Note: Intro -- Preface -- Contents -- 1 In-situ Characterization of Molecular Processes in Liquids by Ultrafast X-ray Absorption Spectroscopy -- Abstract -- 1.1 Introduction -- 1.2 X-ray Absorption Spectroscopy -- 1.2.1 Extended X-ray Absorption Fine Structure (EXAFS) -- 1.2.2 X-ray Absorption Near Edge Spectroscopy (XANES) -- 1.3 Methodology -- 1.4 Applications -- 1.4.1 Intramolecular Charge Transfer -- 1.4.2 Bond Formation in Bimetallic Complexes -- 1.4.3 Spin Cross-over in Fe(II)-Complexes -- 1.4.4 Dynamics of Pure Water -- 1.4.5 Solvation Dynamics and Hydrophobicity -- 1.4.6 Towards Biological Systems -- 1.5 Conclusion and Outlook -- References -- 2 In-situ X-ray Diffraction at Synchrotrons and Free-Electron Laser Sources -- Abstract -- 2.1 The Need for In-situ X-ray Observations -- 2.2 Advantages and Disadvantages of In-situ X-ray Diffraction -- 2.3 Selected Examples of In-situ X-ray Diffraction -- 2.3.1 Complex Transition Metal Oxides -- 2.3.1.1 Pulsed Laser Deposition (PLD) -- 2.3.1.2 Growth of YBa2Cu3O7-x -- 2.3.1.3 Experimental Set-Up -- 2.3.1.4 In-situ Surface X-ray Diffraction During Thin Film Growth -- 2.3.2 Experimental Results -- 2.3.3 Deeply Buried Interfaces -- 2.3.3.1 X-ray Reflectivity -- 2.3.3.2 High-Energy Microdiffraction -- 2.4 X-ray Free Electron Lasers -- 2.4.1 Source Parameters -- 2.4.2 Potential for In-situ Experiments at FELs -- 2.4.2.1 Coherent Diffraction Imaging (CDI) -- 2.4.2.2 X-ray Photon Correlation Spectroscopy (XPCS) -- 2.5 Summary -- References -- 3 In-situ Transmission Electron Microscopy -- Abstract -- 3.1 What is the In-situ TEM and Why It Is Important -- 3.2 A Brief History of In-situ Microscopy -- 3.3 In-situ TEM Technologies -- 3.3.1 In-situ Heating and Cooling TEM -- 3.3.1.1 Chemical Analysis at Elevated Temperatures -- 3.3.2 In-situ Gas Environmental TEM (ETEM) -- 3.3.2.1 Windows-Type Gas E-Cell. , 3.3.2.2 Differentially Pumped Gas E-Cell -- 3.3.2.3 Spherical Aberration (Cs)-Corrected Gas ETEM -- 3.3.3 In-situ Liquid ETEM -- 3.3.3.1 Window-Type Liquid E-Cell -- 3.3.3.2 Liquid ETEM with an In-Column Differentially Pumped Liquid E-Cell -- 3.3.4 In-situ Biasing TEM -- 3.3.5 In-situ Nanomechanical TEM -- 3.3.5.1 Conventional Tensile Straining TEM Holder -- 3.3.5.2 MEMS-Based Straining TEM Holder -- 3.3.5.3 Nanoindentation TEM Holder -- 3.3.5.4 TEM Grid-Based Straining Holder -- 3.3.6 In-situ Lorentz TEM and In-situ Electron Holography for Imaging Magnetic or Electric Field Distribution -- 3.3.6.1 Lorentz TEM: Principle -- 3.3.6.2 Electron Holography: Principle -- 3.3.6.3 In-situ Lorentz TEM and In-situ Electron Holography -- 3.3.7 In-situ Ion Beam Irradiation TEM -- 3.4 Some Important Notes -- 3.4.1 In-situ TEM: Holders and Atomic Resolution -- 3.4.2 Effects of Electron Beam Irradiation -- 3.4.3 Digital Recording -- 3.4.4 Technical Challenges Ahead -- 3.5 Summary -- References -- 4 Ultrafast Transmission Electron Microscopy and Electron Diffraction -- Abstract -- 4.1 Introduction -- 4.2 Electron Sources -- 4.2.1 Electron Emission -- 4.2.2 Emitter Materials -- 4.3 Electron Pulse Propagation -- 4.4 Electron- and Laser-Material Interactions -- 4.4.1 Ultrafast Conditions in Matter -- 4.5 Time Resolution and Synchronization -- 4.5.1 Electron Pulse Profile -- 4.5.2 Synchronization at the Sample and Time Zero -- 4.6 Experimental Variations and Ultrafast Electron Detection -- 4.6.1 Single- Versus Multi-shot Experiments -- 4.6.2 Electron Detection Techniques -- 4.7 Conclusion -- References -- 5 In-situ and Kinetic Studies Using Neutrons -- Abstract -- 5.1 Introduction -- 5.2 Conditions Available for In-situ Studies -- 5.2.1 Temperature -- 5.2.2 Pressure and Stress -- 5.2.3 Magnetic Fields -- 5.2.4 Electric Fields. , 5.2.5 Chemical Potential: Partial Pressure -- 5.3 Single-Shot Kinetic Experiments -- 5.3.1 Cement Hydration -- 5.3.2 Transition Between Ice-Phases -- 5.3.3 Crystallization of Glass-Phases -- 5.3.4 Crystallization Reactions and Extreme Conditions -- 5.3.5 Self-Assembly in Soft Matter -- 5.4 Stroboscopic Kinetic Experiments -- 5.4.1 Decomposition Kinetics -- 5.4.2 Switching Processes In Ferroelectrics and Piezoelectrics -- 5.4.3 Limitations of Stroboscopic Techniques -- 5.4.4 Magnetic Relaxation in Ferrofluids -- 5.5 Further Prospects of In-situ Investigations -- References -- 6 Scanning Tunneling Microscopy at Elevated Pressure -- Abstract -- 6.1 Introduction -- 6.1.1 Are High Pressures Necessary? -- 6.1.2 Why Can't We Use the Thermodynamic Back Door of Temperature? -- 6.2 High-Pressure Techniques -- 6.3 High-Pressure STM Instrumentation -- 6.3.1 Requirements for STM Under Catalytic Conditions -- 6.3.1.1 Atmospheric Pressures -- 6.3.1.2 Elevated Temperatures -- 6.3.1.3 Atmospheric Pressures Combined with Elevated Temperatures -- 6.3.1.4 Correlation with Catalytic Performance -- 6.3.1.5 Minimal Chemical Side Effects -- 6.3.1.6 Well-Prepared Model Catalysts -- 6.3.2 Design of the ReactorSTM -- 6.4 High-Pressure Observations -- 6.4.1 CO Oxidation: The Special Role of Surface Oxides -- 6.4.2 CO Oxidation: Roughness, Steps and Spontaneous Reaction Oscillations -- 6.4.3 NO Reduction: From LH to LH -- 6.5 Conclusion and Outlook -- References -- 7 Detectors for Electron and X-ray Scattering and Imaging Experiments -- Abstract -- 7.1 Detectors for Electrons -- 7.1.1 Introduction -- 7.1.2 Electron Image Recording Devices -- 7.1.2.1 Photographic Film -- 7.1.2.2 Imaging Plate -- 7.1.2.3 CCD-Based Indirect Electron Detector -- 7.1.3 Critical Parameters for Detector Characterization -- 7.1.3.1 Modulation Transfer Function -- 7.1.3.2 Detector Quantum Efficiency. , 7.1.3.3 Dynamic Range -- 7.1.3.4 Linearity -- 7.1.3.5 Uniformity -- 7.1.3.6 Resolution and Pixel Size -- 7.1.4 Comparison of Electron Detectors -- 7.1.5 Direct Electron Detectors -- 7.1.5.1 The Active Pixel Sensor -- 7.1.5.2 The Direct CCD -- 7.1.5.3 Performance of a Direct CCD -- 7.2 Detectors for X-rays -- 7.2.1 Introduction -- 7.2.2 Storage Ring Based X-ray Sources -- 7.2.2.1 Source Developments -- 7.2.2.2 Examples of Detectors for In-situ Experiments at Storage Rings -- The Cornell AP-HPAD -- The PILATUS detector -- 7.2.3 Free-Electron Laser Based X-ray Sources -- 7.2.3.1 Source Developments -- 7.2.3.2 Requirements for X-ray Detectors for FEL Based Sources -- 7.2.3.3 The Adaptive Gain Integrating Pixel Detector Project -- 7.2.4 Outlook -- References -- Index.

Note: Intro -- Preface -- Table of Contents -- Author Index.

Note: Intro -- Title Page -- Preface -- Organization -- Table of Contents -- Neural Networks -- Complex Functional Network Hebbian-Type Learning Algorithm and Convergence -- Introduction -- Complex Value Functional Networks -- Complex Value Functional Network Learning Algorithm -- Conclusions -- References -- A New Intelligent Control Strategy of High-Voltage Power Supply for ECRH Based on CMAC Neural Network -- Introduction -- State Space Model of ECRH System -- Inverse Model Learning Control for ECRH on CMAC -- Simulation -- Conclusions -- References -- Self-configuration Using Artificial Neural Networks -- Introduction -- Related Work -- ANN Based Self-configuration Approach -- Case Study: Autonomic Fire Forest Application -- Conclusion and Future Work -- References -- Evolutionary Learning and Genetic Algorithms -- An Improvement of AdaBoost for Face Detection with Random Forests -- Introduction -- Basic Concepts of Algorithm -- AdaBoost Algorithm -- Random Forests Algorithm -- AdaBoost Method for Face Detection Based on Random Forests -- Experimental Results and Analysis -- Conclusions -- References -- Hybrid Good Point Set Evolutionary Strategy for Constrained Optimization -- Introduction -- Our Mechanisms and Algorithms -- PSO Operator -- Good Point Set (GPS):[3][4] -- GPS Operator -- Mutation Operator -- Select Next Generation -- Empirical Study -- Conclusion -- References -- Research of Modified Quantum Genetic Algorithm and It's Application in Collision Detection -- Introduction -- Proposed Algorithm -- Related Definitions -- Algorithm Description -- Simulation Experiment -- Conclusion -- References -- Granular Computing and Rough Sets -- A New Method of Attribute Reduction and Prediction in Fuzzy Decision System -- Introduction -- Construction of Fuzzy Rough Approximation Operators -- Example -- References. , Particle Swarm Optimization and Niche Technology -- Development of Automatic Code Generation Tool for Condensation Algorithm -- Introduction -- CONDENSATION Algorithm -- CONDENSATION Algorithm -- Application of CONDENSATION for the Multiple Target Tracking -- Program Structures -- Generation of Gaussian Distribution -- Generation of Filter Code Bloks -- Experiment Result -- Conclusions -- References -- Swarm Intelligence and Optimization -- A New Hybrid Multi-objective Pareto Archive PSO Algorithm for a Classic Job Shop Scheduling Problem with Ready Times -- Introduction -- Proposed Model -- Index -- Parameters -- Variables -- Proposed Mathematical Model -- Proposed Pareto Archive PSO -- Solution Representation -- Initialization -- Update the Pareto Archive -- Improvement by VNS -- Update the Position of Particles -- Experimental Results -- Algorithm Assumptions -- Comparative Results -- Conclusion -- References -- Multi-objective Particle Swarm Optimization for Sequencing and Scheduling a Cellular Manufacturing System -- Introduction -- Mathematical Model -- Indices -- Parameters -- Decision Variables -- Minimizing Makespan and Intra-cellular Movement -- Minimizing Tardiness Cost -- Pareto Frontier Concepts -- Particle Swarm Optimization for Multi-objective Problems -- Comparison Metrics -- Conclusion -- References -- A Hybrid PSO Algorithm with Transposon for Multiobjective Optimization -- Introduction -- Particle Swarm Optimization -- Multiojective Optimization and the Concept of Domiance -- A Hybrid PSO with Transposon -- Transposon Operation -- The Details of a Hybrid PSO with Transposon -- Experiment Results and Discussion -- Test Functions and Performance Metrics -- Parameters Selection -- Results and Discussion -- Conclusion -- References -- Independent Component Analysis and Blind Source Separation. , Joint Multichannel Blind Speech Separation and Dereverberation: A Real-Time Algorithmic Implementation -- Introduction -- Problem Formulation -- The Multichannel Blind Speech Separation and Dereverberation Algorithm -- MIMO Blind System Identification -- Speech Separation Stage -- Speech Dereverberation Stage -- Real-Time Algorithm Implementation -- Computer Simulations -- Conclusions -- References -- An Efficient Pairwise Kurtosis Optimization Algorithm for Independent Component Analysis -- Introduction -- Pairwise Optimization of the Kurtosis-Sum -- Pairwise Kurtosis Optimization Algorithm -- Computation Complexity and Simulation -- Conclusions -- References -- Combinatorial and Numerical Optimization -- The Mechanical Behavior of the Double Piece of Tape Spring -- Introduction -- Model of the Hinge and Simulation Techniques -- FEA Analysis and Results -- Experiment for Measuring Bend Moment of the Hinge -- Deployable Experiment of the Tape Spring -- Fold Experiment of the Tape Spring -- Conclusion -- References -- Systems Biology and Computational Biology -- Cancer Immunoprevention: What Can We Learn from in Silico Models? -- Introduction -- The Model -- Tuning and Validation -- The Problem of Schedule -- Conclusions -- References -- Oscillatory Dynamics of Double Negative Feedback Loop Motif by MicroRNAs -- Introduction -- Mathematical Model of The Double Negative Feedback Loop Involving Small RNAs -- Oscilatory Dynamics Induced by Time Delay and Hill Coeffiecient n -- Discussion -- References -- Neural Computing and Optimization -- Neural Network Approach for Greenery Warranty Systems -- Introduction -- Background -- Greenery Warranty Claims Architecture -- Two-Attribute Warranty Policy -- Warranty Function Approximation -- Case Study Example -- Conclusions -- References -- Knowledge Discovery and Data Mining. , Comprehensive Evaluation of Effects of Naomaitong and Rhubarb Aglycone Combined with Bone Mesenchymal Stem Cells Transplantation on Brain in Rats with Cerebral Ischemia Based on Analytic Hierarchy Process -- Introduction -- Application Steps -- Establishing Hierarchy Model -- Constructing of Comparison Matrix in Pair (Means Judging Matrix) -- Calculating Vector and Testing the Consistency -- Calculating the Combined Weight Vectors and Conducting Consistency Test -- Calculation and Results -- To Construct the Model of Hierarchical Structure -- To Construct the Paired Comparison Matrix (Judging Matrix) -- To Calculate the Combined Weight Vectors and Testing Consistency -- To Calculate the Results -- Discussion -- References -- Aggregating and Weighting Expert Knowledge in Group Decision Making -- Introduction -- Related Work -- Weighting Expert Opinions Scheme for Decision Making Procedure -- Sort the Alternatives and Assign a Score -- Calculate the Euclidean Distance -- Aggregate the Expert Opinions -- A Case Study -- Conclusion and Future Work -- References -- A New Heuristic Feature Selection Algorithm Based on Rough Sets -- Introduction -- Preliminaries -- The New Algorithm -- Experiment -- Conclusions -- References -- Developing a Procedure to Obtain Knowledge of Optimum Solutions in a Travelling Salesman Problem -- Introduction -- Proposed Algorithm -- Business Understanding -- Data Understanding -- Data Preparation -- Modeling -- Evaluation -- Conclusion and Future Research -- References -- Trajectory Simplification and Classification for Moving Object with Road-Constraint -- Introduction -- Problem Formulations and Motivation -- Exclude Useless Trajectories Based on Temporal Filterer -- Simplified Single Trajectory -- The TRI Algorithm: An Easier and More Practical Method -- Experiment -- Computational Complexity -- Experimental Results. , Conclusions and Future Work -- References -- Training a Pac-Man Player with Minimum Domain Knowledge and Basic Rationality -- Introduction -- Game Modeling -- Experiments -- Discussion -- Conclusion -- References -- Hybrid Self-Organizing Map and Neural Network Clustering Analysis for Technology Professionals Turnover Rate Forecasting -- Introduction -- Procedure for Paper Submission -- Turnover Trend -- Data Mining and Clustering Analysis Method -- Methodology -- Data Preprocessing -- Sample Dealing and Cluster Analysis -- SOM Clustering Process -- Neural Network Clustering Method -- Analysis Results -- SOM Clustering Result -- SOM+BPN Clustering Result -- Conclusions -- References -- Ensemble Methods -- A Study of Strength and Correlation in Random Forests -- Introduction -- The Forest-RI Algorithm -- Strength and Correlation -- Tree Selection -- Datasets Used -- Experimental Protocol -- Results and Discussion -- Conclusion -- References -- Machine Learning Theory and Methods -- A Comparison Study of Conditional Random Fields Toolkits -- Introduction -- Conditional Random Fields -- Training Methods -- Introduction of Each Toolkit -- crf++ -- crfsgd -- flexcrf -- crfsuite -- mallet -- Experiment and Discussion -- Experiment Content -- Experiment Settings -- Experiment Results -- Conclusion -- References -- Robot Reinforcement Learning Based on Learning Classifier System -- Introduction -- Background Materials -- Reinforcement Learning (RL) -- Learning Classifier System (LCS) -- Reinforcement Learning Design -- Encoding of Operating Message and Rules -- Fitness Function Design -- Experiments and Simulation -- Conclusions -- References -- Intelligent Computing in Bioinformatics -- Research of Marker Gene Selection for Tumor Classfication Based on Decision Forests -- Background -- Methods and Principles -- Decision Forests -- ReliefF, SAM and PCA. , Results and Analysis.

Note: Intro -- Preface -- Table of Contents -- Author Index.