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End date: 2019 × Start date: 2014 × DDC: 004 × Version: publishedVersion × Publisher: Amsterdam [u.a.] : Elsevier Science ×

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Now showing 1 - 6 of 6
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    A survey on Bluetooth multi-hop networks
    (Amsterdam [u.a.] : Elsevier Science, 2019) Todtenberg, Nicole; Kraemer, Rolf
    Bluetooth was firstly announced in 1998. Originally designed as cable replacement connecting devices in a point-to-point fashion its high penetration arouses interest in its ad-hoc networking potential. This ad-hoc networking potential of Bluetooth is advertised for years - but until recently no actual products were available and less than a handful of real Bluetooth multi-hop network deployments were reported. The turnaround was triggered by the release of the Bluetooth Low Energy Mesh Profile which is unquestionable a great achievement but not well suited for all use cases of multi-hop networks. This paper surveys the tremendous work done on Bluetooth multi-hop networks during the last 20 years. All aspects are discussed with demands for a real world Bluetooth multi-hop operation in mind. Relationships and side effects of different topics for a real world implementation are explained. This unique focus distinguishes this survey from existing ones. Furthermore, to the best of the authors’ knowledge this is the first survey consolidating the work on Bluetooth multi-hop networks for classic Bluetooth technology as well as for Bluetooth Low Energy. Another individual characteristic of this survey is a synopsis of real world Bluetooth multi-hop network deployment efforts. In fact, there are only four reports of a successful establishment of a Bluetooth multi-hop network with more than 30 nodes and only one of them was integrated in a real world application - namely a photovoltaic power plant. © 2019 The Authors
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    Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change
    (Amsterdam [u.a.] : Elsevier Science, 2019) Warren, R.F.; Edwards, N.R.; Babonneau, F.; Bacon, P.M.; Dietrich, J.P.; Ford, R.W.; Garthwaite, P.; Gerten, D.; Goswami, S.; Haurie, A.; Hiscock, K.; Holden, P.B.; Hyde, M.R.; Joshi, S.R.; Kanudia, A.; Labriet, M.; Leimbach, M.; Oyebamiji, O.K.; Osborn, T.; Pizzileo, B.; Popp, A.; Price, J.; Riley, G.D.; Schaphoff, S.; Slavin, P.; Vielle, M.; Wallace, C.
    We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal. © 2018 The Authors
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    Web technologies for environmental Big Data
    (Amsterdam [u.a.] : Elsevier Science, 2014) Vitolo, Claudia; Elkhatib, Yehia; Reusser, Dominik; Macleod, Christopher J.A.; Buytaert, Wouter
    Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.
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    pyGIMLi: An open-source library for modelling and inversion in geophysics
    (Amsterdam [u.a.] : Elsevier Science, 2017) Rücker, Carsten; Günther, Thomas; Wagner, Florian M.
    Many tasks in applied geosciences cannot be solved by single measurements, but require the integration of geophysical, geotechnical and hydrological methods. Numerical simulation techniques are essential both for planning and interpretation, as well as for the process understanding of modern geophysical methods. These trends encourage open, simple, and modern software architectures aiming at a uniform interface for interdisciplinary and flexible modelling and inversion approaches. We present pyGIMLi (Python Library for Inversion and Modelling in Geophysics), an open-source framework that provides tools for modelling and inversion of various geophysical but also hydrological methods. The modelling component supplies discretization management and the numerical basis for finite-element and finite-volume solvers in 1D, 2D and 3D on arbitrarily structured meshes. The generalized inversion framework solves the minimization problem with a Gauss-Newton algorithm for any physical forward operator and provides opportunities for uncertainty and resolution analyses. More general requirements, such as flexible regularization strategies, time-lapse processing and different sorts of coupling individual methods are provided independently of the actual methods used. The usage of pyGIMLi is first demonstrated by solving the steady-state heat equation, followed by a demonstration of more complex capabilities for the combination of different geophysical data sets. A fully coupled hydrogeophysical inversion of electrical resistivity tomography (ERT) data of a simulated tracer experiment is presented that allows to directly reconstruct the underlying hydraulic conductivity distribution of the aquifer. Another example demonstrates the improvement of jointly inverting ERT and ultrasonic data with respect to saturation by a new approach that incorporates petrophysical relations in the inversion. Potential applications of the presented framework are manifold and include time-lapse, constrained, joint, and coupled inversions of various geophysical and hydrological data sets.
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    Rapid aggregation of global gridded crop model outputs to facilitate cross-disciplinary analysis of climate change impacts in agriculture
    (Amsterdam [u.a.] : Elsevier Science, 2015) Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, Carol
    We discuss an on-line tool that facilitates access to the large collection of climate impacts on crop yields produced by the Agricultural Model Intercomparison and Improvement Project. This collection comprises the output of seven crop models which were run on a global grid using climate data from five different general circulation models under the current set of representative pathways. The output of this modeling endeavor consists of more than 36,000 publicly available global grids at a spatial resolution of one half degree. We offer flexible ways to aggregate these data while reducing the technical barriers implied by learning new download platforms and specialized formats. The tool is accessed trough any standard web browser without any special bandwidth requirement.
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    To what extent is climate change adaptation a novel challenge for agricultural modellers?
    (Amsterdam [u.a.] : Elsevier Science, 2019) Kipling, R.P.; Topp, C.F.E.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.J.; Lauwers, L.; Özkan Gülzari, Ş.; Reidsma, P.; Rolinski, S.; Ruiz-Ramos, M.; Sandars, D.L.; Sándor, R.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Schönhart, M.; Seddaiu, G.; van Middelkoop, J.; Shrestha, S.; Weindl, I.; Eory, V.
    Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change. © 2019 The Authors