Search

Accurate and fast path computation is essential for applications such as onboard navigation systems and traffic network routing. While a number of heuristic algorithms have been developed in the past few years for faster path queries, the accuracy of them are always far below satisfying. In this paper, we first develop an agglomerative graph partitioning method for generating high balanced traverse distance partitions, and we constitute a three-level graph model based on the graph partition scheme for structuring the urban road network. Then, we propose a new hierarchical path computation algorithm, which benefits from the hierarchical graph model and utilizes a region pruning strategy to significantly reduce the search space without compromising the accuracy. Finally, we present a detailed experimental evaluation on the real urban road network of New York City, and the experimental results demonstrate the effectiveness of the proposed approach to generate optimal fast paths and to facilitate real-time routing applications. [ABSTRACT FROM AUTHOR]

This article argues that U.S. education reforms for "failing" schools are strikingly similar to a domestic Structural Adjustment Program; and that comparing the two clarifies: how K–12 schools are neoliberalized and how neoliberalism's key feature is the making of a larger yet less democratic state. The study contrasts with the scholarship claiming that reforms epitomized by the "No Child Left Behind Act" are neoliberal because they stem from interests in privatization for capital accumulation. The analysis focuses on a "failing" school navigating federal reforms in New York State, drawing on education policy, school documents, ethnography, and interviews. It shows how the neoliberal state took power from local school authorities, and largely did not shrink the state via privatization. This work illustrates how neoliberal reforms for "failing" schools are at least as much about power as they are about profits and demonstrates the large-scale continuity in neoliberal restructuring strategies and outcomes. [ABSTRACT FROM AUTHOR]

Motor vehicle crashes are a leading cause of injury related deaths. Urban areas accommodate multiple road users and pedestrians account for a larger share of traffic fatalities. Speed reduction has been one component of New York City's multidisciplinary approach to reduce traffic fatalities—Vision Zero. Data from the New York City (NYC) Community Health Survey 2015–2016 were used to document population-based estimates of self-reported speeding (defined as driving ten miles per hour or more over the posted speed limit in the past 30 days) among NYC adult drivers collected soon after the adoption of Vision Zero in 2014. Self-reported speeding is common, with nearly two-thirds (63%) of adult drivers indicating they ever sped and 13% often speeding. In adjusted multivariable models, often speeding was more common among younger drivers vs. older drivers (adjusted prevalence ratio: 2.77; 95%CI 1.93–3.98), males vs. females (adjusted prevalence ratio: 1.59; 95%CI 1.35–1.87), wealthier drivers vs. poorer drivers (adjusted prevalence ratio: 1.37; 95%CI 1.10–1.70) and those reporting worse perceived social cohesion vs. better perceived social cohesion (adjusted prevalence ratio 1.51; 95%CI 1.09–2.10). Population-based health surveys facilitate exploration of a range of potential influences on health behaviors. [ABSTRACT FROM AUTHOR]

Child–nature interaction has undergone drastic changes in modern history, from a free outdoor childhood to a confined daily life connected to electronic devices, with negative consequences to development and well-being. Any resulting lack of connection to the natural environment can hamper involvement in solving environmental problems. This research attempted to assess children’s perceptions of nature, as well as their feelings and values. Six- to 14-year-old children from the Tupinambá group (n = 91), an indigenous society in Brazil, and from New York (n = 54) drew pictures of nature and answered five questions about their drawings, feelings, and values in regard to natural environments. Quantitative (descriptive) and qualitative (content) analyses of the drawings were carried out, and their liveness and animism were estimated. The answers given by children to the questions about nature were organized into emerging categories from the data. The Tupinambá children’s drawings were generally livelier than those of the New York children. However, the difference failed to reach statistical significance among the younger children, and the difference only approached significance among the older children. The drawings of the Tupinambá contained more animism, depicting non-humans and non-animals with facial expressions, than those of the New Yorkers. Compared with the New Yorkers, the Tupinambá children more often included human constructions such as roads and houses in their drawings. The indigenous children more often saw human and non-human elements as integrated compared with the nonindigenous children. The study reinforces theoretical tendencies about the environmental perception of children in relation to the natural environment and highlights peculiarities of the participating groups, indicating relevant questions for future investigations. [ABSTRACT FROM AUTHOR]

Surveillance technologies may be capable of monitoring a domain, but they need a sufficiently orderly domain to monitor. This article examines the secretive effort to institute artificial-intelligence-based ‘smart surveillance’ in the New York subway, using object- and pattern-recognition algorithms to identify dangerous activities in video feeds, such as a person abandoning a package. By considering the necessary preconditions for computer vision systems to recognize patterns and objects, I show how smart surveillance was challenged by the lack of visual and social uniformities necessary for smart surveillance systems to make its fine-toothed distinctions. In spite of vast resources and involvement of a major military contractor, the project was eventually deemed a failure. Although problems in computer vision are being incrementally solved, those improvements do not yet add up to a holistic technology capable of parsing the real-world ambiguity of open-ended settings which do not meet the assumptions of the detection algorithms. In the absence of technologies that can handle the actual mess, the world itself must cooperate, but it often does not. The article demonstrates the importance of looking beyond the claims of technical efficacy in the study of security and surveillance to discover how technologies of inspection and control actually work, as a means to cut through the heavy rhetorical packaging in which they are sold to their publics. [ABSTRACT FROM AUTHOR]