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.
This book examines the theory and methods of remote sensing intelligent interpretation based on deep learning. Based on geological and environmental effects on mines, this book constructs a set of systematic mine remote sensing datasets focusing on the multi-level task with the system of “target detection→scene classification→semantic segmentation." Taking China’s Hubei Province as an example, this book focuses on the following four aspects: 1. Development of a multiscale remote sensing dataset of the mining area, including mine target remote sensing dataset, mine (including non-mine areas) remote sensing scene dataset, and semantic segmentation remote sensing dataset of mining land cover. The three datasets are the basis of intelligent interpretation based on deep learning. 2. Research on mine target remote sensing detection method based on deep learning. 3. Research on remote sensing scene classification method of mine and non-mine areas based on deep learning. 4. Research on the fine-scale classification method of mining land cover based on semantic segmentation. The book is a valuable reference both for scholars, practitioners and as well as graduate students who are interested in mining environment research.
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
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.
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.
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) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 4) Deep learning-based remote sensing detection of landslide, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data. 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.
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
This book presents the theories and methods for geology intelligent interpretation based on deep learning and remote sensing technologies. The main research subjects of this book include lithology and mineral abundance. This book focuses on the following five aspects: 1. Construction of geology remote sensing datasets from multi-level (pixel-level, scene-level, semantic segmentation-level, prior knowledge-assisted, transfer learning dataset), which are the basis of geology interpretation based on deep learning. 2. Research on lithology scene classification based on deep learning, prior knowledge, and remote sensing. 3. Research on lithology semantic segmentation based on deep learning and remote sensing. 4. Research on lithology classification based on transfer learning and remote sensing. 5. Research on inversion of mineral abundance based on the sparse unmixing theory and hyperspectral remote sensing. The book is intended for undergraduate and graduate students who are interested in geology, remote sensing, and artificial intelligence. It is also used as a reference book for scientific and technological personnel of geological exploration.
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 examines the theory and methods of remote sensing intelligent interpretation based on deep learning. Based on geological and environmental effects on mines, this book constructs a set of systematic mine remote sensing datasets focusing on the multi-level task with the system of “target detection→scene classification→semantic segmentation." Taking China’s Hubei Province as an example, this book focuses on the following four aspects: 1. Development of a multiscale remote sensing dataset of the mining area, including mine target remote sensing dataset, mine (including non-mine areas) remote sensing scene dataset, and semantic segmentation remote sensing dataset of mining land cover. The three datasets are the basis of intelligent interpretation based on deep learning. 2. Research on mine target remote sensing detection method based on deep learning. 3. Research on remote sensing scene classification method of mine and non-mine areas based on deep learning. 4. Research on the fine-scale classification method of mining land cover based on semantic segmentation. The book is a valuable reference both for scholars, practitioners and as well as graduate students who are interested in mining environment research.
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) Intelligent analysis of landslide evolution based on optical satellite remote sensing data, 4) Deep learning-based remote sensing detection of landslide, 5) Intelligent assessment methods of landslide susceptibility, 6) Intelligent recognition of ground figure based on airspace-based remote sensing data. 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.
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.
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.
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.
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.
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.
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