Contemporary distributed file systems are monolithic and only support single file abstractions. Nowadays, as Sai-Lai Lo explains, network storage devices have to accommodate new information media such as digital audio and video, with data radically different from the traditional text and binary code that contemporary file systems are optimized for. In this book, the author shows how, by combining new and traditional media, information can be recorded and presented in the most suitable way, and the value of a piece of information can be further enhanced by linking together related pieces. However, composite data and cross-reference between data items raise a number of system issues that have not been addressed properly before. Lo defines a new multiservice storage architecture that meets the needs of existing and emerging applications and can support multiple file abstractions. He also explores a number of related design issues. Researchers in the areas of distributed systems, network multimedia and network storage services will enjoy this book.
This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy - the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy - understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation - are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.
The potential use of hydrogen as a clean and renewable fuel resource has generated significant attention in recent years, especially given the rapidly increasing demand for energy sources and the dwindling availability of fossil fuels. Hydrogen is an ?ideal fuel? in several ways. Its only byproduct of consumption is water; it is the most abundant element in the universe; and it is available at low cost. Hydrogen generation is possible via a number of possible chemical processes, to separate the hydrogen from its bond with atoms such as carbon, nitrogen, and oxygen.
In this book, the authors provide the scientific foundations for established and innovative methods of hydrogen extraction; outline solutions for its storage; and illustrate its applications in the fields of petroleum, chemical, metallurgical, physics, and manufacturing.
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