Salvatore Rampone

Salvatore Rampone
Università degli Studi del Sannio | UniSannio · Department of Law, Economics, Management and Quantitative Methods (D.E.M.M.)

About

72
Publications
8,567
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971
Citations
Citations since 2017
25 Research Items
696 Citations
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
Additional affiliations
November 2018 - November 2020
Università degli Studi del Sannio
Position
  • Professor

Publications

Publications (72)
Article
Full-text available
In this work two soft computing methods, Artificial Neural Networks and Genetic Programming, are proposed in order to forecast the mean air temperature that will occur in future seasons. The area in which the soft computing techniques were applied is that of the surroundings of the town of Benevento, in the south of Italy, having the geographic coo...
Article
Full-text available
Coronavirus disease 19 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus, which is responsible for the ongoing global pandemic. Stringent measures have been adopted to face the pandemic, such as complete lockdown, shutting down businesses and trade, as well as travel restrictions. Nevertheless, such solutions have had a tremendous...
Article
Full-text available
A main factor motivating consumer choice is the packaging: in many cases, the consumer choices are prevalently based on it. Actually, in planning the packaging of a new product on the market, due to the many variables that can influence the result, it is necessary to conduct a high number of preliminary analyses. It is therefore desirable to develo...
Article
Full-text available
Huge quantities of pollutants are released into the atmosphere of many cities every day. These emissions, due to physicochemical conditions, can interact with each other, resulting in additional pollutants such as ozone. The resulting accumulation of pollutants can be dangerous for human health. To date, urban pollution is recognized as one of the...
Conference Paper
The observation of marine systems and the acquisition of physical, chemical, biological, and ecological data have increasingly grown in the last century. Marine systems are undergoing multiple and overlapping impacts that menace ecological communities, but global change impacts on the ecosystem functioning are not easily assessable, for several rea...
Article
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In Basilicata (Southern Italy), in areas around energy-related plants, including oil extraction sites, oil refineries, and underground gas storage plants, we consider a set of annual air quality measurements, the analysis of toxic substances emitted, and the percentage of tumours with respect the habitants. Artificial Neural Networks and Genetic Pr...
Article
Background The complications associated with infections from pathogens increasingly resistant to traditional drugs lead to a constant increase in the mortality rate among those affected. In such cases the fundamental purpose of the microbiology laboratory is to determine the sensitivity profile of pathogens to antimicrobial agents. This is an inten...
Article
Full-text available
In this work, new implementations of the U-BRAIN (Uncertainty-managing Bach Relevance-Based Artificial Intelligence) supervised machine learning algorithm are described. The implementations, referred as SP-BRAIN (SP stands for Spark), aim to efficiently process large datasets. Given the iterative nature of the algorithm together with its dependence...
Article
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In the fields of Internet of Things (IoT) infrastructures, attack and anomaly detection are rising concerns. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing proportionally. In this paper the performances of several machine learning algorithms in identifying cyber-attacks (n...
Article
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Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Global warming is thought to affect phytoplankton production both directly, by impacting their photosynthetic metabolism, and indirectly by modifying the physical environment in which they grow. In this respect, the Bermuda Atla...
Chapter
Thanks to next-generation sequencing techniques, a very big amount of genomic data are available. Therefore, in the last years, biomedical databases are growing more and more. Analyzing this big amount of data with bioinformatics and big data techniques could lead to the discovery of new knowledge for the treatment of serious diseases. In this work...
Article
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Meningitis is an inflammation of the protective membranes covering the brain and the spinal cord. Meningitis can have different causes, and discriminating between meningitis etiologies is still considered a hard task, especially when some specific clinical parameters, mostly derived from blood and cerebrospinal fluid analysis, are not completely av...
Article
Full-text available
In this work Artificial Neural Networks and Genetic Programming are applied in order to assess the desertification status, a kind of land degradation, of an area, from meteorological and land use data. The approach has been tested in the Sannio (central Italy) region. Both the used soft computing methods show low error rates, and the Genetic Progra...
Article
In pervasive/ubiquitous computing environments, interacting users may evaluate their respective trustworthiness by using historical data coming from their past interactions. Nevertheless, when two users are at the first interaction, they have no historical data involving their own activities to be analyzed, and then use information (recommender-dat...
Article
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This paper describes a novel Video Surveillance as a Service (VSaaS) architecture. The proposed solution uses an add-on component, named WS-Gateway (WebSocket-based gateway), installed in the client’s private network (along with IP-cameras network). The WebSocket protocol is used to establish a bi-directional communication among the actors in the s...
Article
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Exposure to high levels of hyperbaric oxygen (\(\hbox {HBO}_{2}\)) can induce central nervous system oxygen toxicity in humans and animals, a phenomenon characterized by repeated tonic–clonic seizures. The risk of developing this type of convulsions represents the limiting factor in using \(\hbox {HBO}_{2}\) for a number of clinical and diving appl...
Article
In this paper, we present a fast method for classification of defects detected by eddy current testing (ECT). This is done by using defects derived by lab experiments. For any defect, the ECT magnetic field response for different EC-probe's paths is represented on a complex plane to obtain Lissajous' figures. Their shapes are described through the...
Chapter
Security and Resilience in Intelligent Data-Centric Systems and Communication Networks presents current, state-of-the-art work on novel research in theoretical and practical resilience and security aspects of intelligent data-centric critical systems and networks. The book analyzes concepts and technologies that are successfully used in the impleme...
Article
Full-text available
Pervasive computing is one of the latest and more advanced paradigms currently available in the computers arena. Its ability to provide the distribution of computational services within environments where people live, work or socialize leads to make issues such as privacy, trust and identity more challenging compared to traditional computing enviro...
Conference Paper
Spacecraft on-board autonomy is an important topic in currently developed and future space missions. In this study, we present a robust approach to the optimal policy of autonomous space systems modeled via Markov Decision Process (MDP) from the values assigned to its transition probability matrix. After addressing the curse of dimensionality in so...
Conference Paper
Fuzzy transform (F-transform) is a functional operator that proved to be effective in multiple processing tasks concerning time series and images, including summarization, compression, filtering and information fusion. Its operational definition is originally based on Ruspini partitions that, if on one side provides an easier interpretation of resu...
Chapter
Full-text available
Comunità e territori (bioterritori) intelligenti appartengono a una area di ricerca emergente mirata alla creazione di un ambiente migliore. Questo lavoro si focalizza sull’intelligenza computazionale per la protezione del paesaggio e lo sviluppo sostenibile dei territori attraverso la definizione di sistemi informativi distribuiti, focalizzati su...
Article
Full-text available
This study concerns the effectiveness of several techniques and methods of signals processing and data interpretation for the diagnosis of aerospace structure defects. This is done by applying different known feature extraction methods, in addition to a new CBIR-based one; and some soft computing techniques including a recent HPC parallel implement...
Conference Paper
Pervasive Computing is one of the latest and more advanced paradigms currently available in the computers arena. Its ability to provide the distribution of computational services within environments where people live, work or socialize leads to make issues such as privacy, trust and identity more challenging compared to traditional computing enviro...
Article
Full-text available
The aim of this work is to classify the aerospace structure defects detected by eddy current non-destructive testing. The proposed method is based on the assumption that the defect is bound to the reaction of the probe coil impedance during the test. Impedance plane analysis is used to extract a feature vector from the shape of the coil impedance i...
Article
The main aim in network anomaly detection is effectively spotting hostile events within the traffic pattern associated to network operations, by distinguishing them from normal activities. This can be only accomplished by acquiring the a-priori knowledge about any kind of hostile behavior that can potentially affect the network (that is quite impos...
Chapter
Full-text available
Worldwide, foodborne diseases are an important cause of mortality. There is a strong need to strengthen surveillance systems for foodborne diseases. Traceability is an increasingly common element of public and private systems for monitoring compliance with quality, environmental, and other product and process attributes related to food. The key iss...
Chapter
Intelligent communities and territories belong to an emerging movement targeting the creation of better environments. Technological information is recognized as an important factor shaping territorial systems of innovation. This paper focuses on territorial intelligence: distributed information systems localized over a region allowing continuous up...
Chapter
The use of the Internet has grown continuously in recent years and it is expected it still continues to grow significantly. The eCommerce applications are also growing significantly. In this work we describe an explicit reliable method for calculating the CO2 emissions of an eCommerce systen, using simple to find data. The methods use variables tha...
Article
Full-text available
Background: The huge quantity of data produced in Biomedical research needs sophisticated algorithmic methodologies for its storage, analysis, and processing. High Performance Computing (HPC) appears as a magic bullet in this challenge. However, several hard to solve parallelization and load balancing problems arise in this context. Here we discus...
Conference Paper
Full-text available
This study concerns with the diagnosis of aerospace structure defects by applying a HPC parallel implementation of a novel learning algorithm, named U-BRAIN. The Soft Computing approach allows advanced multi-parameter data processing in composite materials testing. The HPC parallel implementation overcomes the limits due to the great amount of data...
Article
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We investigate the potential of neural-network based classifiers for discriminating gravitational wave bursts (GWBs) of a given canonical family (e.g. core-collapse supernova waveforms) from typical transient instrumental artifacts (glitches), in the data of a single detector. The further classification of glitches into typical sets is explored. In...
Article
The ability of artificial neural networks (ANN) to model the rainfall–discharge relationships of karstic aquifers has been studied in the Terminio massif (Southern Italy), which supplies the Naples area with a yearly mean discharge of approximately 1–3.5 m3/s. The Mediterranean climate causes a rapid increase in evapotranspiration and a decrease in...
Article
Full-text available
Credit scoring is the assessment of the risk associated with lending to an organization or an individual. Genetic Programming is an evolutionary computational technique that enables computers to solve problems without being explicitly programmed. This paper proposes a genetic programming approach for risk assessment. In particular, the study is set...
Article
Full-text available
Understanding soil properties is an essential pre-requisite for sustainable land management. Assessment of these properties has long been gained through conventional laboratory analysis, which is considered costly and time consuming. Therefore, there is a need to develop alternative cheaper and faster techniques for soil analysis. In recent years,...
Article
Full-text available
Landslide hazard mapping is often performed through the identification and analysis of hillslope instability factors. In heuristic approaches, these factors are rated by the attribution of scores based on the assumed role played by each of them in controlling the development of a sliding process. The objective of this research is to forecast landsl...
Article
The problem of digital copyright protection can be considered as strictly tied to the rapid growth of the Internet, which has increased the cap abilities of reproducing and distributing digital content at a very low cost without loss of quality. Digital entertainment contents are easily accessible due to the reduction in cost of high-per formance d...
Article
Full-text available
Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (Uncertainty-managing Batch Relevance-based Artificial INtelligence), conceived for learning DNF Boolean formulas from partial truth tables, possibly with uncertain values o...
Article
We describe a VLSI implementation based on a FPGA of a new greedy algorithm for approximating minimum set covering in ad hoc wireless network applications. The implementation makes the algorithm suitable for embedded and real-time architectures. The algorithm, while not randomized, is based on a probability distribution that leads the greedy choice...
Article
In this paper, we consider learning problems defined on graph-structured data. We propose an incremental supervised learning algorithm for network-based estimators using diffusion kernels. Diffusion kernel nodes are iteratively added in the training process. For each new node added, the kernel function center and the output connection weight are de...
Conference Paper
A version of a new greedy algorithm for approximating minimum set cover is presented. The algorithm, while not randomized, is based on a probability distribution that leads the greedy choice. The algorithm has been specifically tailored to run on platforms with minimal computational hardware. We also describe an implementation based on a FPGA which...
Conference Paper
Full-text available
The problem addressed in this paper is to define a learning algorithm for the prediction of splice site locations in human DNA in the presence of sequence annotation errors in the training data. To this aim we generalize a previous machine learning algorithm. Experimental results on a common dataset including errors show the algorithm outperforms i...
Article
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We emphasize the difficulties of an experiment that can definitely discriminate between local realistic hidden-variables theories and quantum mechanics using the Bell CHSH inequalities and a real measurement apparatus. In particular, we analyze some examples in which the noise in real instruments can alter the experimental results, and the nontrivi...
Article
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The aim of this work is to describe a cleaning procedure of GenBank data, producing material to train and to assess the prediction accuracy of computational approaches for gene characterization. A procedure (GenBank2HS(3)D) has been defined, producing a dataset ((HSD)-D-3 - Homo Sapiens Splice Sites Dataset) of Homo Sapiens Splice regions extracted...
Article
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ionaccuracy of computational approaches for gene identification andcharacterization. From the complete GenBank Primate Sequences Rel.123(8436 entries), 697 entries of Human Nuclear DNA including a Gene withComplete CDS and with more than one exon have been selected accordingto assessed selection criteria[18] (file genbank_filtered.inf). 4450 exonsa...
Article
In this paper we consider the problem of approximating functions from noisy data. We propose an incremental supervised learning algorithm for RBF networks. Hidden Gaussian nodes are added in an iterative manner during the training process. For each new node added, the activation function center and the output connection weight are settled according...
Article
Editor: In a previous work (Esposito, Rampone, & Tagliaferri, 1994), a neural net model which can be used to decode codewords belonging to a binary linear code and to correct noisy patterns which it receives from a transmission channel has been described. The net reduces the error probability to zero in the range of the error correcting capacity of...
Article
In this work we investigate the use of a speaker adaptation technique, for speech recognition, based on neural network spectral mapping. Different multilayer perceptron neural network architectures are analyzed in order to optimize the spectral difference reduction in acoustic data of two speakers. Experiments are carried out in a telecontrol envir...
Article
We describe a neural net model that can be used to decode codewords belonging to a binary linear code and to correct noisy patterns that it receives from a transmission channel. The net reduces the error probability to zero in the range of the error correcting capacity of the code. Moreover we show a net simulation done in DISC, a general purpose p...
Article
Full-text available
We discuss the Carter's formula about the mankind evolution probability following the derivation proposed by Barrow and Tipler. We stress the relation between the existence of billions of galaxies and the evolution of at least one intelligent life, whose living time is not trivial, all over the Universe. We show that the existence probability and t...
Article
this paper we propose an incremental RBF network for function approximation from noisy data. Hidden gaussian nodes are iteratively added in the training process. For each new added node, the activation function center and the output connection weight are settled according to an extended chained version of the Nadaraja-Watson estimator [1]. Then the...
Conference Paper
We propose an incremental support vector machine (SVM) approach to regularization. Support vectors are added in an iterative manner during the training process. For each new vector added, the kernel parameters are settled according to an extended chained version of the Nadaraja-Watson estimator. We show this approach minimize the expected risk and...
Article
This paper describes a new learning algorithm (BRAIN), inferring DNF Boolean formulae from examples. The formula terms are computed in an iterative way, by identifying from the training set a relevance coefficient for each attribute. Results on splice-junction gene sequences and breast cancer machine learning data sets are reported.
Article
Full-text available
The problem addressed in this paper is the prediction of splice site locations in human DNA. The aims of the proposed approach are explicit splicing rule description, high recognition quality, and robust and stable 'one shot' data processing. These results are achieved by means of a new learning algorithm [BRAIN (Batch Relevance-based Artificial IN...
Conference Paper
Splice junctions are points on a DNA sequence at which superfluous DNA is removed during the process of protein creation in higher organisms. The problem afforded in this paper is to recognize, given a sequence of DNA, the boundaries between exons (the parts of the DNA sequence retained after splicing) and introns (the parts of the DNA sequence tha...
Article
By utilizing a new definition of product, we develop a neural net model. The memorization and generalization capabilities are investigated in an Information Theory fashion. To show the memorization capabilities, we use it as a decoder, and prove the net reduces the error probability to zero in the range of the error correcting capacity of the used...
Article
Astronomically controlled variations in the Earth's climate induce cyclic trends in the sedimentary process and record (Milankovitch periodicity). One of the main difficulties to be solved in order to choose among the registered periodicities is the conversion from the spatial (i.e. recurrent variations along the stratal sequences) to the temporal...
Article
An algorithm inferring a boolean linear code from noisy patterns received by a noisy channel, under the assumption of uniform occurrence distribution over the codewords, and an upper bound to the amount of data are presented. A vector quantizer is designed from the noisy patterns, choosing the obtained codebook as code approximation. It is shown bo...
Chapter
The aim of this paper is to show that additional perspectives are added to research on linear Neural Nets by utilizing a new definition of product, recently introduced (Caianiello, 92) in the context of Neural Nets defined on semirings rather than number fields. This we do by exhibiting its use for the design “on inspection” of a Neural Net which s...
Conference Paper
Full-text available
The authors develop a mathematical model of the mechanisms that the auditory apparatus uses for signal processing. They have studied the model of the peripheral auditory apparatus described by S. Seneff (1985, 1988). They complete it by adding new features such as a pitch detector and a neural synchrony detector module, by modifying some filter par...
Chapter
The developement of neural net research has involved several theoretical studies, neurobiological connections, learning architectures. Nevertheless few people investigated the minimal functional requirements of a neural-like hardware. In this paper it has show that, using a learning law developed in the last years [2,3,5,6], we obtain the elementar...

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