GAN Hyperparameters search through Genetic Algorithm

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceRecent developments in Deep Learning are remarkable when it comes to generative models. The main reason for such progress is because of Generative Adversarial Networks (GANs) [1]. Introduced in a paper by Ian Goodfellow in 2014 GANs are machine learning models that are made of two neural networks: a Generator and a Discriminator. These two compete amongst each other to generate new, synthetic instances of data that resemble the real one. Despite their great potential, there are present challenges in their training, which include training instability, mode collapse, and vanishing gradient. A lot of research has been done on how to overcome these challenges, however, there was no significant proof found on whether modern techniques consistently outperform vanilla GAN. The performances of GANs are also highly dependent on the dataset they are trained on. One of the main challenges is related to the search for hyperparameters. In this thesis, we try to overcome this challenge by applying an evolutionary algorithm to search for the best hyperparameters for a WGAN. We use Kullback-Leibler divergence to calculate the fitness of the individuals, and in the end, we select the best set of parameters generated by the evolutionary algorithm. The parameters of the best-selected individuals are maintained throughout the generations. We compare our approach with the standard hyperparameters given by the state-of-art

Tropospheric Delay in the Neapolitan and Vesuvius Areas (Italy) by Means of a Dense GPS Array: A Contribution for Weather Forecasting and Climate Monitoring

Studying the spatiotemporal distribution and motion of water vapour (WV), the most variable greenhouse gas in the troposphere, is pivotal, not only for meteorology and climatology, but for geodesy, too. In fact, WV variability degrades, in an unpredictable way, almost all geodetic observation based on the propagation of electromagnetic signal through the atmosphere. We use data collected on a dense GPS network, designed for the purposes of monitoring the active Neapolitan (Italy) volcanoes, to retrieve the tropospheric delay parameters and precipitable water vapour (PWV). This study has two main targets: (a) the analysis of long datasets (11 years) to extract trends of climatological meaning for the region; (b) studying the main features of the time evolution of the PWV during heavy raining events to gain knowledge on the preparatory stages of highly impacting thunderstorms. For the latter target, both differential and precise point positioning (PPP) techniques are used, and the results are compared and critically discussed. An increasing trend, amounting to about 2 mm/decades, has been recognized in the PWV time series, which is in agreement with the results achieved in previous studies for the Mediterranean area. A clear topographic effect is detected for the Vesuvius volcano sector of the network and a linear relationship between PWV and altitude is quantitatively assessed. This signature must be taken into account in any modelling for the atmospheric correction of geodetic and remote-sensing data (e.g., InSAR). Characteristic temporal evolutions were recognized in the PWV in the targeted thunderstorms (which occurred in 2019 and 2020), i.e., a sharp increase a few hours before the main rain event, followed by a rapid decrease when the thunderstorm vanished. Accounting for such a peculiar trend in the PWV could be useful for setting up possible early warning systems for those areas prone to flash flooding, thus potentially providing a tool for disaster risk reduction

NeVoCGPS network: contributions to the Deformation Analysis in Neapolitan Volcanic area based on Continuous GPS measurements

Osservatorio Vesuviano, department of Istituto Nazionale di Geofisica e Vulcanologia, installed a permanent GPS network (NeVoCGPS), constituted of 25 stations, in Neapolitan volcanic area, where three active volcanoes (Somma-Vesuvius, Campi Flegrei caldera and Ischia Island) rise, each characterized by a peculiar type of ground movements activity. The Somma-Vesuvius system exhibits now a low level of ground deformation; the Campi Flegrei, caracterized from over 2000 years by slow up and down vertical movements (bradyseism), at present is in a very slow uplift phase; Ischia, finally, shows subsidence in the specific areas (Southern and North-West sectors of the island). The presence of these volcanoes and the dense urbanization of the area make the ground deformation monitoring a crucial point for risk mitigation and modelling aims. The 3D ground displacements are calculated using CGPS data, acquired with a 30s rate and with the daily and weekly vertexes position estimate. All the stations are managed by remote control and the data are automatically downloaded and processed using Bernese software package. The entire chain of acquisition, processing and data analysis is accurately described and some results obtained in the last years are shown

Experimental study for evaluation of a suitable ground displacement monitoring system: Pilot hole Campi Flegrei Deep Drilling Project case

The paper presents an experimental study carried out in 2012 during the drilling activity for a pilot hole performed in the framework of the Campi Flegrei Deep Drilling Project. A monitoring network has been installed to test and choose a suitable ground deformation system for the subsequent deep drilling of about 3.5 km in the Campi Flegrei Caldera (Italy). We describe the seismic network installed to characterize the structure of the pilot hole area and the ground deformation monitoring system chosen for the small drilling area. Data analysis and results obtained indicate that Total Station is a suitable tool for this case.Published4V. Dinamica dei processi pre-eruttiviN/A or not JC

Concurrent deformation processes in the Matese massif area (Central-Southern Apennines, Italy)

We investigated the interseismic GPS velocity field across the transition zone between Central and Southern Apennine comprising the Meta–Mainarde-Venafro and Alto Molise–Sannio-Matese mounts. The kinematic field obtained by combining GPS network solutions is based on data collected by the unpublished episodic campaigns carried out on Southern Apennine Geodetic network (SAGNet from 2000 to 2013), IGM95 network (Giuliani et al., 2009 from 1994 to 2007) and continuous GPS stations. The data collected after the 29 December 2013 earthquake (Mw 5.0) until early 2014 allowed estimating displacements at 15 SAGNet stations. The extension rate computed across the Matese massif along an anti-Apennine profile is 2.0±0.2 mm/yr. The interseismic velocities projected along the profile show that the maximum extension does not follow the topographic high of the Apennines but is shifted toward the eastern outer belt. No significant GPS deformation corresponding to inner faults systems of the Matese massif is detected. Taking into account our results and other geophysical data, we propose a conceptual model, which identifies the 2013–2014 seismic sequence as not due to an extensional deformation style usual along the Apennine chain. In fact, we have measured too large “coseismic” displacements, that could be explained as the result of tectonic regional stress, CO2-rich fluid migration and elastic loading of water in the karst Matese massif. We recognized a tensile source as model of dislocation of 2013–2014 earthquakes. It represents a simplification of a main fault system and fracture zone affecting the Matese massif. The dislocation along NE-dipping North Matese Fault System (NMFS) could be the driving mechanism of the recent seismic sequences. Moreover, to the first time the SAGnet GPS data collected from 1994 to 2014, are share and available to the scientific community in the open access data archive.INGV and DPCS1-C1 - 2012-2021.Published2282342T. Deformazione crostale attivaJCR Journa

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Non-geodetic approaches in the analysis of terrestrial CDGPS data for the retrieval of the atmospheric precipitable water at local scale during severe weather phenomena

Precipitable water (PW) derived from the CDGPS (Continuous Differential Global Positioning System) zenith tropospheric delay (ZTD) is evaluated through comparison of three procedures: using GPT (Global Pressure and Temperature) and GPT2 global models as well as observed data. The results show that the difference between PW retrieved from models (GPT and GPT2) and PW obtained by observed meteorological data, at least for sites and period observed in this paper, is also a function of the position of the station. The short period considered does not allow for any consideration of possible intra-annual or annual periodicity. The analysis of the residuals between observed PW and modeled PW shows a peak before the rain event

GPS time series at Campi Flegrei caldera (2000-2013)

The Campi Flegrei caldera is an active volcanic system associated to a high volcanic risk, and represents a well known and peculiar example of ground deformations (bradyseism), characterized by intense uplift periods, followed by subsidence phases with some episodic superimposed mini-uplifts. Ground deformation is an important volcanic precursor, and, its continuous monitoring, is one of the main tool for short time forecast of eruptive activity. This paper provides an overview of the continuous GPS monitoring of the Campi Flegrei caldera from January 2000 to July 2013, including network operations, data recording and processing, and data products. In this period the GPS time series allowed continuous and accurate tracking of ground deformation of the area. Seven main uplift episodes were detected, and during each uplift period, the recurrent horizontal displacement pattern, radial from the “caldera center”, suggests no significant change in deformation source geometry and location occurs. The complete archive of GPS time series at Campi Flegrei area is reported in the Supplementary materials. These data can be usefull for the scientific community in improving the research on Campi Flegrei caldera dynamic and hazard assessment

2D strain rate and ground deformation modelling from continuous and survey mode GNSS data in El Hierro, Canary Islands

[EN] We present a study of the deformation pattern in El Hierro Island through the analysis of GNSS data from surveys carried out between 2015 and 2019 as well as continuous data. The last eruption in El Hierro occurred under the sea on the south rift, lasted from October 2011 to March 2012, and it was preceded by intense seismic activity and nearly 5 cm ground inflation. After this eruptive cycle, further magmatic intrusions were detected, from June 2012 to March 2014, associated to intense seismic swarms and inflation (about 22 cm of uplift). Nevertheless, these magmatic intrusions did not culminate in any eruption. Following these post-eruptive episodes, the seismic activity became less intense. Thus, for the period of this study, about 500 earthquakes with magnitude ranging from mbLG 2 to mbLG 3.9 were recorded, the ground deformation measured is of lower magnitude, still remaining a slight uplift trend in the GNSS stations up to 2017 and followed by a slight subsidence of about 1.5 cm between 2017-2019. Our purpose is to explain the ground displacements measured and the earthquake occurrence in terms of geodynamics and seismotectonic activity along the island, for the period 2015-2019. Firstly, we retrieved the geodetic velocities from the GNSS daily solutions. Secondly, we computed the 2D infinitesimal strain rates from the velocities through a triangular segmentation approach to map the deformation pattern along the respective GNSS surveys.Projects PID2019-104726GB-I00 and CGL2015- 63799-P of the Spanish Research Agency has supported this research. We wish to acknowledge GRAFCAN (www.grafcan.es) of the Government of the Canary Islands for providing GNSS data from permanent station FRON. Likewise, to the Spanish IGN (www.ign.es) for providing the EH01 and LRES data.Arnoso, J.; Riccardi, U.; Tammaro, U.; Benavent, M.; Montesinos, F.; Vélez, E. (2023). 2D strain rate and ground deformation modelling from continuous and survey mode GNSS data in El Hierro, Canary Islands. Editorial Universitat Politècnica de València. 23-29. https://doi.org/10.4995/JISDM2022.2022.13632232