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  • 1
    Online Resource
    Online Resource
    Berlin, Heidelberg :Springer Berlin / Heidelberg,
    Keywords: Neural networks (Computer science). ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (280 pages)
    Edition: 1st ed.
    ISBN: 9783642600449
    Series Statement: Springer Series in Advanced Microelectronics Series ; v.1
    Language: English
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  • 2
    Online Resource
    Online Resource
    Cham :Springer International Publishing AG,
    Keywords: Production of electric energy or. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (105 pages)
    Edition: 1st ed.
    ISBN: 9783319387642
    Series Statement: SpringerBriefs in Energy Series
    DDC: 551.52710287
    Language: English
    Note: Intro -- Preface -- Acknowledgments -- Contents -- Abbreviations -- 1 Time Series Methods -- 1.1 Stationarity Analysis -- 1.2 Recurrence Plots -- 1.3 Linear Detrending -- 1.4 Noise Reduction -- 1.5 Power Spectrum -- 1.6 Autocorrelation -- 1.7 Mutual Information -- 1.8 Noise 1/f and Random Walks -- 1.9 Fractal Dimension and Hurst Exponent -- 1.9.1 The Box-Dimension -- 1.9.2 The Hurst Exponent -- 1.10 Multifractals -- 1.11 False Nearest Neighbors -- 1.12 Lyapunov Spectrum -- 1.13 Daily Patterns -- 1.14 Time Series Clustering -- 1.14.1 The Exclusive Clustering -- 1.14.2 The Overlapping Clustering -- 1.14.3 The Hierarchical Clustering -- 1.14.4 The Probabilistic Clustering -- 1.14.5 Feature Based Clustering -- 1.14.6 Choosing the Number of Clusters -- 1.15 Conclusions -- References -- 2 Analysis of Solar Radiation Time Series -- 2.1 Energy from the Sun -- 2.2 The Solar Radiation Data Set -- 2.2.1 Stationarity Analysis -- 2.2.2 Autocorrelation and Mutual Information -- 2.2.3 Power Spectra -- 2.2.4 Hurst Exponent and Fractal Dimension -- 2.2.5 Multifractal Analysis of Solar Radiation -- 2.2.6 Estimation of the Embedding Dimension -- 2.2.7 Maximal Lyapunov Exponent -- 2.3 Conclusions -- References -- 3 Analysis of Wind Speed Time Series -- 3.1 Energy from the Wind -- 3.2 The Wind Speed Data Set -- 3.3 Stationary Analysis -- 3.4 Autocorrelation and Mutual Information -- 3.5 Power Spectra -- 3.6 Hurst Exponent and Fractal Dimension -- 3.7 Multifractal Spectrum -- 3.8 Estimation of the Embedding Dimension -- 3.9 Lyapunov Exponents -- 3.10 Conclusions -- References -- 4 Prediction Models for Solar Radiation and Wind Speed Time Series -- 4.1 NARX Time Series Models -- 4.2 Multistep Ahead Prediction Models -- 4.3 EPS Time Series Models -- 4.4 Mapping Approximation -- 4.4.1 The Neuro-Fuzzy Approach -- 4.4.2 The Feedforward Neural Network Approach. , 4.5 Assessing the Model Performances -- 4.5.1 Reference Models -- 4.6 Conclusions -- References -- 5 Modeling Hourly Average Solar Radiation Time Series -- 5.1 Introduction -- 5.2 Modeling Results -- 5.2.1 Performances of the EPSNF Approach -- 5.2.2 Performances of the EPSNN Approach -- 5.2.3 A Direct Comparison Between EPSNF and EPSNN -- 5.2.4 Average Skill Index Considering the P24 Reference Model -- 5.3 Conclusions -- References -- 6 Modeling Hourly Average Wind Speed Time Series -- 6.1 Introduction -- 6.2 Considerations on the Choice of Model Parameters -- 6.3 Performances for All the Considered Stations -- 6.4 Conclusions -- References -- 7 Clustering Daily Solar Radiation Time Series -- 7.1 Two Features of Solar Radiation Time Series -- 7.1.1 The Area Ratio Ar Index -- 7.1.2 The GPHr Index -- 7.2 Clustering Daily Patterns of Solar Radiation -- 7.3 Daily Pattern Shapes -- 7.3.1 Weight of a Solar Radiation Class -- 7.3.2 Permanence of a Solar Radiation Class -- 7.4 Conclusions -- References -- 8 Clustering Daily Wind Speed Time Series -- 8.1 Introduction -- 8.2 Two Features of Daily Wind Speed Time Series -- 8.3 The Wr Index -- 8.4 The Hurst Exponent of Daily Wind Speed -- 8.5 Clustering Wind Speed Daily Patterns -- 8.5.1 Stability of the Wind Speed Features Cluster Centers -- 8.6 Some Applications -- 8.6.1 Weight of a Class -- 8.6.2 Permanence of Patterns in a Class -- 8.7 Conclusions -- References -- 9 Concluding Remarks -- Appendix ASoftware Tools and Data -- Index.
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  • 3
    Electronic Resource
    Electronic Resource
    s.l. ; Stafa-Zurich, Switzerland
    Advances in science and technology Vol. 61 (Sept. 2008), p. 131-140 
    ISSN: 1662-0356
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Natural Sciences in General , Technology
    Notes: IPMCs are suitable candidates to realize artificial muscles for possible autonomous applications. Insuch a field power budget is of great importance. The goal of this paper is to maximize the IPMCelectromechanical conversion efficiency in order to increase the performance of these transducers.More specifically, the optimal frequency, amplitude, and waveform to be used to drive the IPMCmembrane has been investigated. By using a novel model of IPMC actuators, the waveform of theapplied voltage signal that maximize the IPMC conversion efficiency was found. The amplitude ofthe first 15 harmonics of the IPMC driving signal was determined, for different constrains such asthe minimum output power and the maximum input voltage.The paper reports about the proposed IPMC model, the optimization algorithm, the optimal drivingsignals, and the validation of the approach
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    s.l. ; Stafa-Zurich, Switzerland
    Advances in science and technology Vol. 58 (Sept. 2008), p. 85-90 
    ISSN: 1662-0356
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Natural Sciences in General , Technology
    Notes: In this work the design and realization of an artificial vestibular system demonstrator ispresented. The whole system is biologically inspired to the human vestibular apparatus. The mototransductioncapabilities of ionomeric polymer-metal composite (IPMC) have been used in order todevelop the prototype [1]. The reported results are the starting point to the future design anddevelopment of a miniaturized artificial vestibular system, integrating biocompatible materials andall-organic electronic devices [2]
    Type of Medium: Electronic Resource
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  • 5
    Publication Date: 2020-11-17
    Description: Lava flow modeling is important in many practical applications, such as the simulation of potential hazard scenarios and the planning of risk mitigation measures, as well as in scientific research to improve our understanding of the physical processes governing the dynamics of lava flow emplacement. Existing predictive models of lava flow behavior include various methods and solvers, each with its advantages and disadvantages. Codes differ in their physical implementations, numerical accuracy, and computational efficiency. In order to validate their efficiency and accuracy, several benchmark test cases for computational lava flow modeling have been established. Despite the popularity gained by the Smoothed Particle Hydrodynamics (SPH) method in Computational Fluid Dynamics (CFD), very few validations against lava flows have been successfully conducted. At the Tecnolab of INGVCatania we designed GPUSPH, an implementation of the weakly-compressible SPH method running fully on Graphics Processing Units (GPUs). GPUSPH is a particle engine capable of modeling both Newtonian and non-Newtonian fluids, solving the three-dimensional Navier– Stokes equations, using either a fully explicit integration scheme, or a semi-implicit scheme in the case of highly viscous fluids. Thanks to the full coupling with the thermal equation, and its support for radiation, convection and phase transition, GPUSPH can be used to faithfully simulate lava flows. Here we present the preliminary results obtained with GPUSPH for a benchmark series for computational lava-flow modeling, including analytical, semi-analytical and experimental problems. The results are reported in terms of correctness and performance, highlighting the benefits and the drawbacks deriving from the use of SPH to simulate lava flows.
    Description: Published
    Description: VO224
    Description: 5V. Processi eruttivi e post-eruttivi
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 6
    Publication Date: 2020-11-17
    Description: Complex patterns are commonly retrieved in spatially-extended systems formed by coupled nonlinear dynamical units. In particular, Turing patterns have been extensively studied investigating mathematical models pertaining to different fields, such as chemistry, physics, biology, mechanics, and electronics. In this paper, we focus on the emergence of Turing patterns in memristive cellular nonlinear networks by means of spatial pinning control. The circuit architecture is made by coupled units formed by only two elements, namely, a capacitor and a memristor. The analytical conditions for which Turing patterns can be derived in the proposed architecture are discussed in order to suitably design the circuit parameters. In particular, we derive the conditions on the density of the controlled nodes for which a Turing pattern is globally generated. Finally, it is worth to note that the proposed architecture can be considered as the simplest ideal electronic circuit able to undergo Turing instability and give rise to pattern formation.
    Description: Published
    Description: id 103145
    Description: 3IT. Calcolo scientifico
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 7
    Publication Date: 2020-11-17
    Description: The past few decades have seen an explosion of satellite remote sensing techniques for the monitoring of volcanic thermal features. Here, we propose an artificial neural network approach for improving the cloud detection through imperfect multispectral satellite images analysis. The cloud detection algorithm has been tested on a data set of MSGSEVIRI images acquired over the area of Etna volcano in Sicily (Italy) before and during the 2008 eruption. Results show that this approach is robust in terms of percentage of correctly classified pixels.
    Description: Published
    Description: 1443-1447
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: N/A or not JCR
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
    Publication Date: 2020-11-17
    Description: GPUSPH is an implementation of Weakly-Compressible Smoothed Particle Hydrodynamics with an explicit predictor–corrector integration scheme, that takes advantage of the parallel nature of the method to run on Graphic Processing Units (GPUs). Despite the massive speed-up granted by the use of GPUs, the application of GPUSPH to the simulation of highly viscous fluids is still problematic, due to the severe time-stepping restrictions imposed by the explicit integration scheme when the viscous term becomes dominant. This is an issue in the simulation of lava flows, where the thermal-dependent rheology can lead to kinematic viscosities in the order of 104m2s−1 or more at low temperatures. To overcome this limitation, we introduce a semi-implicit integration scheme, where only the viscous part of the momentum equation is solved implicitly. Here we show the significant advantages of our approach in terms of simulation run times as well as better quality of the results over the fully explicit scheme.
    Description: Published
    Description: 854-870
    Description: 5V. Processi eruttivi e post-eruttivi
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2020-11-17
    Description: Complex fluid dynamics encompasses a large variety of flows, such as fluids with non-Newtonian rheology, multiphase and multi-fluid flows (suspensions, lather, solid/fluid interaction with floating objects, etc.), violent flows breaking waves, dam-breaks, etc.), fluids with thermal dependencies and phase transition or free-surface flows. Correctly modeling the behavior of such flows can be quite challenging, and has led to significant advances in the field of Computational Fluid Dynamics (CFD). Recently, the Smoothed Particle Hydrodynamics (SPH) method has emerged as a powerful alternative to more classic CFD methods (such as finite volumes or finite elements) in many fields, including oceanography, volcanology, structural engineering, nuclear physics and medicine. With SPH, the fluid is discretized by means of particles and thanks to the meshless, Lagrangian nature of the model, it easily allows the modeling and simulation of both simple and complex fluids, simplifying the treatment of aspects that can be challenging with more traditional methods: dynamic free surfaces, large deformations, phase transition, fluid/solid interaction and complex geometries. In addition, the most common SPH formulations are fully parallelizable, which favors implementation on high-performance parallel computing hardware, such as modern Graphics Processing Units (GPUs). We present here how GPUSPH, an implementation of the SPH method that runs on GPUs, can model a variety of complex fluids, highlighting the computational challenges that arise in its applications to problem of great interest in volcanology.
    Description: Published
    Description: PH699
    Description: 5V. Dinamica dei processi eruttivi e post-eruttivi
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
    Publication Date: 2020-11-25
    Description: In this paper a new approach for processing arrays of data is proposed. It is based on fuzzy logic and the concepts of cellular computation. Arrays of simple, identical processing elements (called fuzzy cells) are defined by using fuzzy rules. Moreover, each fuzzy cell interacts with its local neighbors. The overall behavior of these locally interacting fuzzy systems is used to process arrays of data. Some examples of practical applications are proposed. Among these, the new approach is applied to image-processing problems, and to the simulation of heat diffusion phenomena.
    Description: This work was partially supported by the Italian National Research Council (C.N.R.) under the special project "Reti neurali per i sistemi di controllo".
    Description: Published
    Description: 47-52
    Description: 3IT. Calcolo scientifico
    Description: JCR Journal
    Keywords: fuzzy logic ; partial differential equations ; 05.09. Miscellaneous
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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