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Nothing in cities makes sense except in the light of accessibility. Transport cannot be understood without reference to the location of activities (land use), and vice versa. To understand one requires understanding the other. However, for a variety of historical reasons, transport and land use are quite divorced in practice. Typical transport engineers only touch land use planning courses once at most, and only then if they attend graduate school. Land use planners understand transport the way everyone does, from the perspective of the traveler, not of the system, and are seldom exposed to transport aside from, at best, a lone course in graduate school. This text aims to bridge the chasm, helping engineers understand the elements of access that are associated not only with traffic, but also with human behavior and activity location, and helping planners understand the technology underlying transport engineering, the processes, equations, and logic that make up the transport half of the accessibility measure. It aims to help both communicate accessibility to the public.
This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.
This comprehensive new resource provides an introduction to fundamental Attribute Based Access Control (ABAC) models. This book provides valuable information for developing ABAC to improve information sharing within organizations while taking into consideration the planning, design, implementation, and operation. It explains the history and model of ABAC, related standards, verification and assurance, applications, as well as deployment challenges. Readers find authoritative insight into specialized topics including formal ABAC history, ABAC’s relationship with other access control models, ABAC model validation and analysis, verification and testing, and deployment frameworks such as XACML. Next Generation Access Model (NGAC) is explained, along with attribute considerations in implementation. The book explores ABAC applications in SOA/workflow domains, ABAC architectures, and includes details on feature sets in commercial and open source products. This insightful resource presents a combination of technical and administrative information for models, standards, and products that will benefit researchers as well as implementers of ABAC systems in the field.
TRB's Airport Cooperative Research Program (ACRP) Report 70: Guidebook for Implementing Intelligent Transportation Systems Elements to Improve Airport Traveler Access Information provides descriptions, component details, and examples of how airport ground access information can be disseminated using various intelligent transportation systems (ITS) technologies. The guidebook contains tables to help airport operators determine the applicability of certain ITS strategies based on airport operational needs and airport size. The printed version of the report includes an interactive CD-ROM designed to help explore and evaluate the information needs of various airport traveler market segments and to identify ITS technologies that best meet the needs of the airport user. The CD-ROM also contains a decision support tool that allows users to identify appropriate methods of delivering airport traveler information based on the airport traveler market segment.
Accessible Elements informs science educators about current practices in online and distance education: distance-delivered methods for laboratory coursework, the requisite administrative and institutional aspects of online and distance teaching, and the relevant educational theory. Delivery of university-level courses through online and distance education is a method of providing equal access to students seeking post-secondary education. Distance delivery offers practical alternatives to traditional on-campus education for students limited by barriers such as classroom scheduling, physical location, finances, or job and family commitments. The growing recognition and acceptance of distance education, coupled with the rapidly increasing demand for accessibility and flexible delivery of courses, has made distance education a viable and popular option for many people to meet their science educational goals.
Elements of Information Organization and Dissemination provides Information on how to organize and disseminate library and information science (LIS), a subject that is taught in many international Library Information Science university programs. While there are many books covering different areas of the subject separately, this book covers the entire subject area and incorporates the latest developments. - Presets an overview of the entire subject, covering all relevant areas of library and information science - Contains bulletpoints that highlight key features in each chapter - Written in an accessible language, this book is aimed at a wide audience of LIS academics
Shows the interconnections among the elements of well-being, how they cannot be considered independently, and provides readers with a research-based approach to improving all aspects of their lives.
Transport cannot be understood without reference to the location of activities (land use), and vice versa. To understand one requires understanding the other. However, for a variety of historical reasons, transport and land use are quite divorced in practice. Typical transport engineers only touch land use planning courses once at most, and only then if they attend graduate school. Land use planners understand transport the way everyone does, from the perspective of the traveler, not of the system, and are seldom exposed to transport aside from, at best, a lone course in graduate school. This text aims to bridge the chasm, helping engineers understand the elements of access that are associated not only with traffic, but also with human behavior and activity location, and helping planners understand the technology underlying transport engineering, the processes, equations, and logic that make up the transport half of the accessibility measure. It aims to help both communicate accessibility to the public.
This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system.
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.