Metodología para el uso de los niveles de gris en verificación de firmas manuscritas

Programa de doctorado: Cibernética y telecomunicaciones

Efecto de la presión hiperbárica y diferentes presiones parciales de gases sobre la modulación vegetativa de la respuesta cardiaca : aplicación de métodos lineales y no lineales en el análisis de VFC

Programa de doctorado: Actividad Física, Salud y Rendimiento Deportivo

Sviluppo di metodologie di localizzazione nel contesto del Comprehensive Nuclear Test-Ban Treaty

Since the first underground nuclear explosion, carried out in 1958, the analysis of seismic signals generated by these sources has allowed seismologists to refine the travel times of seismic waves through the Earth and to verify the accuracy of the location algorithms (the ground truth for these sources was often known). Long international negotiates have been devoted to limit the proliferation and testing of nuclear weapons. In particular the Treaty for the comprehensive nuclear test ban (CTBT), was opened to signatures in 1996, though, even if it has been signed by 178 States, has not yet entered into force, The Treaty underlines the fundamental role of the seismological observations to verify its compliance, by detecting and locating seismic events, and identifying the nature of their sources. A precise definition of the hypocentral parameters represents the first step to discriminate whether a given seismic event is natural or not. In case that a specific event is retained suspicious by the majority of the State Parties, the Treaty contains provisions for conducting an on-site inspection (OSI) in the area surrounding the epicenter of the event, located through the International Monitoring System (IMS) of the CTBT Organization. An OSI is supposed to include the use of passive seismic techniques in the area of the suspected clandestine underground nuclear test. In fact, high quality seismological systems are thought to be capable to detect and locate very weak aftershocks triggered by underground nuclear explosions in the first days or weeks following the test. This PhD thesis deals with the development of two different seismic location techniques: the first one, known as the double difference joint hypocenter determination (DDJHD) technique, is aimed at locating closely spaced events at a global scale. The locations obtained by this method are characterized by a high relative accuracy, although the absolute location of the whole cluster remains uncertain. We eliminate this problem introducing a priori information: the known location of a selected event. The second technique concerns the reliable estimates of back azimuth and apparent velocity of seismic waves from local events of very low magnitude recorded by a trypartite array at a very local scale. For the two above-mentioned techniques, we have used the crosscorrelation technique among digital waveforms in order to minimize the errors linked with incorrect phase picking. The cross-correlation method relies on the similarity between waveforms of a pair of events at the same station, at the global scale, and on the similarity between waveforms of the same event at two different sensors of the try-partite array, at the local scale. After preliminary tests on the reliability of our location techniques based on simulations, we have applied both methodologies to real seismic events. The DDJHD technique has been applied to a seismic sequence occurred in the Turkey-Iran border region, using the data recorded by the IMS. At the beginning, the algorithm was applied to the differences among the original arrival times of the P phases, so the cross-correlation was not used. We have obtained that the relevant geometrical spreading, noticeable in the standard locations (namely the locations produced by the analysts of the International Data Center (IDC) of the CTBT Organization, assumed as our reference), has been considerably reduced by the application of our technique. This is what we expected, since the methodology has been applied to a sequence of events for which we can suppose a real closeness among the hypocenters, belonging to the same seismic structure. Our results point out the main advantage of this methodology: the systematic errors affecting the arrival times have been removed or at least reduced. The introduction of the cross-correlation has not brought evident improvements to our results: the two sets of locations (without and with the application of the cross-correlation technique) are very similar to each other. This can be commented saying that the use of the crosscorrelation has not substantially improved the precision of the manual pickings. Probably the pickings reported by the IDC are good enough to make the random picking error less important than the systematic error on travel times. As a further justification for the scarce quality of the results given by the cross-correlation, it should be remarked that the events included in our data set don’t have generally a good signal to noise ratio (SNR): the selected sequence is composed of weak events ( magnitude 4 or smaller) and the signals are strongly attenuated because of the large distance between the stations and the hypocentral area. In the local scale, in addition to the cross-correlation, we have performed a signal interpolation in order to improve the time resolution. The algorithm so developed has been applied to the data collected during an experiment carried out in Israel between 1998 and 1999. The results pointed out the following relevant conclusions: a) it is necessary to correlate waveform segments corresponding to the same seismic phases; b) it is not essential to select the exact first arrivals; and c) relevant information can be also obtained from the maximum amplitude wavelet of the waveforms (particularly in bad SNR conditions). Another remarkable point of our procedure is that its application doesn’t demand a long time to process the data, and therefore the user can immediately check the results. During a field survey, such feature will make possible a quasi real-time check allowing the immediate optimization of the array geometry, if so suggested by the results at an early stage.

Fault detection in rotating machines by vibration signal processing techniques

Machines with moving parts give rise to vibrations and consequently noise. The setting up and the status of each machine yield to a peculiar vibration signature. Therefore, a change in the vibration signature, due to a change in the machine state, can be used to detect incipient defects before they become critical. This is the goal of condition monitoring, in which the informations obtained from a machine signature are used in order to detect faults at an early stage. There are a large number of signal processing techniques that can be used in order to extract interesting information from a measured vibration signal. This study seeks to detect rotating machine defects using a range of techniques including synchronous time averaging, Hilbert transform-based demodulation, continuous wavelet transform, Wigner-Ville distribution and spectral correlation density function. The detection and the diagnostic capability of these techniques are discussed and compared on the basis of experimental results concerning gear tooth faults, i.e. fatigue crack at the tooth root and tooth spalls of different sizes, as well as assembly faults in diesel engine. Moreover, the sensitivity to fault severity is assessed by the application of these signal processing techniques to gear tooth faults of different sizes.

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

TCAD approaches to multidimensional simulation of advanced semiconductor devices

Technology scaling increasingly emphasizes complexity and non-ideality of the electrical behavior of semiconductor devices and boosts interest on alternatives to the conventional planar MOSFET architecture. TCAD simulation tools are fundamental to the analysis and development of new technology generations. However, the increasing device complexity is reflected in an augmented dimensionality of the problems to be solved. The trade-off between accuracy and computational cost of the simulation is especially influenced by domain discretization: mesh generation is therefore one of the most critical steps and automatic approaches are sought. Moreover, the problem size is further increased by process variations, calling for a statistical representation of the single device through an ensemble of microscopically different instances. The aim of this thesis is to present multi-disciplinary approaches to handle this increasing problem dimensionality in a numerical simulation perspective. The topic of mesh generation is tackled by presenting a new Wavelet-based Adaptive Method (WAM) for the automatic refinement of 2D and 3D domain discretizations. Multiresolution techniques and efficient signal processing algorithms are exploited to increase grid resolution in the domain regions where relevant physical phenomena take place. Moreover, the grid is dynamically adapted to follow solution changes produced by bias variations and quality criteria are imposed on the produced meshes. The further dimensionality increase due to variability in extremely scaled devices is considered with reference to two increasingly critical phenomena, namely line-edge roughness (LER) and random dopant fluctuations (RD). The impact of such phenomena on FinFET devices, which represent a promising alternative to planar CMOS technology, is estimated through 2D and 3D TCAD simulations and statistical tools, taking into account matching performance of single devices as well as basic circuit blocks such as SRAMs. Several process options are compared, including resist- and spacer-defined fin patterning as well as different doping profile definitions. Combining statistical simulations with experimental data, potentialities and shortcomings of the FinFET architecture are analyzed and useful design guidelines are provided, which boost feasibility of this technology for mainstream applications in sub-45 nm generation integrated circuits.