Information Engineering for Port and Marine Environments provides the technology of tidal level prediction, the technology of oil spill early-warning, and the research for the theory of storm sedimentation, the construction for monitor ability, the early-warning service for numerical simulation and operational, which involves many aspects such as theoretical research, system establishment, and application of information technology, et al. Because of the certain prospective and advancement of multiple work, it will play a positive role in promoting the related technology of the field. There are several of important offshore ports in China, such as Tianjin port, Yangshan Port, Ningbo-Zhoushan port, Huanghua port et al., most of them are located in the coast of muddy and muddy silty, and the depth of water is shallow, the sediment deposition is serious, the large ship is operated by tide. In order to sufficiently keep the rapid and stable economic growth in bay, estuary and delta, guarantee the security of port, channel, maritime, oceanic engineering and resource development of oil and gas, and better escort for the social economy activities, it is essential to provide the information service of sediment and ocean hydrometeorology with width coverage, and forecasting and warning information. It is all the latest research results in the book, which involves many fields such as physical oceanography, meteorology, biology, chemistry, geology, environment, transportation and law and so on. The development of information assurance and prediction system for port shipping and ocean environment is a huge and arduous project. It is too hasty to finish the book, due to the limited knowledge of the author, the careless is unavoidable, cordially invites the readers to point out. Features: An entire system to forecast the port shipping and ocean environment information is proposed, including what is the port shipping and ocean environment information. The concept of port shipping and ocean environment data integration is presented, and the essential modules are built for the ocean dynamics model. The high performance port shipping and ocean environment data processing system is constructed, and the model dataset and geographic information is obtained to build the basic database. The application of information assurance technology for port shipping and ocean environment is conducted at Tianjin port and Yangshan Port. This book is meant for senior undergraduates and postgraduate students in the fields of geoinformatics, Port engineering and Marine engineering. Engineers and technicians in the related fields can also use it for reference.

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors' papers in top-tier, peer-reviewed, scientific conference proceedings and journals. The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms-such as simulation cloning methods and algorithms-that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena. Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.

Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors papers in top-tier, peer-reviewed, scientific conference proceedings and journals.

The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms such as simulation cloning methods and algorithms that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.

Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.

Identifies Recent Technological Developments Worldwide The field of grid computing has made rapid progress in the past few years, evolving and developing in almost all areas, including concepts, philosophy, methodology, and usages. Grid Computing: Infrastructure, Service, and Applications reflects the recent advances in this field, covering the research aspects that involve infrastructure, middleware, architecture, services, and applications. Grid Systems Across the Globe The first section of the book focuses on infrastructure and middleware and presents several national and international grid systems. The text highlights China Research and Development environment Over Wide-area Network (CROWN), several ongoing cyberinfrastructure efforts in New York State, and Enabling Grids for E-sciencE (EGEE), which is co-funded by the European Commission and the world's largest multidisciplinary grid infrastructure today. The second part of the book discusses recent grid service advances. The authors examine the UK National Grid Service (NGS), the concept of resource allocation in a grid environment, OMIIBPEL, and the possibility of treating scientific workflow issues using techniques from the data stream community. The book describes an SLA model, reviews portal and workflow technologies, presents an overview of PKIs and their limitations, and introduces PIndex, a peer-to-peer model for grid information services. New Projects and Initiatives The third section includes an analysis of innovative grid applications. Topics covered include the WISDOM initiative, incorporating flow-level networking models into grid simulators, system-level virtualization, grid usage in the high-energy physics environment in the LHC project, and the Service Oriented HLA RTI (SOHR) framework. With a comprehensive summary of past advances, this text is a window into the future of this nascent technology, forging a path for the next generation of cyberinfrastructure developers.

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.

This handbook covers recent advances in the integration of three areas, namely, cloud computing, cyber-physical systems, and the Internet of things which is expected to have a tremendous impact on our daily lives. It contains a total of thirteen peer-reviewed and edited chapters. This book covers topics such as context-aware cyber-physical systems, sustainable cloud computing, fog computing, and cloud monitoring; both the theoretical and practical aspects belonging to these topics are discussed. All the chapters also discuss open research challenges in the areas mentioned above. Finally, the handbook presents three use cases regarding healthcare, smart buildings and disaster management to assist the audience in understanding how to develop next-generation IoT- and cloud-enabled cyber-physical systems. This timely handbook is edited for students, researchers, as well as professionals who are interested in the rapidly growing fields of cloud computing, cyber-physical systems, and the Internet of things.

This handbook covers recent advances in the integration of three areas, namely, cloud computing, cyber-physical systems, and the Internet of things which is expected to have a tremendous impact on our daily lives. It contains a total of thirteen peer-reviewed and edited chapters. This book covers topics such as context-aware cyber-physical systems, sustainable cloud computing, fog computing, and cloud monitoring; both the theoretical and practical aspects belonging to these topics are discussed. All the chapters also discuss open research challenges in the areas mentioned above. Finally, the handbook presents three use cases regarding healthcare, smart buildings and disaster management to assist the audience in understanding how to develop next-generation IoT- and cloud-enabled cyber-physical systems. This timely handbook is edited for students, researchers, as well as professionals who are interested in the rapidly growing fields of cloud computing, cyber-physical systems, and the Internet of things.

This guidebook on e-science presents real-world examples of practices and applications, demonstrating how a range of computational technologies and tools can be employed to build essential infrastructures supporting next-generation scientific research. Each chapter provides introductory material on core concepts and principles, as well as descriptions and discussions of relevant e-science methodologies, architectures, tools, systems, services and frameworks. Features: includes contributions from an international selection of preeminent e-science experts and practitioners; discusses use of mainstream grid computing and peer-to-peer grid technology for "open" research and resource sharing in scientific research; presents varied methods for data management in data-intensive research; investigates issues of e-infrastructure interoperability, security, trust and privacy for collaborative research; examines workflow technology for the automation of scientific processes; describes applications of e-science.

This book comprehensively utilizes the new generation of artificial intelligence and remote sensing science and technology to systematically carry out researches on high-precision recognition, monitoring, analysis, and assessment of geological disasters by using different technologies of "ground, airspace, and space-based systems" and different scales of "target-semantic-region". The main contents include: 1) Intelligent interpretation theory and methods of geological disasters, 2) Intelligent analysis of landslide based on long-term ground monitoring data, 3) Deep learning-based remote sensing detection of landslide, 4) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data, 7) Intelligent monitoring of land subsidence in mining areas based on InSAR technology. The book is of interest to graduate student, scientific, and technological personnel who work in the area of geological disasters, natural hazards, remote sensing, and artificial intelligence.

Oil spills are a serious marine disaster. Oil spill accidents usually occur in shipping, ports and offshore oil development. Although most are emergent events, once an oil spill occurs, it will cause great harm to the marine ecological environment, and bring direct harm to the economic development along the affected coast as well as to human health and public safety. Information Engineering of Emergency Treatment for Marine Oil Spill Accidents analyzes the causes of these accidents, introduces China's emergency response system, discusses technologies such as remote sensing and monitoring of oil spill on the sea surface and oil fingerprint identification, studies model prediction of marine oil spill behavior and fate and emergency treatment technologies for oil spills on the sea surface, and emphatically introduces the emergency prediction and warning system for oil spills in the Bohai Sea as well as oil spill-sensitive resources and emergency resource management systems. Features: The status quo and causes of marine oil spill pollution, as well as hazards of oil spill on the sea. The emergency response system for marine oil spills. Model-based prediction methods of marine oil spills. A series of used and developing emergency treatments of oil spill on the sea. This book serves as a reference for scientific investigators who want to understand the key technologies for emergency response to marine oil spill accidents, including the current level and future development trend of China in this field.

Cloud computing has created a shift from the use of physical hardware and locally managed software-enabled platforms to that of virtualized cloud-hosted services. Cloud assembles large networks of virtual services, including hardware (CPU, storage, and network) and software resources (databases, message queuing systems, monitoring systems, and load-balancers). As Cloud continues to revolutionize applications in academia, industry, government, and many other fields, the transition to this efficient and flexible platform presents serious challenges at both theoretical and practical levels-ones that will often require new approaches and practices in all areas. Comprehensive and timely, Cloud Computing: Methodology, Systems, and Applications summarizes progress in state-of-the-art research and offers step-by-step instruction on how to implement it. Summarizes Cloud Developments, Identifies Research Challenges, and Outlines Future Directions Ideal for a broad audience that includes researchers, engineers, IT professionals, and graduate students, this book is designed in three sections: Fundamentals of Cloud Computing: Concept, Methodology, and Overview Cloud Computing Functionalities and Provisioning Case Studies, Applications, and Future Directions It addresses the obvious technical aspects of using Cloud but goes beyond, exploring the cultural/social and regulatory/legal challenges that are quickly coming to the forefront of discussion. Properly applied as part of an overall IT strategy, Cloud can help small and medium business enterprises (SMEs) and governments in optimizing expenditure on application-hosting infrastructure. This material outlines a strategy for using Cloud to exploit opportunities in areas including, but not limited to, government, research, business, high-performance computing, web hosting, social networking, and multimedia. With contributions from a host of internationally recognized researchers, this reference delves into everything from necessary changes in users' initial mindset to actual physical requirements for the successful integration of Cloud into existing in-house infrastructure. Using case studies throughout to reinforce concepts, this book also addresses recent advances and future directions in methodologies, taxonomies, IaaS/SaaS, data management and processing, programming models, and applications.

This book provides the users with quick and easy data acquisition, processing, storage and product generation services. It describes the entire life cycle of remote sensing data and builds an entire high performance remote sensing data processing system framework. It also develops a series of remote sensing data management and processing standards. Features: Covers remote sensing cloud computing Covers remote sensing data integration across distributed data centers Covers cloud storage based remote sensing data share service Covers high performance remote sensing data processing Covers distributed remote sensing products analysis

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 20th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, presents a representative and useful selection of articles covering a wide range of important topics in the domain of advanced techniques for big data management. Big data has become a popular term, used to describe the exponential growth and availability of data. The recent radical expansion and integration of computation, networking, digital devices, and data storage has provided a robust platform for the explosion in big data, as well as being the means by which big data are generated, processed, shared, and analyzed. In general, data are only useful if meaning and value can be extracted from them. Big data discovery enables data scientists and other analysts to uncover patterns and correlations through analysis of large volumes of data of diverse types. Insights gleaned from big data discovery can provide businesses with significant competitive advantages, leading to more successful marketing campaigns, decreased customer churn, and reduced loss from fraud. In practice, the growing demand for large-scale data processing and data analysis applications has spurred the development of novel solutions from both industry and academia.

Blockchain technology is a powerful, cost-effective method for network security. Essentially, it is a decentralized ledger for storing all committed transactions in trustless environments by integrating several core technologies such as cryptographic hash, digital signature and distributed consensus mechanisms. Over the past few years, blockchain technology has been used in a variety of network interaction systems such as smart contracts, public services, Internet of Things (IoT), social networks, reputation systems and security and financial services. With its widespread adoption, there has been increased focus on utilizing blockchain technologies to address network security concerns and vulnerabilities as well as understanding real-world security implications. The book begins with an introduction to blockchains, covering key principles and applications. Further chapters cover blockchain system architecture, applications and research issues; blockchain consensuses and incentives; blockchain applications, projects and implementations; blockchain for internet of things; blockchain in 5G and 6G networks; edgechain to provide security in organization based multi agent systems; blockchain driven privacy-preserving machine learning; performance evaluation of differential privacy mechanisms in blockchain based smart metering; scaling-out blockchains with sharding; blockchain for GIS; and finally blockchain applications in remote sensing big data management and production.

Distinguished from conventional parallel and distributed computing, the innovative field of grid computing focuses on resources shared among geographically distributed sites, providing high qualitative services for users and applications. Quantitative Quality of Service for Grid Computing: Applications for Heterogeneity, Large-Scale Distribution, and Dynamic Environments defines and characterizes the latest research achievements in grid computing. This book provides an important reference for academicians, practitioners, and researchers in fields such as parallel and distributed computing, high performance computing, and grid computing.

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and data becomes more critical with emerging security and privacy threats and challenges. This book presents a comprehensive view on how to advance security and privacy in big data, cloud computing, and their applications. Topics include cryptographic tools, SDN security, big data security in IoT, privacy preserving in big data, security architecture based on cyber kill chain, privacy-aware digital forensics, trustworthy computing, privacy verification based on machine learning, and chaos-based communication systems. This book is an essential reading for networking, computing, and communications professionals, researchers, students and engineers, working with big data and cloud computing.

Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos.

Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion.

The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.

Identifies Recent Technological Developments Worldwide

The field of grid computing has made rapid progress in the past few years, evolving and developing in almost all areas, including concepts, philosophy, methodology, and usages. Grid Computing: Infrastructure, Service, and Applications reflects the recent advances in this field, covering the research aspects that involve infrastructure, middleware, architecture, services, and applications.

Grid Systems Across the Globe

The first section of the book focuses on infrastructure and middleware and presents several national and international grid systems. The text highlights China Research and Development environment Over Wide-area Network (CROWN), several ongoing cyberinfrastructure efforts in New York State, and Enabling Grids for E-sciencE (EGEE), which is co-funded by the European Commission and the world s largest multidisciplinary grid infrastructure today.

The second part of the book discusses recent grid service advances. The authors examine the UK National Grid Service (NGS), the concept of resource allocation in a grid environment, OMIIBPEL, and the possibility of treating scientific workflow issues using techniques from the data stream community. The book describes an SLA model, reviews portal and workflow technologies, presents an overview of PKIs and their limitations, and introduces PIndex, a peer-to-peer model for grid information services.

New Projects and Initiatives

The third section includes an analysis of innovative grid applications. Topics covered include the WISDOM initiative, incorporating flow-level networking models into grid simulators, system-level virtualization, grid usage in the high-energy physics environment in the LHC project, and the Service Oriented HLA RTI (SOHR) framework.

With a comprehensive summary of past advances, this text is a window into the future of this nascent technology, forging a path for the next generation of cyberinfrastructure developers.