The thought experiment proposed by Langevin in 1911, known under the popular names, 'Clock Paradox' or 'Twin Paradox', is the most surprising result of the theory of Relativity: A twin who travels to a star at nearly the velocity of light comes back to Earth and finds his twin brother much older. In over a century, several thousands of published articles debated both in favor of and against this result. Unique to the physics of Relativity, this baffling phenomenon is analyzed as a main goal of this book.Among an incredible number of solutions, is there one of simplicity and clarity which may be accepted unanimously by all of the physics community? The answer is yes and this solution, which has its origin in Einstein himself, is developed in the framework of the Special Theory of Relativity. In detailing this solution, it is shown that the essential ingredient to understand the theory is the acceleration of the twins. All the models which do not include acceleration are incompatible with the original idea of Langevin. If one considers this phenomenon, several questions come to mind. Why did physicists debate excessively on the paradox and struggle to reach an agreement? Why was there resistance to integrate acceleration into their studies? Why is the solution developed in this book known only by a minority of scientists?Written for physicists, historians and philosophers of science, this book seeks to answer these questions based on (1) the psychological difficulty to accept the theoretical results, and (2) the fact that scientific knowledge is not uniformly distributed among scientists.

This synthesis reports on the state of the practice in real-time traveler information systems. Emphasis is placed on the needs and expectations of travelers, the current status of a variety of traveler information systems in the United States, available and emerging data sources, and business models for sustaining traveler information. This synthesis will benefit state DOT transportation managers and others that provide or seek to provide affordable, accurate, timely, and effective information in a format that travelers can use.

This book deals with the estimation of travel time in a very comprehensive and exhaustive way. Travel time information is and will continue to be one key indicator of the quality of service of a road network and a highly valued knowledge for drivers. Moreover, travel times are key inputs for comprehensive traffic management systems. All the above-mentioned aspects are covered in this book. The first chapters expound on the different types of travel time information that traffic management centers work with, their estimation, their utility and their dissemination. They also remark those aspects in which this information should be improved, especially considering future cooperative driving environments.Next, the book introduces and validates two new methodologies designed to improve current travel time information systems, which additionally have a high degree of applicability: since they use data from widely disseminated sources, they could be immediately implemented by many administrations without the need for large investments. Finally, travel times are addressed in the context of dynamic traffic management systems. The evolution of these systems in parallel with technological and communication advancements is thoroughly discussed. Special attention is paid to data analytics and models, including data-driven approaches, aimed at understanding and predicting travel patterns in urban scenarios. Additionally, the role of dynamic origin-to-destination matrices in these schemes is analyzed in detail.

This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-toll highways with the existing surveillance equipment, suggesting that highway operators might provide their customers with such an added value with little additional investment in technology.

This two volume set LNCS 9261 and LNCS 9262 constitutes the refereed proceedings of the 26th International Conference on Database and Expert Systems Applications, DEXA 2015, held in Valencia, Spain, September 1-4, 2015. The 40 revised full papers presented together with 32 short papers, and 2 keynote talks, were carefully reviewed and selected from 125 submissions. The papers discuss a range of topics including: temporal, spatial and high dimensional databases; semantic Web and ontologies; modeling, linked open data; NoSQLm NewSQL, data integration; uncertain data and inconsistency tolerance; database system architecture; data mining, query processing and optimization; indexing and decision support systems; modeling, extraction, social networks; knowledge management and consistency; mobility, privacy and security; data streams, Web services; distributed, parallel and cloud databases; information retrieval; XML and semi-structured data; data partitioning, indexing; data mining, applications; WWW and databases; data management algorithms. These volumes also include accepted papers of the 8th International Conference on Data Management in Cloud, Grid and P2P Systems, Globe 2015, held in Valencia, Spain, September 2, 2015. The 8 full papers presented were carefully reviewed and selected from 13 submissions. The papers discuss a range of topics including: MapReduce framework: load balancing, optimization and classification; security, data privacy and consistency; query rewriting and streaming.