The Experts below are selected from a list of 15009 Experts worldwide ranked by ideXlab platform

Rueixi Chen - One of the best experts on this subject based on the ideXlab platform.

  • temperature control framework using wireless sensor networks and Geostatistical Analysis for total spatial awareness
    International Symposium on Pervasive Systems Algorithms and Networks, 2009
    Co-Authors: Charles C Castello, Jeffrey Fan, A Davari, Rueixi Chen
    Abstract:

    This paper presents a novel framework for intelligent temperature control in smart homes using Wireless Sensor Networks (WSN) and Geostatistical Analysis for total spatial awareness. Sampled temperature readings from sensor nodes have the ability to inform the system on temperatures at specific locations. However, these locations where readings are taken do not completely describe the area under consideration. To solve this issue, Geostatistical techniques are utilized, which include variography and kriging to predict temperature where measurements are not available. This added information would allow the system to control cooling and heating mechanisms in buildings at every location for improved user comfort.

  • ISPAN - Temperature Control Framework Using Wireless Sensor Networks and Geostatistical Analysis for Total Spatial Awareness
    2009 10th International Symposium on Pervasive Systems Algorithms and Networks, 2009
    Co-Authors: Charles C Castello, Jeffrey Fan, A Davari, Rueixi Chen
    Abstract:

    This paper presents a novel framework for intelligent temperature control in smart homes using Wireless Sensor Networks (WSN) and Geostatistical Analysis for total spatial awareness. Sampled temperature readings from sensor nodes have the ability to inform the system on temperatures at specific locations. However, these locations where readings are taken do not completely describe the area under consideration. To solve this issue, Geostatistical techniques are utilized, which include variography and kriging to predict temperature where measurements are not available. This added information would allow the system to control cooling and heating mechanisms in buildings at every location for improved user comfort.

Antonio Galgaro - One of the best experts on this subject based on the ideXlab platform.

  • insights into bedrock surface morphology using low cost passive seismic surveys and integrated Geostatistical Analysis
    Science of The Total Environment, 2017
    Co-Authors: Sebastiano Trevisani, Jacopo Boaga, Laura Agostini, Antonio Galgaro
    Abstract:

    The HVSR (Horizontal to Vertical Spectral Ratio) technique is very popular in the context of seismic microzonation and for the mapping of shallow seismic reflectors, such as the sediment/bedrock transition surface. This easy-to-deploy single station passive seismic technique permits the collection of a considerable amount of HVSR data in a cost-effective way. It is not surprising that some recent studies have adopted single station micro-tremor analyses in order to retrieve information on geological structures in 1D, 2D or even 3D reconstructions. However, the interpolation approaches followed in these studies for extending the punctual HVSR data spatially are not supported by a detailed spatial statistical Analysis. Conversely, in order to exploit the informative content and quantify the related uncertainty of HVSR data it is necessary to utilize a deep spatial statistical Analysis and objective interpolation approaches. Moreover, the interpolation approach should make it possible to use expert knowledge and auxiliary information. Accordingly, we present an integrated Geostatistical approach applied to HVSR data, collected for retrieving information on the morphology of a buried bedrock surface. The Geostatistical study is conducted on an experimental dataset of 116 HVSR data collected in a small thermal basin located in the Venetian Plain (Caldiero Basin, N-E Italy). The explorative Geostatistical Analysis of the data coupled with the use of interpolation kriging techniques permit the extraction of relevant information on the resonance properties of the subsoil. The utilized approach, based on kriging with external drift (or its extension, i.e. regression kriging), permits the researcher to take into account auxiliary information, evaluate the related prediction uncertainty, and highlight abrupt variations in subsoil resonance frequencies. The results of the Analysis are discussed, also with reflections pertaining to the geo-engineering and geo-environmental context.

Rodrigues Hugo - One of the best experts on this subject based on the ideXlab platform.

  • Geostatistical Analysis of settlements induced by liquefaction: case study river Lis Alluviums, Portugal
    'Springer Science and Business Media LLC', 2020
    Co-Authors: Veiga Anabela, Mourato Sandra, Rodrigues Hugo
    Abstract:

    In the present work the result of the application of Geostatistical methods to soil settlement data is presented. The settlements are induced by liquefaction as a result of an earthquake of magnitude 5.5. In the present paper the ArcGIS Geostatistical Analyst software was used, where a number of Kriging methods are available. Geostatistical Analysis was performed on two phases: (i) modelling the semivariogram to analyse the surface properties and; (ii) application of a Kriging method. The best adjustment was obtained with a Gaussian model with a first order function trend removal. The settlement values were obtained from the Analysis and treatment of results of SPT tests carried out on soils corresponding to alluvial soils in the urban centre of Leiria, Portugal. The results show a significant area where are expected large settlements that can generate significant damages in the building stock and infrastructures.info:eu-repo/semantics/publishedVersio

Sebastiano Trevisani - One of the best experts on this subject based on the ideXlab platform.

  • Geostructural complexity and passive seismic surveys: a Geostatistical Analysis in the Kathmandu basin
    2020
    Co-Authors: Sebastiano Trevisani, Dev Kumar Maharian, Denis Sandron, Surya Narayan Shrestha, Sarmila Paudyal, Franco Pettenati, Massimo Giorgi
    Abstract:

    <p>In this study a set of 39 single station passive seismic surveys conducted in the Kathmandu basin (Nepal), based on the horizontal to vertical spectral ratio methodology (HVSR), is analyzed by means of a Geostatistical approach. The Kathmandu basin is characterized by a heterogeneous sedimentary cover and by a complex geostructural setting, inducing high spatial variability of the bedrock depth. In relation to the complex geological setting, the interpretation and Analysis of HVSR data are challenging, both from the perspective of bedrock depth Analysis as well as of seismic site effects detection. In order to maximize the broad range of information available, the HVSR data are analyzed according to a Geostatistical approach. First, the spatial continuity structure of HVSR data is analyzed and interpreted taking into consideration the geological setting and available stratigraphic and seismic information. In addition, we test the possibility to integrate the Analysis with potential auxiliary variables, derived from geomorphometric variables and considering the distance from outcropping bedrock. The explorative Geostatistical Analysis confirms the complexity of the geo-structural setting of the area. Finally, a mapping of HVSR resonance periods, with the evaluation of interpolation uncertainty, is obtained by means of ordinary kriging interpolation. The resulting map, even if characterized by a large interpolation support, is congruent with the geo-structural setting and the main lineaments of the area. The adopted approach is particularly useful in the context of micro-zonation studies based on HVSR methodology conducted in historical urban areas. Moreover, this work contributes to the geo-structural knowledge of the deep structure of the Kathmandu basin.</p><p>References</p><p>Paudyal YR, Yatabe R, Bhandary NP, Dahal RK, 2013. Basement topography of the Kathmandu Basin using microtremor observation. J Asian Earth Sci 62:627–637, doi.org/10.1016/j.jseaes.2012.11.011.</p><p>Nakamura Y., 1989. A method for dynamic characteristic estimation of subsurface using microtremors on the ground surface. Quart. Rep. Railway Tech. Res. Inst. 30, 25-33</p><p>Sandron D., S. .Maskey , M. Giorgi, D. V. Maharjan, S. N. Narayan, C. Cravos, F. Pettenati, 2019. Environmental and on buildings noise measures: Laliptur (Kathmandu). Earthquake Engineering. Vol. 60, n. 1, 17-38: March 2019, doi 10.4430/bgta0259.</p><p>Trevisani S., Boaga J., Agostini L., Galgaro A., 2017. Insights into bedrock surface morphology using low-cost passive seismic surveys and integrated Geostatistical Analysis. Science of the Total Environment, 578, 186-202, http://dx.doi.org/ 10.1016/j.scitotenv.2016.11.041.</p>

  • insights into bedrock surface morphology using low cost passive seismic surveys and integrated Geostatistical Analysis
    Science of The Total Environment, 2017
    Co-Authors: Sebastiano Trevisani, Jacopo Boaga, Laura Agostini, Antonio Galgaro
    Abstract:

    The HVSR (Horizontal to Vertical Spectral Ratio) technique is very popular in the context of seismic microzonation and for the mapping of shallow seismic reflectors, such as the sediment/bedrock transition surface. This easy-to-deploy single station passive seismic technique permits the collection of a considerable amount of HVSR data in a cost-effective way. It is not surprising that some recent studies have adopted single station micro-tremor analyses in order to retrieve information on geological structures in 1D, 2D or even 3D reconstructions. However, the interpolation approaches followed in these studies for extending the punctual HVSR data spatially are not supported by a detailed spatial statistical Analysis. Conversely, in order to exploit the informative content and quantify the related uncertainty of HVSR data it is necessary to utilize a deep spatial statistical Analysis and objective interpolation approaches. Moreover, the interpolation approach should make it possible to use expert knowledge and auxiliary information. Accordingly, we present an integrated Geostatistical approach applied to HVSR data, collected for retrieving information on the morphology of a buried bedrock surface. The Geostatistical study is conducted on an experimental dataset of 116 HVSR data collected in a small thermal basin located in the Venetian Plain (Caldiero Basin, N-E Italy). The explorative Geostatistical Analysis of the data coupled with the use of interpolation kriging techniques permit the extraction of relevant information on the resonance properties of the subsoil. The utilized approach, based on kriging with external drift (or its extension, i.e. regression kriging), permits the researcher to take into account auxiliary information, evaluate the related prediction uncertainty, and highlight abrupt variations in subsoil resonance frequencies. The results of the Analysis are discussed, also with reflections pertaining to the geo-engineering and geo-environmental context.

Hugo Rodrigues - One of the best experts on this subject based on the ideXlab platform.

  • Geostatistical Analysis of settlements induced by liquefaction: case study river Lis Alluviums, Portugal
    Information Technology in Geo-Engineering, 2019
    Co-Authors: Anabela Veiga, Sandra Mourato, Hugo Rodrigues
    Abstract:

    In the present work the result of the application of Geostatistical methods to soil settlement data is presented. The settlements are induced by liquefaction as a result of an earthquake of magnitude 5.5. In the present paper the ArcGIS Geostatistical Analyst software was used, where a number of Kriging methods are available. Geostatistical Analysis was performed on two phases: (i) modelling the semivariogram to analyse the surface properties and; (ii) application of a Kriging method. The best adjustment was obtained with a Gaussian model with a first order function trend removal. The settlement values were obtained from the Analysis and treatment of results of SPT tests carried out on soils corresponding to alluvial soils in the urban centre of Leiria, Portugal. The results show a significant area where are expected large settlements that can generate significant damages in the building stock and infrastructures.