# Ardelio GallettiParthenope University of Naples | Università Parthenope · Department of Science and Technology

Ardelio Galletti

Ph.D. in Applied Mathematics (Numerical Analysis)

## About

84

Publications

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Introduction

Additional affiliations

May 2008 - April 2016

May 2008 - April 2016

October 2006 - April 2008

## Publications

Publications (84)

Deep Learning algorithms are currently widely used in astronomy for providing accurate predictions in classification problems, and more specifically to the search for planets outside the Solar System, called “exoplanets” (e.g., [16] and references therein). For instance, NASA’s Transiting Exoplanet Survey Satellite (TESS) has already observed 76% o...

We report the Transiting Exoplanet Survey Satellite (TESS) discovery of a three-planet system around the bright Sun-like star HD~22946(V=8.3 mag),also known as TIC~100990000, located 63 parsecs away.The system was observed by TESS in Sectors 3, 4, 30 and 31 and two planet candidates, labelled TESS Objects of Interest (TOIs) 411.01 (planet $c$) and...

Nowadays, the Machine Learning (ML) approach is needful to many research fields. Among these, the Environmental Science (ES) which involves a large amount of data to be processed and collected. On the other hand, in order to provide a reliable output, those data information must be assimilated. Since this process requires a large execution time whe...

Gaussian convolution operation is a fundamental procedure in several data analysis tasks and scientific fields. For example, Gaussian convolution is a central step in data assimilation and machine learning and it is also frequently used in image and signal processing. Gaussian recursive filters are a class of methods designed to approximate Gaussia...

The purpose of this paper is to provide a parallel acceleration of peer methods for the numerical solution of systems of Ordinary Differential Equations (ODEs) arising from the space discretization of Partial Differential Equations (PDEs) modeling the growth of vegetation in semi-arid climatic zones. The parallel algorithm is implemented by using t...

In recent years, Machine Learning (ML) algorithms have proved to be very helpful in several research fields, such as engineering, health-science, physics etc. Among these fields, Astrophysics also started to develop a stronger need of ML techniques for the management of big-data collected by ongoing and future all-sky surveys (e.g. Gaia, LAMOST, LS...

Data Assimilation process is generally used to estimate the best initial state of a system in order to predict carefully the future states. This powerful technique has been widely applied in investigations of the atmosphere, ocean, and land surface. In this work, we deal with the Gaussian convolution operation which is a central step of the Data As...

In the current work, an efficient and powerful computational technique is implemented to simulate an anomalous mobile-immobile solute transport process. The process is mathematically modelled as a time-fractional mobile-immobile diffusion equation in the sense of Riemann-Liouville derivative. Firstly, an implicit time integration procedure is used...

Machine Learning algorithms try to provide an adequate forecast for predicting and understanding a multitude of phenomena. However, due to the chaotic nature of real systems, it is very difficult to predict data: a small perturbation from initial state can generate serious errors. Data Assimilation is used to estimate the best initial state of a sy...

While the everything as a sensor is a typical data gathering pattern in the Internet of Things (IoT) applications in contexts such as smart cities, smart factories, and precision agriculture, among others, the use of the same technique in the coastal marine environment is still not explored at full potential. Nevertheless, when it comes to maritime...

This paper deals with the solution of an inverse time fractional diffusion equation described by a Caputo fractional derivative. Numerical simulations, involving large domains, give rise to a huge practical problem. Hence, by starting from an accurate meshless localized collocation method using radial basis functions (RBFs), here we propose a fast...

In this work we deal with the solution of a two-dimensional inverse time fractional diffusion equation, involving a Caputo fractional derivative in his expression. Since we deal with a huge practical problem with a large domain, by starting from an accurate meshless localized collocation method using RBFs, here we propose a fast algorithm, implemen...

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position,...

In this work, we describe and implement a data assimilation approach for PM10 pollution data in Northern Italy. This was done by combining the best available information from observations and chemical transport models. Specifically, by (1) incorporating PM10 surface daily concentrations and model results from the CAMS (Copernicus Atmosphere Monitor...

Fast technology development has influenced the widespread use of low‐power devices in different scientific, environmental, and everyday life areas, giving birth to the Internet of Things. In this paper, we focus on the context of marine studies, addressing the problem of marine bathymetry data processing and analysis via pervasive and Internet‐conn...

It is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced versio...

Data crowdsourcing is one of most remarkable results of pervasive and internet connected low-power devices making diverse and different “things” as a world wide distributed system. This paper is focused on a vertical application of GPGPU virtualization software exploitation targeted on high performance geographical data interpolation. We present an...

Data reduction algorithms often produce inaccurate results for loss of relevant information. Recently, the singular value decomposition (SVD) method has been used as preprocessing method in order to deal with high-dimensional data and achieve fuzzy-rough reduct convergence on higher dimensional datasets. Despite the well-known fact that SVD offers...

Recursive Filters (RFs) are a well-known way to approximate the Gaussian convolution and, due to their computational efficiency, are intensively used in several technical and scientific fields. The accuracy of the RFs can be improved by means of the repeated application of the filter, which gives rise to the so-called K-iterated Gaussian recursive...

Recently, advanced computing systems are widely adopted in order to intensively elaborate a huge amount of biomedical data in the e-health field. An interesting challenge is to perform real-time diagnosis by means of complex computational environments. In this paper, we suggest to deal the most computationally expensive processing steps of a distri...

Nowadays fishes and mussels farming is very important, from an economical point of view, for the local social background of the Bay of Naples. Hence, the accurate forecast of marine pollution becomes crucial to have reliable evaluation of its adverse effects on coastal inhabitants’ health. The use of connected smart devices for monitoring the sea w...

Sensors incorporated into mobile devices provide unique opportunities to capture detailed environmental information that cannot be readily collected in other ways. We show here how data from networked navigational sensors on leisure vessels can be used to construct unique new datasets, using the example of underwater topography (bathymetry) to demo...

Generic Virtualization Service (GVirtuS) is a new solution for enabling GPGPU on Virtual Machines or low powered devices. This paper focuses on the performance analysis that can be obtained using a GPGPU virtualized software. Recently, GVirtuS has been extended in order to support CUDA ancillary libraries with good results. Here, our aim is to anal...

In many applications, the Gaussian convolution is approximately computed by means of recursive filters, with a significant improvement of computational efficiency. We are interested in theoretical and numerical issues related to such an use of recursive filters in a three-dimensional variational data assimilation (3Dvar) scheme as it appears in the...

In this paper, we propose a fine-to-coarse parallelization strategy in order to
exploit, in a case study, a parallel hybrid architecture. We consider the Optical
Flow numerical problem, modelled by partial differential equations, and implement
a parallel multilevel software. Our hybrid software solution is a smart
combination between codes on Graph...

In this paper, starting from a comprehensive mathematical model of a Collaborative Reputation Systems (CRSes), we present a research study within the Cultural Heritage domain. The main goal of this study has been the evaluation and classification of the visitors’ behaviour during a cultural event. By means of mobile technological instruments, oppor...

Data for which ratios of parts are more important than absolute values have a compositional nature and should be analysed in the (D - 1)-dimensional simplex, but in order to use standard multivariate analysis techniques they are often mapped bijectively from the simplex into the ordinary Euclidean space. The additive log-ratio (alr) is one popular...

The extraction of information from IoT data plays a fundamental role in many fields. In this paper we focus our attention on financial data and we use them to describe derivatives in the Black-Scholes model. This model lets us obtain an expression of the price of a derivative in a complete market with no possibility of arbitrage portfolios. Traders...

Nowadays, in the Internet of Things (IoT) society, the massive use of technological devices available to the people makes possible to collect a lot of data describing tastes, choices and behaviours related to the users of services and tools. These information can be rearranged and interpreted in order to obtain a rating (i.e., evaluation) of the su...

Among the many challenges that the Internet of Things poses, the accuracy of the sensor network and relative data flow is of the foremost importance: sensors monitor the surrounding environment of an object and give information on its position, situation or context, and an error in the acquired data can lead to inappropriate decisions and uncontrol...

Representation of curves and surfaces is a basic topic in computer graphic and computer aided design (CAD). In this paper we focus on theoretical and practical issues in using radial basis functions (RBF) for reconstructing implicit curves and surfaces from point clouds. We study the conditioning of the problem and give some insight on how the prob...

The algorithms based on the Bregman iterative regularization are known for efficiently solving convex constraint optimization problems. In this paper, we introduce a second order derivative scheme for the class of Bregman algorithms. Its properties of convergence and stability are investigated by means of numerical evidences. Moreover, we apply the...

Recursive filters (RFs) have achieved a central role in several research fields over the last few years. For example, they are used in image processing, in data assimilation and in electrocardiogram denoising. More in particular, among RFs, the Gaussian RFs are an efficient computational tool for approximating Gaussian-based convolutions and are su...

The implementation of neural network models enables to reproduce complex biological phenomena. The tuning of a large number of biological parameters and synaptic mechanisms of several different cells that belong to a model is a very critical issue. In this work, we present the effects of increasing cAMP Response Element Binding protein (CREB)-depen...

We focus on the Overcomplete Local Principal Component Analysis (OLPCA) method, which is widely considered as the state-of-the-art denoising filter. We propose a programming approaches resorting to massively parallel architectures, known as Graphic Processor Units (GPUs), in order to deal with the heavy computational complexity of the algorithm. In...

An interesting challenge in e-Health is to develop tools and software in order to benefit the healthcare services. Our applicative context is Magnetic Resonance Imaging (MRI). The main purpose of this paper is to propose a regularization framework for solving an inverse reconstruction problem in MRI. We focus on the Split Bregman method, which is a...

We focus on the Overcomplete Local Principal Component Analysis (OLPCA) method, which is widely adopted as denoising filter. We propose a programming approach resorting to Graphic Processor Units (GPUs), in order to massively parallelize some heavy computational tasks of the method. In our approach, we design and implement a parallel version of the...

In the last decade, algorithms for reputation systems are been widely developed in order to achieve correct ratings for products, services, companies, digital contents and people. We start from a comprehensive mathematical model for Collaborative Reputation Systems (CRSes), present in the literature and formally defined as a recurrence relation tha...

A smart system for a cultural exhibition, generally, has the ability to infer interests of users and to track the propagation of the information into the event. We are interested in analysing and studying the visiting styles of users in a real cultural heritage exhibition, named The Beauty or the Truth. Starting from data that was collected during...

In many healthcare applications, artifacts mask or corrupt important features of Electrocardiogram (ECG) signals. In this paper we describe a revised scheme for ECG signal denoising based on a recursive filtering methodology. We suggest a suitable class of kernel functions in order to remove artifacts in the ECG signal, starting from noise frequenc...

In recent years, the real-time diagnosis in the E-health is widely used practice. Employing distributed computing systems, it is possible to obtain excellent results, avoiding long delays and invasive processes. However, the data processing stage, generally assigned on standard computational CPU environments, is a critical aspect, especially when t...

Classify the dynamic of users in a cultural heritage exhibition in order to infer information about the event fruition is a very interesting research field. In this paper, starting from real data, we investigate the user dynamics related to the interaction with artworks and how a spectator interacts with available technologies. Accordingly with the...

Classify the dynamic of users in a cultural heritage exhibition in order to infer information about the event fruition is a very interesting research field. In this paper, starting from real data, we investigate the user dynamics related to the interaction with artworks and how a spectator interacts with available technologies. Accordingly with the...

In this work we present a multi-level parallel framework for the Optical Flow computation on a GPUs cluster, equipped with a scientific computing middleware (the PetSc library). Starting from a flow-driven isotropic method, which models the optical flow problem through a parabolic partial differential equation (PDE), we have designed a parallel alg...

The prototyping and the development of computational codes for biological models, in terms of reliability, efficient and portable building blocks allow to simulate real cerebral behaviours and to validate theories and experiments. A critical issue is the tuning of a model by means of several numerical simulations with the aim to reproduce real scen...

High quality Electrocardiogram (ECG) data is very important because this signal is generally used for the analysis of heart diseases. Wearable sensors are widely adopted for physical activity monitoring and for the provision of healthcare services, but noise always degrades the quality of these signals. This paper describes a new algorithm for ECG...

In this paper, starting from a real case
of an art exhibit, we propose a mathematical model
to simulate social network interactions of a visitor
that shares his experience on a social network. The
Integrate & Fire (I&F) model is used to reproduce the
interest of spectators in a cultural heritage community.
In our approach, visitor is modelled as a...

An interesting challenge in E-health is to perform real-time diagnosis. In many distributed computing systems
the data processing stage, generally assigned on standard computational CPU environments, is a critical aspect. In
particular, the analysis of magnetic resonance imaging (MRI) for improving the quality of images and helping the diagnosis
re...

Wearable sensors are widely adopted for the provision of healthcare services. Unfortunately the noise always degrades the quality of the acquired signals. In this paper, we propose a framework for mobile ECG denoising, based on a novel numerical scheme with low computational requirements. The proposed system is able to store a signal from a wearabl...

Piecewise interpolation methods, as spline or Hermite cubic interpolation methods, define the interpolating function by means of polynomial pieces and ensure that some regularity conditions hold at the break-points. In this paper, starting from a previous work, where we proposed a class of piecewise interpolating functions whose expression depends...

Many problems in computer visualization, scientific computing, medical imag-
ing, computer-aided design and manufacturing (CAD/CAM) require to recon-
struct a graphic object starting from an unorganized 2D/3D point cloud, i.e. a
set of scattered points in R^2 or R^3. Here, we
– establish how the problem parameters and the results have to be taken i...

In this paper, a biologically inspired mathematical model to simulate social network behaviours is presented. We propose a computational network of Integrate & Fire (IF) neurons to model the dynamics of spectators in a community that shares interests on cultural heritage assets. In our approach, users are assimilated to neurons, while the friendshi...

Piecewise interpolation methods, as spline or Hermite cubic interpolation methods, define the interpolant function by means of polynomial pieces and ensure that some regularity conditions are guaranteed at the break-points. In this work, we propose a novel class of piecewise interpolating functions whose expression depends on the barycentric coordi...

Computational kernel of the three-dimensional variational data assimilation
(3D-Var) problem is a linear system, generally solved by means of an iterative
method. The most costly part of each iterative step is a matrix-vector product
with a very large covariance matrix having Gaussian correlation structure. This
operation may be interpreted as a Ga...

Local numerical methods for scattered data interpolation often require a smart subdivision of the domain in geometrical polyhedral structures. In particular triangulations in the plane (2D) and tetrahedrizations in the space (3D) are widely used to define interpolation models. In this paper we give a short survey on the main methods for the scatter...

This paper concerns the connection between Mathematics and Music. After a description of the nature of sound, the problem of the construction of the musical scale, from the studies of Pythagoras to the tempered scale is considered. An algorithm for the construction of a scale is given. © 2014 Salvatore Cuomo, Ardelio Galletti and Gabriele Guerriero...

In this paper we describe a parallel implicit method based on radial basis
functions (RBF) for surface reconstruction. The applicability of RBF methods is
hindered by its computational demand, that requires the solution of linear
systems of size equal to the number of data points. Our reconstruction
implementation relies on parallel scientific libr...

This paper provides a mathematical framework for modelling collaborative reputation systems CRSs, which are useful in many fields of electronic commerce. A CRS is an algorithm that, at discrete points in time, receives in input from a set of users some ratings of a set of objects and generates a reputation for both the raters and the evaluated obje...

The scientific and application-oriented interest in the Laplace transform and its inversion is testified by more than 1000 publications in the last century. Most of the inversion algorithms available in the literature assume that the Laplace transform function is available everywhere. Unfortunately, such an assumption is not fulfilled in the applic...

Real time image sequences analysis is a challenge. Using high performance computing technologies, a parallel algorithm for performing data sequence analysis is proposed. We call it pipelined algorithm PA. The idea underlying the design of PA comes from the Pipes and Filters design approach: to partition the sequence into ordered subsets and to over...

We describe a fast, reliable and automatic algorithm for image sequence inpainting that combines spatio-temporal interpolation with fine texture preservation inside missing areas. The algorithm provides an estimate of the inpainting error by using an automatic geometric recognition of missing regions. Computational kernels are sparse linear systems...

Many applications are tackled using the Laplace Transform (LT) known on a countable number of real values [J. Electroanal.
Chem. 608, 37–46 (2007), Int. J. solid Struct. 41, 3653–3674 (2004), Imaging 26, 1183–1196 (2008), J. Magn. Reson. 156, 213–221
(2002)]. The usual approach to solve the LT inverse problem relies on a regularization technique co...

We describe the numerical approximation of the inverse Laplace function based on the Laplace transform's eigenfunction expansion of the inverse function, in a real case. The error analysis allows us to introduce a regularization technique involving computable upper bounds of amplification factors of local errors introduced by the computational proc...