NET-VISA: Network Processing Vertically Integrated Seismic Analysis

Arora, Neha; Russell, Stuart; Sudderth, Erik B.

doi:10.1785/0120120107

Cited by 38 publications

(15 citation statements)

References 12 publications

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“…This will lead to the association of individual array detections into an event, in an operational environment. The association procedure is preferably an automated algorithm applied to regional (Arrowsmith et al 2008) or global networks like the IMS (Arora et al 2013). The moving nature of the source is important for its identification.…”

Section: Discussion a N D C O N C L U S I O Nmentioning

confidence: 99%

Infrasound from the 2009 and 2017 DPRK rocket launches

Evers

Assink

Smets

2018

Geophysical Journal International

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Summary Supersonic rockets generate low-frequency acoustic waves, that is, infrasound, during the launch and re-entry. Infrasound is routinely observed at infrasound arrays from the International Monitoring System, in place for the verification of the Comprehensive Nuclear-Test-Ban Treaty. Association and source identification are key elements of the verification system. The moving nature of a rocket is a defining criterion in order to distinguish it from an isolated explosion. Here, it is shown how infrasound recordings can be associated, which leads to identification of the rocket. Propagation modelling is included to further constrain the source identification. Four rocket launches by the Democratic People's Republic of Korea in 2009 and 2017 are analysed in which multiple arrays detected the infrasound. Source identification in this region is important for verification purposes. It is concluded that with a passive monitoring technique such as infrasound, characteristics can be remotely obtained on sources of interest, that is, infrasonic intelligence, over 4500+ km.

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Section: Discussion a N D C O N C L U S I O Nmentioning

confidence: 99%

Infrasound from the 2009 and 2017 DPRK rocket launches

Evers

Assink

Smets

2018

Geophysical Journal International

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“…This formulation lends itself nicely to the problem of estimating whale positions because many of the factors affecting signal amplitude are uncertain, including the amplitude of the original signal itself. The Bayesian approach has been used in related problems such as the detection of seismic events using a network of seismic stations (Arora et al, 2013).…”

Section: Bayesian Network Model For Estimating Whale Positionsmentioning

confidence: 99%

Observations and Bayesian location methodology of transient acoustic signals (likely blue whales) in the Indian Ocean, using a hydrophone triplet

Bras

Kuzma

Sucic

et al. 2016

The Journal of the Acoustical Society of America

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A notable sequence of calls was encountered, spanning several days in January 2003, in the central part of the Indian Ocean on a hydrophone triplet recording acoustic data at a 250 Hz sampling rate. This paper presents signal processing methods applied to the waveform data to detect, group, extract amplitude and bearing estimates for the recorded signals. An approximate location for the source of the sequence of calls is inferred from extracting the features from the waveform. As the source approaches the hydrophone triplet, the source level (SL) of the calls is estimated at 187 ± 6 dB re: 1 μPa-1 m in the 15-60 Hz frequency range. The calls are attributed to a subgroup of blue whales, Balaenoptera musculus, with a characteristic acoustic signature. A Bayesian location method using probabilistic models for bearing and amplitude is demonstrated on the calls sequence. The method is applied to the case of detection at a single triad of hydrophones and results in a probability distribution map for the origin of the calls. It can be extended to detections at multiple triads and because of the Bayesian formulation, additional modeling complexity can be built-in as needed.

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“…If, however, a program is not PAST, the simulation may take forever. In addition, the use of probabilistic programs in safety-critical environments [2,7,20] necessitates providing formal guarantees on termination. Different techniques are considered for probabilistic program termination ranging from probabilistic term rewriting [3], sized types [17], and Büchi automata theory [14], to weakest pre-condition calculi for checking PAST [31].…”

Section: Introductionmentioning

confidence: 99%

Automated Termination Analysis of Polynomial Probabilistic Programs

Marcel

Bartocci

Katoen

et al. 2021

Programming Languages and Systems

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The termination behavior of probabilistic programs depends on the outcomes of random assignments. Almost sure termination (AST) is concerned with the question whether a program terminates with probability one on all possible inputs. Positive almost sure termination (PAST) focuses on termination in a finite expected number of steps. This paper presents a fully automated approach to the termination analysis of probabilistic while-programs whose guards and expressions are polynomial expressions. As proving (positive) AST is undecidable in general, existing proof rules typically provide sufficient conditions. These conditions mostly involve constraints on supermartingales. We consider four proof rules from the literature and extend these with generalizations of existing proof rules for (P)AST. We automate the resulting set of proof rules by effectively computing asymptotic bounds on polynomials over the program variables. These bounds are used to decide the sufficient conditions – including the constraints on supermartingales – of a proof rule. Our software tool Amber can thus check AST, PAST, as well as their negations for a large class of polynomial probabilistic programs, while carrying out the termination reasoning fully with polynomial witnesses. Experimental results show the merits of our generalized proof rules and demonstrate that Amber can handle probabilistic programs that are out of reach for other state-of-the-art tools.

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NET-VISA: Network Processing Vertically Integrated Seismic Analysis

Cited by 38 publications

References 12 publications

Infrasound from the 2009 and 2017 DPRK rocket launches

Infrasound from the 2009 and 2017 DPRK rocket launches

Observations and Bayesian location methodology of transient acoustic signals (likely blue whales) in the Indian Ocean, using a hydrophone triplet

Automated Termination Analysis of Polynomial Probabilistic Programs

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