Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions. The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection. Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development. Key Features: Describes the development and challenges associated with Intelligent Transportation Systems (ITS) Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersection Has the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts
To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to make this decoupling a reality. The proposed syste
This book covers major topics in the Anglo-American tradition, including deixis, presupposition, implicature, speech acts, and (im)politeness. These key topics are illustrated with examples and case studies from various contexts such as romantic relationships, online forums, social media posts, and popular culture. The book also includes a methods chapter that offers a hands-on guide for literature search, data collection, and data analysis. This book is particularly suitable for readers who have no prior knowledge of pragmatics.
This SpringerBrief presents the concept of the smart grid architecture and investigates the security issues of the smart grid and the existing encrypted data query techniques. Unique characteristics of smart grid impose distinguished challenges on this investigation, such as multidimensional attributes in metering data and finer grained query on each dimension. Three kinds of queries are introduced, namely, equality query, conjunctive query and range query. For the equality query over encrypted metering data, an efficient searchable encryption scheme is introduced and can be applied for auction in emerging smart grid marketing. Later chapters examine the conjunctive query and range query over encrypted data. Different techniques are used, including the Public key Encryption with Keyword Search (PEKS) and Hidden Vector Encryption (HVE), to construct the comparison predicate and range query predicate. Their correctness is demonstrated in the book. Concise and practical, Encrypted Data Querying in Smart Grids is valuable for professionals and researchers involved in data privacy or encryption. It is also useful for graduate students interested in smart grid and related technologies.
This study has developed a complete procedure for the measurement of oxygen isotopes in arsenic oxyanions in natural waters by using different adsorbents. The experimental results of kinetic exchange of oxygen between AsO43- and water show that the entire exchange procedure happens in a very short time at different pH conditions and temperatures.
Computational Fluid-Structure Interaction: Methods, Models, and Applications provides detailed explanations of a range of FSI models, their mathematical formulations, validations, and applications, with an emphasis on conservative unstructured-grid FVM. The first part of the book presents the nascent numerical methods, algorithms and solvers for both compressible and incompressible flows, computational structural dynamics (CSD), parallel multigrid, IOM, IMM and ALE methods. The second half covers the validations of these numerical methods and solvers, as well as their applications in a broad range of areas in basic research and engineering. - Provides a comprehensive overview of the latest numerical methods used in FSI, including the unstructured-grid finite volume method (FVM), parallel multigrid scheme, overlapping mesh, immersed object method (IOM), immersed membrane method (IMM), arbitrary Lagragian-Eulerian (ALE), and more - Provides full details of the numerical methods, solvers and their validations - Compares different methods to help readers more effectively choose the right approach for their own FSI problems - Features real-life FSI case studies, such as large eddy simulation of aeroelastic flutter of a wing, parallel computation of a bio-prosthetic heart valve, and ALE study of a micro aerial vehicle
The integration of MOEMS microelement arrays into smart glass for light steering shows promising features and valuable advantages in terms of energy conservation, enhancing lighting conditions, and improving human comfort. This study explores various actuation solutions and concludes that electrostatically actuated MOEMS devices from INA offer rapid actuation speed, minimum energy consumption, long lifetime and high stability.
Applied Geochemistry: Advances in Mineral Exploration Techniques is a book targeting all levels of exploration geologists, geology students and geoscientists working in the mining industry. This reference book covers mineral exploration techniques from multiple dimensions, including the application of statistics - both principal component analysis and factor analysis - to multifractal modeling. The book explains these approaches step-by-step and gives their limitations. In addition to techniques and applications in mineral exploration, Applied Geochemistry describes mineral deposits and the theories underpinning their formation through worldwide case studies.
This book focuses on three emerging research topics in mobile social networks (MSNs): privacy-preserving profile matching (PPM) protocols, privacy-preserving cooperative data forwarding (PDF) protocols, and trustworthy service evaluation (TSE) systems. The PPM helps two users compare their personal profiles without disclosing the profiles. The PDF helps users forward data to their friends via multiple cooperative relay peers while preserving their identity and location privacy. The TSE enables users to locally share service reviews on the vendors such that users receive more valuable information about the services not only from vendors but also from their trusted social friends. The authors address both theoretic and practical aspects of these topics by introducing the system model, reviewing the related works, and presenting the solutions. Security and Privacy for Mobile Social Networks further provides the security analysis and the performance evaluation based on real-trace simulations. It also summarizes the future research directions for this rapidly growing area of research. The book will be valuable for researchers and practitioners who work with mobile social networks, communication platforms, wireless communication techniques, and internet applications. "Suitable for any type of reader as an introduction to the topic... The chapters are well motivated and presented... It is recommended for researchers." -ACM Computing Reviews, 21 July 2014
Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches, including a two-stream convolutional network architecture for vehicle detection, tracking, and near-miss detection; an unsupervised approach to detect near-misses in fisheye intersection videos using a deep learning model combined with a camera calibration and spline-based mapping method; and algorithms that utilize video analysis and signal timing data to accurately detect and categorize events based on the phase and type of conflict in pedestrian-vehicle and vehicle-vehicle interactions. The book makes use of a real-time trajectory prediction approach, combined with aligned Google Maps information, to estimate vehicle travel time across multiple intersections. Novel visualization software, designed by the authors to serve traffic practitioners, is used to analyze the efficiency and safety of intersections. The software offers two modes: a streaming mode and a historical mode, both of which are useful to traffic engineers who need to quickly analyze trajectories to better understand traffic behavior at an intersection. Overall, this book presents a comprehensive overview of the application of computer vision and machine learning to solve transportation-related problems. Video Based Machine Learning for Traffic Intersections demonstrates how these techniques can be used to improve safety, efficiency, and traffic flow, as well as identify potential conflicts and issues before they occur. The range of novel approaches and techniques presented offers a glimpse of the exciting possibilities that lie ahead for ITS research and development. Key Features: Describes the development and challenges associated with Intelligent Transportation Systems (ITS) Provides novel visualization software designed to serve traffic practitioners in analyzing the efficiency and safety of an intersection Has the potential to proactively identify potential conflict situations and develop an early warning system for real-time vehicle-vehicle and pedestrian-vehicle conflicts
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