997 resultados para catene di Markov catene di Markov reversibili simulazione metodo Montecarlo


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Nell’attuale contesto competitivo, sempre più alla ricerca di un incontro tra esigenze di natura economica e logiche di Sostenibilità Ambientale e di Economia Circolare (E.C.), questo elaborato si pone l’obiettivo di presentare un modello matematico, formulato per la simulazione e la conseguente ottimizzazione di una rete logistica gestita con logiche di Simbiosi Industriale (S.I.). Lo scopo di tale modello è fungere da supporto all’adozione di pratiche di S.I. in un determinato contesto territoriale, attraverso l’individuazione delle sinergie ottime, tra quelle considerate possibili, in grado di ridurre la produzione di rifiuti, a favore del riutilizzo di sottoprodotti e materie prime seconde, minimizzando il costo totale del sistema. Preliminarmente alla presentazione del modello, sarà descritto il contesto in cui la S.I. si colloca e i suoi collegamenti con i concetti di Ecologia Industriale (E.I.) ed E.C., verranno distinti i vari modelli esistenti di S.I. ed i casi di successo presenti nel contesto italiano ed europeo, e sarà illustrato l’attuale inquadramento normativo. In seguito, verranno descritti nel dettaglio il modello matematico e un caso studio, dimensionato allo scopo di validare il modello stesso. Fase particolarmente critica del lavoro è risultata essere quella relativa alla raccolta dati da inserire nel caso studio, in quanto informazioni sensibili e di conseguenza non facilmente reperibili. I risultati ottenuti dimostrano come possa risultare conveniente, dal punto di vista economico, l’adozione di pratiche di S.I. negli scambi tra realtà industriali, e in che modo tale convenienza muti al variare delle condizioni economiche al contorno.

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Il presente studio ha l'obiettivo di individuare una soluzione per l'elevata incidentalità di un'intersezione situata nel comune di Langhirano (PR). L'utilizzo di una rotatoria si rende necessario per poter moderare le velocità di approccio all'intersezione e avere una situazione molto più accettabile dal punto di vista della collettività sia da un punto di vista del costo sociale affrontato dalla collettività stessa e dall'Amministrazione Locale, sia dal punto di vista dell'inquinamento ambientale. Lo studio si compone di tutte le fasi progettuali necessarie per il progetto di un'intersezione a rotatoria e, avendo a disposizione i dati di traffico ricavati da rilievi, si è svolta una simulazione di traffico per simulare gli effetti dell'intervento e confrontare la situazione attuale con quella di progetto. Sono inoltre allegati tutti gli elaborati progettuali necessari per poter configurare il presente studio come un progetto preliminare.

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L’elaborato di tesi discute del progetto di integrazione tra ROS 2, framework open-source per lo sviluppo di applicazioni robotiche, e VxWorks, sistema operativo in tempo reale (RTOS), attraverso l’utilizzo di container OCI compliant su VxWorks. L’integrazione è stata svolta all’interno dello stack software di IMA (Industria Macchine Automatiche). Il progetto ha dunque integrato ROS 2 Humble e VxWorks 7 permettendo l’utilizzo di costrutti software di ROS 2 su dei container in esecuzione a livello User su VxWorks. Successivamente è stata creata una applicazione di pick and place con un robot antropomorfo (Universal Robots Ur5e) avvalendosi di ROS 2 Control, framework per l’introduzione e gestione di hardware e controllori, e MoveIt 2, framework per incorporare algoritmi di motion-planning, cinematica, controllo e navigazione. Una volta progettata l’applicazione, il sistema è stato integrato all’interno dell’architettura di controllo di IMA. L’architettura a container VxWorks di IMA è stata estesa per il caso ROS 2, la comunicazione tra campo e applicazione ROS 2 è passata tramite il master EtherCAT e il modulo WebServer presenti nell’architettura IMA. Una volta eseguito il container ROS 2 posizione e velocità dei servo motori sono stati inviati tramite al WebServer di IMA sfruttando la comunicazione VLAN interna. Una volta ricevuto il messaggio, il WebServer si è occupato di trasferirlo al master EtherCAT che in aggiunta si è occupato anche di ottenere le informazioni sullo stato attuale del robot. L’intero progetto è stato sviluppato in prima battuta in ambiente di simulazione per validarne l’architettura. Successivamente si è passati all’installazione in ambiente embedded grazie all’ausilio di IPC sui quali è stato testato l’effettivo funzionamento dell’integrazione all’interno dell’architettura IMA.

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Gli UAV, o meglio conosciuti come ‘droni’, sono aeromobili a pilotaggio remoto il cui utilizzo si estende dal settore militare a quello civile. Quest’ultimi, possono essere attrezzati con numerosi dispositivi accessori, come ad esempio disturbatori di frequenze. La simbiosi UAV-jammer attacca le comunicazioni wireless tramite interferenze a radiofrequenza, per degradare o interrompere il servizio offerto dalle reti. Questo elaborato, si concentra sull’analisi di algoritmi di localizzazione passiva, per stimare la posizione dell’UAV e interrompere l’interferenza. Inizialmente, viene descritto il segnale emesso dall’UAV, che utilizza lo standard di comunicazione 802.11a. A seguire, dato che la localizzazione passiva si basa sulle misure TDOA rilevate da una stazione di monitoraggio a terra, vengono presentati tre algoritmi di stima TDOA, tra i quali fast TDOA, adaptive threshold-based first tap detection e un algoritmo sviluppato per i nuovi sistemi GNSS. Successivamente, vengono esaminati tre algoritmi di localizzazione passiva, che sfruttano il principio dei minimi quadrati (LS), ovvero il CTLS, LCLS e CWLS. Infine, le prestazioni degli algoritmi di localizzazione vengono valutate in un ambiente di simulazione realistico, con canale AWGN o con canale ITU Extended pedestrian A.

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In the title compound, C17H14N2O6, the conformation about the C=C double bond [1.345 (2) Å] is E, with the ketone moiety almost coplanar [C-C-C-C torsion angle = 9.5 (2)°] along with the phenyl ring [C-C-C-C = 5.9 (2)°]. The aromatic rings are almost perpendicular to each other [dihedral angle = 86.66 (7)°]. The 4-nitro moiety is approximately coplanar with the benzene ring to which it is attached [O-N-C-C = 4.2 (2)°], whereas the one in the ortho position is twisted [O-N-C-C = 138.28 (13)°]. The mol-ecules associate via C-H⋯O inter-actions, involving both O atoms from the 2-nitro group, to form a helical supra-molecular chain along [010]. Nitro-nitro N⋯O inter-actions [2.8461 (19) Å] connect the chains into layers that stack along [001].

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Both high-fat diet and exposure to endocrine-disrupting chemicals have been implicated in susceptibility to pathological prostate lesions, but the consequences of combining the two have not yet been examined. We evaluated the effects of gestational and postnatal exposure to a high-fat diet (20% fat) and low doses of di-n-butyl phthalate (DBP; 5mg/kg/day), individually or in combination, on the tissue response and incidence of pathological lesions in the ventral prostate of adult gerbils. Continuous intake of a high-fat diet caused dyslipidemia, hypertrophy, and promoted the development of inflammatory, premalignant and malignant prostate lesions, even in the absence of obesity. Life-time DBP exposure was obesogenic and dyslipidemic and increased the incidence of premalignant prostate lesions. Combined exposure to DBP and a high-fat diet also caused prostate hypertrophy, but the effects were less severe than those of individual treatments; combined exposure neither induced an inflammatory response nor altered serum lipid content.

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The main goal of this paper is to establish some equivalence results on stability, recurrence, and ergodicity between a piecewise deterministic Markov process ( PDMP) {X( t)} and an embedded discrete-time Markov chain {Theta(n)} generated by a Markov kernel G that can be explicitly characterized in terms of the three local characteristics of the PDMP, leading to tractable criterion results. First we establish some important results characterizing {Theta(n)} as a sampling of the PDMP {X( t)} and deriving a connection between the probability of the first return time to a set for the discrete-time Markov chains generated by G and the resolvent kernel R of the PDMP. From these results we obtain equivalence results regarding irreducibility, existence of sigma-finite invariant measures, and ( positive) recurrence and ( positive) Harris recurrence between {X( t)} and {Theta(n)}, generalizing the results of [ F. Dufour and O. L. V. Costa, SIAM J. Control Optim., 37 ( 1999), pp. 1483-1502] in several directions. Sufficient conditions in terms of a modified Foster-Lyapunov criterion are also presented to ensure positive Harris recurrence and ergodicity of the PDMP. We illustrate the use of these conditions by showing the ergodicity of a capacity expansion model.

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This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs) taking values in a general Borel space and with compact action space depending on the state variable. The control variable acts on the jump rate and transition measure of the PDMP, and the running and boundary costs are assumed to be positive but not necessarily bounded. Our first main result is to obtain an optimality equation for the long run average cost in terms of a discrete-time optimality equation related to the embedded Markov chain given by the postjump location of the PDMP. Our second main result guarantees the existence of a feedback measurable selector for the discrete-time optimality equation by establishing a connection between this equation and an integro-differential equation. Our final main result is to obtain some sufficient conditions for the existence of a solution for a discrete-time optimality inequality and an ordinary optimal feedback control for the long run average cost using the so-called vanishing discount approach. Two examples are presented illustrating the possible applications of the results developed in the paper.

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We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

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We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at the BNL Relativistic Heavy Ion Collider (RHIC). Pairs of back-to-back high-transverse-momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two-and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudorapidity Delta eta or relative azimuthal angle Delta phi from d + Au to central Au + Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.

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Yields, correlation shapes, and mean transverse momenta p(T) of charged particles associated with intermediate-to high-p(T) trigger particles (2.5 < p(T) < 10 GeV/c) in d + Au and Au + Au collisions at root s(NN) = 200 GeV are presented. For associated particles at higher p(T) greater than or similar to 2.5 GeV/c, narrow correlation peaks are seen in d + Au and Au + Au, indicating that the main production mechanism is jet fragmentation. At lower associated particle pT < 2 GeV/c, a large enhancement of the near- (Delta phi similar to 0) and away-side (Delta phi similar to pi) associated yields is found, together with a strong broadening of the away-side azimuthal distributions in Au + Au collisions compared to d + Au measurements, suggesting that other particle production mechanisms play a role. This is further supported by the observed significant softening of the away-side associated particle yield distribution at Delta phi similar to pi in central Au + Au collisions.

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The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

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This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

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We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

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This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.