0000000000334299

AUTHOR

Salvatore Aronica

showing 26 related works from this author

Identifying small pelagic Mediterranean fish schools from acoustic and environmental data using optimized artificial neural networks

2019

Abstract The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of an…

0106 biological sciencesMarine conservationMaximum sustainable yieldFish stockFish school010603 evolutionary biology01 natural sciencesAcoustic surveyEnvironmental dataAnchovymedia_common.cataloged_instanceEuropean unionEcology Evolution Behavior and Systematicsmedia_commonEcologybiologySettore INF/01 - Informaticabusiness.industry010604 marine biology & hydrobiologyApplied MathematicsEcological ModelingEnvironmental resource managementPelagic zonebiology.organism_classificationClassificationComputer Science ApplicationsGeographyComputational Theory and MathematicsFishing industryModeling and SimulationbusinessNeural networks
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Pelagic species identification by using a PNN neural network and echo-sounder data

2017

For several years, a group of CNR researchers conducted acoustic surveys in the Sicily Channel to estimate the biomass of small pelagic species, their geographical distribution and their variations over time. The instrument used to carry out these surveys is the scientific echo-sounder, set for different frequencies. The processing of the back scattered signals in the volume of water under investigation determines the abundance of the species. These data are then correlated with the biological data of experimental catches, to attribute the composition of the various fish schools investigated. Of course, the recognition of the fish schools helps to produce very good results, that is very clo…

Probabilistic neural networkComputer Science (all)ClassificationPelagic species identificationTheoretical Computer Science
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Seismic stratigraphy of the north-westernmost area of the Malta Plateau (Sicily Channel): The Middle Pleistocene-Holocene sedimentation in a tidally …

2022

In this study we present the results of a seismic-stratigraphic analysis of sub-bottom profiles in the north-westernmost area of the Malta Plateau in order to define the depositional mechanisms for the upper Quaternary sequences. During this interval the morphology of the Malta Plateau was characterized by a ramp and bathymetries not exceeding 200 m. Two major unconformities, related to MIS 6 and MIS 2 (the latter corresponding to the Last Glacial Maximum, LGM), characterize the upper Quaternary sequences. The geometries of the recognized seismic units indicate as depositional mechanisms were controlled by subsidence and sea-level fluctuations. In detail, deposits related to the last glacia…

QuaternaryGeochemistry and PetrologySand sheetSand sheet; Infralittoral prograding wedge; Bedforms; Coastal dune system; Malta Plateau; QuaternaryGeologyCoastal dune systemBedforms Coastal dune system Infralittoral prograding wedge Malta Plateau Quaternary Sand sheetOceanographyBedformsMalta PlateauInfralittoral prograding wedge
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STOCHASTIC DYNAMICS OF TWO PICOPHYTOPLANKTON POPULATIONS IN A REAL MARINE ECOSYSTEM

2013

A stochastic reaction-diffusion-taxis model is analyzed to get the stationary distribution along water column of two species of picophytoplankton, that is picoeukaryotes and Prochlorococcus. The model is valid for weakly mixed waters, typical of the Mediterranean Sea. External random fluctuations are considered by adding a multiplicative Gaussian noise to the dynamical equation of the nutrient concentration. The statistical tests show that shape and magnitude of the theoretical concentration profile exhibit a good agreement with the experimental findings. Finally, we study the effects of seasonal variations on picophytoplankton groups, including an oscillating term in the auxiliary equation…

PhysicsGeneral Physics and AstronomySpatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsRandom processeSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)OceanographyStochastic dynamicsMarine ecosystemStochastic differential equationsSpatial ecologyDeep chlorophyll maximumMarine ecosystemPhytoplankton dynamic
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The impact of landfills on the air quality of towns: A simple heuristic model for the city of Palermo

2009

In this study, the landfill of Palermo, is investigated as a potential source of the unusual methane concentrations found in the urban context. The source for these pollution episodes is identified by means of a simple heuristic method. A cross-correlation analysis between wind data and methane concentration levels is also used to confirm the hypotheses formulated. Doppler Sound Detection And Ranging (SODAR) measurements are used to investigate the air masses dynamics at the landfill, in order to better support the adopted assumptions. This interpretative method can be adopted in the first assessment stages of the environmental site performance in order to single out the candidate pollution…

PollutionSettore ING-IND/11 - Fisica Tecnica AmbientaleHeuristicmedia_common.quotation_subjectlandfillAir pollutionSODARContext (language use)Management Monitoring Policy and Lawheuristic impactmedicine.disease_causePollutionCivil engineeringair qualityenvironmental impactSimple (abstract algebra)Greenhouse gasmedicineEnvironmental scienceWaste Management and DisposalAir quality indexmedia_common
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Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion …

2013

A stochastic advection-reaction-diffusion model with terms of multiplicative white Gaussian noise, valid for weakly mixed waters, is studied to obtain the vertical stationary spatial distributions of two groups of picophytoplankton, i.e., picoeukaryotes and Prochlorococcus, which account about for 60% of total chlorophyll on average in Mediterranean Sea. By numerically solving the equations of the model, we analyze the one-dimensional spatio-temporal dynamics of the total picophytoplankton biomass and nutrient concentration along the water column at different depths. In particular, we integrate the equations over a time interval long enough, obtaining the steady spatial distributions for th…

ChlorophyllPopulation DynamicsPopulation ModelingRandom processeAtmospheric scienceschemistry.chemical_compoundTheoretical EcologyWater columnMediterranean seaDeep chlorophyll maximumCalculusMultidisciplinaryEcologybiologyEcologyApplied MathematicsPhysicsQStatisticsRComplex SystemsStochastic differential equationsInterdisciplinary PhysicsMedicineDeep chlorophyll maximumProchlorococcusResearch ArticleChlorophyll aScienceStatistical MechanicsDifferential EquationsPhytoplanktonMarine ecosystemMediterranean SeaSpatial ecologyStatistical MethodsPhytoplankton dynamicBiologyComputerized SimulationsStochastic ProcessesPopulation BiologyAdvectionComputational BiologyRandom VariablesModels TheoreticalSpatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsProbability Theorybiology.organism_classificationMarine EnvironmentsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Nonlinear DynamicschemistryChlorophyllComputer SciencePhytoplanktonEcosystem ModelingMathematicsEcological EnvironmentsPLoS ONE
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Spatio-temporal dynamics of a planktonic system and chlorophyll distribution in a 2D spatial domain: matching model and data

2017

AbstractField data on chlorophyll distribution are investigated in a two-dimensional spatial domain of the Mediterranean Sea by using for phytoplankton abundances an advection-diffusion-reaction model, which includes real values for physical and biological variables. The study exploits indeed hydrological and nutrients data acquired in situ, and includes intraspecific competition for limiting factors, i.e. light intensity and phosphate concentration. As a result, the model allows to analyze how both the velocity field of marine currents and the two components of turbulent diffusivity affect the spatial distributions of phytoplankton abundances in the Modified Atlantic Water, the upper layer…

Chlorophyll0301 basic medicineChlorophyll aScienceSpatial ecology; Marine ecosystems; Phytoplankton dynamics; Partial differential equationsAtmospheric sciencesArticlePhosphates03 medical and health scienceschemistry.chemical_compoundSpatio-Temporal AnalysisMediterranean seaWater columnPhytoplanktonMediterranean SeaMarine ecosystemSpatial ecologySeawaterTransectPhytoplankton dynamicMultidisciplinaryEcologyChlorophyll AQTemperatureRModels TheoreticalPlanktonPartial differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Light intensity030104 developmental biologychemistryChlorophyllPhytoplanktonMedicineEnvironmental scienceSeasonsScientific Reports
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Pattern Classification from Multi-beam Acoustic Data Acquired in Kongsfjorden

2021

Climate change is causing a structural change in Arctic ecosystems, decreasing the effectiveness that the polar regions have in cooling water masses, with inevitable repercussions on the climate and with an impact on marine biodiversity. The Svalbard islands under study are an area greatly influenced by Atlantic waters. This area is undergoing changes that are modifying the composition and distribution of the species present. The aim of this work is to provide a method for the classification of acoustic patterns acquired in the Kongsfjorden, Svalbard, Arctic Circle using multibeam technology. Therefore the general objective is the implementation of a methodology useful for identifying the a…

geographygeography.geographical_feature_categorybusiness.industryMultibeamk-meansk-means clusteringClimate changeGlacierShoaling and schoolingSettore MAT/01 - Logica MatematicaData setWater columnEcho-surveyPolarPhysical geographyArtificial intelligenceCluster analysisbusinessGeology
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Automatic classification of acoustically detected krill aggregations: A case study from Southern Ocean

2022

Acoustic surveys represent the standard methodology to assess the spatial distribution and abundance of pelagic organisms characterized by aggregative behaviour. The species identification of acoustically observed aggregations is usually performed by taking into account the biological sampling and according to expert-based knowledge. The precision of survey estimates, such as total abundance and spatial distribution, strongly depends on the efficiency of acoustic and biological sampling as well as on the species identification. In this context, the automatic identification of specific groups based on energetic and morphological features could improve the species identification process, allo…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEnvironmental EngineeringRoss SeaSettore INF/01 - InformaticaEcological Modelingk-meansAcousticKrillInternal validation indicesSoftwareHierarchical clustering
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Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea)

2021

This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200 kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. Th…

0106 biological sciencesKrillbiologybusiness.industry010604 marine biology & hydrobiologyEuphausiaSettore MAT/01 - Logica MatematicaEuphausia crystallorophiasbiology.organism_classificationSpatial distributionMachine learning for pelagic species classification01 natural sciencesKrill identification010104 statistics & probabilityRoss SeaAcoustic dataArtificial intelligence0101 mathematicsCluster analysisbusinessRelative species abundanceGeologyEnergy (signal processing)Global biodiversityRemote sensing
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Estimation of biogas produced by the landfill of Palermo, applying a Gaussian model

2008

Abstract In this work, a procedure is suggested to assess the rate of biogas emitted by the Bellolampo landfill (Palermo, Italy), starting from the data acquired by two of the stations for monitoring meteorological parameters and polluting gases. The data used refer to the period November 2005–July 2006. The methane concentration, measured in the CEP suburb of Palermo, has been analysed together with the meteorological data collected by the station situated inside the landfill area. In the present study, the methane has been chosen as a tracer of the atmospheric pollutants produced by the dump. The data used for assessing the biogas emission refer to night time periods characterized by weak…

Greenhouse EffectPoint sourceNormal DistributionWindMethaneAtmosphereMultiple pointchemistry.chemical_compoundBiogaswaste; waste management;TRACERwasteWaste Management and DisposalAir PollutantsSettore ING-IND/11 - Fisica Tecnica AmbientaleWaste managementEnvironmental engineeringModels TheoreticalRefuse DisposalchemistryItalyAtmospheric pollutantsEnvironmental sciencewaste managementGasesSingle point source
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Modeling of Sensory Characteristics Based on the Growth of Food Spoilage Bacteria

2016

During last years theoretical works shed new light and proposed new hypothesis on the mechanisms which regulate the time behaviour of biological populations in different natural systems. Despite of this, the role of environmental variables in ecological systems is still an open question. Filling this gap of knowledge is a crucial task for a deeper comprehension of the dynamics of biological populations in real ecosystems. In this work we study how the dynamics of food spoilage bacteria influences the sensory characteristics of fresh fish specimens. This topic is crucial for a better understanding of the role played by the bacterial growth on the organoleptic properties, and for the quality …

Stochastic ordinary differential equationmedia_common.quotation_subjectFood spoilageOrganolepticFOS: Physical sciencesSensory systemContext (language use)BiologyPopulation dynamic01 natural sciencesSensory analysisPopulation dynamics; Predictive microbiology; Stochastic ordinary differential equations; Modeling and Simulation010305 fluids & plasmas0103 physical sciencesStatisticsQuality (business)010306 general physicsQuantitative Biology - Populations and EvolutionCondensed Matter - Statistical Mechanicsmedia_commonPredictive microbiologyStatistical Mechanics (cond-mat.stat-mech)EcologyApplied MathematicsPopulations and Evolution (q-bio.PE)Experimental dataSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Modeling and SimulationFOS: Biological sciencesPredictive microbiology
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A novel method to simulate the 3D chlorophyll distribution in marine oligotrophic waters

2021

Abstract A 3D advection-diffusion-reaction model is proposed to investigate the abundance of phytoplankton in a difficult-to-access ecosystem such as the Gulf of Sirte (southern Mediterranean Sea) characterized by oligotrophic waters. The model exploits experimentally measured environmental variables to reproduce the dynamics of four populations that dominate phytoplankton community in the studied area: Synechococcus, Prochlorococcus HL, Prochlorococcus LL and picoeukaryotes. The theoretical results obtained for phytoplankton abundances are converted into chl-a and Dvchl-a concentrations, and the simulated vertical chlorophyll profiles are compared to the corresponding experimentally acquir…

Numerical AnalysisPhytoplankton dynamicsChlorophyll distributionSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematicibiologyApplied MathematicsSynechococcusbiology.organism_classificationSpatial distributionchemistry.chemical_compoundMediterranean seaOceanographychemistryAbundance (ecology)Modeling and SimulationChlorophyllPhytoplanktonEnvironmental scienceSpatial ecologyMarine ecosystemProchlorococcusMarine ecosystems
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A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden

2022

The Svalbardsis one of the most intensively studied marine regions in the Artic; here the composition and distribution of marine assemblages are changing under the effect of global change, and marine communities are monitored in order to understand the long-term effects on marine biodiversity. In the present work, acoustic data collected in the Kongsfjorden using multi-beam technology was analyzed to develop a methodology for identifying and classifying 3D acoustic patterns related to fish aggregations. In particular, morphological, energetic and depth features were taken into account to develop a multi-variate classification procedure allowing to discriminate fish species. The results obta…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEnvironmental Engineering3D patternSettore INF/01 - InformaticaClusterEcological ModelingFish schoolMulti-beamK-meansSoftwareEnvironmental Modelling & Software
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Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics

2013

In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…

Stochastic modellingFOS: Physical sciencesStructural basinBiologyRandom processe01 natural sciencesIntraspecific competitionMediterranean sea0103 physical sciencesPhytoplanktonMarine ecosystemSpatial ecologyMarine ecosystem14. Life underwaterQuantitative Biology - Populations and Evolution010306 general physicsPhytoplankton dynamic010301 acousticsEcology Evolution Behavior and SystematicsDeep chlorophyll maximumEcologyEcological ModelingPopulations and Evolution (q-bio.PE)Spatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Oceanography13. Climate actionPhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesSpatial ecologyStochastic differential equationsDeep chlorophyll maximumData Analysis Statistics and Probability (physics.data-an)
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I rilasci di biogas della discarica di “Bellolampo” e gli effetti sulla qualità dell’aria urbana di Palermo

2005

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A Gaussian model for evaluating the release of CH4 by the landfill of Palermo

2006

Many landfills for urban solid waste have been developed in sites very close to urbanised areas thus exposing the population to various dangerous pollutants. The landfill of "Bellolampo", located a few kilometres from the city ofPalermo is one of these. It was officially created in the eighties and only some years later it was decided convert it into a controlled landfill, soon becoming a catch basin of refuse for a large hinterland constituted by approximately 50 small towns. In recent years the city of Palermo has been equipped with a network of weather and air-quality stations for monitoring the main components that afe responsible for atmospheric pollution; it consists of 10 fixed stati…

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Artificial neural networks for fault tollerance of an air-pressure sensor network

2017

A meteorological tsunami, commonly called Meteotsunami, is a tsunami-like wave originated by rapid changes in barometric pressure that involve the displacement of a body of water. This phenomenon is usually present in the sea cost area of Mazara del Vallo (Sicily, Italy), in particular in the internal part of the seaport canal, sometimes making local population at risk. The Institute for Coastal Marine Environment (IAMC) of the National Research Council in Italy (CNR) have already conducted several studies upon meteotsunami phenomenon. One of the project has regarded the creation of a sensors network composed by micro-barometric sensors, located in 4 different stations close to the seaport …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMeteotsunamiSettore INF/01 - InformaticaPressure sensorComputer Science (all)Neural networkTheoretical Computer Science
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Evaluation of concentrations in sites near the landfill of Palermo

2006

In this paper a new method is presented for the evaluation of methane concentration near urban sites. The work is based on field measurements taken for a lon period of time on selected sites of the town of Palermo. The main finding of the work is that the landfill seriously affects the air quality of the town, at least around the selected sites

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Linking ecological and physical features in the Strait of Sicily preliminary results of air - sea interaction.

2007

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Stima dei flussi di calore latente e sensibile in differenti aree del Mediterraneo Centrale, attraverso strumentazione acustica e tradizionale.

2007

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Evaluation of methane concentrations in sites near the landfill of Palermo

2006

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Urban Daily Peak-Forecasting NOx Using Recurrent Neural Network

2006

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Daily Urban NOx Peak Forecasting Using Recurrent Neural Network

2006

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ANN (Artificial Neural Network) model for daily prediction of Methane concentration

2007

According to the protocols for the reduction of the production of the gases responsible of the greenhouse effect, it makes necessary to develop systems able to forecast and to evaluate such gases. The dump of Bellolampo, situated in proximity of the urban area in Palermo, is a source of CO2 and CH4. It was officially created in the eighties and only some years later it was decided to convert it into a controlled landfill, soon becoming a catch basin of refuse for a large hinterland constituted by approximately 50 small towns. The city of Palermo has been equipped with a network of weather and air-quality stations far monitoring the main components that are responsible for atmospherlc pollut…

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Stima dei flussi energetici all’interfaccia aria-mare con l’impiego di SST da Satellite e dati rilevati in situ.

2007

La conoscenza dei flussi energetici scambiati fra oceano e bassa atmosfera è un requisito utile per modellare e comprendere il sistema climatico e la dinamica degli oceani. L’elevata difficoltà di effettuare misure in situ ed in continuo in ambiente marino induce spesso all’utilizzo ausiliario di strumentazione satellitare. Nel presente lavoro è stato effettuato un confronto tra la stima dei flussi energetici superficiali valutati con dati provenienti da satellite e quelli ottenuti da misure in situ. In particolare, per il confronto, sono stati utilizzati i dati SST acquisiti dal satellite NOAA e i dati raccolti in situ dai sensori istallati a bordo della Nave Oceanografica Urania nel corso…

Flusso di Calore Latente Flusso di Calore Sensibile SST Bulk Formula Immagini Satellitari.Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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