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1.

電子ブック

EB
edited by Zoltan Szallasi, Jörg Stelling, Vipul Periwal
出版情報: Cambridge, Mass. ; London : MIT Press, c2006  1 online resource (xiv, 448 p.)
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Preface
General Concepts / I:
The Role of Modeling in Systems Biology / Douglas B. Kell ; Joshua D. Knowles1:
Complexity and Robustness of Cellular Systems / Jorg Stelling ; Uwe Sauer ; Francis J. Doyle III ; John Doyle2:
On Modules and Modularity / Zoltan Szallasi ; Vipul Periwal3:
Modeling Approaches / II:
Bayesian Inference of Biological Systems: The Logic of Biology / 4:
Stoichiometric and Constraint-based Modeling / Steffen Klamt5:
Modeling Molecular Interaction Networks with Nonlinear Ordinary Differential Equations / Emery D. Conrad ; John J. Tyson6:
Qualitative Approaches to the Analysis of Genetic Regulatory Networks / Hidde de Jong ; Delphine Ropers7:
Stochastic Modeling of Intracellular Kinetics / Johan Paulsson ; Johan Elf8:
Kinetics in Spatially Extended Systems / Karsten Kruse9:
Models And Reality / III:
Biological Data Acquisition for System Level Modeling-An Exercise in the Art of Compromise / 10:
Methods to Identify Cellular Architecture and Dynamics from Experimental Data / Rudiyanto Gunawan ; Kapil G. Gadker11:
Using Control Theory to Study Biology / Brian P. Ingalls ; Tau-Mi Yi ; Pablo A. Iglesias12:
Synthetic Gene Regulatory Systems / Mads Kaern ; Ron Weiss13:
Multilevel Modeling in Systems Biology: From Cells to Whole Organs / Denis Noble14:
Computational Modeling / IV:
Computational Constraints on Modeling in Systems Biology / 15:
Numerical Simulation for Biochemical Kinetics / Daniel T. Gillespie ; Linda R. Petzold16:
Software Infrastructure for Effective Communication and Reuse of Computational Models / Andrew Finney ; Michael Hucka ; Benjamin J. Bornstein ; Sarah M. Keating ; Bruce E. Shapiro ; Joanne Matthews ; Ben L. Kovitz ; Maria J. Schilstra ; Akira Funahashi ; Hiroaki Kitano17:
A Software Tools for Biological Modeling
References
Contributors
Index
Preface
General Concepts / I:
The Role of Modeling in Systems Biology / Douglas B. Kell ; Joshua D. Knowles1:
2.

電子ブック

EB
edited by Susan Pockett, William P. Banks, and Shaun Gallagher
出版情報: Cambridge, Mass. ; London : MIT, c2006  1 online resource (vi, 364 p.)
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Introduction / Susan Pockett ; William P. Banks ; Shaun Gallagher
Neuroscience / I:
The Neuroscience of Movement / 1:
Consciousness of Action as an Embodied Consciousness / Marc Jeannerod2:
Intentions, Actions, and the Self / Suparna Choudhury ; Sarah-Jayne Blakemore3:
Free Choice and the Human Brain / Richard E. Passingham ; Hakwan C. Lau4:
Consciousness, Intentionality, and Causality / Walter J. Freeman5:
Philosophy / II:
Where's the Action? Epiphenomenalism and the Problem of Free Will / 6:
Empirical Constraints on the Problem of Free Will / Peter W. Ross7:
Toward a Dynamic Theory of Intentions / Elisabeth Pacherie8:
Phenomenology and the Feeling of Doing: Wegner on the Conscious Will / Timothy Bayne9:
Free Will: Theories, Analysis, and Data / Alfred R. Mele10:
Of Windmills and Straw Men: Folk Assumptions of Mind and Action / Bertram F. Malle11:
Law and Public Policy / III:
Does Consciousness Cause Misbehavior? / 12:
Free Will as a Social Institution / Wolfgang Prinz13:
Truth and/or Consequences: Neuroscience and Criminal Responsibility / Leonard V. Kaplan14:
Bypassing Conscious Control: Unconscious Imitation, Media Violence, and Freedom of Speech / Susan Hurley15:
Neurosciety Ahead? Debating Free Will in the Media / Sabine Maasen16:
List of Contributors
Index
Introduction / Susan Pockett ; William P. Banks ; Shaun Gallagher
Neuroscience / I:
The Neuroscience of Movement / 1:
3.

電子ブック

EB
[edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
出版情報: Cambridge, Mass. ; London : MIT, c2006  1 online resource (x, 508 p.)
シリーズ名: Adaptive computation and machine learning ;
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Series Foreword
Preface
Introduction to Semi-Supervised Learning / 1:
Supervised, Unsupervised, and Semi-Supervised Learning / 1.1:
When Can Semi-Supervised Learning Work? / 1.2:
Classes of Algorithms and Organization of This Book / 1.3:
Generative Models / I:
A Taxonomy for Semi-Supervised Learning Methods / Matthias W. Seeger2:
The Semi-Supervised Learning Problem / 2.1:
Paradigms for Semi-Supervised Learning / 2.2:
Examples / 2.3:
Conclusions / 2.4:
Semi-Supervised Text Classification Using EM / N. C. Nigam ; Andrew McCallum ; Tom Mitchell3:
Introduction / 3.1:
A Generative Model for Text / 3.2:
Experminental Results with Basic EM / 3.3:
Using a More Expressive Generative Model / 3.4:
Overcoming the Challenges of Local Maxima / 3.5:
Conclusions and Summary / 3.6:
Risks of Semi-Supervised Learning / Fabio Cozman ; Ira Cohen4:
Do Unlabled Data Improve or Degrade Classification Performance? / 4.1:
Understanding Unlabeled Data: Asymptotic Bias / 4.2:
The Asymptotic Analysis of Generative Smei-Supervised Learning / 4.3:
The Value of Labeled and Unlabeled Data / 4.4:
Finite Sample Effects / 4.5:
Model Search and Robustness / 4.6:
Conclusion / 4.7:
Probabilistic Semi-Supervised Cluster with Constraints / Sugato Basu ; Mikhail Bilenko ; Arindam Banerjee ; Raymond J. Mooney5:
HMRF Model for Semi-Supervised Clustering / 5.1:
HMRF-KMeans Algorithm / 5.3:
Active Learning for Constraint Acquistion / 5.4:
Experimental Results / 5.5:
Related Work / 5.6:
Low-Density Separation / 5.7:
Transductive Support Vector Machines / Thorsten Joachims6:
Why Use Margin on the Test Set? / 6.1:
Experiments and Applications of the TSVMs / 6.4:
Solving the TSVM Optimization Problem / 6.5:
Connection to Related Approaches / 6.6:
Summary and Conclusions / 6.7:
Semi-Supervised Learning Using Semi-Definite Programming / Tijl De Bie ; Nello Cristianini7:
Relaxing SVM transduction / 7.1:
An Approximation for Speedup / 7.2:
General Semi-Supervised Learning Settings / 7.3:
Empirical Results / 7.4:
Summary and Outlook / 7.5:
Appendix
The Extended Schur Complement Lemma
Gaussian Processes and the Null-Category Noise Model / Neil D. Lawrence ; Michael I. Jordan8:
The Noise Model / 8.1:
Process Model and the Effect of the Null-Category / 8.3:
Posterior Inference and Prediction / 8.4:
Results / 8.5:
Discussion / 8.6:
Entropy Regularization / Yves Grandvalet ; Yoshua Bengio9:
Derivation of the Criterion / 9.1:
Optimization Algorithms / 9.3:
Related Methods / 9.4:
Experiments / 9.5:
Proof of Theorem 9.1 / 9.6:
Data-Dependent Regularization / Adrian Corduneanu ; Tommi S. Jaakkola10:
Information Regularization on Metric Spaces / 10.1:
Information Regularization and Relational Data / 10.3:
Graph-Based Models / 10.4:
Label Propogation and Quadratic Criterion / Olivier Delalleau ; Nicolas Le Roux11:
Label Propogation on a Similarity Graph / 11.1:
Quadratic Cost Criterion / 11.3:
From Transduction to Induction / 11.4:
Incorporating Class Prior Knowledge / 11.5:
Curse of Dimensionality for Semi-Supervised Learning / 11.6:
The Geometric Basis of Semi-Supervised Learning / Vikas Sindhwani ; Misha Belkin ; Partha Niyogi11.7:
Incorporating Geometry in Regularization / 12.1:
Algorithms / 12.3:
Data-Dependent Kernels for Semi-Supervised Learning / 12.4:
Linear Methods for Large-Scale Semi-Supervised Learning / 12.5:
Connections to Other Algorithms and Related Work / 12.6:
Future Directions / 12.7:
Discrete Regularization / Dengyong Zhou ; Bernhard Scholkopf13:
Discrete Analysis / 13.1:
Semi-Supervised Learning with Conditional Harmonic Mixing / Christopher J. C. Burges ; John C. Platt13.3:
Conditional Harmonic Mixing / 14.1:
Learning in CHM Models / 14.3:
Incorporating Prior Knowledge / 14.4:
Learning the Conditionals / 14.5:
Model Averaging / 14.6:
Change of Representation / 14.7:
Graph Kernels by Spectral Transforms / Xiaojin Zhu ; Jaz Kandola ; John Lafferty ; Zoubin Ghahramani15:
The Graph Laplacian / 15.1:
Kernels by Spectral Transforms / 15.2:
Kernel Alignment / 15.3:
Optimizing Alignment Using QCQP for Semi-Supervised Learning / 15.4:
Semi-Supervised Kernels with Order Restraints / 15.5:
Spectral Methods for Dimensionality Reduction / Lawrence K. Saul ; Kilian Weinberger ; Fei Sha ; Jihun Ham15.6:
Linear Methods / 16.1:
Graph-Based Methods / 16.3:
Kernel Methods / 16.4:
Modifying Distances / Alon Orlitsky ; Sajama16.5:
Estimating DBD Metrics / 17.1:
Computing DBD Metrics / 17.3:
Semi-Supervised Learning Using Density-Based Metrics / 17.4:
Conclusions and Future Work / 17.5:
Semi-Supervised Learning in Practice / V:
Large-Scale Algorithms / 18:
Cost Approximations / 18.1:
Subset Selection / 18.3:
Semi-Supervised Protein Classification Using Cluster Kernels / Jason Weston ; Christina Leslie ; Eugene Ie ; William Stafford Noble18.4:
Representation and Kernels for Protein Sequences / 19.1:
Semi-Supervised Kernels for Protein Sequences / 19.3:
Prediction of Protein Function from Networks / Hyunjung Shin ; Koji Tsuda19.4:
Graph-Based Semi-Supervised Learning / 20.1:
Combining Multiple Graphs / 20.3:
Experiments on Function Prediction of Proteins / 20.4:
Conclusion and Outlook / 20.5:
Analysis of Benchmarks / 21:
The Benchmark / 21.1:
Application of SSL Methods / 21.2:
Results and Discussion / 21.3:
Perspectives / VI:
An Augmented PAC Model for Semi-Supervised Learning / Maria-Florina Balcan ; Avrim Blum22:
A Formal Framework / 22.1:
Sample Complexity Results / 22.3:
Algorithmic Results / 22.4:
Related Models and Discussion / 22.5:
Metric-Based Approaches for Semi-Supervised Regression and Classification / Dale Schuurmans ; Finnegan Southey ; Dana Wilkinson ; Yuhong Guo23:
Metric Structure of Supervised Learning / 23.1:
Model Selection / 23.3:
Regularization / 23.4:
Classification / 23.5:
Transductive Inference and Semi-Supervised Learning / Vladimir Vapnik23.6:
Problem Settings / 24.1:
Problem of Generalization in Inductive and Transductive Inference / 24.2:
Structure of the VC Bounds and Transductive Inference / 24.3:
The Symmetrization Lemma and Transductive Inference / 24.4:
Bounds for Transductive Inference / 24.5:
The Structural Risk Minimization Principle for Induction and Transduction / 24.6:
Combinatorics in Transductive Inference / 24.7:
Measures of Size of Equivalence Classes / 24.8:
Algorithms for Inductive and Transductive SVMs / 24.9:
Semi-Supervised Learning / 24.10:
Conclusion: / 24.11:
Transductive Inference and the New Problems of Inference
Beyond Transduction: Selective Inference / 24.12:
A Discussion of Semi-Supervised Learning and Transduction / 25:
References
Notation and Symbols
Contributors
Index
Online Index
Series Foreword
Preface
Introduction to Semi-Supervised Learning / 1:
4.

電子ブック

EB
edited by Dagmar Bruss and Gerd Leuchs
出版情報: Weinheim : Chichester : Wiley-VCH ; John Wiley [distributor], 2006  1 online resource
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5.

電子ブック

EB
Johannes G. de Vries, Cornelis J. Elsevier (eds.)
出版情報: Weinheim : WILEY-VCH, 2006  1 online resource (3 volumes (xxx, 1370 pages))
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6.

電子ブック

EB
edited by Helena Dodziuk
出版情報: Weinheim : Wiley-VCH, 〓2006  1 online resource (xvii, 489 pages)
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Introduction
Reactivity and chemistry Polymers CyD Catalysis
Chromatography Enantioselective separations X-ray Calorimetry NMR
Other physicochemical methods: UV-vis, ICD, Electrochemistry, AFM and STM
Model calculations Rotaxane and catenane structures involving cyclodextrins
Large cyclodextrins Applications in pharmaceutical industry Cyclodextrin aggregates (simple and multiple emulsions, microparticles, nanoparticles, liposomes, niosomes)
Other applications: in cosmetic, toiletry, textile and wrapping industries; in agrochemistry; in electrochemical sensors and devices
Reactivity and chemistry Polymers CyD Catalysis Chromatography Enantioselective separations
X-ray Calorimetry NMR Other physicochemical methods: UV-vis, ICD, Electrochemistry, AFM and STM
Model calculations Rotaxane and catenane structures involving cyclodextrins Large cyclodextrins Applications in pharmaceutical industry Cyclodextrin aggregates (simple and multiple emulsions, microparticles, nanoparticles, liposomes, niosomes)
Introduction
Reactivity and chemistry Polymers CyD Catalysis
Chromatography Enantioselective separations X-ray Calorimetry NMR
7.

電子ブック

EB
S.M. Sze, Kwok K. Ng
出版情報: Wiley Online Library, 2006  1 online resource (x, 815p.)
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Introduction
Semiconductor Physics / Part I:
Physics and Properties of Semiconductors-A Review / Chapter 1:
Crystal Structure / 1.1:
Energy Bands and Energy Gap / 1.3:
Carrier Concentration at Thermal Equilibrium / 1.4:
Carrier-Transport Phenomena / 1.5:
Phonon, Optical, and Thermal Properties / 1.6:
Heterojunctions and Nanostructures / 1.7:
Basic Equations and Examples / 1.8:
Device Building Blocks / Part II:
p-n Junctions / Chapter 2:
Depletion Region / 2.1:
Current-Voltage Characteristics / 2.3:
Junction Breakdown / 2.4:
Transient Behavior and Noise / 2.5:
Terminal Functions / 2.6:
Heterojunctions / 2.7:
Metal-Semiconductor Contacts / Chapter 3:
Formation of Barrier / 3.1:
Current Transport Processes / 3.3:
Measurement of Barrier Height / 3.4:
Device Structures / 3.5:
Ohmic Contact / 3.6:
Metal-Insulator-Semiconductor Capacitors / Chapter 4:
Ideal MIS Capacitor / 4.1:
Silicon MOS Capacitor / 4.3:
Transistors / Part III:
Bipolar Transistors / Chapter 5:
Static Characteristics / 5.1:
Microwave Characteristics / 5.3:
Related Device Structures / 5.4:
Heterojunction Bipolar Transistor / 5.5:
MOSFETS / Chapter 6:
Basic Device Characteristics / 6.1:
Nonuniform Doping and Buried-Channel Device / 6.3:
Device Scaling and Short-Channel Effects / 6.4:
MOSFET Structures / 6.5:
Circuit Applications / 6.6:
Nonvolatile Memory Devices / 6.7:
Single-Electron Transistor / 6.8:
JFETs, MESFETs, and MODFETs / Chapter 7:
JFET and MESFET / 7.1:
MODFET / 7.3:
Negative-Resistance and Power Devices / Part IV:
Tunnel Devices / Chapter 8:
Tunnel Diode / 8.1:
Related Tunnel Devices / 8.3:
Resonant-Tunneling Diode / 8.4:
IMPATT Diodes / Chapter 9:
Dynamic Characteristics / 9.1:
Power and Efficiency / 9.4:
Noise Behavior / 9.5:
Device Design and Performance / 9.6:
BARITT Diode / 9.7:
TUNNETT Diode / 9.8:
Transferred-Electron and Real-Space-Transfer Devices / Chapter 10:
Transferred-Electron Device / 10.1:
Real-Space-Transfer Devices / 10.3:
Thyristors and Power Devices / Chapter 11:
Thyristor Characteristics / 11.1:
Thyristor Variations / 11.3:
Other Power Devices / 11.4:
Photonic Devices and Sensors / Part V:
LEDs and Lasers / Chapter 12:
Radiative Transitions / 12.1:
Light-Emitting Diode (LED) / 12.3:
Laser Physics / 12.4:
Laser Operating Characteristics / 12.5:
Specialty Lasers / 12.6:
Photodetectors and Solar Cells / Chapter 13:
Photoconductor / 13.1:
Photodiodes / 13.3:
Avalanche Photodiode / 13.4:
Phototransistor / 13.5:
Charge-Coupled Device (CCD) / 13.6:
Metal-Semiconductor-Metal Photodetector / 13.7:
Quantum-Well Infrared Photodetector / 13.8:
Solar Cell / 13.9:
Sensors / Chapter 14:
Thermal Sensors / 14.1:
Mechanical Sensors / 14.3:
Magnetic Sensors / 14.4:
Chemical Sensors / 14.5:
Appendixes
List of Symbols / A:
International System of Units / B:
Unit Prefixes / C:
Greek Alphabet / D:
Physical Constants / E:
Properties of Important Semiconductors / F:
Properties of Si and GaAs / G:
Properties of SiO, and Si3N / H:
Index
MOSFETs
Properties of SiO[subscript 2] and Si[subscript 3]N[subscript 4]
Introduction
Semiconductor Physics / Part I:
Physics and Properties of Semiconductors-A Review / Chapter 1:
8.

電子ブック

EB
edited by Hyun-Ku Rhee, In-Sik Nam and Jong Moon Park
出版情報: Amsterdam : Oxford : Elsevier, 2006  1 online resource (xxvii, 896 pages)
シリーズ名: Studies in surface science and catalysis ; v. 159
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Plenary Lecture?
Invited Lecture?
Biological and Biochemical Reaction Engineerin?
Catalysis and Catalytic Reaction Engineerin?
Chemical Reaction Engineering in Microelectronic?
Environmental Reaction Engineerin?
Fluidized Bed and Multiphase Reactor?
Fuel Cells and Electrochemical Reaction Engineerin?
Micro-Reaction Technolog?
Modeling, Simulation and Control of Chemical Reactor?
Nano Materials Synthesis and Application
Novel Reactors and Processe?
Polymer Reaction Engineering
Plenary Lecture?
Invited Lecture?
Biological and Biochemical Reaction Engineerin?
9.

電子ブック

EB
edited by Takeshi Shiono, Kotohiro Nomura, Minoru Terano
出版情報: Amsterdam ; Boston : Elsevier, 2006  1 online resource (xv, 282 pages)
シリーズ名: Studies in surface science and catalysis ; 161
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Selected paper headings Creation of New Polyolefin Hybrids on the Surface of Molded Polypropylene Sheet / S. Matsuo et al.
Japanese National Project for the Innovation of Industrial Polypropylene Process Technology / M. Teranoa et al.
Microstructure Characterization of Polyolefins. TREF and CRYSTAF / B. Monrabal
Norbornene and Ethylene Polymerization with Palladium and Nickel Complexes with Potentially Tri-or Tetradentate Ligands / D.W. Lee et al.
Stereoerrors Formation in the Polymerization of Deuterated Propylene / V. Volkis et al.
Ethylene Polymerization with an Anilinonaphthoquinone-Ligated Nickel Complex / M. Okada et al.
Synthesis of Polymeric Radical Scavengers via ROMP of Norbornene Derivatives and Their Antioxidation Activities / K. Horikawa et al.
Effects of Silica Particles on the Transparency of Polypropylene Based Nanocomposites / Kazuo Asuka et al.
Selected paper headings Creation of New Polyolefin Hybrids on the Surface of Molded Polypropylene Sheet / S. Matsuo et al.
Japanese National Project for the Innovation of Industrial Polypropylene Process Technology / M. Teranoa et al.
Microstructure Characterization of Polyolefins. TREF and CRYSTAF / B. Monrabal
10.

電子ブック

EB
edited by E.M. Gaigneaux [and others]
出版情報: Amsterdam ; Boston : Elsevier, 2006  1 online resource (xxii, 1048 pages)
シリーズ名: Studies in surface science and catalysis ; 162
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