Search results for " Informatica"

showing 10 items of 978 documents

Semi-automatic registration of retinal images based on line matching approach

2013

Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model i…

Semi-automatic registration of retinal images based on line matching approachGround truthSettore INF/01 - InformaticaMatching (graph theory)Computer sciencebusiness.industryFeature extractionImage registrationRetinalSimilarity measureTree (graph theory)chemistry.chemical_compoundchemistrySegmentationComputer visionArtificial intelligencebusinessProceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems
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A Layered Architecture for Sentiment Classification of Products Reviews in Italian Language

2017

The paper illustrates a system for the automatic classification of the sentiment orientation expressed into reviews written in Italian language. A proper stratification of linguistic resources is adopted in order to solve the lacking of an opinion lexicon specifically suited for the Italian language. Experiments show that the proposed system can be applied to a wide range of domains.

Sentiment analysis Text Classification of ReviewsSettore INF/01 - InformaticaComputer scienceOrientation (computer vision)business.industryMultitier architectureItalian languageSentiment analysis02 engineering and technologyLexiconcomputer.software_genreRange (mathematics)020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNatural language processing
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Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues

2021

DNA sequences are the basic data type that is processed to perform a generic study of biological data analysis. One key component of the biological analysis is represented by sequence classification, a methodology that is widely used to analyze sequential data of different nature. However, its application to DNA sequences requires a proper representation of such sequences, which is still an open research problem. Machine Learning (ML) methodologies have given a fundamental contribution to the solution of the problem. Among them, recently, also Deep Neural Network (DNN) models have shown strongly encouraging results. In this chapter, we deal with specific classification problems related to t…

SequenceBiological dataSequence classificationSettore INF/01 - InformaticaArtificial neural networkProcess (engineering)Computer sciencebusiness.industryDeep learningBacteria classificationSequence classificationBacteria classificationNucleosome identificationDeep neural networkMachine learningcomputer.software_genreData typeNucleosome identificationComponent (UML)Artificial intelligenceMetagenomicsRepresentation (mathematics)businesscomputer
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Lightweight algorithms for constructing and inverting the BWT of string collections

2013

Recent progress in the field of \{DNA\} sequencing motivates us to consider the problem of computing the Burrows‚ÄìWheeler transform (BWT) of a collection of strings. A human genome sequencing experiment might yield a billion or more sequences, each 100 characters in length. Such a dataset can now be generated in just a few days on a single sequencing machine. Many algorithms and data structures for compression and indexing of text have the \{BWT\} at their heart, and it would be of great interest to explore their applications to sequence collections such as these. However, computing the \{BWT\} for 100 billion characters or more of data remains a computational challenge. In this work we ad…

SequenceTheoretical computer scienceSettore INF/01 - InformaticaGeneral Computer ScienceComputer scienceString (computer science)Search engine indexingProcess (computing)Data_CODINGANDINFORMATIONTHEORYData structureField (computer science)Theoretical Computer ScienceBWTConstant (computer programming)Text indexeBWT; Text indexes; Next-generation sequencingText indexesNext-generation sequencingAlphabetAlgorithmAuxiliary memoryTheoretical Computer Science
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Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: Comparison among different strategie…

2008

We compare the different existing strategies of mutual nonlinear prediction regarding their ability to assess the coupling strength and directionality of the interactions in bivariate time series. Under the common framework of $k$-nearest neighbor local linear prediction, we test three approaches based on cross prediction, mixed prediction, and predictability improvement. The measures of interdependence provided by these approaches are first evaluated on short realizations of bivariate time series generated by coupled Henon models, investigating also the effects of noise. The usefulness of the three mutual nonlinear prediction schemes is then assessed in a common physiological application d…

Series (mathematics)Computer scienceBivariate analysisCondensed Matter PhysicSynchronizationk-nearest neighbors algorithmNoisePhysics and Astronomy (all)StatisticsSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPredictabilityTime seriesAlgorithmMathematical PhysicsInterpretabilityStatistical and Nonlinear Physic
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Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction

2008

The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…

Series (mathematics)Degree (graph theory)Computer Science Applications1707 Computer Vision and Pattern Recognitionk-nearest neighbors algorithmTerm (time)Nonlinear systemPosition (vector)Control theorySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaComputer Science Applications1707 Computer Vision and Pattern Recognition; Cardiology and Cardiovascular MedicineTime seriesPredictabilityCardiology and Cardiovascular MedicineAlgorithmMathematics
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Information dynamics in cardiorespiratory time series during mental stress testing

2014

In this study, we assessed the information dynamics of respiration and heart rate variability during mental stress testing by means of the cross-entropy, a measure of cardiorespiratory coupling, and the self-entropy of the tachogram conditioned to the knowledge of respiration. Although stress is related to a reduction in vagal activity, no difference in cardiorespiratory coupling was found when 5 minutes of rest and stress were compared. The conditional self-entropy, on the other hand, showed significantly higher values during stress, indicating a higher predictability of the tachogram. These results show that entropy analyses of cardiorespiratory data reveal new information that could not …

Series (mathematics)Mental stressSpeech recognitionSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaBiomedical EngineeringCardiorespiratory fitnessInformation dynamicsMathematicsCognitive psychology
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Privacy-preserving data allocation in decentralized online social networks

2016

International audience; Distributed Online Social Networks (DOSNs) have been recently proposed as an alternative to centralized solutions to allow a major control of the users over their own data. Since there is no centralized service provider which decides the term of service, the DOSNs infrastructure exploits users’ devices to take on the online social network services. In this paper, we propose a data allocation strategy for DOSNs which exploits the privacy policies of the users to increase the availability of the users’ contents without diverging from their privacy preferences. A set of replicas of the profile’s content of a user U are stored on the devices of other users who are entitl…

Service (systems architecture)ExploitComputer sciencePrivacy policyControl (management)02 engineering and technologyPeer-to-peercomputer.software_genreComputer securityTheoretical Computer ScienceSet (abstract data type)[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI]0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Privacy policySocial networkSettore INF/01 - Informaticabusiness.industryComputer Science (all)020206 networking & telecommunicationsService providerDecentralized online social network Data availability Privacy policy Peer-to-peerData availabilityPeer-to-peerDecentralized online social network020201 artificial intelligence & image processingbusinesscomputerComputer network
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Some Remarks on Automata Minimality

2011

It is well known that the minimization problem of deterministic finite automata (DFAs) is related to the indistinguishability notion of states (cf. [HMU00]). Indeed, a well known technique to minimize a DFA, essentially, consists in finding pairs of states that are equivalent (or indistinguishable), namely pairs of states (p,q) such that it is impossible to assert the difference between p and q only by starting in each of the two states and asking whether or not a given input string leads to a final state. Since, in the testing states equivalence, the notion of initial state is irrelevant, some of the main techniques for the minimization of automata, such as Moore’s algorithm [Moo56] and Ho…

Set (abstract data type)Discrete mathematicsDeterministic finite automatonSettore INF/01 - InformaticaRegular languageCayley graphString (computer science)state-pair graph uniformly minimal automataState (functional analysis)Equivalence (measure theory)Computer Science::Formal Languages and Automata TheoryAutomatonMathematics
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Dense Geometry of Music and Visual Arts: Vanishing Points, Continuous Tonnetz, and Theremin Performance

2018

The dualism between continuous and discrete is relevant in music theory as well as in performance practice of musical instruments. Geometry has been used since longtime to represent relationships between notes and chords in tonal system. Moreover, in the field of mathematics itself, it has been shown that the continuity of real numbers can arise from geometrical observations and reasoning. Here, we consider a geometrical approach to generalize representations used in music theory introducing continuous pitch. Such a theoretical framework can be applied to instrument playing where continuous pitch can be naturally performed. Geometry and visual representations of concepts of music theory and…

Settore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciSettore INF/01 - Informaticamedia_common.quotation_subject05 social sciencesSettore ING-INF/02 - Campi Elettromagnetici06 humanities and the artsArtSettore MAT/04 - Matematiche ComplementariContinuum and discrete music theory050105 experimental psychology060404 musicComputer graphics (images)0501 psychology and cognitive sciencesVanishing pointTonnetz0604 artsmedia_common
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