Search results for "HIDDEN"
showing 10 items of 210 documents
On Hagelbarger’s and Shannon’s matching pennies playing machines
2020
Abstract In the 1950s, Hagelbarger’s Sequence Extrapolating Robot (SEER) and Shannon’s Mind-Reading Machine (MRM) were the state-of-the-art research results in playing the well-known “matching pennies” game. In our research we perform a software implementation for both machines in order to test the common statement that MRM, even simpler, beats SEER. Also, we propose a simple contextual predictor (SCP) and use it to compete with SEER and MRM. As expected, experimental results proves the claimed MRM superiority over SEER and even the SCP’s superiority over both SEER and MRM. At the end, we draw some conclusions and propose further research ideas, like the use of mixing models methods and the…
Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks
2015
Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epide…
Bayesian Markov switching models for the early detection of influenza epidemics
2008
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…
‘Sociability before individuality’: lesson structure in lower secondary classrooms
2018
This paper contributes to the research field of classroom research by offering an empirical analysis of classroom instruction on the level of lesson structure. The research questions are: What are ...
Not all bull and bear markets are alike: insights from a five-state hidden semi-Markov model
2022
This paper employs the hidden semi-Markov model and a novel model selection procedure to detect different states in the US stock market. The empirical results suggest that the market is switching between five states that can be classified into three bull states and two bear states. The three bull states are categorized as a low volatility bull market, a high volatility bull market, and a stock market bubble. One of the bear states represents a regular bear market, while the other one corresponds to either a stock market crash or a market correction. The paper demonstrates that the five-state model is consistent with a number of stylized facts and provides many valuable insights into the dyn…
A Hidden Markov Model for Automatic Generation of ER Diagrams from OWL Ontology
2014
Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented using ERD notation. In this paper we propose an innovative technique for estimating the most likely composition of ERD constructs that correspond to a given sequence of OWL axioms. We model such a process using a Hidden Markov Model (HMM) where the OWL inputs are the observable states, while E…
THE MULTIPLE COUNTING OF TOURISTS IN SICILY AND THE ANALYSIS OF INTRA-REGIONAL TOURIST FLOWS
2008
Tourist arrivals are often wrongly interpreted as the number of tourists. The non-agreement between arrivals and tourists (Parroco and Vaccina, 2006) produces a large overestimation of the number of tourists really present at the destinations (tourists replication), so determining heavy consequences on economic and territorial planning. In order to get a first estimate of replications and to analyse the typical tourist tours throughout Sicily, in summer 2005 a census research was made on 8.883 tourists intercepted at 13 hotels in Cefalù, a well-known bathing resort in the Northern coast of Sicily (Italy).
The experimental facility for the Search for Hidden Particles at the CERN SPS
2019
The Search for Hidden Particles (SHiP) Collaboration has shown that the CERN SPS accelerator with its 400 $\mathrm{\small GeV/c}$ proton beam offers a unique opportunity to explore the Hidden Sector. The proposed experiment is an intensity frontier experiment which is capable of searching for hidden particles through both visible decays and through scattering signatures from recoil of electrons or nuclei. The high-intensity experimental facility developed by the SHiP collaboration is based on a number of key features and developments which provide the possibility of probing a large part of the parameter space for a wide range of models with light long-lived superweakly interacting particles…
Una storia italiana: Giorgio e Isabella
2018
Si tratta, qui, della storia di due italiani dalla “pelle scura” raccontata, per Giorgio Marincola, da Carlo Costa e Lorenzo Teodonio in Razza partigiana e, per la sorella Isabella, da Wu Ming 2 e Antar Mohamed in Timira. Romanzo meticcio. Le loro vicende, così come molti altri aspetti della nostra storia coloniale, neocoloniale e postcoloniale, sono riemerse dal buio nel quale erano state occultate solo nell’ultimo quindicennio, grazie alla riapertura degli archivi che ha permesso di ridiscutere molti degli aspetti che nelle pagine di Storia, così come in quelle letterarie, erano stati raccontati in altro modo. I due testi, che hanno inevitabilmente finito per incontrarsi e che potremmo in…
Learning the structure of HMM's through grammatical inference techniques
2002
A technique is described in which all the components of a hidden Markov model are learnt from training speech data. The structure or topology of the model (i.e. the number of states and the actual transitions) is obtained by means of an error-correcting grammatical inference algorithm (ECGI). This structure is then reduced by using an appropriate state pruning criterion. The statistical parameters that are associated with the obtained topology are estimated from the same training data by means of the standard Baum-Welch algorithm. Experimental results showing the applicability of this technique to speech recognition are presented. >