Search results for "artificial intelligence"

showing 10 items of 6122 documents

SESAMO: An integrated framework for gathering, managing and sharing environmental data

2016

ICT systems are widely adopted for environmental management, but existing solutions address limited tasks and compose a plethora of heterogeneous tools, which impose a great additional effort on the operators. This work presents SESAMO, a novel framework to provide the operators with a unique tool for gathering, managing and merging environmental and territorial data. SESAMO uses WSNs for providing pervasive monitoring of environmental phenomena and exploits a multi-tier infrastructure in order to integrate data coming from heterogeneous information sources.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge managementEnvironmental managementExploitSESAMOComputer sciencebusiness.industryPervasive sensing020206 networking & telecommunications02 engineering and technologyData scienceEnvironmental dataHuman-Computer InteractionComputer Networks and CommunicationWork (electrical)Information and Communications TechnologyOrder (exchange)Computer systems and technologie0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHeterogeneous informationbusinessSoftware
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An Ontology Design Methodology for Knowledge-Based Systems with Application to Bioinformatics

2012

Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the what to do question), the solver method to resolve it (answering the how to do question) and the type of input data required (answering the what I need question). The main purpose of the proposed paradigm is to facilitate the generalization of the application do…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningComputer sciencebusiness.industryKnowledge organizationOpen Knowledge Base ConnectivityOntology (information science)BioinformaticsArtificial intelligence; Expert systems; Knowledge representation; Ontology; ProteinsKnowledge-based systemsKnowledge extractionKnowledge baseArtificial IntelligenceDomain knowledgebusiness
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Learning high-level tasks through imitation

2006

This paper presents the cognitive architecture Con-SCIS (Conceptual Space based Cognitive Imitation System), which tightly links low-level data processing with knowledge representation in the context of imitation learning. We use the word imitate to refer to the paradigm of program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a simplified two-dimensional world populated with vario…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningComputer sciencebusiness.industrymedia_common.quotation_subjectImitation learningContext (language use)Cognitive architectureKinematicsMotion (physics)RoboticTask (computing)Human–computer interactionMachine learningRobotComputer visionArtificial intelligenceCognitive imitationImitationbusinessHumanoid robotmedia_common2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
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Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots

2007

The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically a…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningINFORMATIONComputer scienceLatent semantic analysisbusiness.industryConcept mapcomputer.software_genreSoftware agentSemantic layerArtificial intelligencebusinessAGENTScomputerNatural language processing
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Sub-Symbolic Knowledge Representation for Evocative Chat-Bots

2008

A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE a…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningLatent semantic analysisOntology Conceptbusiness.industryComputer scienceWordNetOntology (information science)Part of speechcomputer.software_genreArtificial intelligenceDialog systemLayer (object-oriented design)businesssemantic space chatbotcomputerNatural language processing
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A Novel Expert System for Non-Invasive Liver Iron Overload Estimation in Thalassemic Patients

2014

Expert Systems can integrate logic based often on computational intelligence methods and they are used in complex problem solving. In this work an Expert System for classifying liver iron concentration in thalassemic patients is presented. In this work, an ANN is used to validate the output of the L.I.O.MO.T (Liver Iron Overload Monitoring in Thalassemia) method against the output of the state-of-the-art method based on MRI T2 assessment for liver iron concentration. The model has been validated with a dataset of 200 samples. The experimental Mean Squared Error results and Correlation show interesting performances. The proposed algorithm has been developed as a plug in for OsiriX Dicom View…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniLiver Iron ConcentrationMean squared errorArtificial neural networkComputer scienceRemote patient monitoringbusiness.industryComputational intelligenceComplex problem solvingcomputer.software_genreExpert systemLIOMOT MRI T2* Iron Liver Thalassemia Artificial Neural Network Expert System OsiriXLiver ironArtificial intelligenceData miningbusinesscomputer
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Object Matching in Distributed Video Surveillance Systems by LDA-Based Appearance Descriptors

2009

Establishing correspondences among object instances is still challenging in multi-camera surveillance systems, especially when the cameras’ fields of view are non-overlapping. Spatiotemporal constraints can help in solving the correspondence problem but still leave a wide margin of uncertainty. One way to reduce this uncertainty is to use ap- pearance information about the moving objects in the site. In this paper we present the preliminary results of a new method that can capture salient appearance characteristics at each camera node in the network. A Latent Dirichlet Allocation (LDA) model is created and maintained at each node in the camera network. Each object is encoded in terms of the…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMatching (statistics)business.industryComputer scienceNode (networking)Video surveillanceObject matchingObject (computer science)Latent Dirichlet allocationsymbols.namesakeSalientMargin (machine learning)symbolsComputer visionArtificial intelligencebusinessCorrespondence problemconsistent labelling
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Referenceless thermometry using radial basis function interpolation

2014

The Proton Resonance Frequency (PRF) shift provide a method for temperature change measurements during thermotherapy. Conventional PRF thermometry works subtracting one or multiple baseline images. The method leads to artifacts caused by tissue motion and frequency drift. Various works estimating the background phase from each acquired image phase are present in literature. These algorithms are called “referenceless” because they don’t require any subtraction of baseline images for calculating temperature increment. Conventional referenceless methods estimate baseline image by fitting the background phase outside the heated region through a polynomial approach. In this work a background pha…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMaterials sciencebusiness.industryRadial basis function interpolationThermometry ultrasound thermal ablation referenceless methods RBF interpolation MRgFUSComputer visionArtificial intelligencebusinessComputational physics2014 World Symposium on Computer Applications & Research (WSCAR)
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Simulation and anticipation as tools for coordinating with the future

2013

A key goal in designing an artificial intelligence capable of performing complex tasks is a mechanism that allows it to efficiently choose appropriate and relevant actions in a variety of situations and contexts. Nowhere is this more obvious than in the case of building a general intelligence, where the contextual choice and application of actions must be done in the presence of large numbers of alternatives, both subtly and obviously distinct from each other. We present a framework for action selection based on the concurrent activity of multiple forward and inverse models. A key characteristic of the proposed system is the use of simulation to choose an action: the system continuously sim…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMechanism (biology)Computer sciencebusiness.industryAction selectionOutcome (game theory)AnticipationVariety (cybernetics)Domain (software engineering)Action SelectionAction (philosophy)Anticipation (artificial intelligence)Key (cryptography)Artificial intelligencebusinessMachine learning techniquesSimulation
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Design and Implementation of an Efficient Fingerprint Features Extractor

2014

Biometric recognition systems are rapidly evolving technologies and their use in embedded devices for accessing and managing data and resources is a very challenging issue. Usually, they are composed of three main modules: Acquisition, Features Extraction and Matching. In this paper the hardware design and implementation of an efficient fingerprint features extractor for embedded devices is described. The proposed architecture, designed for different acquisition sensors, is composed of four blocks: Image Pre-processor, Macro-Features Extractor, Micro- Features Extractor and Master Controller. The Image Pre- processor block increases the quality level of the input raw image and performs an a…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinutiaeBiometricsComputer sciencebusiness.industryFingerprint (computing)Feature extractionFingerprint recognitionComputer visionArtificial intelligenceFPGA Fingerprint Features Extraction Adaptive ProcessingField-programmable gate arraybusinessImage resolutionBlock (data storage)2014 17th Euromicro Conference on Digital System Design
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