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This book highlights the developments, discoveries, and practical and advanced experiences related to responsive distributed computing and how it can support the deployment of trajectory-based applications in smart systems. Smart Trajectories: Metamodeling, Reactive Architecture for Analytics and Smart Applications deals with the representation and manipulation of smart trajectories in various applications and scenarios. Presented in three parts, the book first discusses the foundation and principles for spatial information systems, complex event processing, and building a reactive architecture. Next, the book discusses modeling and architecture in relation to smart trajectory metamodeling, mining and big trajectory data, and clustering trajectories. The final section discusses advanced applications and trends in the field, including congestion trajectory analytics and real-time Big Data analytics in cloud ecosystems. Metamodeling, distributed architectures, reactive programming, Big Data analytics, NoSQL databases, connected objects, and edge-fog-cloud computing form the basis of the concepts and applications discussed. The book also presents a number of case studies to demonstrate smart trajectories related to spatiotemporal events such as traffic congestion and pedestrian accidents. This book is intended for graduate students in computer engineering, spatial databases, complex event processing, distributed systems, and geographical information systems (GIS). The book will also be useful for practicing traffic engineers, city managers, and environmental engineers interested in monitoring and security analysis.
This proceedings book contains 37 papers selected from the submissions to the 6th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2019), which was held on 19–20 December, 2019, in Hanoi, Vietnam. The book covers theoretical and algorithmic as well as practical issues connected with several domains of Applied Mathematics and Computer Science, especially Optimization and Data Science. The content is divided into four major sections: Nonconvex Optimization, DC Programming & DCA, and Applications; Data Mining and Data Processing; Machine Learning Methods and Applications; and Knowledge Information and Engineering Systems. Researchers and practitioners in related areas will find a wealth of inspiring ideas and useful tools & techniques for their own work.
The continuing requirement for better urban transport systems and the need for a healthier environment have led to an increased level of research around the world. This is reflected in the proceedings presented at the well-established International Conference on Urban Transport and the Environment in the 21st Century. This volume presents the steady growth in research into urban transport and will be of particular interest to engineers, scientists and managers working in industry, universities, research organizations and government; involved in the planning and management of urban transportation systems and transport policy.The variety of topics covered are of primary importance for analysing the complex interaction in the urban transport environment and for establishing action strategies for transport and traffic problems. Featured topics include: Transport Modelling and Simulation; Public Transport Systems; Traffic Integration and Control; Infrastructure and Maintenance; Transport Sustainability; Environment and Ecological Aspects; Air and Noise Pollution; Energy and Transport Fuels; Transport Security and Safety; Road and Parking Pricing; Economic and Social Impact; Land Use and Transport Integration; Advanced Transport Systems; Transportation Demand Analysis.