Time to digital converter

In questa tesi è analizzato il caso di sensori con uscita in frequenza e periodo, si traduce in ultima analisi nella capacità di misurare con precisione un intervallo temporale. La rivelazione del tempo risulta essere lo stadio fondamentale da cui deriva la risoluzione dell'intero sistema di misura. Nella realtà, la questione della simultaneità cioè individuare con assoluta precisione due eventi che si verificano contemporaneamente, in un determinato istante t, è un problema piuttosto complesso: le difficoltà sono correlate soprattutto alle limitazioni fisiche intrinseche degli strumenti di misura. E' utile allora fornire un'analisi sui principi e le tecniche alla base della misura di intervalli temporali, detta Time Interval Measurement (TIM). Lo scopo della tesi è studiare i vari metodi per realizzare TDC lineari digitali, facendo un'analisi critica e ed evidenziando pro e contro che i vari approcci presentano, attingendo e analizzando criticamente informazioni dalle varie fonti riportate in bibliografia.

Optimized methods to digital survey and 3D modelling of cultural heritage assets

Currently making digital 3D models and replicas of the cultural heritage assets play an important role in the preservation and having a high detail source for future research and intervention. In this dissertation, it is tried to assess different methods for digital surveying and making 3D replicas of cultural heritage assets in different scales of size. The methodologies vary in devices, software, workflow, and the amount of skill that is required. The three phases of the 3D modelling process are data acquisition, modelling, and model presentation. Each of these sections is divided into sub-sections and there are several approaches, methods, devices, and software that may be employed, furthermore, the selection process should be based on the operation's goal, available facilities, the scale and properties of the object or structure to be modeled, as well as the operators' expertise and experience. The most key point to remember is that the 3D modelling operation should be properly accurate, precise, and reliable; therefore, there are so many instructions and pieces of advice on how to perform 3D modelling effectively. It is an attempt to compare and evaluate the various ways of each phase in order to explain and demonstrate their differences, benefits, and drawbacks in order to serve as a simple guide for new and/or inexperienced users.

Instrument transformers with Digital outputting high voltage power networks

In recent years, energy modernization has focused on smart engineering advancements. This entails designing complicated software and hardware for variable-voltage digital substations. A digital substation consists of electrical and auxiliary devices, control and monitoring devices, computers, and control software. Intelligent measurement systems use digital instrument transformers and IEC 61850-compliant information exchange protocols in digital substations. Digital instrument transformers used for real-time high-voltage measurements should combine advanced digital, measuring, information, and communication technologies. Digital instrument transformers should be cheap, small, light, and fire- and explosion-safe. These smaller and lighter transformers allow long-distance transmission of an optical signal that gauges direct or alternating current. Cost-prohibitive optical converters are a problem. To improve the tool's accuracy, amorphous alloys are used in the magnetic circuits and compensating feedback. Large-scale voltage converters can be made cheaper by using resistive, capacitive, or hybrid voltage dividers. In known electronic voltage transformers, the voltage divider output is generally on the low-voltage side, facilitating power supply organization. Combining current and voltage transformers reduces equipment size, installation, and maintenance costs. These two gadgets cost less together than individually. To increase commercial power metering accuracy, current and voltage converters should be included into digital instrument transformers so that simultaneous analogue-to-digital samples are obtained. Multichannel ADC microcircuits with synchronous conversion start allow natural parallel sample drawing. Digital instrument transformers are created adaptable to substation operating circumstances and environmental variables, especially ambient temperature. An embedded microprocessor auto-diagnoses and auto-calibrates the proposed digital instrument transformer.

Description and Prediction of Freezing of Gait in Parkinson's Disease from Wearable Inertial Measurements Units

Parkinson's disease (PD) is a neuro-degenerative disorder, the second most common after Alzheimer's disease. After diagnosis, treatments can help to relieve the symptoms, but there is no known cure for PD. PD is characterized by a combination of motor and no-motor dysfunctions. Among the motor symptoms there is the so called Freezing of Gait (FoG). The FoG is a phenomenon in PD patients in which the feet stock to the floor and is difficult for the patient to initiate movement. FoG is a severe problem, since it is associated with falls, anxiety, loss of mobility, accidents, mortality and it has substantial clinical and social consequences decreasing the quality of life in PD patients. Medicine can be very successful in controlling movements disorders and dealing with some of the PD symptoms. However, the relationship between medication and the development of FoG remains unclear. Several studies have demonstrated that visual or auditory rhythmical cuing allows PD patients to improve their motor abilities. Rhythmic auditory stimulation (RAS) was shown to be particularly effective at improving gait, specially with patients that manifest FoG. While RAS allows to reduce the time and the effects of FoGs occurrence in PD patients after the FoG is detected, it can not avoid the episode due to the latency of detection. An improvement of the system would be the prediction of the FoG. This thesis was developed following two main objectives: (1) the finding of specifics properties during pre FoG periods different from normal walking context and other walking events like turns and stops using the information provided by the inertial measurements units (IMUs) and (2) the formulation of a model for automatically detect the pre FoG patterns in order to completely avoid the upcoming freezing event in PD patients. The first part focuses on the analysis of different methods for feature extraction which might lead in the FoG occurrence.

Tree regularized neural networks for key point analysis

This thesis contributes to the ArgMining 2021 shared task on Key Point Analysis. Key Point Analysis entails extracting and calculating the prevalence of a concise list of the most prominent talking points, from an input corpus. These talking points are usually referred to as key points. Key point analysis is divided into two subtasks: Key Point Matching, which involves assigning a matching score to each key point/argument pair, and Key Point Generation, which consists of the generation of key points. The task of Key Point Matching was approached using different models: a pretrained Sentence Transformers model and a tree-constrained Graph Neural Network were tested. The best model was the fine-tuned Sentence Transformers, which achieved a mean Average Precision score of 0.75, ranking 12 compared to other participating teams. The model was then used for the subtask of Key Point Generation using the extractive method in the selection of key point candidates and the model developed for the previous subtask to evaluate them.

Experimental evaluation of the z-resolution in different clinical Digital Breast Tomosynthesis systems using commercial phantoms

Digital Breast Tomosynthesis (DBT) is an advanced mammography technique based on the reconstruction of a pseudo-volumetric image. To date, image quality represents the most deficient section of DBT quality control protocols. In fact, related tests are not yet characterized by either action levels or typical values. This thesis work focuses on the evaluation of one aspect of image quality: the z-resolution. The latter is studied in terms of Artifact Spread Function (ASF), a function that describes the signal spread of a detail along the reconstructed focal planes. To quantify the ASF numerically, its Full Width at Half Maximum (FWHM) is calculated and used as a representative index of z-resolution. Experimental measurements were acquired in 24 DBT systems, of 7 different models, currently in use in 20 hospital facilities in Italy. The analysis, performed on the clinical reconstructed images, of 5 different commercial phantoms, lead to the identification of characteristic FWHM values for each type of DBT system. The ASF clearly showed a dependence on the size of the detail, providing higher FWHM values for larger objects. The z-resolution was found to be positively influenced by the acquisition angle: Fujifilm sistematically showed wider ASF profiles in ST mode (15°) than in HR mode (40°). However, no clear relationship was found between angular range and ASF, among different DBT systems, due to the influence of the peculiarities of each reconstruction algorithm. The experimental approach shown in this thesis work can be proposed as a z-resolution quality control test procedure. Contextually, the values found could be used as a starting point for identifying typical values to be included in the test, in a DBT protocol. Clearly, a statistically significant number of images is needed to do this. The equipment involved in this work is located in hospitals and is not available for research purposes, so only a limited amount of data was acquired and processed.