Tecniche MonteCarlo per l'analisi di sistemi a rete

The assessment of the RAMS (Reliability, Availability, Maintainability and Safety) performances of system generally includes the evaluations of the “Importance” of its components and/or of the basic parameters of the model through the use of the Importance Measures. The analytical equations proposed in this study allow the estimation of the first order Differential Importance Measure on the basis of the Birnbaum measures of components, under the hypothesis of uniform percentage changes of parameters. The aging phenomena are introduced into the model by assuming exponential-linear or Weibull distributions for the failure probabilities. An algorithm based on a combination of MonteCarlo simulation and Cellular Automata is applied in order to evaluate the performance of a networked system, made up of source nodes, user nodes and directed edges subjected to failure and repair. Importance Sampling techniques are used for the estimation of the first and total order Differential Importance Measures through only one simulation of the system “operational life”. All the output variables are computed contemporaneously on the basis of the same sequence of the involved components, event types (failure or repair) and transition times. The failure/repair probabilities are forced to be the same for all components; the transition times are sampled from the unbiased probability distributions or it can be also forced, for instance, by assuring the occurrence of at least a failure within the system operational life. The algorithm allows considering different types of maintenance actions: corrective maintenance that can be performed either immediately upon the component failure or upon finding that the component has failed for hidden failures that are not detected until an inspection; and preventive maintenance, that can be performed upon a fixed interval. It is possible to use a restoration factor to determine the age of the component after a repair or any other maintenance action.

Landscape ecology and genetics of the wolf in Italy

This PhD Thesis includes five main parts on diverse topics. The first two parts deal with the trophic ecology of wolves in Italy consequently to a recent increase of wild ungulates abundance. Data on wolf diet across time highlighted how wild ungulates are important food resource for wolves in Italy. Increasing wolf population, increasing numbers of wild ungulates and decreasing livestock consume are mitigating wolf-man conflicts in Italy in the near future. In the third part, non-invasive genetic sampling techniques were used to obtain genotypes and genders of about 400 wolves. Thus, wolf packs were genetically reconstructed using diverse population genetic and parentage software. Combining the results on pack structure and genetic relatedness with sampling locations, home ranges of wolf packs and dispersal patterns were identified. These results, particularly important for the conservation management of wolves in Italy, illustrated detailed information that can be retrieved from genetic identification of individuals. In the fourth part, wolf locations were combined with environmental information obtained as GIS-layers. Modern species distribution models (niche models) were applied to infer potential wolf distribution and predation risk. From the resulting distribution maps, information pastures with the highest risk of depredation were derived. This is particularly relevant as it allows identifying those areas under danger of carnivore attack on livestock. Finally, in the fifth part, habitat suitability models were combined with landscape genetic analysis. On one side landscape genetic analyses on the Italian wolves provided new information on the dynamics and connectivity of the population and, on the other side, a profound analysis of the effects that habitat suitability methods had on the parameterization of landscape genetic analyses was carried out to contributed significantly to landscape genetic theory.

High temporal resolution insights into early life histories: integrating histomorphometric, trace element and isotopic analyses of dental hard tissues in archaeological populations from Italy

Teeth, with their high mineralisation, incremental growth, and lack of remodelling, serve as biological archives that document an individual's development. This project aims to utilise the potential of teeth in bioarchaeological studies to achieve three primary objectives: 1) to investigate the application of histological and histochemical methods in reconstructing developmental bio-chronologies and early life histories; 2) to refine the temporal precision of isotopic analysis of dentine collagen by developing a novel protocol that integrates micro-sampling techniques with high-resolution histomorphometrics; and 3) to synthesise data from enamel and dentine for a comprehensive understanding of early life development and dietary transitions. This study adopts an integrated multidisciplinary bioarchaeological approach, conducting histomorphometric analysis on enamel and dentine across deciduous and permanent dentitions. It applies high-temporal resolution trace element analysis to enamel using LA-ICPMS and δ13C and δ15N isotope analyses through sequential micro-sampling to dentine of permanent teeth. Samples were selected from diverse archaeological contexts across the Italian peninsula, covering the Upper Palaeolithic, Copper Age, and Early Medieval periods, providing insight into diachronic variations in infant development and life history. Findings highlight the efficacy of histological and histochemical techniques in accurately determining growth rates, physiological stress, dietary shifts (particularly timing of weaning), and age at death in infant remains. The consistency and comparison between enamel and dentine underscores the enhanced insight obtained from integrating information from both tissues. Importantly, the newly proposed protocol significantly improves the temporal accuracy of dentine collagen analysis, facilitating precise chronological placement of the results over broad developmental associations. This study reaffirms the significance of teeth as valuable bioarchaeological instruments. By introducing and testing multidisciplinary methods, it provides deeper insights into early life history and cultural practices across diverse chronological contexts, highlighting the importance of advanced methodologies in extracting detailed, accurate, and nuanced information from past populations.

Secure gossiping techniques and components

Gossip protocols have proved to be a viable solution to set-up and manage largescale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent load balancing capabilities, fast spreading, and redundancy of information. In some sense, these services or protocols mimic natural system behaviors in order to achieve their goals. The key idea of this work is that the remarkable properties of gossip hold when all the participants follow the rules dictated by the actual protocols. If one or more malicious nodes join the network and start cheating according to some strategy, the result can be catastrophic. In order to study how serious the threat posed by malicious nodes can be and what can be done to prevent attackers from cheating, we focused on a general attack model aimed to defeat a key service in gossip overlay networks (the Peer Sampling Service [JGKvS04]). We also focused on the problem of protecting against forged information exchanged in gossip services. We propose a solution technique for each problem; both techniques are general enough to be applied to distinct service implementations. As gossip protocols, our solutions are based on stochastic behavior and are fully decentralized. In addition, each technique’s behaviour is abstracted by a general primitive function extending the basic gossip scheme; this approach allows the adoptions of our solutions with minimal changes in different scenarios. We provide an extensive experimental evaluation to support the effectiveness of our techniques. Basically, these techniques aim to be building blocks or P2P architecture guidelines in building more resilient and more secure P2P services.

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).