Sour Gas and Related Technologies (Advances in Natural Gas Engineering)

Wu, Ying

Wiley-Scrivener

This is the fourth volume in a series of books focusing on natural gas engineering, focusing on two of the most important issues facing the industry today: disposal and enhanced recovery of natural gas. This volume includes information for both upstream and downstream operations, including chapters on shale, geological issues, chemical and thermodynamic models, and much more. Written by some of the most well-known and respected chemical and process engineers working with natural gas today, the chapters in this important volume represent the most cutting-edge and state-of-the-art processes and operations being used in the field. Not available anywhere else, this volume is a must-have for any chemical engineer, chemist, or process engineer working with natural gas. There are updates of new technologies in other related areas of natural gas, in addition to disposal and enhanced recovery, including sour gas, acid gas injection, and natural gas hydrate formations. Advances in Natural Gas Engineering is an ongoing series of books meant to form the basis for the working library of any engineer working in natural gas today. Every volume is a must-have for any engineer or library.

Gas Injection for Disposal and Enhanced Recovery (Advances in Natural Gas Engineering)

Engineering & Transportation

Carroll, John J.

Li, Qi

Engineering

CO? Capture and Acid Gas Injection (Advances in Natural Gas Engineering)

This study, first published in 1994, is intended to deepen the readers understanding of the phenomenon of equilibrium credit rationing in two areas. The first area concerns the form that equilibrium credit rationing assumes and its importance in determining the behaviour of interest rates. The second concerns the role of equilibrium credit rationing in transmitting monetary shocks to the real sector. This title will be of interest to students of monetary economics.

An Analysis of Credit and Equilibrium Credit Rationing (Routledge Library Editions: Monetary Economics)

Business & Money

Economics

Routledge

A title in the Elements of the Extraordinary series takes an intriguing look into the Chinese mythology of Feng Shui and teaches kids how it can bring them good luck, improve their grades, protect them from evils, and more. Original.

Do-It-Yourself Feng Shui: Take Charge of Your Destiny! (Element of the Extraordinary)

Yin, Wu

Children's Books

Element Books Ltd.

Face Reading: Can You Face the Facts? (Elements of the Extraordinary)

Teen & Young Adult

Ying, WU

Literature & Fiction

Visual object tracking, i.e., consistently inferring the motion of a target from image sequences, is a must-have component to bridge low-level image processing and high-level video analysis, which gains great popularity due to its applications in diverse areas, such as human-computer interaction, security video surveillance, medical image processing, and robotics. In this book, we focus on how to enhance the generality and reliability of object-level tracking given no prior knowledge about targets. We propose two novel ideas: context-aware and attentional tracking, where the tracker discovers some auxiliary objects that have short-term motion correlations with the target as the spatial contexts, or augments the observation models by selectively attending discriminative regions inside the target, or adaptively tuning the feature granularity and model elasticity.  These approaches achieve promising results on challenging real-world videos. The book sheds some light on recent progress of visual tracking and should be useful to professionals in computer vision research, or anyone else who may be considering utilizing visual tracking in intelligent video analysis systems.

Context-aware and Attentional Visual Tracking: Concepts, Algorithms, Experiments

Yang, Ming

VDM Verlag Dr. Müller

Non-Standard Parameter Adaptation for Exploratory Data Analysis (Studies in Computational Intelligence, 249)

Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variations thereof. In this book, we first lay the groundwork by reviewing some standard clustering algorithms and projection algorithms before presenting various non-standard criteria for clustering. The family of algorithms developed are shown to perform better than the standard clustering algorithms on a variety of datasets. We then consider extensions of the basic mappings which maintain some topology of the original data space. Finally we show how reinforcement learning can be used as a clustering mechanism before turning to projection methods. We show that several varieties of reinforcement learning may also be used to define optimal projections for example for principal component analysis, exploratory projection pursuit and canonical correlation analysis. The new method of cross entropy adaptation is then introduced and used as a means of optimising projections. Finally an artificial immune system is used to create optimal projections and combinations of these three methods are shown to outperform the individual methods of optimisation.

Computers & Technology

Barbakh, Wesam Ashour

Fyfe, Colin

Computer Science

Springer

Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variations thereof. In this book, we first lay the groundwork by reviewing some standard clustering algorithms and projection algorithms before presenting various non-standard criteria for clustering. The family of algorithms developed are shown to perform better than the standard clustering algorithms on a variety of datasets. We then consider extensions of the basic mappings which maintain some topology of the original data space. Finally we show how reinforcement learning can be used as a clustering mechanism before turning to projection methods. We show that several varieties of reinforcement learning may also be used to define optimal projections for example for principal component analysis, exploratory projection pursuit and canonical correlation analysis. The new method of cross entropy adaptation is then introduced and used as a means of optimising projections. Finally an artificial immune system is used to create optimal projections and combinations of these three methods are shown to outperform the individual methods of optimisation.

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Books by Wu, Ying