Search results for "Markov"
showing 10 items of 628 documents
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…
Weak convergence to the coalescent in neutral population models
1999
For a large class of neutral population models the asymptotics of the ancestral structure of a sample of n individuals (or genes) is studied, if the total population size becomes large. Under certain conditions and under a well-known time-scaling, which can be expressed in terms of the coalescence probabilities, weak convergence in D E ([0,∞)) to the coalescent holds. Further the convergence behaviour of the jump chain of the ancestral process is studied. The results are used to approximate probabilities which are of certain interest in applications, for example hitting probabilities.
Explainable Reinforcement Learning with the Tsetlin Machine
2021
The Tsetlin Machine is a recent supervised machine learning algorithm that has obtained competitive results in several benchmarks, both in terms of accuracy and resource usage. It has been used for convolution, classification, and regression, producing interpretable rules. In this paper, we introduce the first framework for reinforcement learning based on the Tsetlin Machine. We combined the value iteration algorithm with the regression Tsetlin Machine, as the value function approximator, to investigate the feasibility of training the Tsetlin Machine through bootstrapping. Moreover, we document robustness and accuracy of learning on several instances of the grid-world problem.
Monte Carlo simulation in phylogenies: an application to test the constancy of evolutionary rates.
1994
Monte Carlo simulation has commonly been used in phylogenetic studies to test different tree-reconstruction methods, and consequently, its application for testing evolutionary models can be considered as a natural extension of this usage. Repetitive simulation of a given evolutionary process, under the restrictions imposed by the model to be tested, along a determinate tree topology allow the estimate of probability distributions for the desired parameters. Next, the phylogenetic tree can be reconstructed again without the constraints of the model, and the parameter of interest, derived from this tree, can be compared to the corresponding probability distribution derived from the restricted…
Fault detection for discrete-time Markov jump linear systems with partially known transition probabilities
2010
In this article, the fault detection (FD) problem for a class of discrete-time Markov jump linear system (MJLS) with partially known transition probabilities is investigated. The proposed systems are more general, which relax the traditional assumption in Markov jump systems that all the transition probabilities must be completely known. A residual generator is constructed and the corresponding FD is formulated as an H ∞ filtering problem by which the error between residual and fault are minimised in the H ∞ sense. The linear matrix inequality-based sufficient conditions for the existence of FD filter are derived. A numerical example on a multiplier–accelerator model economic system is give…
Estimated prevalence of undiagnosed HCV infected individuals in Italy: A mathematical model by route of transmission and fibrosis progression
2021
Abstract Background The universal treatment of diagnosed patients with chronic HCV infection has been widely conducted in Italy since 2017. However, the pool of individuals diagnosed but yet to be treated in Italy has been estimated to end around 2025, leaving a significant proportion of infected individuals undiagnosed/without care. Estimates of this population are currently unknown. Methods A probabilistic modelling approach was applied to estimate annual historical HCV incident cases by their age-group (0–100 years) distribution from available literature and Italian National database (1952 to October 2019). Viraemic infection rates were modelled on the main infection routes in Italy: peo…
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…
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…
A Novel Approach for Faulty Sensor Detection and Data Correction in Wireless Sensor Network
2013
he main Wireless Sensor Networks purpose is represented by areas of interest monitoring. Even if the Wireless sensor network is properly initialized, errors can occur during its monitoring tasks. The present work describes an approach for detecting faulty sensors in Wireless Sensor Network and for correcting their corrupted data. The approach is based on the assumption that exist a spatio-temporal cross- correlations among sensors. Two sequential mathematical tools are used. The first stage is a probabilistic tools, namely Markov Random Field, for a two-fold sensor classification (working or damaged). The last stage is represented by the Locally Weighted Regression model, a learning techniq…
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…