839 resultados para Random utility


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L’impacchettamento risulta essere importante in molti settori industriali, come il settore minerario, farmaceutico e soprattutto il settore spaziale, in quanto permette di massimizzare il grado di riempimento del propellente solido di un razzo ottenendo prestazioni migliori e notevoli vantaggi economici. Il lavoro di tesi presentato nel seguente elaborato consiste nello studio dell’impacchettamento casuale, in particolare il caso Random Close Packing, di un propellente solido; per fare ciò è stato implementato un codice in ambiente C++ presso l’hangar della Scuola di Ingegneria ed Architettura con sede a Forlì. L’obiettivo principale era quello di trovare la granulometria delle particelle di perclorato di ammonio e delle particelle di alluminio tali da minimizzare gli spazi lasciati vuoti dalle particelle stesse.

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This thesis deals with three different physical models, where each model involves a random component which is linked to a cubic lattice. First, a model is studied, which is used in numerical calculations of Quantum Chromodynamics.In these calculations random gauge-fields are distributed on the bonds of the lattice. The formulation of the model is fitted into the mathematical framework of ergodic operator families. We prove, that for small coupling constants, the ergodicity of the underlying probability measure is indeed ensured and that the integrated density of states of the Wilson-Dirac operator exists. The physical situations treated in the next two chapters are more similar to one another. In both cases the principle idea is to study a fermion system in a cubic crystal with impurities, that are modeled by a random potential located at the lattice sites. In the second model we apply the Hartree-Fock approximation to such a system. For the case of reduced Hartree-Fock theory at positive temperatures and a fixed chemical potential we consider the limit of an infinite system. In that case we show the existence and uniqueness of minimizers of the Hartree-Fock functional. In the third model we formulate the fermion system algebraically via C*-algebras. The question imposed here is to calculate the heat production of the system under the influence of an outer electromagnetic field. We show that the heat production corresponds exactly to what is empirically predicted by Joule's law in the regime of linear response.

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This work has mainly focused on the poly (L-lactide) (PLLA) which is a material for multiple applications with performances comparable to those of petrochemical polymers (PP, PS, PET, etc. ...), readily recyclable and also compostable. However, PLLA has certain shortcomings that limit its applications. It is a brittle, hard polymer with a very low elongation at break, hydrophobic, exhibits low crystallization kinetics and takes a long time to degrade. The properties of PLLA may be modified by copolymerization (random, block, and graft) of L-lactide monomers with other co-monomers. In this thesis it has been studied the crystallization and morphology of random copolymers poly (L-lactide-ran-ε-caprolactone) with different compositions of the two monomers since the physical, mechanical, optical and chemical properties of a material depend on this behavior. Thermal analyses were performed by differential scanning calorimetry (DSC) and thermogravimetry (TGA) to observe behaviors due to the different compositions of the copolymers. The crystallization kinetics and morphology of poly (L-lactide-ran-ε-caprolactone) was investigated by polarized light optical microscopy (PLOM) and differential scanning calorimetry (DSC). Their thermal behavior was observed with crystallization from melt. It was observed that with increasing amounts of PCL in the copolymer, there is a decrease of the thermal degradation. Studies on the crystallization kinetics have shown that small quantities of PCL in the copolymer increase the overall crystallization kinetics and the crystal growth rate which decreases with higher quantities of PCL.

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L'obiettivo di questo lavoro di tesi è quello di implementare un codice di calcolo, attraverso l'algoritmo di Lubachevsky-Stillinger, in modo da poter prevedere la frazione volumetrica occupata dalle particelle solide che costituiscono il grain negli endoreattori a propellente solido. Particolare attenzione verrà rivolta al problema dell'impacchettamento sferico random (Random-Close Packing) che tale algoritmo cerca di modellare, e le ipotesi per cui tale modellazione può essere applicata al tipo di problema proposto. Inoltre saranno descritte le procedure effettuate per l'ottenimento dei risultati numerici delle simulazioni e la loro motivazione, oltre ai limiti del modello utilizzato e alle migliorie apportate per un'esecuzione più efficiente e veloce.

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In questo elaborato si affronta il progetto di un nucleo di calcolo per misure d'impedenza sulla pelle tramite l'utilizzo di segnali pseudo-random. La misura viene effettuata applicando il segnale casuale all'impedenza per ottenere la risposta impulsiva tramite un'operazione di convoluzione. Il nucleo di calcolo è stato implementato in VHDL.

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In questa tesi si è studiato l’insorgere di eventi critici in un semplice modello neurale del tipo Integrate and Fire, basato su processi dinamici stocastici markoviani definiti su una rete. Il segnale neurale elettrico è stato modellato da un flusso di particelle. Si è concentrata l’attenzione sulla fase transiente del sistema, cercando di identificare fenomeni simili alla sincronizzazione neurale, la quale può essere considerata un evento critico. Sono state studiate reti particolarmente semplici, trovando che il modello proposto ha la capacità di produrre effetti "a cascata" nell’attività neurale, dovuti a Self Organized Criticality (auto organizzazione del sistema in stati instabili); questi effetti non vengono invece osservati in Random Walks sulle stesse reti. Si è visto che un piccolo stimolo random è capace di generare nell’attività della rete delle fluttuazioni notevoli, in particolar modo se il sistema si trova in una fase al limite dell’equilibrio. I picchi di attività così rilevati sono stati interpretati come valanghe di segnale neurale, fenomeno riconducibile alla sincronizzazione.

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In most real-life environments, mechanical or electronic components are subjected to vibrations. Some of these components may have to pass qualification tests to verify that they can withstand the fatigue damage they will encounter during their operational life. In order to conduct a reliable test, the environmental excitations can be taken as a reference to synthesize the test profile: this procedure is referred to as “test tailoring”. Due to cost and feasibility reasons, accelerated qualification tests are usually performed. In this case, the duration of the original excitation which acts on the component for its entire life-cycle, typically hundreds or thousands of hours, is reduced. In particular, the “Mission Synthesis” procedure lets to quantify the induced damage of the environmental vibration through two functions: the Fatigue Damage Spectrum (FDS) quantifies the fatigue damage, while the Maximum Response Spectrum (MRS) quantifies the maximum stress. Then, a new random Power Spectral Density (PSD) can be synthesized, with same amount of induced damage, but a specified duration in order to conduct accelerated tests. In this work, the Mission Synthesis procedure is applied in the case of so-called Sine-on-Random vibrations, i.e. excitations composed of random vibrations superimposed on deterministic contributions, in the form of sine tones typically due to some rotating parts of the system (e.g. helicopters, engine-mounted components, …). In fact, a proper test tailoring should not only preserve the accumulated fatigue damage, but also the “nature” of the excitation (in this case the sinusoidal components superimposed on the random process) in order to obtain reliable results. The classic time-domain approach is taken as a reference for the comparison of different methods for the FDS calculation in presence of Sine-on-Random vibrations. Then, a methodology to compute a Sine-on-Random specification based on a mission FDS is presented.

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This thesis investigates one-dimensional random walks in random environment whose transition probabilities might have an infinite variance. The ergodicity of the dynamical system ''from the point of view of the particle'' is proved under the assumptions of transitivity and existence of an absolutely continuous steady state on the space of the environments. We show that, if the average of the local drift over the environments is summable and null, then the RWRE is recurrent. We provide an example satisfying all the hypotheses.

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In this thesis we dealt with the problem of describing a transportation network in which the objects in movement were subject to both finite transportation capacity and finite accomodation capacity. The movements across such a system are realistically of a simultaneous nature which poses some challenges when formulating a mathematical description. We tried to derive such a general modellization from one posed on a simplified problem based on asyncronicity in particle transitions. We did so considering one-step processes based on the assumption that the system could be describable through discrete time Markov processes with finite state space. After describing the pre-established dynamics in terms of master equations we determined stationary states for the considered processes. Numerical simulations then led to the conclusion that a general system naturally evolves toward a congestion state when its particle transition simultaneously and we consider one single constraint in the form of network node capacity. Moreover the congested nodes of a system tend to be located in adjacent spots in the network, thus forming local clusters of congested nodes.

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We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

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It is one of the most important tasks of the forensic pathologist to explain the forensically relevant medical findings to medical non-professionals. However, it is often difficult to comment on the nature and potential consequences of organ injuries in a comprehensive way to individuals with limited knowledge of anatomy and physiology. This rare case of survived pancreatic transaction after kicks to the abdomen illustrates how the application of dedicated software programs for three-dimensional reconstruction can overcome these difficulties, allowing for clear and concise visualization of complex findings.

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Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

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We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.