Geophysical Application for Splines

The exponential dissemination of proximity computing devices (smartphones, tablets, nanocomputers, etc.) raises important questions on how to transmit, store and analyze data in networks integrating those devices. New approaches like edge computing aim at delegating part of the work to devices in the “edge” of the network. In this article, the focus is on the use of pervasive grids to implement edge computing and leverage such challenges, especially the strategies to ensure data proximity and context awareness, two factors that impact the performance of big data analyses in distributed systems. This article discusses the limitations of traditional big data computing platforms and introduces the principles and challenges to implement edge computing over pervasive grids. Finally, using CloudFIT, a distributed computing platform, the authors illustrate the deployment of a real geophysical application on a pervasive network.

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Geophysical characterization of an engineering infrastructure: laboratory tests.

10.5194/egusphere-egu21-4508 ◽

2021 ◽

Author(s):

Giacomo Fornasari ◽

Luigi Capozzoli ◽

Gregory De Martino ◽

Valeria Giampaolo ◽

Enzo Rizzo

Keyword(s):

Urban Areas ◽

New Technologies ◽

Detailed Knowledge ◽

Reinforced Concrete Frame ◽

The Public ◽

Civil Infrastructures ◽

Concrete Frame ◽

Geophysical Application ◽

Ground Penetrating

<p>The increase of the metropolises stresses the urban areas and intensive planning works is necessary. Therefore, the development of new technologies and methodologies able to explore the subsoil and manage its resources in urban areas becomes an important source in terms of saving time and money. In the last decade, a new subdiscipline in the Applied Geophysics started: Urban Geophysics (Lapenna, 2017). Urban Geophysics analyzes the contribute, in terms of limits and potentialities, that geophysical methodologies can give for providing useful information about the subsoil, environment, buildings and civil infrastructures and supporting the public administrations in planning interventions in urban scenarios.</p><p>This work introduces a laboratory test, that was performed at the Hydrogeosite CNR-IMAA laboratory of Marsico Nuovo (Basilicata region, Italy). The test consisted in a multisensor geophysical application on an analogue engineering model. Thanks to the possibility to work in laboratory conditions, a detailed knowledge of the structure was available, providing great advantages for assess the capability of the geophysical methodologies for analyze engineering issues, regarding the characterization of the infrastructural critical zone placed at the interface soil-structure. For this purpose, geoelectrical and electromagnetic methodologies, including Cross hole Electrical Resistivity Tomography and Ground Penetrating Radar, were used to characterize the geometry of the foundation structures and the disposition of the rebar for the reinforced concrete frame. Finally, new geophysical approaches were applied in order to define the corrosion rate of reinforcement.</p>

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Geophysical Application of Global Optimization Methods

10.3997/2214-4609-pdb.324.91 ◽

1993 ◽

Author(s):

M.K. Sen ◽

P.L. Stoffa ◽

R.K. Chunduru

Keyword(s):

Global Optimization ◽

Optimization Methods ◽

Geophysical Application ◽

Global Optimization Methods

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A Fuzzy Approach Using Euclidean Geometrical Formulation for Classifying SAR Images

International Journal on Measurement Technologies and Instrumentation Engineering ◽

10.4018/ijmtie.2013100103 ◽

2013 ◽

Vol 3 (4) ◽

pp. 27-35

Author(s):

Biagio Cammaroto ◽

Matteo Cacciola ◽

Mario Versaci

Keyword(s):

Scientific Literature ◽

Geometric Approach ◽

Classification Problem ◽

Coastal Protection ◽

Sar Images ◽

Good Tool ◽

Geophysical Application ◽

Geometrical Formulation ◽

Standard Techniques

Synthetic Aperture Radar (SAR) is a good tool to investigate problems in many geophysical application as classification of ground terrain types and coastal protection. In scientific literature, many analytical and/or numerical techniques have been taken into account to solve the classification problem at hand, especially in all of applications in which it is necessary to classify portion of images with uncertainty and imprecision. In fact, according to the conventional classification approaches, the assignment of a class to each portion of an image could be particularly inadequate for all those portions that span more than a class (for example the coastal areas of the shoreline). This article is devoted to present a fuzzy-geometric approach based on fuzzy subsethood operator to classify SAR images for coastal protection applications. The obtained results were compared, in terms of accuracy, with standard techniques of classification.

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Implicit Equal-Weights Variational Particle Smoother

Atmosphere ◽

10.3390/atmos11040338 ◽

2020 ◽

Vol 11 (4) ◽

pp. 338

Author(s):

Pinqiang Wang ◽

Mengbin Zhu ◽

Yan Chen ◽

Weimin Zhang

Keyword(s):

Particle Filter ◽

Weather Prediction ◽

Ensemble Methods ◽

Great Success ◽

Ensemble Spread ◽

Ensemble Kalman Filters ◽

Error Covariance ◽

Filter Methods ◽

Geophysical Application ◽

Prediction Systems

Under the motivation of the great success of four-dimensional variational (4D-Var) data assimilation methods and the advantages of ensemble methods (e.g., Ensemble Kalman Filters and Particle Filters) in numerical weather prediction systems, we introduce the implicit equal-weights particle filter scheme in the weak constraint 4D-Var framework which avoids the filter degeneracy through implicit sampling in high-dimensional situations. The new variational particle smoother (varPS) method has been tested and explored using the Lorenz96 model with dimensions N x = 40 , N x = 100 , N x = 250 , and N x = 400 . The results show that the new varPS method does not suffer from the curse of dimensionality by construction and the root mean square error (RMSE) in the new varPS is comparable with the ensemble 4D-Var method. As a combination of the implicit equal-weights particle filter and weak constraint 4D-Var, the new method improves the RMSE compared with the implicit equal-weights particle filter and LETKF (local ensemble transformed Kalman filter) methods and enlarges the ensemble spread compared with ensemble 4D-Var scheme. To overcome the difficulty of the implicit equal-weights particle filter in real geophysical application, the posterior error covariance matrix is estimated using a limited ensemble and can be calculated in parallel. In general, this new varPS performs slightly better in ensemble quality (the balance between the RMSE and ensemble spread) than the ensemble 4D-Var and has the potential to be applied into real geophysical systems.

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Authors’ Reply

Geophysics ◽

10.1190/1.1486519 ◽

1944 ◽

Vol 9 (1) ◽

pp. 76-78

Author(s):

L. L. Nettleton ◽

T. A. Elkins

Keyword(s):

Geophysical Application ◽

Great Body ◽

To Receive

We are very glad to receive a petrologist’s generally favorable comments on our paper. Perhaps, in our extremely limited petrographic knowledge, we have “rushed in where angels fear to tread,” although not without some appreciation of the pitfalls in our path. Our excuses are, first, that to a certain extent, these pitfalls may be bridged by a broad statistical base and second, that our aim has been to find a way of making a geophysical application of the great body of existing fact in petrographic literature rather than to make new measurements of the particular properties discussed. Since we agree with most of the criticisms stated, apparently we did not emphasize certain points as much as may be desirable and, therefore, we shall take this opportunity to explain some details more fully.

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