1,720,995 research outputs found
How “good” are real-time ground motion predictions from Earthquake Early Warning systems?
No full textReal-time ground motion alerts, as can be provided by Earthquake Early Warning (EEW) systems, need to be both timely and sufficiently accurate to be useful. Yet how timely and how accurate the alerts of existing EEW algorithms are is often poorly understood. In part, this is because EEW algorithm performance is usually evaluated not in terms of ground motion prediction accuracy and timeliness but in terms of other metrics (e.g., magnitude and location estimation errors), which do not directly reflect the usefulness of the alerts from an end user perspective. Here we attempt to identify a suite of metrics for EEW algorithm performance evaluation that directly quantify an algorithm's ability to identify target sites that will experience ground motion above a critical (user-defined) ground motion threshold. We process 15,553 recordings from 238 earthquakes with M > 5 (mostly from Japan and southern California) in a pseudo-real-time environment and investigate two end-member EEW methods. We use the metrics to highlight both the potential and limitations of the two algorithms and to show under which circumstances useful alerts can be provided. Such metrics could be used by EEW algorithm developers to convincingly demonstrate the added value of new algorithms or algorithm components. They can complement existing performance metrics that quantify other relevant aspects of EEW algorithms (e.g., false event detection rates) for a comprehensive and meaningful EEW performance analysis
Advancing Real-Time Seismic Risk Mitigation: Probabilistic Earthquake Early Warning and Physics Based Earthquake Triggering Models
No full textApplying Depth Distribution of Seismicity to Determine Thermo-Mechanical Properties of the Seismogenic Crust in Southern California: Comparing Lithotectonic Blocks
No full textWe analyze waveform-relocated seismicity (1981–2016) and other geophysical and geological datasets from 16 lithotectonic crustal blocks in southern California. We explore how earthquake depth histograms (EDH) are related to crustal strength, lithology, and temperature of the crust. First, we calculate relative EDHs to quantify the depth distribution of seismicity for each lithotectonic block. Second, we calculate depth profiles of maximum differential stress (“yield strength envelopes”, YSEs) using Byerlee’s law and a non-linear dislocation creep law. We use observed average heat flow values, strain rates, and states of stress to parameterize YSEs for five different crustal candidate lithologies in each lithotectonic block. We assume that seismicity ceases where the mechanical rock strength falls below a critical threshold level, and identify the YSE that best predicts the depth extent of seismicity in each block. The lithologies of the best matching YSEs are found to agree well with expectations from past tectonics: they are mostly quartz-dominated except for the feldspar-rich diorite lithologies in the Great Valley, the southernmost western Sierra Nevada, Inner Continental Borderland, and Rifted crust in the Salton Trough. Similarly, the inferred thermo-mechanical properties, including differential stress, lithology, and geotherms reflect the previously mapped tectonic variability between the 16 lithotectonic blocks. On average, the differential yield stress is smaller and peaks at a shallower depth in hotter and more quartz rich crust but is larger and peaks at greater depths for colder and predominantly diorite crust. The good agreement between the modeled YSEs, the EDHs and tectonic considerations suggests that EDHs indeed reflect long-term geophysical properties of the crust and can be used to infer thermo-mechanical properties at depth. In contrast, shallow seismicity may be more likely to reflect short-term strain transients from fluid flow or recent anthropogenic disturbances
Exploring Gravitational Waves Recordings with Machine Learning Techniques
No full textThe study of Gravitational Waves (GWs) opened a new window of possibilities to improve our understanding of the Universe. GWs provide suitable astronomical messengers for studying events that were not possible before through electromagnetic radiation, or in other cases complementing their observations. Ground-based interferometers like LIGO have been recording multiple GW events since the first detections in 2015. Despite the success of Earth-based observatories, the space limitations and noise sources on Earth point toward the need of building a spaceborne interferometer. The Laser Interferometer Space Antenna (LISA) is a planned project that will provide us with such a detector and will allow gaining access to lower frequency bands and more types of GW sources. To make the most out of LISA’s strengths, it is important to identify and develop alternative data analysis tools which are more appropriate for low latency searches of GWs than the current ones in use. Machine Learning techniques are a promising candidate since they can provide high accuracies, higher speeds, and a lower computational cost. Therefore, they can be used for the development of Low Latency Detectors (LLD) of GWs, which will be used to analyze the LISA recordings. I propose to build a prototype LLD by using a Sliding Window Algorithm, which makes use of Convolutional Neural Networks (CNNs) as its classification mechanism. To implement the LLD, I first create datasets composed of synthetic GW recordings of two different GW source types: Galactic Binaries (GBs) and Merging Blackhole Binaries (MBHBs). Then, I transform these recordings originally represented only in the time domain, into the frequency domain, and the time-frequency domain and train two different ML architectures (CNNs and Fully-Connected Neural Networks) using both the original and the transformed data. A performance evaluation is done to select the best combination of ML architecture and domain representation for solving the detection task. The chosen combination is then used as the classifier mechanism of the LLD acting in windows of five days duration. The LLD is tested on one-year-long recordings with different levels of noise. The analysis suggests that the time-frequency domain representations offer the most promising results for detecting both types of sources (GBs and MBHBs) reaching high accuracies in recordings with low to moderate signal-to-noise ratio (SNR).Applied Geophysics | IDEA Leagu
Fault reactivation by fluid injection: insights from laboratory friction experiments with multiple reactivation sequences
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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