Mining of Data with Complex Structures:

- Clarifies the type and nature of data with complex structure including sequences, trees and graphs

- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.

-Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.

- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)

- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.

- Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.

- Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.

- Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.

- Details the extension of the TMG framework for sequence mining

- Provides an overview of the future research direction with respect to technical extensions and application areas

The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains."

The advancement of methods and technologies in the oil and gas industries calls for new insight into the corrosion problems these industries face daily. With the application of more precise instruments and laboratory techniques as well as the development of new scientific paradigms, corrosion professionals are also witnessing a new era in the way data are gathered and interpreted. Corrosion and Materials in the Oil and Gas Industries draws on state-of-the-art corrosion and materials technology as well as integrity management to offer guidance on dealing with aging and life extension in the oil and gas industries. Get Expert Insights on Corrosion Identification, Prevention, and Mitigation The book features contributions by engineers, scientists, and business managers from around the world, including major oil- and gas-producing and -exporting countries. Organized into four parts, the book first provides introductory and background information. The second part explains the properties of construction materials and the underlying mechanisms of degradation, including a chapter on microbiologically influenced corrosion. The third part of the book delves into inspection and maintenance issues, examining material selection, corrosion prevention strategies, and the role of design. It also supplies models to help you estimate corrosion damage and select mitigation and monitoring techniques. The fourth part tackles corrosion hazards, safety and risk, and reliability. It also links corrosion mitigation and the management of asset integrity, highlighting the need for companies to maintain their infrastructure to remain competitive. Interpret Field Findings More Confidently and Discover Solutions to Your Corrosion Problems Throughout, this richly illustrated book combines theory with practical strategies and examples from industry. As infrastructure ages and is pushed beyond its original design life to meet increasing energy demands, it is essential that those responsible for managing the infrastructure have a thorough understanding of material degradation and corrosion. This book is an invaluable reference for anyone involved in corrosion management and materials selection, particularly in the oil and gas industries, whether upstream, midstream, or downstream.

Mining of Data with Complex Structures:

- Clarifies the type and nature of data with complex structure including sequences, trees and graphs

- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.

-Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.

- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)

- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.

- Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.

- Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.

- Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.

- Details the extension of the TMG framework for sequence mining

- Provides an overview of the future research direction with respect to technical extensions and application areas

The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains."