Automatic inspection and analysis of digital waveform images by means of convolutional neural networks

AbstractAnalyzing seismic data to get information about earthquakes has always been a major task for seismologists and, more in general, for geophysicists. Recently, thanks to the technological development of observation systems, more and more data are available to perform such tasks. However, this data "grow up" makes "human possibility" of data processing more complex in terms of required efforts and time demanding. That is why new technological approaches such as artificial intelligence are becoming very popular and more and more exploited. In this paper, we explore the possibility of interpreting seismic waveform segments by means of pre-trained deep learning. More specifically, we apply convolutional networks to seismological waveforms recorded at local or regional distances without any pre-elaboration or filtering. We show that such an approach can be very successful in determining if an earthquake is "included" in the seismic wave image and in estimating the distance between the earthquake epicenter and the recording station

An analysis of ground and instrumental short-period noise

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An algorithm for doble difference joint hypocenter determination: application to the 2002 Molise (Central Italy) earthquake sequence

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Matlab software for the analysis of seismic waves recorded by three-element arrays

We develop and implement an algorithm for inverting three-element array data on a Matlab platform. The algorithm allows reliable estimation of back azimuth and apparent velocity from seismic records under low signal-to-noise conditions. We start with a cubic spline interpolation of the waveforms and determine the differences between arrival times at pairs of array elements. The time differences are directly computed from cross-correlation functions. The advantages of this technique are (a) manual picking of the onset of each arrival is not necessary at each array element; (b) interpolation makes it possible to estimate time differences at a higher resolution than the sampling rate of the digital waveforms; (c) consistency among three independent determinations provides a reliability check; and (d) the value of apparent velocity indicates the nature of the recorded wavelet and physically checks the results. The algorithm was tested on data collected by a tri-partite array (with an aperture of 250 m) deployed in 1998 by the National Data Center of Israel, during a field experiment in southern Israel, 20km southwest of the Dead Sea. The data include shallow explosions and natural earthquakes under both high and low signal-to-noise conditions. The procedure developed in this study is considered suitable for searching of small aftershocks subsequent to an underground explosion, in the context of on-site inspections according to the Comprehensive Nuclear-Test-Ban Treaty (CTBT)

Daily earthquake forecasts during the May-June 2012 Emilia earthquake sequence (northern Italy)

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Assessing Vegetation Decline Due to Pollution from Solid Waste Management by a Multitemporal Remote Sensing Approach

Nowadays, the huge production of Municipal Solid Waste (MSW) is one of the most strongly felt environmental issues. Consequently, the European Union (EU) delivers laws and regulations for better waste management, identifying the essential requirements for waste disposal operations and the characteristics that make waste hazardous to human health and the envi-ronment. In Italy, environmental regulations define, among other things, the characteristics of sites to be classified as “potentially contaminated”. From this perspective, the Basilicata region is cur-rently one of the Italian regions with the highest number of potentially polluted sites in proportion to the number of inhabitants. This research aimed to identify the possible effects of potentially toxic element (PTE) pollution due to waste disposal activities in three “potentially contaminated” sites in southern Italy. The area was affected by a release of inorganic pollutants with values over the thresholds ruled by national/European legislation. Potential physiological efficiency variations of vegetation were analyzed through the multitemporal processing of satellite images. Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images were used to calcu-late the trend in the Normalized Difference Vegetation Index (NDVI) over the years. The mul-titemporal trends were analyzed using the median of the non-parametric Theil–Sen estimator. Fi-nally, the Mann–Kendall test was applied to evaluate trend significance featuring areas according to the contamination effects on investigated vegetation. The applied procedure led to the exclu-sion of significant effects on vegetation due to PTEs. Thus, waste disposal activities during previ-ous years do not seem to have significantly affected vegetation around targeted sites

Study of recent seismicity in the area of Southern Apennines

In questo lavoro è stata effettuata una dettagliata analisi della sismicità dell’Italia meridionale in particolare della zona comprendente l’Appennino lucano e l’avanfossa bradanica. Sono stati utilizzati i tempi d’arrivo delle fasi P e S di terremoti locali registrati dalla Rete Sismica Nazionale (RSNC), dalla rete temporanea SAPTEX (2001-2004) (Cimini et al., 2006), e dalla rete locale dell’Eni-Agip operante nella Val d’Agri, registrate nel periodo 2001-2006. In questo modo è stato creato un database costituito da 7570 fasi P e 4956 fasi S, associate a 514 eventi con magnitudo maggiore di 2.0. Lo studio realizzato consiste nel: 1) Calcolo del rapporto VP/VS utilizzando il metodo di Wadati modificato (Chatelain, 1978), ottenendo un valore di 1.83 (Fig.1) leggermente superiore a quello ottenuto da studi precedenti; 2) Analisi del profilo di velocità 1D che meglio approssima la struttura crostale dell’area studiata (Fig.2) utilizzando il codice VELEST (Kissling et al., 1995) e tre modelli iniziali ottenuti da studi precedenti (Chiarabba and Frepoli, 1997; Cassinis et al., 2003; Chiarabba at al., 2005; Frepoli et al., 2005). 3) Localizzazione ipocentrale, calcolo dei meccanismi focali e campo di stress. Le localizzazioni ipocentrali calcolate sono prevalentemente di qualità A(243) e B(59), così come definite dal programma HYPOELLIPSE (Lahr, 1989). Rispetto a quelle ottenute utilizzando i dati della sola rete RSNC, esse risultano avere profondità ipocentrali piú vincolate ed errori di localizzazione inferiori. Considerando la distribuzione della sismicità in Fig.3 si possono distinguere tre zone principali: una situata nella parte ovest della catena appenninica, caratterizzata soprattutto da eventi piú superficiali; una situata in corrispondenza dell’avanfossa bradanica caratterizzata da una sismicità sparsa e da eventi piú profondi; ed infine un gruppo di eventi sparsi localizzati nell’area della Sila, separati da quelli esistenti nella zona del monte Pollino da un evidente gap sismico. Seguendo la procedura di calcolo dei meccanismi focali, col metodo delle polarità dei primi arrivi, ne sono stati selezionati 69 in base ai due fattori di qualità definiti dal codice FPFIT (Reasenberg and Oppenheimer, 1985). Le soluzioni ottenute sono in gran parte normali e trascorrenti con gli assi T che descrivono una generalizzata estensione dell’Appennino lucano in direzione NE-SW. Per la determinazione del campo di stress regionale è stata utilizzata la tecnica di inversione elaborata da Gephart & Forsyth (1984). I risultati ottenuti sono coerenti con i precedenti studi nella stessa area

Referral Patterns, Procedures, and Outcomes of a Large Community- Based Urology Group: a Retrospective Chart Review

In 2012 The United States Preventive Services Task Force (USPSTF) recommended against prostate cancer (Pca) screening. The purpose of our study is to assess the effects of the USPSTF grade D recommendation for PSA based screening on new PCa diagnoses within a large-community based private practice setting. We completed a retrospective chart review of men with an elevated PSA seen in our clinic between May 2009–May 2015 who had undergone a prostate biopsy and were diagnosed with PCa. We observed that following the 2012 USPSTF recommendations, there was a significant increase in patients with clinically significant prostate cancer GG ≥ 2, with the majority being 55-65 years of age. In addition we observed a decrease in the diagnosis of very low and low risk PCa with an increased incidence of intermediate and high risk PCa