2023
Software
Unknown
Experimenting with formal verification and model-based development in railways: the case of UMC and Sparx Enterprise Architect - Complementary data
Basile D., Mazzanti F., Ferrari A.
This repository contains the UMC and SPARX EA data used in the paper: Experimenting with Formal Verification and Model-based Development in Railways: the case of UMC and Sparx Enterprise Architect by Davide Basile, Franco Mazzanti and Alessio Ferrari.DOI: 10.5281/zenodo.7920448
Project(s): 4SECURAIL
Metrics:
Basile D., Mazzanti F., Ferrari A.
This repository contains the UMC and SPARX EA data used in the paper: Experimenting with Formal Verification and Model-based Development in Railways: the case of UMC and Sparx Enterprise Architect by Davide Basile, Franco Mazzanti and Alessio Ferrari.DOI: 10.5281/zenodo.7920448
Project(s): 4SECURAIL
Metrics:
See at: CNR ExploRA
2023
Software
Unknown
A toolchain for strategy synthesis with spatial properties - Complementary material
Basile D., Ter Beek M. H., Bussi L., Ciancia V.
This is the complementary material for our paper ``A Toolchain for Strategy Synthesis with Spatial Properties'' accepted for publication at the Journal of Software Tools and Technology Transfer. This repository contains a permanent snapshot of https://github.com/contractautomataproject/CATLib_PngConverter/tree/ec0938043146b008bbbcb4ed3ec79c06dd2e47d6DOI: 10.5281/zenodo.8220527
Metrics:
Basile D., Ter Beek M. H., Bussi L., Ciancia V.
This is the complementary material for our paper ``A Toolchain for Strategy Synthesis with Spatial Properties'' accepted for publication at the Journal of Software Tools and Technology Transfer. This repository contains a permanent snapshot of https://github.com/contractautomataproject/CATLib_PngConverter/tree/ec0938043146b008bbbcb4ed3ec79c06dd2e47d6DOI: 10.5281/zenodo.8220527
Metrics:
See at: CNR ExploRA
2023
Software
Unknown
MEC: Mesoscale Events Classifier
Papini O.
This software consists of a Python 3 implementation of the Mesoscale Events Classifier (MEC) algorithm, which has been developed as part of the activities of Task 8.5 of the NAUTILOS project. The algorithm uses Sea Surface Temperature data coming from satellite missions to detect and classify patterns associated with "mesoscale events" in an upwelling ecosystem.Project(s): NAUTILOS
Papini O.
This software consists of a Python 3 implementation of the Mesoscale Events Classifier (MEC) algorithm, which has been developed as part of the activities of Task 8.5 of the NAUTILOS project. The algorithm uses Sea Surface Temperature data coming from satellite missions to detect and classify patterns associated with "mesoscale events" in an upwelling ecosystem.Project(s): NAUTILOS
See at: github.com | CNR ExploRA
2023
Software
Unknown
Modelling, verifying and testing the contract automata runtime environment with Uppaal: complementary data
Basile D.
This repository contains the complementary material for the paper: "Modelling and Verifying the Contract Automata Runtime Environment", Basile D. The latest version of the included files can be accessed through the GitHub repository of the Contract Automata Runtime Environment, https://github.com/contractautomataproject/CARE/tree/master/src/spec/uppaal In addition to the other contents, this Zenodo repository contains all the logs of the experiments.
Basile D.
This repository contains the complementary material for the paper: "Modelling and Verifying the Contract Automata Runtime Environment", Basile D. The latest version of the included files can be accessed through the GitHub repository of the Contract Automata Runtime Environment, https://github.com/contractautomataproject/CARE/tree/master/src/spec/uppaal In addition to the other contents, this Zenodo repository contains all the logs of the experiments.
See at: CNR ExploRA | zenodo.org
2023
Software
Unknown
Robot personalities module
Zedda E.
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
Zedda E.
Description: An application designed to enhance cognitive stimulation among older adults by manipulating robot behaviours into a cooking game. The application incorporates a personality module that generates two robot personalities (extravert and introvert) designed and implemented to improve the Human-Robot Interaction (HRI) of older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL Version: 5.0 CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/Personality
See at: CNR ExploRA
2023
Software
Unknown
Robot personalities adaptation system
Zedda E.
Description: An application with an adaptation technique implemented on a humanoid robot to make it autonomously adapt its behaviour during user interaction. The application read the user's state (smile value and gaze direction), classified the engagement level following a defined classification and adapted its behaviours using a Q-learning algorithm (Reinforcement Learning algorithm) performing different robot movements and dialogues according to the user state detected and robot personality chosen. The adaption system is applied at a difficult level of a cooking serious game. Technologies used: Java, QiSDK, SQL, Python CNR Link: https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/MediumAdaptation
Zedda E.
Description: An application with an adaptation technique implemented on a humanoid robot to make it autonomously adapt its behaviour during user interaction. The application read the user's state (smile value and gaze direction), classified the engagement level following a defined classification and adapted its behaviours using a Q-learning algorithm (Reinforcement Learning algorithm) performing different robot movements and dialogues according to the user state detected and robot personality chosen. The adaption system is applied at a difficult level of a cooking serious game. Technologies used: Java, QiSDK, SQL, Python CNR Link: https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/MediumAdaptation
See at: CNR ExploRA
2023
Software
Unknown
Match-mismatch user/robot personality
Zedda E.
An application that autonomously adapts the robot's personality based on the user personality test results, displaying a robot personality that aligns better with the user's traits in a cooking serious game for older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL
Zedda E.
An application that autonomously adapts the robot's personality based on the user personality test results, displaying a robot personality that aligns better with the user's traits in a cooking serious game for older adults with cognitive impairments. Technologies used: Java, QiSDK, SQL
See at: CNR ExploRA
2023
Software
Unknown
DialogFlow, Google speech API and ChatGPT4 on Pepper
Zedda E., Manca M.
Integration of DialogFlow and Google Speech API on a HRI application for Pepper robot. Technologies used: Java, QiSDK, SQL, Google Speech API, DialogFlow API, Azure and OpenAI API CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/DialogFlow_Pepper https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/GoogleSpeechAPI https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/ChatGPTAzure
Zedda E., Manca M.
Integration of DialogFlow and Google Speech API on a HRI application for Pepper robot. Technologies used: Java, QiSDK, SQL, Google Speech API, DialogFlow API, Azure and OpenAI API CNR Link: https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/DialogFlow_Pepper https://giteas2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/GoogleSpeechAPI https://gitea-s2i2s.isti.cnr.it/Human_in_Information_Systems_HIIS/ChatGPTAzure
See at: CNR ExploRA
2023
Software
Unknown
Q-Learning algorithm for robot behaviour adaptation
Zedda E.
An application that applies the Q-learning algorithm to support an adaptation strategy for the robot in the context of an application for cognitive training. The goal is to help the user maintain a high-engaged level and stimulate in case the user is at a low-engaged level. In the project, the robot agent learns its policy by leveraging the simulator by interacting with the simulated users, updating its knowledge using the Bellman Equation. The algorithm returns a trained Q matrix(s, a). Programming Language: Python
Zedda E.
An application that applies the Q-learning algorithm to support an adaptation strategy for the robot in the context of an application for cognitive training. The goal is to help the user maintain a high-engaged level and stimulate in case the user is at a low-engaged level. In the project, the robot agent learns its policy by leveraging the simulator by interacting with the simulated users, updating its knowledge using the Bellman Equation. The algorithm returns a trained Q matrix(s, a). Programming Language: Python
See at: CNR ExploRA
2023
Software
Unknown
VAE for dummies
Martino G.
Semplice implementazione di un Variational Autoencoder (VAE) in Pytorch Lightning con un applicativo interattivo ausiliario per esplorare in tempo reale lo spazio latente del VAE.
Martino G.
Semplice implementazione di un Variational Autoencoder (VAE) in Pytorch Lightning con un applicativo interattivo ausiliario per esplorare in tempo reale lo spazio latente del VAE.
See at: github.com | CNR ExploRA
2023
Software
Unknown
Image segmentation tool
Martino G.
Software sviluppato in Python con GUI che permette la creazione di dataset per la segmentazione di immagini e l'esportazione in formato COCO.
Martino G.
Software sviluppato in Python con GUI che permette la creazione di dataset per la segmentazione di immagini e l'esportazione in formato COCO.
See at: github.com | CNR ExploRA
2022
Software
Unknown
Concern - COmplex eveNt proCEssing monitoR iNfrastructure
Calabrò A.
Concern is a predictive simulation monitoring infrastructure that aims to cooperate within Digital Twin in execution on a simulated environment to avoid possible accidents or failures happen in real systems using forecasting and self-generation rules techniques.Project(s): BIECO
Calabrò A.
Concern is a predictive simulation monitoring infrastructure that aims to cooperate within Digital Twin in execution on a simulated environment to avoid possible accidents or failures happen in real systems using forecasting and self-generation rules techniques.Project(s): BIECO
See at: github.com | CNR ExploRA
2022
Software
Unknown
Contract automata runtime environment (v.1.0.0 - February 2022)
Basile D.
This document links the zenodo repository of CARE. Contract Automata Runtime Environment (v. February 2022) CARE is a library for implementing applications specified via contract automata. CARE provides a runtime environment to coordinate the CARE services that are implementing the contracts of the synthesised orchestration. Thus, CARE is the missing piece between specifications through contract automata and their implementations, so making explicit the low-level interactions realising the prescribed actions.DOI: 10.5281/zenodo.6393314
Metrics:
Basile D.
This document links the zenodo repository of CARE. Contract Automata Runtime Environment (v. February 2022) CARE is a library for implementing applications specified via contract automata. CARE provides a runtime environment to coordinate the CARE services that are implementing the contracts of the synthesised orchestration. Thus, CARE is the missing piece between specifications through contract automata and their implementations, so making explicit the low-level interactions realising the prescribed actions.DOI: 10.5281/zenodo.6393314
Metrics:
See at: CNR ExploRA
2022
Software
Unknown
Multivariate time series dataset generator
Belli D., Miori V.
A Java class that provides constructors and methods to generate synthetic data sets of multi-variate time series with/without anomalies. The class Random is used to introduce the right percentage of aleatority to the generation of the signals. Temporal patterns have been modeled based on trigonometric functions, randomly selected feature by feature. To reproduce the anomalies, a little noise is added to the generated signals. The class has been designed to test machine learning algorithms developed for anomaly detection in multivariate time series data.
Belli D., Miori V.
A Java class that provides constructors and methods to generate synthetic data sets of multi-variate time series with/without anomalies. The class Random is used to introduce the right percentage of aleatority to the generation of the signals. Temporal patterns have been modeled based on trigonometric functions, randomly selected feature by feature. To reproduce the anomalies, a little noise is added to the generated signals. The class has been designed to test machine learning algorithms developed for anomaly detection in multivariate time series data.
See at: github.com | CNR ExploRA
2022
Software
Unknown
Story Map Building and Visualising Tool (SMBVT)
Lenzi E., Bartalesi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud, MOVING
Lenzi E., Bartalesi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud
, MOVING See at: github.com | CNR ExploRA
2022
Software
Unknown
IMAGO Annotation Tool
Pratelli N., Bartalesi V., Lenzi E.
To populate the ontology developed within the Index Medii Aevi Geographiae Operum (IMAGO) -- Italian National Research Project (2020-23), we developed a semi-automatic Web tool, called IMAGO Annotation Tool, to allow scholars to insert knowledge about Medieval and Reinassance works through a user-friendly interface. The tool was created to reduce the time to insert knowledge and to avoid the insertion of mistakes thanks to the use of predefined lists of works, authors, libraries, places, geographic coordinates, and literary genres. Each field of the interface maps a class of the IMAGO ontology. The frontend interface is built using HTML5, CSS3, JavaScript, and the Bootstrap library, using a Python backend, e.i., a Django framework and a PostgreSQL DB. Once the data about a work is inserted through the tool interface, this is encoded as an OWL knowledge base and stored in a triple store. The data is first exported to a JSON object. Indeed our software uses a JSON schema to represent the data, structured according to the IMAGO ontology classes. The JSON object is processed by Java software, which transforms it into an OWL graph encoded in RDF/XML and Turtle formats. This software carries out its task by relying on the Apache Jena library. The graph is finally stored in a Fuseki triple store, and it can be queried through a SPARQL endpoint.
Pratelli N., Bartalesi V., Lenzi E.
To populate the ontology developed within the Index Medii Aevi Geographiae Operum (IMAGO) -- Italian National Research Project (2020-23), we developed a semi-automatic Web tool, called IMAGO Annotation Tool, to allow scholars to insert knowledge about Medieval and Reinassance works through a user-friendly interface. The tool was created to reduce the time to insert knowledge and to avoid the insertion of mistakes thanks to the use of predefined lists of works, authors, libraries, places, geographic coordinates, and literary genres. Each field of the interface maps a class of the IMAGO ontology. The frontend interface is built using HTML5, CSS3, JavaScript, and the Bootstrap library, using a Python backend, e.i., a Django framework and a PostgreSQL DB. Once the data about a work is inserted through the tool interface, this is encoded as an OWL knowledge base and stored in a triple store. The data is first exported to a JSON object. Indeed our software uses a JSON schema to represent the data, structured according to the IMAGO ontology classes. The JSON object is processed by Java software, which transforms it into an OWL graph encoded in RDF/XML and Turtle formats. This software carries out its task by relying on the Apache Jena library. The graph is finally stored in a Fuseki triple store, and it can be queried through a SPARQL endpoint.
See at: imagoarchive.it | CNR ExploRA
2022
Software
Unknown
Geoportal data entry app [Release 3.0.0]
Mangiacrapa F.
Il sistema "geoportal-data-entry-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali, si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, il Project management (data entry e gestione del ciclo di vita) di prodotti spazio-temporali basati su Use Case Descriptor (UCD) document che ne specificano il modello del documento, gestione, lifecycle, handler, etc. Pertanto il sistema permette di: (i) accedere e ricercare i prodotti pubblicati nel sistema, (ii) accedere al report di pubblicazione dei prodotti, visionare lo stato di pubblicazione (SUCCESS, WARNING, ERROR), etc., (iii) accedere alla loro visualizzazione su mappa, (iv) gestire il loro contenuto mediante il flusso (Workflow) di pubblicazione, (v) gestire le relazioni (collegamenti temporali e/o qualitativi) tra i prodotti. Il sistema in generale consente il data-entry di qualsivoglia prodotto avente caratteristiche spazio-temporali e non, i cui metadati sono specificati da un indice che specifica uno o più Metadata Profile e la struttura del JSON risultante. Un Metadata Profile è un documento XML-based di specifica di un "prodotto generico" (es. un dataset spazio-temporale) e dei suoi attributi, che indica la lista dei metadati che lo compongono e che possono essere di tipo descrittivo, spaziale, temporale, risorsa (es. file immagine), ecc..Project(s): ARIADNEplus
Mangiacrapa F.
Il sistema "geoportal-data-entry-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali, si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, il Project management (data entry e gestione del ciclo di vita) di prodotti spazio-temporali basati su Use Case Descriptor (UCD) document che ne specificano il modello del documento, gestione, lifecycle, handler, etc. Pertanto il sistema permette di: (i) accedere e ricercare i prodotti pubblicati nel sistema, (ii) accedere al report di pubblicazione dei prodotti, visionare lo stato di pubblicazione (SUCCESS, WARNING, ERROR), etc., (iii) accedere alla loro visualizzazione su mappa, (iv) gestire il loro contenuto mediante il flusso (Workflow) di pubblicazione, (v) gestire le relazioni (collegamenti temporali e/o qualitativi) tra i prodotti. Il sistema in generale consente il data-entry di qualsivoglia prodotto avente caratteristiche spazio-temporali e non, i cui metadati sono specificati da un indice che specifica uno o più Metadata Profile e la struttura del JSON risultante. Un Metadata Profile è un documento XML-based di specifica di un "prodotto generico" (es. un dataset spazio-temporale) e dei suoi attributi, che indica la lista dei metadati che lo compongono e che possono essere di tipo descrittivo, spaziale, temporale, risorsa (es. file immagine), ecc..Project(s): ARIADNEplus
See at: code-repo.d4science.org | CNR ExploRA
2022
Software
Unknown
Geoportal data viewer app [Release 3.0.0]
Mangiacrapa F.
Il sistema "geoportal-data-viewer-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, l'accesso e la ricerca di prodotti spazio-temporali, mediante una web-map GIS che consente di: (i) fruire e ricercare i prodotti pubblicati nel sistema tramite "mappa geografica" (dimensione spaziale), (ii) navigazione delle relazioni tra progetti (evoluzione dei progetti nel tempo) tramite "timeline" widget (dimensione temporale), (iii) visionare i metadati e le risorse (immagini, layer, ecc..) dei prodotti tramite la "vista sui dettagli", (iv) esportare una vista della mappa con il layer di interesse o aggiungere i layer di un progetto alla mappa principale, (v) gestire ordine e sovrapposizione dei layer, (vi) fare interrogazioni spaziali sui layer e visionare il loro risultato, (vii) ricercare tramite interrogazioni su metadati o dimensione temporale i prodotti di interesse.Project(s): ARIADNEplus
Mangiacrapa F.
Il sistema "geoportal-data-viewer-app", nasce nell'ambito del progetto europeo "ARIADNEPlus", in cui in collaborazione e per i referenti dell'Istituto centrale per l'Archeologia (ICA) e per il Ministero dei Beni Culturali si è realizzato un ambiente di prototipazione per il Geoportale Nazionale per l'Archeologia (GNA). In particolare, il sistema permette agli attori che lo utilizzano, l'accesso e la ricerca di prodotti spazio-temporali, mediante una web-map GIS che consente di: (i) fruire e ricercare i prodotti pubblicati nel sistema tramite "mappa geografica" (dimensione spaziale), (ii) navigazione delle relazioni tra progetti (evoluzione dei progetti nel tempo) tramite "timeline" widget (dimensione temporale), (iii) visionare i metadati e le risorse (immagini, layer, ecc..) dei prodotti tramite la "vista sui dettagli", (iv) esportare una vista della mappa con il layer di interesse o aggiungere i layer di un progetto alla mappa principale, (v) gestire ordine e sovrapposizione dei layer, (vi) fare interrogazioni spaziali sui layer e visionare il loro risultato, (vii) ricercare tramite interrogazioni su metadati o dimensione temporale i prodotti di interesse.Project(s): ARIADNEplus
See at: code-repo.d4science.org | CNR ExploRA
2022
Software
Unknown
gCube D4Science Data Catalog [Release 2.2.4]
Mangiacrapa F.
The gCube Data Catalogue is a software component that provides facilities for: a) (meta)data publishing and management based on roles; b) vres' products publishing; c) making data products publicly available; d) enriching products of metadata to maximise their potential reuse and making them searchable (via title, tags etc) are based on the CKAN technology. The gcube-ckan-datacatalog application allows to show all the metadata available in the CKAN instance, as well as publish a new product, retrieve the list of organizations (i.e. Virtual Research Environments) to which the user belongs and his/her already published products. Moreover, the "gcube-ckan-datacatalog" application (via configuration) provides moderation of its content enabling the user/s with the Moderator role to approve/reject the products under review.Project(s): Blue Cloud
Mangiacrapa F.
The gCube Data Catalogue is a software component that provides facilities for: a) (meta)data publishing and management based on roles; b) vres' products publishing; c) making data products publicly available; d) enriching products of metadata to maximise their potential reuse and making them searchable (via title, tags etc) are based on the CKAN technology. The gcube-ckan-datacatalog application allows to show all the metadata available in the CKAN instance, as well as publish a new product, retrieve the list of organizations (i.e. Virtual Research Environments) to which the user belongs and his/her already published products. Moreover, the "gcube-ckan-datacatalog" application (via configuration) provides moderation of its content enabling the user/s with the Moderator role to approve/reject the products under review.Project(s): Blue Cloud
See at: code-repo.d4science.org | CNR ExploRA
2022
Software
Unknown
Nautilos citizen science application
Tampucci M., Pieri G.
Applicazione per dispositivi Android, sviluppata nell'ambito del progetto Nautilos, per la raccolta di dati derivanti da campagne per la raccolta di plastiche sulla spiaggia, catalogazione di fauna e flora marina e analisi della qualità delle acque.Project(s): NAUTILOS
Tampucci M., Pieri G.
Applicazione per dispositivi Android, sviluppata nell'ambito del progetto Nautilos, per la raccolta di dati derivanti da campagne per la raccolta di plastiche sulla spiaggia, catalogazione di fauna e flora marina e analisi della qualità delle acque.Project(s): NAUTILOS
See at: CNR ExploRA