Way Unstructured Comparisons / 4.5：
Displaying means for the one-way layout / 4.5.1：
Multiple comparisons / 4.5.2：
Data with a two-way structure / 4.5.3：
Presentation issues / 4.5.4：
Response Curves / 4.6：
Data with a Nested Variation Structure / 4.7：
Degrees of freedom considerations / 4.7.1：
General multi-way analysis of variance designs / 4.7.2：
Resampling Methods for Tests and Confidence Intervals / 4.8：
The one-sample permutation test / 4.8.1：
The two-sample permutation test / 4.8.2：
Bootstrap estimates of confidence intervals / 4.8.3：
Further Comments on Formal Inference / 4.9：
Confidence intervals versus hypothesis tests / 4.9.1：
If there is strong prior information, use it! / 4.9.2：
Regression with a Single Predictor / 4.10：
Fitting a Line to Data / 5.1：
Lawn roller example / 5.1.1：
Calculating fitted values and residuals / 5.1.2：
Residual plots / 5.1.3：
The analysis of variance table / 5.1.4：
Outliers, Influence and Robust Regression / 5.2：
Standard Errors and Confidence Intervals / 5.3：
Confidence intervals and tests for the slope / 5.3.1：
SEs and confidence intervals for predicted values / 5.3.2：
Implications for design / 5.3.3：
Regression versus Qualitative ANOVA Comparisons / 5.4：
Assessing Predictive Accuracy / 5.5：
Training/test sets, and cross-validation / 5.5.1：
Cross-validation--an example / 5.5.2：
Bootstrapping / 5.5.3：
A Note on Power Transformations / 5.6：
Size and Shape Data / 5.7：
Allometric growth / 5.7.1：
There are two regression lines! / 5.7.2：
The Model Matrix in Regression / 5.8：
Methodological References / 5.9：
Multiple Linear Regression / 5.11：
Basic Ideas: Book Weight and Brain Weight Examples / 6.1：
Omission of the intercept term / 6.1.1：
Diagnostic plots / 6.1.2：
Further investigation of influential points / 6.1.3：
Example: brain weight / 6.1.4：
Multiple Regression Assumptions and Diagnostics / 6.2：
Influential outliers and Cook's distance / 6.2.1：
Component plus residual plots / 6.2.2：
Further types of diagnostic plot / 6.2.3：
Robust and resistant methods / 6.2.4：
A Strategy for Fitting Multiple Regression Models / 6.3：
Preliminaries / 6.3.1：
Model fitting / 6.3.2：
An example--the Scottish hill race data / 6.3.3：
Measures for the Comparison of Regression Models / 6.4：
R[superscript 2] and adjusted R[superscript 2] / 6.4.1：
AIC and related statistics / 6.4.2：
How accurately does the equation predict? / 6.4.3：
An external assessment of predictive accuracy / 6.4.4：
Interpreting Regression Coefficients--the Labor Training Data / 6.5：
Problems with Many Explanatory Variables / 6.6：
Variable selection issues / 6.6.1：
Principal components summaries / 6.6.2：
Multicollinearity / 6.7：
A contrived example / 6.7.1：
The variance inflation factor (VIF) / 6.7.2：
Remedying multicollinearity / 6.7.3：
Multiple Regression Models--Additional Points / 6.8：
Confusion between explanatory and dependent variables / 6.8.1：
Missing explanatory variables / 6.8.2：
The use of transformations / 6.8.3：
Non-linear methods--an alternative to transformation? / 6.8.4：
Exploiting the Linear Model Framework / 6.9：
Levels of a Factor--Using Indicator Variables / 7.1：
Example--sugar weight / 7.1.1：
Different choices for the model matrix when there are factors / 7.1.2：
Polynomial Regression / 7.2：
Issues in the choice of model / 7.2.1：
Fitting Multiple Lines / 7.3：
Methods for Passing Smooth Curves through Data / 7.4：
Scatterplot smoothing--regression splines / 7.4.1：
Other smoothing methods / 7.4.2：
Generalized additive models / 7.4.3：
Smoothing Terms in Multiple Linear Models / 7.5：
Logistic Regression and Other Generalized Linear Models / 7.6：
Generalized Linear Models / 8.1：
Transformation of the expected value on the left / 8.1.1：
Noise terms need not be normal / 8.1.2：
Log odds in contingency tables / 8.1.3：
Logistic regression with a continuous explanatory variable / 8.1.4：
Logistic Multiple Regression / 8.2：
A plot of contributions of explanatory variables / 8.2.1：
Cross-validation estimates of predictive accuracy / 8.2.2：
Logistic Models for Categorical Data--an Example / 8.3：
Poisson and Quasi-Poisson Regression / 8.4：
Data on aberrant crypt foci / 8.4.1：
Moth habitat example / 8.4.2：
Residuals, and estimating the dispersion / 8.4.3：
Ordinal Regression Models / 8.5：
Exploratory analysis / 8.5.1：
Proportional odds logistic regression / 8.5.2：
Other Related Models / 8.6：
Loglinear models / 8.6.1：
Survival analysis / 8.6.2：
Transformations for Count Data / 8.7：
Multi-level Models, Time Series and Repeated Measures / 8.8：
Introduction / 9.1：
Example--Survey Data, with Clustering / 9.2：
Alternative models / 9.2.1：
Instructive, though faulty, analyses / 9.2.2：
Predictive accuracy / 9.2.3：
A Multi-level Experimental Design / 9.3：
The ANOVA table / 9.3.1：
Expected values of mean squares / 9.3.2：
The sums of squares breakdown / 9.3.3：
The variance components / 9.3.4：
The mixed model analysis / 9.3.5：
Different sources of variance--complication or focus of interest? / 9.3.6：
Within and between Subject Effects--an Example / 9.4：
Time Series--Some Basic Ideas / 9.5：
Preliminary graphical explorations / 9.5.1：
The autocorrelation function / 9.5.2：
Autoregressive (AR) models / 9.5.3：
Autoregressive moving average (ARMA) models--theory / 9.5.4：
Regression Modeling with Moving Average Errors--an Example / 9.6：
Repeated Measures in Time--Notes on the Methodology / 9.7：
The theory of repeated measures modeling / 9.7.1：
Correlation structure / 9.7.2：
Different approaches to repeated measures analysis / 9.7.3：
Further Notes on Multi-level Modeling / 9.8：
An historical perspective on multi-level models / 9.8.1：
Meta-analysis / 9.8.2：
Tree-based Classification and Regression / 9.9：
The Uses of Tree-based Methods / 10.1：
Problems for which tree-based regression may be used / 10.1.1：
Tree-based regression versus parametric approaches / 10.1.2：
Summary of pluses and minuses / 10.1.3：
Detecting Email Spam--an Example / 10.2：
Choosing the number of splits / 10.2.1：
Terminology and Methodology / 10.3：
Choosing the split--regression trees / 10.3.1：
Within and between sums of squares / 10.3.2：
Choosing the split--classification trees / 10.3.3：
The mechanics of tree-based regression--a trivial example / 10.3.4：
Assessments of Predictive Accuracy / 10.4：
Cross-validation / 10.4.1：
The training/test set methodology / 10.4.2：
Predicting the future / 10.4.3：
A Strategy for Choosing the Optimal Tree / 10.5：
Cost-complexity pruning / 10.5.1：
Prediction error versus tree size / 10.5.2：
Detecting Email Spam--the Optimal Tree / 10.6：
The one-standard-deviation rule / 10.6.1：
Interpretation and Presentation of the rpart Output / 10.7：
Data for female heart attack patients / 10.7.1：
Printed Information on Each Split / 10.7.2：
Additional Notes / 10.8：
Multivariate Data Exploration and Discrimination / 10.9：
Multivariate Exploratory Data Analysis / 11.1：
Scatterplot matrices / 11.1.1：
Principal components analysis / 11.1.2：
Discriminant Analysis / 11.2：
Example--plant architecture / 11.2.1：
Classical Fisherian discriminant analysis / 11.2.2：
Logistic discriminant analysis / 11.2.3：
An example with more than two groups / 11.2.4：
Principal Component Scores in Regression / 11.3：
Propensity Scores in Regression Comparisons--Labor Training Data / 11.4：
The R System--Additional Topics / 11.5：
Graphs in R / 12.1：
Functions--Some Further Details / 12.2：
Common useful functions / 12.2.1：
User-written R functions / 12.2.2：
Functions for working with dates / 12.2.3：
Data input and output / 12.3：
Input / 12.3.1：
Data output / 12.3.2：
Factors--Additional Comments / 12.4：
Missing Values / 12.5：
Lists and Data Frames / 12.6：
Data frames as lists / 12.6.1：
Reshaping data frames; reshape () / 12.6.2：
Joining data frames and vectors--cbind () / 12.6.3：
Conversion of tables and arrays into data frames / 12.6.4：
Merging data frames--merge () / 12.6.5：
The function sapply () and related functions / 12.6.6：
Splitting vectors and data frames into lists--split () / 12.6.7：
Matrices and Arrays / 12.7：
Outer products / 12.7.1：
Arrays / 12.7.2：
Classes and Methods / 12.8：
Printing and summarizing model objects / 12.8.1：
Extracting information from model objects / 12.8.2：
Data-bases and Environments / 12.9：
Workspace management / 12.9.1：
Function environments, and lazy evaluation / 12.9.2：
Manipulation of Language Constructs / 12.10：
Epilogue--Models / 12.11：
S-PLUS Differences / Appendix：
References
Index of R Symbols and Functions
Index of Terms
Index of Names
Preface
A Chapter by Chapter Summary
A Brief Introduction to R / 1：
9.

図書
図書
9. Data-driven techniques in speech synthesis
edited by R.I. Damper
出版情報: Dordrecht : Kluwer Academic Publishers, c2001  xviii, 316 p. ; 25 cm
シリーズ名: Telecommunications technology & application series
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10.

学位論文
学位
10. Studies on the spectrum of the Laplacian on Riemannian manifolds
by Katsuhiro Yoshiji
出版情報: 東京 : 東京工業大学, 2001
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11.

学位論文
学位
11. Study on keV-neutron capture reaction by [140]Ce and [141]Pr
Suhe Harnood
出版情報: 東京 : 東京工業大学, 2001
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12.

学位論文
学位
12. A study on longitudinal mass-diffusion enhancement for oscillatory tube flows
Ye Xiao-Feng
出版情報: 東京 : 東京工業大学, 2001
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13.

学位論文
学位
13. Black Hole Entropy and the Generalized Second Law : The RosettaStone of Black Hole Thermodynamics
Takeshi Shimomura
出版情報: 東京 : 東京工業大学, 2001
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14.

学位論文
学位
14. Structure and electronic properties of sp[2]/sp[3]-mixed carbon systems
by Kazuyuki Takai
出版情報: 東京 : 東京工業大学, 2001
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15.

学位論文
学位
15. Synthesis and characterization of tungsten bronze type new ferroelectric compounds (Mc[2+][1-x]Ln[3+][2x/3])[5]Nb[10]O[30] (M=Ba, Pb and Sr, Ln=rare earth)
汪睿凱
出版情報: 東京 : 東京工業大学, 2001
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16.

学位論文
学位
16. Kinetics of heterogeneous electron-transfer at platinum singele crystal electrodes
Noriaki Wakabayashi
出版情報: 東京 : 東京工業大学, 2001
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17.

学位論文
学位
17. Translation from register transfer level specification to signal transition graph representation for four-phase handshaking asynchronous controllers
by Rafael Kazumiti Morizawa
出版情報: 東京 : 東京工業大学, 2001
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18.

図書
図書
18. Approximating integrals via Monte Carlo and deterministic methods
Michael Evans and Tim Swartz
出版情報: Oxford ; New York : Oxford University Press, c2000  ix, 288 p. ; 24 cm
シリーズ名: Oxford statistical science series ; 20
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19.

図書
図書
19. Digital image processing algorithms and applications
I. Pitas
出版情報: New York ; Chichester : Wiley, c2000  xi, 419 p. ; 25 cm
シリーズ名: A Wiley-Interscience publication
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目次情報: 続きを見る
Preface
Digital image processing fundamentals / 1：
Introduction / 1.1：
Topics of digital image processing and analysis / 1.2：
Digital image formation / 1.3：
Digital image representation / 1.4：
Elementary digital image processing operations / 1.5：
Digital image display / 1.6：
Fundamentals of color image processing / 1.7：
Noise generators for digital image processing / 1.8：
References
Digital image transform algorithms / 2：
Two-dimensional discrete Fourier transform / 2.1：
Row--column FFT algorithm / 2.3：
Memory problems in 2-d DFT calculations / 2.4：
Vector-radix fast Fourier transform algorithm / 2.5：
Polynomial transform FFT / 2.6：
Two-dimensional power spectrum estimation / 2.7：
Discrete cosine transform / 2.8：
Two-dimensional discrete cosine transform / 2.9：
Discrete wavelet transform / 2.10：
Digital image filtering and enhancement / 3：
Direct implementation of two-dimensional FIR digital filters / 3.1：
Fast Fourier transform implementation of FIR digital filters / 3.3：
Block methods in the linear convolution calculation / 3.4：
Inverse filter implementations / 3.5：
Wiener filters / 3.6：
Median filter algorithms / 3.7：
Digital filters based on order statistics / 3.8：
Signal Adaptive order statistic filters / 3.9：
Histogram and histogram equalization techniques / 3.10：
Pseudocoloring algorithms / 3.11：
Digital image halftoning / 3.12：
Image interpolation algorithms / 3.13：
Anisotropic Diffusion / 3.14：
Image Mosaicing / 3.15：
Image watermarking / 3.16：
Digital image compression / 4：
Huffman coding / 4.1：
Run-length coding / 4.3：
Modified READ coding / 4.4：
LZW compression / 4.5：
Predictive coding / 4.6：
Transform image coding / 4.7：
JPEG2000 compression standard / 4.8：
Edge detection algorithms / 5：
Edge detection / 5.1：
Edge thresholding / 5.3：
Hough transform / 5.4：
Edge-following algorithms / 5.5：
Image segmentation algorithms / 6：
Image segmentation by thresholding / 6.1：
Split/merge and region growing algorithms / 6.3：
Relaxation algorithms in region analysis / 6.4：
Connected component labeling / 6.5：
Texture description / 6.6：
Shape description / 7：
Chain codes / 7.1：
Polygonal approximations / 7.3：
Fourier descriptors / 7.4：
Quadtrees / 7.5：
Pyramids / 7.6：
Shape features / 7.7：
Moment descriptors / 7.8：
Thinning algorithms / 7.9：
Mathematical morphology / 7.10：
Grayscale morphology / 7.11：
Skeletons / 7.12：
Shape decomposition / 7.13：
Voronoi tesselation / 7.14：
Watershed transform / 7.15：
Face detection and recognition / 7.16：
Digital Image Processing Lab Exercises Using EIKONA / 8：
Overview / 8.1：
Structure / 8.3：
BW image processing / 8.4：
Black-and-White / 8.4.1：
Basic / 8.4.2：
Processing / 8.4.3：
Analysis / 8.4.4：
Transforms / 8.4.5：
Filtering / 8.4.6：
Nonlinear filtering / 8.4.7：
Color image processing / 8.5：
Color Representation / 8.5.1：
Modules / 8.6：
Arts module / 8.6.1：
Crack Restoration / 8.6.2：
Watermark module / 8.6.3：
EIKONA Source, Library/DLL / 8.7：
Instructions for using the educational material / 8.8：
Index
Preface
Digital image processing fundamentals / 1：
Introduction / 1.1：
20.

図書
図書
20. The quantum mechanics solver : how to apply quantum theory to modern physics
Jean-Louis Basdevant, Jean Dalibard
出版情報: Berlin : Springer, c2000  xi, 241 p ; 24 cm
シリーズ名: Advanced texts in physics
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図書
図書
21. Set-indexed martingales
Gail Ivanoff, Ely Merzbach
出版情報: Boca Raton : Chapman & Hall/CRC, c2000  212 p. ; 24 cm
シリーズ名: Monographs on statistics and applied probability ; 85
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目次情報: 続きを見る
Introduction
General Theory / I：
Generalities / 1：
Framework and Assumptions / 1.1：
Examples / 1.2：
The Hausdorff Metric / 1.3：
The Probability Structure / 1.4：
Stopping Sets / 1.5：
Predictability / 2：
A characterization by stochastic intervals / 2.1：
Announcability / 2.2：
Progressivity / 2.3：
Left-continuous processes / 2.4：
Martingales / 3：
Definitions / 3.1：
Classical properties / 3.2：
Stopping theorems / 3.3：
Decompositions and Quadratic Variation / 3.4：
Admissible Functions and Measures / 4.1：
Compensator and Quadratic Variation / 4.3：
Discrete Approximations / 4.4：
Point Processes and Compensators / 4.5：
Martingale Characterizations / 5：
Flows / 5.1：
Brownian Motion / 5.2：
The Poisson Process / 5.3：
Generalizations of Martingales / 6：
Local Martingales / 6.1：
Doob-Meyer Decompositions / 6.2：
Quasimartingales / 6.3：
Weak Convergence / II：
Weak Convergence of Set-Indexed Processes / 7：
The Function Space D(A) / 7.1：
Weak Convergence on D(A) / 7.2：
Semi-Functional Convergence / 7.3：
Limit Theorems for Point Processes / 8：
Strictly simple point processes / 8.1：
Poisson limit theorem / 8.2：
Empirical processes / 8.3：
Martingale Central Limit Theorems / 9：
Central Limit Theorems / 9.1：
The Weighted Empirical Process / 9.2：
References
Index
Introduction
General Theory / I：
Generalities / 1：
22.

図書
図書
22. Speech processing and synthesis toolboxes
D. G. Childers
出版情報: New York : Wiley, c2000  ix, 483 p. ; 26 cm
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目次情報: 続きを見る
Speech Analysis Toolbox
Speech Production, Labeling, and Characteristics
Data and Measurements
Linear Prediction
Speech Synthesis and a Formant Speech Synthesis Toolbox
Vocos - A Voice Conversion Toolbox
Time Modification of Speech Toolbox
Animated Vocal Fold Model Toolbox
Articulatory Speech Synthesis Toolbox
Appendices
Index
Speech Analysis Toolbox
Speech Production, Labeling, and Characteristics
Data and Measurements
23.

図書
図書
23. Neural and adaptive systems : fundamentals through simulations
José C. Principe, Neil R. Euliano, W. Curt Lefebvre
出版情報: New York : Wiley, c2000  xiii, 656 p. ; 25 cm
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Data Fitting with Linear Models
Pattern Recognition
Multilayer Perceptrons
Designing and Training MLPs
Function Approximation with MLPs, Radial Basis Functions, and Support Vector Machines
Hebbian Learning and Principal Component Analysis
Competitive and Kohonen Networks
Principles of Digital Signal Processing
Adaptive Filters
Temporal Processing with Neural Networks
Training and Using Recurrent Networks
Appendices
Glossary
Index
Data Fitting with Linear Models
Pattern Recognition
Multilayer Perceptrons
24.

図書
図書
24. The process-centered enterprise : the power of commitments
Gabriel A. Pall ; forewords by A. Blantin [i.e. Blanton] Godfrey, Stephan H. Haeckelsa
出版情報: Boca Raton : St. Lucie Press, c2000  xxix, 325 p. ; 25 cm
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目次情報: 続きを見る
The Case for Process Centering / Part I：
Doing Business in the Face of Change / Chapter 1.：
The Changing Business Environment / 1.1：
The Fundamental Success Factors / 1.1.1：
The New Challenge: Accelerated and Unpredictable Change / 1.1.2：
The Results of Change: What Is Really Happening? / 1.1.3：
The History of Change / 1.1.4：
Where Are We Today? / 1.2：
Problems with Today's Corporation / 1.2.1：
Today's Challenge / 1.2.2：
Summary / 1.3：
Traditional Ways of Coping with Change / Chapter 2.：
The Nature and Sources of Change / 2.1：
The Ping-Pong Response of Organizations to Change / 2.1.1：
Today's Customer-Driven Environment / 2.1.2：
Competition in the 21st Century / 2.1.3：
Traditional Responses to Change / 2.2：
Total Quality Management / 2.2.1：
Business Process Reengineering / 2.2.2：
Limitations of Traditional Reengineering / 2.2.3：
Limitations of the Traditional Approaches to Process Change / 2.3：
The Imperfection of Customer Needs / 2.3.1：
The Process Paradox / 2.3.2：
What Now? A Change in Managerial Attitudes / 2.4：
The Economic Value in Process Centering / 2.5：
Managing Work for Value Enhancement / 3.1：
The Value Contribution of Work / 3.1.1：
The Questionable Value Contribution of Downsizing / 3.1.2：
Investment in Business Processes for Economic Value Added / 3.2：
Impact on the Customer / 3.2.1：
Relevance to Overall Strategic Direction / 3.2.2：
The Viability of the Process / 3.2.3：
The Worth of the Process / 3.2.4：
Process Cost / 3.3：
The Cost of Conformance / 3.3.1：
The Cost of Nonconformance / 3.3.2：
The Cost of Quality as Management Tool / 3.3.3：
Productivity and Value / 3.3.4：
The Intellectual Value in Process Centering / 3.4：
The Emergence of Intellectual Assets / 4.1：
Intellectual Value Added / 4.2：
Customer Capital / 4.2.1：
Intellectual Capital / 4.2.2：
Net Added Value of Information Processed / 4.2.3：
The Role of Knowledge Management in Process Design / 4.3：
Process Centering Fundamentals / 4.4：
Understanding Processes / Chapter 5.：
Process Fundamentals / 5.1：
Classic Definitions / 5.1.1：
Process Control / 5.1.2：
Process Capability / 5.1.3：
Core Concepts of Process Thinking / 5.2：
Subject Process / 5.2.1：
Example for Subject Processes / 5.2.2：
Process Feedback / 5.2.3：
Process Quality / 5.2.4：
The Concept of Social Processes: The Human Element / 5.3：
Open Systems / 5.3.1：
Business Processes / 5.3.2：
Process Centering: The Basic Approach / 5.4：
Process Centering as the Prerequisite for Change / 6.1：
Definition of Process Centering / 6.1.1：
Commitment Management / 6.1.2：
Process Reengineering / 6.1.3：
Organizational Adaptability / 6.1.4：
Process Performance and Adaptability / 6.2：
Definitions / 6.2.1：
Adaptive Loops in Processes / 6.2.2：
The Superiority of Process Centering / 6.2.3：
Commitment Coordination and Process Alignment / 6.2.4：
What Needs To Be Done / 6.2.5：
Process Centering: The Response to Change / 6.3：
Response to Change / 7.1：
Upsizing and Growth / 7.1.1：
The Nature of Change / 7.1.2：
Response Characteristics / 7.2：
Information Intensity and Process Adaptability / 7.2.1：
Process Robustness / 7.2.2：
The Economics of Increasing Returns / 7.2.3：
Response Strategies for Growth / 7.3：
Processes as Product Offerings / 7.3.1：
Market Preempting / 7.3.2：
Process Investment Strategies for Growth / 7.3.3：
Process Centering: Role of the Individual / 7.4：
Process People / 8.1：
Empowerment, Commitment and Accountability / 8.1.1：
The Process Professional / 8.1.2：
The Process Team / 8.1.3：
Process Work / 8.2：
Multifunctional Work / 8.2.1：
Multidimensional Work / 8.2.2：
Valuable Work / 8.2.3：
Productive Work / 8.2.4：
Knowledge-Based Work / 8.2.5：
Rewarding Work / 8.2.6：
Work-Driven Shift in Personal Characteristics and Skills / 8.2.7：
Process-Related Roles and Responsibilities / 8.3：
Process Centering: The Management Team / 8.4：
Overseers and Implementers / 9.1：
Enterprise Transformation Executive / 9.1.1：
Enterprise Transformation Council / 9.1.2：
Business Process Management Executive / 9.1.3：
Business Process Owner / 9.1.4：
Business Process Management Team / 9.1.5：
Business Process Management Team Leader / 9.1.6：
Business Process Stakeholders / 9.1.7：
Process Management Resources / 9.2：
Process Contract / 9.2.1：
Process Training / 9.2.2：
Information Technology: The Response Integrator / 9.3：
Change and Information Intensity / 10.1：
Information Technology / 10.1.1：
Information Management for Adaptability / 10.2：
Two Key Process Components / 10.2.1：
Basic Functional Capabilities / 10.2.2：
Technology Assessment / 10.2.3：
Networked Collaborative Systems / 10.3：
Employee Training / 10.3.1：
Collaborative Work Practices / 10.3.2：
Wide-Area Networks / 10.3.3：
Groupware and Collaborative Computing / 10.3.4：
Fundamentals of Online Collaborative Systems / 10.3.5：
Collaborative System Architecture / 10.3.6：
Information Technology as Integrator / 10.4：
Deductive Thinking / 10.4.1：
Inductive Thinking / 10.4.2：
The Need Paradox / 10.4.3：
Process-Centered Management / 10.5：
Basics of Business Process Management / Chapter 11.：
Process Management Overview / 11.1：
The Process Management Roadmap / 11.1.1：
Classification of Business Processes / 11.1.2：
Process Planning / 11.2：
Process Identification and Mapping / 11.2.1：
Process Selection for Reengineering / 11.2.2：
Process Definition / 11.2.3：
Customer Requirements / 11.2.4：
Effective Process-Centered Management / 11.3：
The Operational View / 12.1：
The Two Dimensions of Process Management / 12.1.1：
Commitment Management and Communications / 12.1.2：
Process Resources / 12.1.3：
Process Measurements and Controls / 12.1.4：
Process Adaptability / 12.1.5：
Process Centering / 12.2：
Process Structure: The Holistic View / 12.3：
The Dynamic Business Process / 13.1：
The Holistic Process Model / 13.1.1：
The Workflow and Adaptive Loops / 13.1.3：
Alignment Engineering / 13.2：
Process Performance and Resources / 13.3：
Performance Measurement and Control / 14.1：
Process Measurement / 14.1.1：
Cycle-Time Reduction / 14.1.2：
Cycle-Time Basics / 14.2.1：
Business Cycle Time / 14.2.2：
Time To Respond / 14.2.3：
Time to Commitment / 14.2.4：
Performance Cycle Time / 14.2.5：
Human Resources and Adaptive Management Organization / 14.3：
Groupware / 14.4：
Enterprise Applications / 14.4.2：
Business Processes as Assets / 14.4.3：
Design for Adaptability / 14.5：
Traditional Design Approach to Adaptability / 15.1：
The Holistic Design Approach / 15.2：
Process Design Concepts / 15.2.1：
Design of New Process Structure / 15.2.2：
Redesign of Existing Process Structure / 15.2.3：
Design for Robust Commitments / 15.3：
Design for Process Adaptability / 16.1：
Backbone Network of Commitments / 16.1.1：
Workflow Reconfiguration / 16.1.2：
Design for Accountability / 16.2：
Culture of Accountability / 16.3：
Continuous Improvement and Planning / 16.4：
Process Improvement / 16.4.1：
Launching the Process / 16.4.2：
Process Implementation Planning / 17.1：
Integrated Implementation Planning / 17.1.1：
The Three Steps of Implementation Planning / 17.1.2：
Planning for Implementation Problems / 17.2：
Company-Wide Constraints / 17.2.1：
Process-Level Impediments / 17.2.2：
Cultural Resistance / 17.2.3：
Technology Constraints / 17.2.4：
Planning for Action / 17.3：
Process Deployment / 17.4：
The Process-Centered Organization in Operation / 17.5：
The Business Process Level / 18.1：
Process Ownership / 18.1.1：
Accountability Framework / 18.1.2：
Process Stakeholders / 18.1.3：
Continuous Process Assessment / 18.1.4：
The Enterprise Level / 18.2：
Operational Responsibilities / 18.2.1：
The Millennium Enterprise / 18.2.2：
Appendixes / 18.3：
The Tools of Process Centering / Appendix 1.：
Stand-Alone Software Tools / A1.1：
Process Modeling Tools / A1.1.1：
Process Documentation Tools / A1.1.2：
Process Simulation Tools / A1.1.3：
Process Mapping-Related Activity-Based Costing Tools / A1.1.4：
Project Management Tools / A1.1.5：
Groupware/Software Tools for Team Effectiveness / A1.1.6：
ERP-Based Software Tools / A1.2：
SAP / A1.2.1：
Oracle / A1.2.2：
Abbreviations and Acronyms / Appendix 2.：
Glossary
Endnotes
Bibliography
Index
The Case for Process Centering / Part I：
Doing Business in the Face of Change / Chapter 1.：
The Changing Business Environment / 1.1：
25.

図書
図書
25. 日米両国におけるドキュメント・デリバリー・サービスの改善に関するプロジェクト (1999年度報告 ; 2000年度報告 ; 2001年度報告)
学術情報センター [編]
出版情報: 東京 : 学術情報センター, 2000.3-  冊 ; 26cm
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26.

図書
図書
26. Introduction to data compression. 2nd ed
Khalid Sayood
出版情報: San Francisco, Calif. : Morgan Kaufmann, c2000  xx, 636 p.
シリーズ名: The Morgan Kaufmann series in multimedia information and systems
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Introduction / 1：
Mathematical Preliminaries for Lossless Compression / 2：
Huffman Coding / 3：
Arithmetic Coding / 4：
Dictionary Techniques / 5：
Predictive Coding / 6：
Mathematical Preliminaries for Lossy Coding / 7：
Scalar Quantization / 8：
Vector Quantization / 9：
Differential Encoding / 10：
Mathematical Preliminaries for Transforms, Subbands, and Wavelets / 11：
Transform Coding / 12：
Subband Coding / 13：
Wavelets / 14：
Analysis/Synthesis Schemes / 15：
Video Compression / 16：
Probability and Random Processes / A：
A Brief Review of Matrix / B：
Concepts
Introduction / 1：
Mathematical Preliminaries for Lossless Compression / 2：
Huffman Coding / 3：
27.

図書
図書
27. 学術用語集 : 地震学編. 増訂版
文部省 [編]
出版情報: 東京 : 日本学術振興会 , 東京 : 丸善(発売), 2000.3  310p ; 19cm
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28.

図書
図書
28. A practical handbook of speech coders
Randy Goldberg, Lance Riek
出版情報: Boca Raton : CRC Press, c2000  xx, 231 p. ; 24 cm
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29.

図書
図書
29. S programming
W.N. Venables, B.D. Ripley
出版情報: New York : Springer, c2000  x, 264 p. ; 24 cm
シリーズ名: Statistics and computing
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30.

図書
図書
30. Bioenvironmental and public health statistics
edited by P.K. Sen, C.R. Rao
出版情報: Amsterdam ; Tokyo : Elsevier, 2000  xxiv, 1105 p. ; 25 cm
シリーズ名: Handbook of statistics ; v. 18
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31.

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図書
31. Modelling and control of robot manipulators. 2nd ed (: pbk)
L. Sciavicco and B. Siciliano
出版情報: Lodon ; Tokyo : Springer, c2000  xxiii, 377 p. ; 24 cm
シリーズ名: Advanced textbooks in control and signal processing
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32.

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図書
32. Computational probability
edited by Winfried K. Grassmann
出版情報: Boston : Kluwer Academic, c2000  viii, 490 p. ; 25 cm
シリーズ名: International series in operations research & management science
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目次情報: 続きを見る
Preface
Computational Probability: Challenges and Limitations / W.K. Grassmann.1：
Tools for Formulating Markov Models / G. Ciardo2：
Transient Solutions for Markov Chains / E. de Souza e Silva ; H.R. Gail.3：
Numerical Methods for Computing Stationary Distributions of Finite Irreducible Markov Chains / W.J. Stewart.4：
Stochastic Automata Networks / B. Plateau ; W.J. Steward5：
Matrix Analytic Methods / W.K. Grassmann ; D.A. Stanford6：
Use of Characteristic Roots for Solving Infinite State Markov Chains / H.R. Gail, et al.7：
An Introduction to Numerical Transform Inversion and Its Application to Probability Models / J. Abate, et al.8：
Optimal Control of Markov Chains / S. Stidham, Jr.9：
On Numerical Computations of Some Discrete-Time Queues / M.L. Chaudhry.10：
The Product Form Tool for Queueing Networks / N.M. van Dijk11：
Techniques for System Dependability Evaluation / J.K. Muppala, et al.12：
Index
Preface
Computational Probability: Challenges and Limitations / W.K. Grassmann.1：
Tools for Formulating Markov Models / G. Ciardo2：
33.

図書
図書
33. Materials science and engineering : an introduction. 5th ed
William D. Callister, Jr
出版情報: New York : Wiley, c2000  xxi, 871 p. ; 26 cm
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List of Symbols
Introduction
Atomic Structure and Interatomic Bonding
The Structure of Crystalline Solids
Imperfections in Solids
Diffusion
Mechanical Properties of Metals
Dislocations and Strengthening Mechanisms
Failure
Phase Diagrams
Phase Transformations in Metals: Development of Microstructure and Alteration of Mechanical Properties
Thermal Processing of Metal Alloys
Metals Alloys
Structures and Properties of Ceramics
Applications and Processing of Ceramics
Polymer Structures
Characteristics, Applications, and Processing of Polymers
Composites
Corrosion and Degradation of Materials
Electrical Properties
Thermal Properties
Magnetic Properties
Optical Properties
Materials Selection and Design Considerations
Economic, Environmental, and Societal Issues in Materials Science and Engineering
The International System of Units (SI / Appendix A：
Properties of Selected Engineering Materials / Appendix B：
Costs and Relative Costs for Selected Engineering Materials / Appendix C：
Mer Structures for Common Polymers / Appendix D：
Glass Transition and Melting Temperatues for Common Polymeric Materials / Appendix E：
Glossary
Answers to Selected Problems
Index
List of Symbols
Introduction
Atomic Structure and Interatomic Bonding
34.

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図書
34. Chemistry : the central science. 8th ed
Theodore L. Brown, H. Eugene LeMay,Jr., Bruce E. Bursten ; with contributions by Julia R. Burdge
出版情報: Upper Saddle River, N.J. : Prentice Hall International, c2000  1 v. (various pagings) ; 26 cm
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35.

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図書
35. Robust speech recognition in embedded systems and PC applications
by Jean-Claude Junqua
出版情報: Boston : Kluwer Academic Pub., c2000  xxi, 177 p. ; ill. : 25 cm
シリーズ名: The Kluwer international series in engineering and computer science ; SECS 563
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36.

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図書
36. Lexicon development for speech and language processing
edited by Frank Van Eynde, and Dafydd Gibbon
出版情報: Dordrecht ; Boston : Kluwer, c2000  xi, 298 p. ; 25 cm
シリーズ名: Text, speech, and language technology ; v. 12
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図書
37. 学術情報の高度化および次世代情報ネットワークの構築に関する研究 : 次世代学術情報環境を支えるオープンプラットフォーム
小野欽司研究代表 ; 相澤彰子 [ほか] 編
出版情報: 東京 : 学術情報センター, 2000.3  227p ; 30cm
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38.

図書
図書
38. Surveys on solution methods for inverse problems
David Colton ... [et al] (eds.)
出版情報: Wien ; New York : Springer, c2000  275 p. ; 25 cm
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39.

図書
図書
39. Advanced digital signal processing and noise reduction. 2nd ed
Saeed V. Vaseghi
出版情報: Chichester : John Wiley & Sons, c2000  xxiii, 473 p. ; 25 cm
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Preface
Symbols
Abbreviations
Introduction / 1：
Signals and Information / 1.1：
Signal Processing Methods / 1.2：
Transform-based Signal Processing / 1.2.1：
Model-based Signal Processing / 1.2.2：
Bayesian Signal Processing / 1.2.3：
Neural Networks / 1.2.4：
Applications of Digital Signal Processing / 1.3：
Adaptive Noise Cancellation / 1.3.1：
Adaptive Noise Reduction / 1.3.2：
Blind Channel Equalisation / 1.3.3：
Signal Classification and Pattern Recognition / 1.3.4：
Linear Prediction Modelling of Speech / 1.3.5：
Digital Coding of Audio Signals / 1.3.6：
Detection of Signals in Noise / 1.3.7：
Directional Reception of Waves: Beam-forming / 1.3.8：
Dolby Noise Reduction / 1.3.9：
Radar Signal Processing: Doppler Frequency Shift / 1.3.10：
Sampling and Analogue-to-digital Conversion / 1.4：
Sampling and Reconstruction of Analogue Signals / 1.4.1：
Quantisation / 1.4.2：
Bibliography
Noise and Distortion / 2：
White Noise / 2.1：
Band-limited White Noise / 2.2.1：
Coloured Noise / 2.3：
Impulsive Noise / 2.4：
Transient Noise Pulses / 2.5：
Thermal Noise / 2.6：
Shot Noise / 2.7：
Electromagnetic Noise / 2.8：
Channel Distortions / 2.9：
Echo and Multipath Reflections / 2.10：
Modelling Noise / 2.11：
Additive White Gaussian Noise Model / 2.11.1：
Hidden Markov Model for Noise / 2.11.2：
Probability and Information Models / 3：
Random Signals / 3.1：
Random and Stochastic Processes / 3.2.1：
The Space of a Random Process / 3.2.2：
Probability Models / 3.3：
Probability and Random Variables / 3.3.1：
Probability Mass Function / 3.3.2：
Probability Density Function / 3.3.3：
Probability Dgnsity Functions of Random Processes / 3.3.4：
Information Models / 3.4：
Entropy / 3.4.1：
Mutual Information / 3.4.2：
Entropy Coding / 3.4.3：
Stationary and Nonstationary Random Processes / 3.5：
Strict-sense Stationary Processes / 3.5.1：
Wide-sense Stationary Processes / 3.5.2：
Nonstationary Processes / 3.5.3：
Statistics (Expected Values) of a Random Process / 3.6：
The Mean Value / 3.6.1：
Autocorrelation / 3.6.2：
Autocovariance / 3.6.3：
Power Spectral Density / 3.6.4：
Joint Statistical Averages of Two Random Processes / 3.6.5：
Cross-correlation and Cross-covariance / 3.6.6：
Cross-power Spectral Density and Coherence / 3.6.7：
Ergodic Processes and Time-averaged Statistics / 3.6.8：
Mean-ergodic Processes / 3.6.9：
Correlation-ergodic Processes / 3.6.10：
Some Useful Classes of Random Processes / 3.7：
Gaussian (Normal) Process / 3.7.1：
Multivariate Gaussian Process / 3.7.2：
Mixture Gaussian Process / 3.7:3：
A Binary-state Gaussian Process / 3.7.4：
Poisson Process / 3.7.5：
Poisson-Gaussian Model for Clutters and Impulsive Noise / 3.7.6：
Markov Processes / 3.7.8：
Markov Chain Processes / 3.7.9：
Gamma Probability Distribution / 3.7.10：
Rayleigh Probability Distribution / 3.7.11：
Laplacian Probability Distribution / 3.7.12：
Transformation of a Random Process / 3.8：
Monotonic Transformation of Random Processes / 3.8.1：
Many-to-one Mapping of Random Signals / 3.8.2：
Summary / 3.9：
Bayesian Inference / 4：
Bayesian Estimation Theory: Basic Definitions / 4.1：
Dynamic and Probability Models in Estimation / 4.1.1：
Parameter Space and Signal Space / 4.1.2：
Parameter Estimation and Signal Restoration / 4.1.3：
Performance Measures and Desirable Properties of Estimators / 4.1.4：
Prior and Posterior Spaces and Distributions / 4.1.5：
Bayesian Estimation / 4.2：
Maximum a Posteriori Estimation / 4.2.1：
Maximum-likelihood Estimation / 4.2.2：
Minimum Mean Square Error Estimation / 4.2.3：
Minimum Mean Absolute Value of Error Estimation / 4.2.4：
Equivalence of the MAP, ML, MMSE and MAVE for Gaussian Processes with Uniform Distributed Parameters / 4.2.5：
The Influence of the Prior on Estimation Bias and Variance / 4.2.6：
The Relative Importance of the Prior and the Observation / 4.2.7：
The Estimate-Maximise Method / 4.3：
Convergence of the EM Algorithm / 4.3.1：
Cramer-Rao Bound on the Minimum Estimator Variance / 4.4：
Cramer-Rao Bound for Random Parameters / 4.4.1：
Cramer-Rao Bound for a Vector Parameter / 4.4.2：
Design of Gaussian Mixture Models / 4.5：
EM Estimation of Gaussian Mixture Model / 4.5.1：
Bayesian Classification / 4.6：
Binary Classification / 4.6.1：
Classification Error / 4.6.2：
Bayesian Classification of Discrete-valued Parameters / 4.6.3：
Maximum a Posteriori Classification / 4.6.4：
Maximum-likelihood Classification / 4.6.5：
Minimum Mean Square Error Classification / 4.6.6：
Bayesian Classification of Finite State Processes / 4.6.7：
Bayesian Estimation of the Most Likely State Sequence / 4.6.8：
Modelling the Space of a Random Process / 4.7：
Vector Quantisation of a Random Process / 4.7.1：
Vector Quantisation using Gaussian Models / 4.7.2：
Design of a Vector Quantiser: K-means Clustering / 4.7.3：
Hidden Markov Models / 4.8：
Statistical Models for Nonstationary Processes / 5.1：
Comparison of Markov and Hidden Markov Models / 5.2：
A Physical Interpretation: HMMs of Speech / 5.2.2：
Hidden Markov Model as a Bayesian Model / 5.2.3：
Parameters of a Hidden Markov Model / 5.2.4：
State Observation Probability Models / 5.2.5：
State Transition Probabilities / 5.2.6：
State-Time Trellis Diagram / 5.2.7：
Training Hidden Markov Models / 5.3：
Forward-Backward Probability Computation / 5.3.1：
Baum-Welch Model Re-estimation / 5.3.2：
Training HMMs with Discrete Density Observation Models / 5.3.3：
HMMs with Continuous Density Observation Models / 5.3.4：
HMMs with Gaussian Mixture pdfs / 5.3.5：
Decoding of Signals using Hidden Markov Models / 5.4：
Viterbi Decoding Algorithm / 5.4.1：
HMMs in DNA and Protein Sequence Modelling / 5.5：
HMMs for Modelling Speech and Noise / 5.6：
Modelling Speech with HMMs / 5.6.1：
HMM-based Estimation of Signals in Noise / 5.6.2：
Signal and Noise Model Combination and Decomposition / 5.6.3：
Hidden Markov Model Combination / 5.6.4：
Decomposition of State Sequences of Signal and Noise / 5.6.5：
HMM-based Wiener Filters / 5.6.6：
Modelling Noise Characteristics / 5.6.7：
Least Square Error Filters / 5.7：
Least Square Error Estimation: Wiener Filters / 6.1：
Block-data Formulation of the Wiener Filter / 6.2：
QR Decomposition of the Least Square Error Equation / 6.2.1：
Interpretation of Wiener Filters as Projections in Vector Space / 6.3：
Analysis of the Least Mean Square Error Signal / 6.4：
Formulation of Wiener Filters in the Frequency Domain / 6.5：
Some Applications of Wiener Filters / 6.6：
Wiener Filters for Additive Noise Reduction / 6.6.1：
Wiener Filters and Separability of Signal and Noise / 6.6.2：
The Square-root Wiener Filter / 6.6.3：
Wiener Channel Equaliser / 6.6.4：
Time-alignment of Signals in Multichannel/Multisensor Systems / 6.6.5：
Implementation of Wiener Filters / 6.7：
The Choice of Wiener Filter Order / 6.7.1：
Improvements to Wiener Filters / 6.7.2：
Adaptive Filters / 6.8：
State-space Kalman Filters / 7.1：
Derivation of the Kalman Filter Algorithm / 7.2.1：
Sample-adaptive Filters / 7.3：
Recursive Least Square Adaptive Filters / 7.4：
The Matrix Inversion Lemma / 7.4.1：
Recursive Time-update of Filter Coefficients / 7.4.2：
The Steepest-descent Method / 7.5：
Convergence Rate / 7.5.1：
Vector-valued Adaptation Step Size / 7.5.2：
The LMS Filter / 7.6：
Leaky LMS Algorithm / 7.6.1：
Normalised LMS Algorithm / 7.6.2：
Linear Prediction Models / 7.7：
Linear Prediction Coding / 8.1：
Frequency Response of LP Models / 8.1.1：
Calculation of Predictor Coefficients / 8.1.2：
Effect of Estimation of Correlation Function on LP Model Solution / 8.1.3：
The Inverse Filter: Spectral Whitening / 8.1.4：
The Prediction Error Signal / 8.1.5：
Forward, Backward and Lattice Predictors / 8.2：
Augmented Equations for Forward and Backward Predictors / 8.2.1：
Levinson-Durbin Recursive Solution / 8.2.2：
Lattice Predictors / 8.2.3：
Alternative Formulations of Least Square Error Prediction / 8.2.4：
Predictor Model Order Selection / 8.2.5：
Short- and Long-term Predictors / 8.3：
MAP Estimation of Predictor Coefficients / 8.4：
Probability Density Function of Predictor Output / 8.4.1：
Using the Prior pdf of the Predictor Coefficients / 8.4.2：
Formant-tracking LP Models / 8.5：
Sub-band Linear Prediction Model / 8.6：
Signal Restoration using Linear Prediction Models / 8.7：
Frequency-domain Signal Restoration using Prediction Models / 8.7.1：
Implementation of Sub-band Linear Prediction Wiener Filters / 8.7.2：
Power Spectrum and Correlation / 8.8：
Fourier Series: Representation of Periodic Signals / 9.1：
Fourier Transform: Representation of Aperiodic Signals / 9.3：
Discrete Fourier Transform / 9.3.1：
Time/Frequency Resolutions, the Uncertainty Principle / 9.3.2：
Energy-spectral Density and Power-spectral Density / 9.3.3：
Nonparametric Power Spectrum Estimation / 9.4：
The Mean and Variance of Periodograms / 9.4.1：
Averaging Periodograms (Bartlett Method) / 9.4.2：
Welch Method: Averaging Periodograms from Overlapped and Windowed Segments / 9.4.3：
Blackman-Tukey Method / 9.4.4：
Power Spectrum Estimation from Autocorrelation of Overlapped Segments / 9.4.5：
Model-based Power Spectrum Estimation / 9.5：
Maximum-entropy Spectral Estimation / 9.5.1：
Autoregressive Power Spectrum Estimation / 9.5.2：
Moving-average Power Spectrum Estimation / 9.5.3：
Autoregressive Moving-average Power Spectrum Estimation / 9.5.4：
High-resolution Spectral Estimation Based on Subspace Eigenanalysis / 9.6：
Pisarenko Harmonic Decomposition / 9.6.1：
Multiple Signal Classification Spectral Estimation / 9.6.2：
Estimation of Signal Parameters via Rotational Invariance Techniques / 9.6.3：
Interpolation / 9.7：
Interpolation of a Sampled Signal / 10.1：
Digital Interpolation by a Factor of I / 10.1.2：
Interpolation of a Sequence of Lost Samples / 10.1.3：
The Factors that affect Interpolation Accuracy / 10.1.4：
Polynomial Interpolation / 10.2：
Lagrange Polynomial Interpolation / 10.2.1：
Newton Polynomial Interpolation / 10.2.2：
Hermite Polynomial Interpolation / 10.2.3：
Cubic Spline Interpolation / 10.2.4：
Model-based Interpolation / 10.3：
Maximum a Posteriori Interpolation / 10.3.1：
Least Square Error Autoregressive Interpolation / 10.3.2：
Interpolation based on a Short-term Prediction Model / 10.3.3：
Interpolation based on Long- and Short-term Correlations / 10.3.4：
LSAR Interpolation Error / 10.3.5：
Interpolation in Frequency-Time Domain / 10.3.6：
Interpolation using Adaptive Codebooks / 10.3.7：
Interpolation through Signal Substitution / 10.3.8：
Spectral Amplitude Estimation / 10.4：
Spectral Representation of Noisy Signals / 11.1：
Vector Representation of the Spectrum of Noisy Signals / 11.1.2：
Spectral Subtraction / 11.2：
Power Spectrum Subtraction / 11.2.1：
Magnitude Spectrum Subtraction / 11.2.2：
Spectral Subtraction Filter: Relation to Wiener Filters / 11.2.3：
Processing Distortions / 11.2.4：
Effect of Spectral Subtraction on Signal Distribution / 11.2.5：
Reducing the Noise Variance / 11.2.6：
Filtering Out the Processing Distortions / 11.2.7：
Nonlinear Spectra] Subtraction / 11.2.8：
Implementation of Spectral Subtraction / 11.2.9：
Bayesian MMSE Spectral Amplitude Estimation / 11.3：
Application to Speech Restoration and Recognition / 11.4：
Autocorrelation and Power Spectrum of Impulsive Noise / 11.5：
Statistical Models for Impulsive Noise / 12.2：
Bernoulli-Gaussian Model of Impulsive Noise / 12.2.1：
Poisson-Gaussian Model of Impulsive Noise / 12.2.2：
A Binary-state Model of Impulsive Noise / 12.2.3：
Signal-to-impulsive-noise Ratio / 12.2.4：
Median Filters / 12.3：
Impulsive Noise Removal using Linear Prediction Models / 12.4：
Impulsive Noise Detection / 12.4.1：
Analysis of Improvement in Noise Detectability / 12.4.2：
Two-sided Predictor for Impulsive Noise Detection / 12.4.3：
Interpolation of Discarded Samples / 12.4.4：
Robust Parameter Estimation / 12.5：
Restoration of Archived Gramophone Records / 12.6：
Transient Noise Waveforms / 12.7：
Transient Noise Pulse Models / 13.2：
Noise Pulse Templates / 13.2.1：
Autoregressive Model of Transient Noise Pulses / 13.2.2：
Hidden Markov Model of a Noise Pulse Process / 13.2.3：
Detection of Noise Pulses / 13.3：
Matched Filter for Noise Pulse Detection / 13.3.1：
Noise Detection based on Inverse Filtering / 13.3.2：
Noise Detection based on HMM / 13.3.3：
Removal of Noise Pulse Distortions / 13.4：
Adaptive Subtraction of Noise Pulses / 13.4.1：
AR-based Restoration of Signals Distorted by Noise Pulses / 13.4.2：
Echo Cancellation / 13.5：
Introduction: Acoustic and Hybrid Echoes / 14.1：
Telephone Line Hybrid Echo / 14.2：
Echo: the Sources of Delay in Telephone Networks / 14.2.1：
Echo Return Loss / 14.2.2：
Hybrid Echo Suppression / 14.3：
Adaptive Echo Cancellation / 14.4：
Echo Canceller Adaptation Methods / 14.4.1：
Convergence of Line Echo Canceller / 14.4.2：
Echo Cancellation for Digital Data Transmission / 14.4.3：
Acoustic Echo / 14.5：
Sub-band Acoustic Echo Cancellation / 14.6：
Multiple-input Multiple-output Echo Cancellation / 14.7：
Stereophonic Echo Cancellation Systems / 14.7.1：
Channel Equalisation and Blind Deconvolution / 14.8：
The Ideal Inverse Channel Filter / 15.1：
Equalisation Error, Convolutional Noise / 15.1.2：
Blind Equalisation / 15.1.3：
Minimum- and Maximum-phase Channels / 15.1.4：
Wiener Equaliser / 15.1.5：
Blind Equalisation using the Channel Input Power Spectrum / 15.2：
Homomorphic Equalisation / 15.2.1：
Homomorphic Equalisation using a Bank of High-pass Filters / 15.2.2：
Equalisation based on Linear Prediction Models / 15.3：
Blind Equalisation through Model Factorisation / 15.3.1：
Bayesian Blind Deconvolution and Equalisation / 15.4：
Conditional Mean Channel Estimation / 15.4.1：
Maximum-likelihood Channel Estimation / 15.4.2：
Maximum a Posteriori Channel Estimation / 15.4.3：
Channel Equalisation based on Hidden Markov Models / 15.4.4：
MAP Channel Estimate based on HMMs / 15.4.5：
Implementations of HMM-based Deconvolution / 15.4.6：
Blind Equalisation for Digital Communications Channels / 15.5：
LMS Blind Equalisation / 15.5.1：
Equalisation of a Binary Digital Channel / 15.5.2：
Equalisation based on Higher-order Statistics / 15.6：
Higher-order Moments, Cumulants and Spectra / 15.6.1：
Higher-order Spectra of Linear Time-invariant Systems / 15.6.2：
Blind Equalisation based on Higher-order Cepstra / 15.6.3：
Speech Enhancement in Noise / 15.7：
Single-input Speech-enhancement Methods / 16.1：
An Overview of a Speech-enhancement System / 16.2.1：
Wiener Filter for De-noising Speech / 16.2.2：
Spectra] Subtraction of Noise / 16.2.3：
Bayesian MMSE Speech Enhancement / 16.2.4：
Kalman Filter / 16.2.5：
Speech Enhancement via LP Model Reconstruction / 16.2.6：
Multiple-input Speech-enhancement Methods / 16.3：
Beam-forming with Microphone Arrays / 16.3.1：
Speech Distortion Measurements / 16.4：
Noise in Wireless Communications / 17：
Introduction to Cellular Communications / 17.1：
Noise, Capacity and Spectral Efficiency / 17.2：
Communications Signal Processing in Mobile Systems / 17.3：
Noise and Distortion in Mobile Communications Systems / 17.4：
Multipath Propagation of Electromagnetic Signals / 17.4.1：
Rake Receivers for Multipath Signals / 17.4.2：
Signal Fading in Mobile Communications Systems / 17.4.3：
Large-scale Signal Fading / 17.4.4：
Small-scale Fast Signal Fading / 17.4.5：
Smart Antennas / 17.5：
Switched and Adaptive Smart Antennas / 17.5.1：
Space-Time Signal Processing - Diversity Schemes / 17.5.2：
Index / 17.6：
Preface
Symbols
Abbreviations
40.

図書
図書
40. Computer networks and systems : queueing theory and performance evaluation. 3rd ed
Thomas G. Robertazzi
出版情報: New York ; Tokyo : Springer-Verlag, c2000  xiii, 409 p. ; 25 cm
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Preface
The Queueing Paradigm / 1：
Single Queueing Systems / 2：
Networks of Queues / 3：
Numerical Solution of Models / 4：
Stochastic Petri Nets / 5：
Discrete Time Queueing Systems / 6：
Network Traffic Modeling Appendix: Probability Theory Review / 7：
References
Index
Preface
The Queueing Paradigm / 1：
Single Queueing Systems / 2：
41.

図書
図書
41. An introduction to superprocesses
Alison M. Etheridge
出版情報: Providence, R.I. : American Mathematical Society, c2000  xii, 187 p. ; 26 cm
シリーズ名: University lecture series ; v. 20
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42.

図書
図書
42. Advances in robot kinematics
edited by J. Lenarčič and M.M. Stanišić
出版情報: Dordrecht : Kluwer Academic, c2000  442 p. ; 25 cm
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Methods in Kinematics / 1.：
Study's kinematic mapping--A tool for motion design / A. Gfrerrer
Kinestatic analysis of serial and parallel robot manipulators using Grassmann-Cayley algebra / E. Staffetti ; F. Thomas
Unit quaternion and CRV: Complementary non-singular representations of rigid-body orientation / V. Milenkovic ; P.H. Milenkovic
Numerically stable methods for converting rotation matrices to Euler parameters / I.D. Coope ; A.B. Lintott ; G.R. Dunlop ; M.I. Vuskovic
Geometry of homokinematic spatial Cardan shafts by dual methods / M. Keler
A concise Bezier clipping technique for solving inverse kinematics problems / C. Bombin ; L. Ros
Geometric calibration of robots using multiple plane constraints / S. Besnard ; W. Khalil ; G. Garcia
Kinematic Synthesis / 2.：
On isotropic sets of points in the plane. Application to the design of robot architectures / J. Angeles ; D. Chablat
Fourier methods for synthesis of coupled serial chain mechanisms / Y. Pang ; V. Krovi
Dimensional synthesis of spatial RR robots / A. Perez ; J. M. McCarthy
Approximate motion synthesis via parametric constraint manifold fitting / P. Larochelle
Designing linkages with symmetric motions: The spherical case / J.M. Rico ; B. Ravani
Kinematic synthesis of planar platforms with RPR, PRR, and RRR chains / A. Murray ; M. Hanchak
Force Analysis / 3.：
Impact analysis as a design tool for the legs of mobile robots / J.P. Schmiedeler ; K.J. Waldron
Vehicle wheel-ground contact angle estimation: with application to mobile robot traction control / K. Iagnemma ; S. Dubowsky
The Melbourne hand / S.R. Lucas ; C.R. Tischler ; A.E. Samuel
Active force closure for multiple objects / K. Harada ; M. Kaneko ; T. Tsuji
SCALPP: A 6-dof robot with a non-spherical wrist for surgical applications / G. Duchemin ; E. Dombre ; F. Pierrot ; E. Degoulange
A framework for multi-contact multi-body dynamic simulation and haptic display / D. Ruspini ; O. Khatib
On the dynamics of a class of parallel robots / F. Caccavale ; G. Ruggiero ; B. Siciliano ; L. Villani
Kinematic Redundancy / 4.：
A simplified criterion for the repeatability of redundant manipulators / R. Schaufler ; C.H. Fedrowitz ; R. Kammuller
An intuitive interface for nullspace teaching of redundant robots / G. Schreiber ; G. Hirzinger
Methods for resolving velocity degeneracies of joint-redundant manipulators / S.B. Nokleby ; R.P. Podhorodeski
Novel kinematics for continuum robots / M.W. Hannan ; I.D. Walker
The optimum quality index for a spatial redundant 4-8 in-parallel manipulator / Y. Zhang ; J. Duffy ; C. Crane
Fuzzy inverse kinematics for underwater vehicle-manipulator systems / G. Antonelli ; S. Chiaverini
Parallel Mechanisms and Workspace Analysis / 5.：
Symmetries in workspace densities of discretely actuated manipulators / G.S. Chirikjian
Workspace characterization of planar three-legged platforms with holonomic higher pairs / M.J.D. Hayes ; M.L. Husty
Estimating the controllable workspace of tendon-based Stewart platforms / R. Verhoeven ; M. Hiller
The chord method for the determination of non-convex workspaces of planar parallel platforms / J.A. Snyman ; A.M. Hay
Elasto-kinematic design tools for parallel mechanisms / J. Kim ; F.C. Park
Kinematic analysis of a new parallel machine tool: the orthoglide / P. Wenger
Optimal trajectory planning of a 5-axis machine-tool based on a 6-axis parallel manipulator / J-P. Merlet ; M-W. Perng ; D. Daney
Analysis and Application of Parallel Mechanisms / 6.：
A 4-dof parallel mechanism simulating the movement of the human sternum-clavicle-scapula complex / J. Lenarcic ; M.M. Stanisic ; V. Parenti-Castelli
Parallel mechanisms applied to the human knee passive motion simulation / R. Di Gregorio
A geometric model for cylinder-cylinder impact with application to vertebrae motion simulation / A. Kecskemethy ; C. Lange ; G. Grabner
Architecture singular parallel manipulators and their self-motions / M. Husty ; A. Karger
Architectural shakiness or architectural mobility of platforms / K. Wohlhart
Mobius mechanisms / O. Roschel
Parallel Mechanisms and Screw Algebra / 7.：
Direct kinematics of the double-triangular manipulator: An exercise in geometric thinking / J.C.F. Shum ; P.J. Zsombor-Murray
A three-dof tripod for generating spherical rotation / M. Karouia ; J.M. Herve
Kinematical analysis and simulation of a new parallel mechanism for robotics' application / G. Olea ; N. Plitea ; K. Takamasu
Early studies in screw theory / M. Ceccarelli
On deriving infinitesimal twists and velocity screws from finite displacement screws / I.A. Parkin
Synthesis by screw algebra of translating in-parallel actuated mechanisms / A. Frisoli ; D. Checcacci ; F. Salsedo ; M. Bergamasco
Author Index
Methods in Kinematics / 1.：
Study's kinematic mapping--A tool for motion design / A. Gfrerrer
Kinestatic analysis of serial and parallel robot manipulators using Grassmann-Cayley algebra / E. Staffetti ; F. Thomas
43.

雑誌
雑誌
43. Progress in informatics : PI
National Institute of Informatics
出版情報: Tokyo : Research Organization of Information and Systems, National Institute of Informatics, 2005-2014  11 v. ; 30 cm
巻次年月次: No. 1 (Mar. 2005)-no. 11 (Mar. 2014)
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44.

雑誌
雑誌
44. Petersen : a magazine about brickwork and responsible architecture
出版情報: Broager : Petersen Tegl Egernsund A/S  v. ; 42 cm
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45.

雑誌
雑誌
45. Annals of library science and documentation
Indian National Scientific Documentation Centre
出版情報: New Delhi : Indian National Scientific Documentation Centre, -2000.12
巻次年月次: (1964)-Vol. 47, no. 4 (2000.12)
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46.

雑誌
雑誌
46. NII journal
National Institute of Informatics = 国立情報学研究所 [編]
出版情報: 東京 : 国立情報学研究所紀要編集委員会, 2000.12-2004.2  8冊 ; 30cm
巻次年月次: No. 1 (Dec. 2000)-no. 8 (Feb. 2004)
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47.

雑誌
雑誌
47. International journal on e-learning : corporate, government, healthcare, & higher education
Association for the Advancement of Computing in Education
出版情報: Norfolk, Va. : Association for the Advancement of Computing in Education, c2002-  v. ; 23-28 cm
巻次年月次: Vol. 1, no. 1 (Jan./Mar. 2002)-
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48.

学位論文
学位
48. Fiber structure development in high-speed melt spinning of aromatic polyesters containing naphthalene dicarboxylate
Ken Miyata
出版情報: 東京 : 東京工業大学, 2000
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49.

学位論文
学位
49. Study for the J/Ψ polarization in B→J/ΨX with the BELLE detector
Shunsuke Ichizawa
出版情報: 東京 : 東京工業大学, 2000
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50.

学位論文
学位
50. Molecular and cellular biological studies on two nucleotide biosynthesis genes and their expression products of the basidiomycete lentinus edodes
Shinya Kaneko
出版情報: 東京 : 東京工業大学, 2000
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