7 resultados para chains with unbounded variable length memory

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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The rheological properties of block co-polymers in water solution at different pH have been investigated. The block copolymers are based on different architectures containing poly(ethylene glycol), poly(propylene glycol) and different blocks of polymer that change their hydrophobic/hydrophilic behavior as a function of pH. The polymer chains of the starting material were extended at their functional ends with the pH-sensitive units using ATRP; this mechanism of controlled radical polymerization was chosen because of the need to minimize polydispersity and avoid transfer reactions possibly leading to homopolymeric inpurities. The starting material were modified in order to use them as macroinitiator for ATRP. The kinetic of each ATRP reaction has been investigated, in order to be able to synthesize polymers with different degree of polymerization, stopping the reaction when the desired polymers chain length has been reached. We will use polymer chains with different basicity and degree of polymerization to link any possible effect of their presence to the conditions under which they become hydrophobic. It has been shown that the rate of polymerization changes changing the type of macroinitiator and the type of monomer synthesized. The slowest rate of polymerization is the one with the most hindered monomer synthesized using the macroinitiator with the highest molecular weight. The water solubility of the synthesized polymers changes depending on the pH of the solution and on the structure of the polymers. It has been shown using 1H-NMR that some of the synthesized polymers are capable to self-aggregation in water solution. The self-aggregation and the type of aggregation is influenced from the structure of the polymer and from the pH of the solution. Changing the structure of the polymers and the pH it is possible to obtain different type of aggregates in solution. This aggregates differ for the volume occupied from them, and for their hardness. Rheological measurements have been demonstrated that the synthesized polymers are capable to form gel phases. The gelation temperature changes changing the structure of the aggregates in solution and it is possible to correlate the changing in the gelation temperature with the changing in the structure of the polymer.

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The convergence of information technology and consumer electronics towards battery powered portable devices has increased the interest in high efficiency, low dissipation amplifiers. Class D amplifiers are the state of the art in low power consumption and high performance amplification. In this thesis we explore the possibility of exploiting nonlinearities introduced by the PWM modulation, by designing an optimized modulation law which scales its carrier frequency adaptively with the input signal's average power while preserving the SNR, thus reducing power consumption. This is achieved by means of a novel analytical model of the PWM output spectrum, which shows how interfering harmonics and their bandwidth affect the spectrum. This allows for frequency scaling with negligible aliasing between the baseband spectrum and its harmonics. We performed low noise power spectrum measurements on PWM modulations generated by comparing variable bandwidth, random test signals with a variable frequency triangular wave carrier. The experimental results show that power-optimized frequency scaling is both feasible and effective. The new analytical model also suggests a new PWM architecture that can be applied to digitally encoded input signals which are predistorted and compared with a cosine carrier, which is accurately synthesized by a digital oscillator. This approach has been simulated in a realistic noisy model and tested in our measurement setup. A zero crossing search on the obtained PWM modulation law proves that this approach yields an equivalent signal quality with respect to traditional PWM schemes, while entailing the use of signals whose bandwidth is remarkably smaller due to the use of a cosine instead of a triangular carrier.

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We introduce the notation of Markov chains and their properties, and give the definition of ergodic, irreducible and aperiodic chains with correspective examples. Then, the definition of hidden Markov models is given and their characteristics are examined. We formulate three basic problems regarding the hidden Markov models and discuss the solution of two of them - the Viterbi algorithm and the forward-backward algorithm.

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Metal nanowires (NWs) - nanostructures 20-100 nm in diameter and up to tens of micrometers long - behave as waveguides when irradiated with light with wavelength much greater than their diameter. This is due to collective excitations of free electrons (plasmons) in the metal which couple to light and travel on the surface of the nanowire. This effect can be used to efficiently absorb laser pulses to produce dense and hot plasma on special nanostructured targets with metal nanowires vertically aligned on the surface. In this thesis work, nanostructured targets with different parameters (length, diameter, metal and fabrication process) have been irradiated with infrared laser light. X-ray flux emitted by the cooling plasma is measured during irradiation, and the depth of craters formed on the target is measured later. This data is used to choose which target parameters are best for plasma production. Different targets are compared with each other and against a control, non-nanostructured (bulk) target. As will be shown, highly significant (> 5 sigma) differences are found between targets with different nanostructures, and between nanostructured and bulk target. This differences are very difficult to explain whithout accounting for the nanostructures in the targets. Therefore, data collected and analized in this thesis work supports the hypotesys that nanostructured targets perform better than bulk targets for laser plasma production purposes, and provides useful indications for optimization of NWS' parameters.

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Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

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In this thesis the design of a pressure regulation system for space propulsion engines (electric and cold gas) has been performed. The Bang-Bang Control (BBC) method has been implemented through the open/close command on a solenoid valve, and the mass flow rate of the propellant has been fixed with suitable flow restrictors. At the beginning, research for the comparison between mechanical and electronic (for BBC) pressure regulators has been performed, which resulted in enough advantages for the selection of the second valve type. The major advantage is about the possibility to have a variable outlet pressure with a variable inlet pressure through a simple remote command, while in mechanical pressure regulators the ratio between inlet and outlet pressures must be mechanically settled. Different pressure control schemes have been analyzed, changing number of solenoid valves, flow restrictors and plenums. For each scheme the valve’s frequencies were evaluated with simplified mathematical models and with the use of simulators implemented on Python; the results obtained from those two methods matched quiet well. From all the schemes it was possible to observe varying frequency and duty cycle, for changes in different parameters. This results, after experimental checks, can be used to design the control system for a given total number of cycles that a specific solenoid valve can guarantee. Finally, tests were performed and it was possible to verify the goodness of the control system. Moreover from the tests it was possible to deduce some tips in order to optimize the running of the simulator.

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The rising of concerns around the scarcity of non-renewable resources has raised curiosity around new frontiers in the polymer science field. Biopolymers is a general term describing different kind of polymers that are linked with the biological world because of either monomer derivation, end of life degradation or both. The current work is aimed at studying one example of both biopolymers types. Polyhydroxibutyrate (P3HB) is a biodegradable microbial-produced polymer which holds massive potentiality as a substitute of polyolefins such as polypropylene. Though, its highly crystalline nature and stereoregularity of structure make it difficult to work with. The project P3HB-Mono take advantage of polarized Raman spectroscopy to see how annealing of chains with different weights influence the crystallinity and molecular structure of the polymer, eventually reflecting on its mechanical properties. The technique employed is also optimal in order to see how mesophase, a particular conformation of chains different from crystalline and amorphous phase, develops in the polymer structure and changes depending on temperature and mechanical stress applied to the fiber. Polycaprolactone (PCL) on the other hand is a biodegradable fossil-fuel polymer which has biocompatibility and bio-resorbability features. As a consequence this material is very appealing for medical industry and can be used for different applications in this field. One interesting option is to produce narrow and long liquid filled fibers for drug delivery inside human body, using a traditional technique in an innovative way. The project BioLiCoF investigates the feasability of producing liquid filled fibers using melt-spinning techniques and will examine the role that melt-spinning parameters and liquids employed as a core solution have on the final fiber. The physical analysis of the fibers is also interpreted and idea on future developments of the trials are suggested.