1,216 research outputs found

    Finite Sholander Trees, Trees, and their Betweenness

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    We provide a proof of Sholander's claim (Trees, lattices, order, and betweenness, Proc. Amer. Math. Soc. 3, 369-381 (1952)) concerning the representability of collections of so-called segments by trees, which yields a characterization of the interval function of a tree. Furthermore, we streamline Burigana's characterization (Tree representations of betweenness relations defined by intersection and inclusion, Mathematics and Social Sciences 185, 5-36 (2009)) of tree betweenness and provide a relatively short proof.Comment: 8 page

    Finite sholander trees, trees, and their betweennesses

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    We provide a proof of a claim made by Sholander (Trees, lattices, order, and betweenness, {\it Proc. Amer. Math. Soc.} {\bf 3}, 369-381 (1952)) concerning the representability of collections of so-called segments by trees. Furthermore, we strengthen Burigana's axiomatic characterization of so-called betweennesses induced by trees (Tree representations of betweenness relations defined by intersection and inclusion, {\it Mathematics and Social Sciences} {\bf 185}, 5-36 (2009)) and provide a short proof

    Null-homotopic graphs and triangle-completions of spanning trees

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    We prove that a connected graph whose cycle space is generated by its triangles and which is either planar or of maximum degree at most four has the property that it arises from an arbitrary spanning tree by iteratively adding edges which complete triangles

    Toward a Digital Platform for Spacecraft Manufacturing

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    Professionals of many disciplines are involved in a spacecraft mission. They all use different software tools that are tailored to their tasks and they share data in various ways among themselves. These data sharing activities form a network, which, given modern software engineering practices, offers a lot of opportunities for improvement: simplify data source discoverability, automate previously manual data sharing activities, and better make use available data sources. To simplify data source discoverability, we propose a digital platform with a serviceoriented architecture. Such an architecture also helps to better make use of available data sources. Additionally, we present our projects that automate previously manual data sharing activities and that make better use of available data sources. With the development of the digital platform we aim at providing a significant reduction in resource expenditure, especially time expenditure, for spacecraft missions

    SmartAQnet: remote and in-situ sensing of urban air quality

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    our time. However, it is very difficult for many cities to take measures to accommodate today’s needs concerning e.g. mobility, housing and work, because a consistent fine-granular data and information on causal chains is largely missing. This has the potential to change, as today, both large-scale basic data as well as new promising measuring approaches are becoming available. The project “SmartAQnet”, funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI), is based on a pragmatic, data driven approach, which for the first time combines existing data sets with a networked mobile measurement strategy in the urban space. By connecting open data, such as weather data or development plans, remote sensing of influencing factors, and new mobile measurement approaches, such as participatory sensing with low-cost sensor technology, “scientific scouts” (autonomous, mobile smart dust measurement device that is auto-calibrated to a high-quality reference instrument within an intelligent monitoring network) and demand-oriented measurements by light-weight UAVs, a novel measuring and analysis concept is created within the model region of Augsburg, Germany. In addition to novel analytics, a prototypical technology stack is planned which, through modern analytics methods and Big Data and IoT technologies, enables application in a scalable way

    SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors

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    The increasing attention paid to urban air quality modeling places higher requirements on urban air quality datasets. This article introduces a new urban air quality dataset—the SmartAQnet2020 dataset—which has a large span and high resolution in both time and space dimensions. The dataset contains 248,572,003 observations recorded by over 180 individual measurement devices, including ceilometers, Radio Acoustic Sounding System (RASS), mid- and low-cost stationary measuring equipment equipped with meteorological sensors and particle counters, and low-weight portable measuring equipment mounted on different platforms such as trolley, bike, and UAV
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