1,721,034 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Bayesian Data-Driven Models for Irrigation Water Management

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    A crucial decision in the real-time management of today’s irrigation systems involves the coordination of diversions and delivery of water to croplands. Since most irrigation systems experience significant lags between when water is diverted and when it should be delivered, an important technical innovation in the next few years will involve improvements in short-term irrigation demand forecasting. The main objective of the researches presented was the development of these critically important models: (1) potential evapotranspiration forecasting; (2) hydraulic model error correction; and (3) estimation of aggregate water demands. These tools are based on statistical machine learning or data-driven modeling. These, of wide application in several areas of engineering analysis, can be used in irrigation and system management to provide improved and timely information to water managers. The development of such models is based on a Bayesian data-driven algorithm called the Relevance Vector Machine (RVM), and an extension of it, the Multivariate Relevance Vector Machine (MVRVM). The use of these types of learning machines has the advantage of avoidance of model overfitting, high robustness in the presence of unseen data, and uncertainty estimation for the results (error bars). The models were applied in an irrigation system located in the Lower Sevier River Basin near Delta, Utah. For the first model, the proposed method allows for estimation of future crop water demand values up to four days in advance. The model uses only daily air temperatures and the MVRVM as mapping algorithm. The second model minimizes the lumped error occurring in hydraulic simulation models. The RVM is applied as an error modeler, providing estimations of the occurring errors during the simulation runs. The third model provides estimation of future water releases for an entire agricultural area based on local data and satellite imagery up to two days in advance. The results obtained indicate the excellent adequacy in terms of accuracy, robustness, and stability, especially in the presence of unseen data. The comparison provided against another data-driven algorithm, of wide use in engineering, the Multilayer Perceptron, further validates the adequacy of use of the RVM and MVRVM for these types of processes

    Vicarious Calibration of sUAS Thermal Imagery for Scientific Remote Sensing Applications [B53H-0607]

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    Small Unmanned Aerial Systems (sUAS) have become an accessible technology for collection of spatially distributed temperature data at fine resolution. Nevertheless, lack of standard procedures for atmospheric temperature correction can have an adverse impact on the conclusions and replicability of studies using this technology. This work presents a vicarious calibration methodology for sUAS thermal imagery traceable back to NIST standards. For this methodology, a 3-yr. data collection campaign with a sUAS technology, called “AggieAir”, developed at the Utah Water Research Laboratory, was performed under different daytime conditions. A comparison between original and vicarious calibration for the sUAS thermal imagery is provided, along with a set of recommendations for scientific thermal sUAS applications

    Initiative for the Production of Spatial Evapotranspiration at the Upper Colorado River Basin

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    Evapotranspiration (ET) is a key component in any hydrologic cycle at farm and basin levels, especially at the Upper Colorado River Basin. Traditionally, ET estimation is done by using data from the closest weather station, providing a single ET value for an irrigation or sub-basin area. In consequence, this ET estimation procedure does not account for the geographic variability of water consumption within a geographic area. Nevertheless, current state-of-the-art research on ET estimation can already provide accurate spatial measurement of this key component given the availability of geo-referenced imagery and weather station data across the area. Until now, the States within the Upper Colorado River Basin have restricted themselves to small efforts to produce spatial ET information, mostly of local impact, with infrequent updates and limited access. To overcome these constraints, a combined effort from research centers and interested government and private parties across the Upper Colorado can achieve the goal of production, standardization and broad access of spatial ET. A recent initiative that includes several Utah parties united by a common vision of better water management at basin and state levels has begun the implementation of methods to produce spatial ET information for the Upper Colorado River Basin. The initiative includes the Utah Divisions of Water Rights and Water Resources in the Utah Department of Natural Resources, NOAA, the US Bureau of Reclamation, and the Utah Water Research Laboratory. This presentation provides a summary of the benefits, objectives, and milestones to achieve the implementation of a state-wide spatial ET system. An invitation is extended to new partners to join and strengthen the group’s capabilities for the production and use of spatial ET information across the Upper Colorado River Basin

    Remote Sensing as a Tool for Water Management

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    Abstract: Advances in remote sensing technology (collection, data management, and analysis) are allowing development of water management procedures that are beneficial due to the spatial and historical coverage this technology can provide for the state of Utah. The remote sensing technology (from UAV/drones to satellites) is already intensively used in several US western states and USU research. In this presentation we introduce some of the current and incoming remote sensing research and products at UWRL as well some of the synergistics efforts in place that can benefit management of water resources in the state of Utah

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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