Search results for " Marko"

showing 10 items of 201 documents

Comparison of Attention Behaviour Across User Sets through Automatic Identification of Common Areas of Interest

2020

Eye tracking is used to analyze and compare user behaviour within numerous domains, but long duration eye tracking experiments across multiple users generate millions of eye gaze samples, making th ...

Identification (information)InformationSystems_MODELSANDPRINCIPLESbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEye trackingComputer visionArtificial intelligencebusinessHidden Markov modelProceedings of the Annual Hawaii International Conference on System Sciences
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First passage time distribution of stationary Markovian processes

2010

The aim of this paper is to investigate how the correlation properties of a stationary Markovian stochastic processes affect the First Passage Time distribution. First Passage Time issues are a classical topic in stochastic processes research. They also have relevant applications, for example, in many fields of finance such as the assessment of the default risk for firms' assets. By using some explicit examples, in this paper we will show that the tail of the First Passage Time distribution crucially depends on the correlation properties of the process and it is independent from its stationary distribution. When the process includes an infinite set of time-scales bounded from above, the FPT…

Infinite setStationary distributionStochastic processStochastic processes Stochastic analysis methods (Fokker-Planck Langevin etc.) Markov processesGeneral Physics and AstronomyMarkov processsymbols.namesakeDistribution (mathematics)Bounded functionsymbolsStatistical physicsExponential decayFirst-hitting-time modelMathematicsEPL (Europhysics Letters)
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An Intra-Subject Approach Based on the Application of HMM to Predict Concentration in Educational Contexts from Nonintrusive Physiological Signals in…

2021

Previous research has proven the strong influence of emotions on student engagement and motivation. Therefore, emotion recognition is becoming very relevant in educational scenarios, but there is no standard method for predicting students’ affects. However, physiological signals have been widely used in educational contexts. Some physiological signals have shown a high accuracy in detecting emotions because they reflect spontaneous affect-related information, which is fresh and does not require additional control or interpretation. Most proposed works use measuring equipment for which applicability in real-world scenarios is limited because of its high cost and intrusiveness. To tackle this…

IntrusivenessComputer scienceEmotionsControl (management)Student engagementContext (language use)02 engineering and technologyuser-centred systemsLearner modellinglcsh:Chemical technologyNonintrusiveMachine learningcomputer.software_genre01 natural sciencesBiochemistryArticleAnalytical ChemistryTask (project management)Heart RateUser-centred systems0202 electrical engineering electronic engineering information engineeringHumanslcsh:TP1-1185Electrical and Electronic EngineeringAffective computingHidden Markov modelaffective computingInstrumentationInformáticabusiness.industry010401 analytical chemistrynonintrusiveAffective computingComputer scienceAtomic and Molecular Physics and Opticsphysiological sensors0104 chemical scienceslearner modellingPhysiological sensors020201 artificial intelligence & image processingArtificial intelligenceState (computer science)Skin TemperaturebusinesscomputerSensors
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Economic Consequences of Investing in Anti-HCV Antiviral Treatment from the Italian NHS Perspective: A Real-World-Based Analysis of PITER Data

2019

OBJECTIVE:\ud We estimated the cost consequence of Italian National Health System (NHS) investment in direct-acting antiviral (DAA) therapy according to hepatitis C virus (HCV) treatment access policies in Italy.\ud \ud METHODS:\ud A multistate, 20-year time horizon Markov model of HCV liver disease progression was developed. Fibrosis stage, age and genotype distributions were derived from the Italian Platform for the Study of Viral Hepatitis Therapies (PITER) cohort. The treatment efficacy, disease progression probabilities and direct costs in each health state were obtained from the literature. The break-even point in time (BPT) was defined as the period of time required for the cumulativ…

Liver CirrhosisPediatricsTime FactorsSettore MED/09 - Medicina InternaNational Health ProgramsERADICATIONOUTBREAKantiviral treatment anti HCV economic consequencesHepacivirusLIVER FIBROSISSeverity of Illness IndexHealth Services AccessibilityCOST-EFFECTIVENESSIndirect costs0302 clinical medicineEpidemiologyvirus infection030212 general & internal medicinehealth care economics and organizationscost effectiveness030503 health policy & servicesHealth PolicyHealth services researchhealthHepatitis CHepatitis CMarkov Chainschronic hepatitis C virus infection fibrosis progression cost effectiveness liver fibrosisItalyPharmacology; Health Policy; Public Health Environmental and Occupational HealthCohortSettore SECS-P/03 - Scienza delle FinanzeDisease ProgressionPublic Health0305 other medical scienceViral hepatitisAnti-HCV antiviral treatmentCHRONIC HEPATITIS-Cmedicine.medical_specialtyGenotypeSettore MED/12 - GASTROENTEROLOGIAVIRUS-INFECTIONAntiviral AgentsNO03 medical and health sciencesCost SavingsAntiviral Agents; Cost Savings; Disease Progression; Genotype; Health Policy; Health Services Accessibility; Hepacivirus; Hepatitis C; Humans; Italy; Liver Cirrhosis; Markov Chains; National Health Programs; Severity of Illness Index; Time FactorsmedicineMANAGEMENTHumanschronic hepatitis CINDUCED DISEASESMETAANALYSISPharmacologyHealth economicsbusiness.industryPublic healthEnvironmental and Occupational HealthPublic Health Environmental and Occupational Healthmedicine.diseaseFIBROSIS PROGRESSIONbusiness
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Early Treatment in HCV: Is it a Cost-Utility Option from the Italian Perspective?

2016

In Italy, the Italian Pharmaceutical Agency (AIFA) criteria used F3–F4 fibrosis stages as the threshold to prioritise the treatment with interferon (IFN)-free regimens, while in genotype 1 chronic hepatitis C (G1 CHC) patients with fibrosis of liver stage 2, an approach with pegylated interferon (PEG-IFN)-based triple therapy with simeprevir was suggested. The key clinical question is whether, in an era of financial constraints, the application of a universal IFN-free strategy in naive G1 CHC patients is feasible within a short time horizon. The aim of this study is to perform an economic analysis to estimate the cost-utility of the early innovative therapy in Italy for managing hepatitis C…

Liver CirrhosisSimeprevirmedicine.medical_specialtyCost-Benefit AnalysisPopulationAntiviral Agents03 medical and health sciencesIndirect costs0302 clinical medicineAntiviral Agents; Cost-Benefit Analysis; Disease Progression; Hepatitis C Chronic; Humans; Interferons; Italy; Liver Cirrhosis; Markov Chains; Monte Carlo Method; Quality-Adjusted Life Years; Ribavirin; Simeprevir; Treatment Outcome; Pharmacology (medical)SimeprevirRibavirinmedicineHumansPharmacology (medical)030212 general & internal medicineChronicIntensive care medicineeducationReimbursementeducation.field_of_studyCost–benefit analysisbusiness.industryHealth services researchGeneral MedicineHepatitis CHepatitis C Chronicmedicine.diseaseHepatitis CMarkov ChainsQuality-adjusted life yearTreatment OutcomeItalyDisease Progression030211 gastroenterology & hepatologyInterferonsQuality-Adjusted Life YearsbusinessMonte Carlo MethodClinical Drug Investigation
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Stationary and Initial-Terminal Value Problem for Collective Decision Making via Mean-Field Games

2017

Given a large number of homogeneous players that are distributed across three possible states, we consider the problem in which these players have to control their transition rates, following some optimality criteria. The optimal transition rates are based on the players' knowledge of their current state and of the distribution of all the other players, thus introducing mean-field terms in the running and the terminal cost. The first contribution is a mean-field model that takes into account the macroscopic and the microscopic dynamics. The second contribution is the study of the mean-field equilibrium resulting from solving the initial-terminal value problem, involving the Kolmogorov equat…

Lyapunov function0209 industrial biotechnologyMathematical optimization010102 general mathematicsMarkov processContext (language use)02 engineering and technology01 natural sciencesTerminal valueNonlinear systemsymbols.namesake020901 industrial engineering & automationStability theoryKolmogorov equationssymbolsGames Mathematical model Markov processes Sociology Statistics Microscopy RobustnessApplied mathematicsLimit (mathematics)0101 mathematicsSettore MAT/09 - Ricerca OperativaMathematics
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Finite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps

2014

This paper is concerned with stochastic finite-time boundedness analysis for a class of uncertain discrete-time neural networks with Markovian jump parameters and time-delays. The concepts of stochastic finite-time stability and stochastic finite-time boundedness are first given for neural networks. Then, applying the Lyapunov approach and the linear matrix inequality technique, sufficient criteria on stochastic finite-time boundedness are provided for the class of nominal or uncertain discrete-time neural networks with Markovian jump parameters and time-delays. It is shown that the derived conditions are characterized in terms of the solution to these linear matrix inequalities. Finally, n…

Lyapunov functionDiscrete-time systems; Linear matrix inequalities; Markovian jump systems; Neural networks; Stochastic finite-time boundedness; Artificial Intelligence; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive NeuroscienceArtificial neural networkMarkov chainStochastic processCognitive NeuroscienceMarkovian jump systemsLinear matrix inequalitiesLinear matrix inequalityComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science Applicationssymbols.namesakeDiscrete time and continuous timeArtificial IntelligenceDiscrete-time systemssymbolsCalculusApplied mathematicsStochastic neural networkJump processNeural networksStochastic finite-time boundednessMathematics
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An Automatic Sleep Scoring Toolbox : Multi-modality of Polysomnography Signals’ Processing

2019

Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. To speed up the process of sleep scoring without compromising accuracy, this paper develops an automatic sleep scoring toolbox with the capability of multi-signal processing. It allows the user to choose signal types and the number of target classes. Then, an automatic process containing signal pre-processing, feature extraction, classifier training (or prediction) and result correction will be performed. Finally, the application interface displays predicted sleep structure, related sleep parameters and the sleep quality index for reference. To improve the identification accuracy of minority stages, a layer-w…

MATLABSpeedupComputer scienceFeature extraction02 engineering and technologyPolysomnographyMachine learningcomputer.software_genreuni (lepotila)polysomnography0202 electrical engineering electronic engineering information engineeringmedicineHidden Markov modelSignal processingSleep Stagesmedicine.diagnostic_testbusiness.industrysignaalianalyysi020206 networking & telecommunicationsautomatic sleep scoringToolboxmulti-modality analysis020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerClassifier (UML)MATLAB toolbox
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Variable length Markov chains and dynamical sources

2010

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical sources is studied. We establish a probabilistic frame for context trees and VLMC and we prove that any VLMC is a dynamical source for which we explicitly build the mapping. On two examples, the ``comb'' and the ``bamboo blossom'', we find a necessary and sufficient condition for the existence and the unicity of a stationary probability measure for the VLMC. These two examples are detailed in order to provide the associated Dirichlet series as well as the gener…

MSC 60J05 MSC 37E05[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Probability (math.PR)[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS][ MATH.MATH-DS ] Mathematics [math]/Dynamical Systems [math.DS]Probabilistic dynamical sources[MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS]Dynamical Systems (math.DS)Variable length Markov chainsOccurrences of words[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]60J05 37E05FOS: MathematicsMathematics - Dynamical SystemsDynamical systems of the intervalDirichlet series[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - Probability
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A case study on feature sensitivity for audio event classification using support vector machines

2016

Automatic recognition of multiple acoustic events is an interesting problem in machine listening that generalizes the classical speech/non-speech or speech/music classification problem. Typical audio streams contain a diversity of sound events that carry important and useful information on the acoustic environment and context. Classification is usually performed by means of hidden Markov models (HMMs) or support vector machines (SVMs) considering traditional sets of features based on Mel-frequency cepstral coefficients (MFCCs) and their temporal derivatives, as well as the energy from auditory-inspired filterbanks. However, while these features are routinely used by many systems, it is not …

Machine listeningComputer sciencebusiness.industryEvent (computing)Speech recognitionFeature extractionContext (language use)Pattern recognition02 engineering and technologySupport vector machine030507 speech-language pathology & audiology03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION0202 electrical engineering electronic engineering information engineeringFeature (machine learning)020201 artificial intelligence & image processingArtificial intelligenceMel-frequency cepstrum0305 other medical sciencebusinessHidden Markov model2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)
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