Multi-Component Acoustic Characterization of Porous Media

Multi-Component Acoustic Characterization of Porous Media

The feasibility to extract porous medium parameters from acoustic recordings is investigated. The thesis gives an excellent discussion of our basic understanding of different wave modes, using a full-waveform and multi-component approach. Focus lies on the dependency on porosity and permeability where especially the latter is difficult to estimate. In this thesis, this sensitivity is shown for interface-wave and reflected-wave modes. For each of the pseudo-Rayleigh and pseudo-Stoneley interface waves unique estimates for permeability and porosity can be obtained when impedance and attenuation are combined. The pseudo-Stoneley wave is most sensitive to permeability: both the impedance and the attenuation are controlled by the fluid flow. Also from reflected-wave modes unique estimates for permeability and porosity can be obtained when the reflection coefficients of different reflected modes are combined. In this case the sensitivity to permeability is caused by subsurface heterogeneities generating mesoscopic fluid flow at seismic frequencies. The results of this thesis suggest that estimation of in-situ permeability is feasible, provided detection is carried out with multi-component measurements. The results of this thesis argely affect geotechnical and reservoir engineering practices.

Multi-Component Acoustic Characterization of Porous Media

Markov Networks in Evolutionary Computation

Markov Networks in Evolutionary Computation

Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis.This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current research trends and future perspectives in the enhancement and applicability of EDAs are also covered. The contributions included in the book address topics as relevant as the application of probabilistic-based fitness models, the use of belief propagation algorithms in EDAs and the application of Markov network based EDAs to real-world optimization problems. The book should be of interest to researchers and practitioners from areas such as optimization, evolutionary computation, and machine learning.

Markov Networks in Evolutionary Computation

The Noble Gases as Geochemical Tracers

The Noble Gases as Geochemical Tracers

The twelve chapters of this volume aim to provide a complete manual for using noble gases in terrestrial geochemistry, covering applications which range from high temperature processes deep in the Earths interior to tracing climatic variations using noble gases trapped in ice cores, groundwaters and modern sediments. Other chapters cover noble gases in crustal (aqueous, CO2 and hydrocarbon) fluids and laboratory techniques for determining noble gas solubilities and diffusivities under geologically relevant conditions. Each chapter deals with the fundamentals of the analysis and interpretation of the data, detailing sampling and sampling strategies, techniques for analysis, sources of error and their estimation, including data treatment and data interpretation using recent case studies.

The Noble Gases as Geochemical Tracers

Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems

Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems

This book presents selected fault diagnosis and fault-tolerant control strategies for non-linear systems in a unified framework. In particular, starting from advanced state estimation strategies up to modern soft computing, the discrete-time description of the system is employed Part I of the book presents original research results regarding state estimation and neural networks for robust fault diagnosis. Part II is devoted to the presentation of integrated fault diagnosis and fault-tolerant systems. It starts with a general fault-tolerant control framework, which is then extended by introducing robustness with respect to various uncertainties. Finally, it is shown how to implement the proposed framework for fuzzy systems described by the well-known TakagiSugeno models.

Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems

Empirical Techniques in Finance

Empirical Techniques in Finance

The rapid advances in financial technology in the past decade have led to a commensurate increase in sophistication for modelling techniques needed by the researchers for the understanding of financial markets. The book aims at equipping graduate students, market analysts and others with a wide range of empirical techniques. It not only discusses the analytical structures behind such modelling approaches, but also explains how they are applied to actual data. Besides traditional elements of financial econometrics and statistical techniques commonly used in quantitative finance, the book covers: estimation of parametric and non-parametric models; advanced tools to deal with unobserved components; discrete time models of asset prices and of interest rates. Illustrations include speculative equity prices, equity and currency risk premium as well as real investment opportunity analysis and interest rate contingent claim valuation.

Empirical Techniques in Finance

Managing and Leading Software Projects

Managing and Leading Software Projects

The book is organized around , principles of , , management: planning and estimating, measuring and controlling, leading and communicating, and managing risk. Introduces software development methods, from traditional (hacking, requirements to code, and waterfall) to iterative (incremental build, evolutionary, agile, and spiral). Illustrates and emphasizes tailoring the development process to each project, with a foundation in the fundamentals that are true for all development methods. Topics such as the WBS, estimation, schedule networks, organizing the project team, and performance reporting are integrated, rather than being relegating to appendices. Each chapter in the book includes an appendix that covers the relevant topics from CMMI-DEV-v1.2, IEEE/ISO Standards 12207, IEEE Standard 1058, and the PMI Body of Knowledge.

Managing and Leading Software Projects