Ground-truth Reference Dataset of 1001 Rocket Launches for Space Missions and their Infrasonic Signatures

The infrasound technique is applied to monitor atmospheric explosions in the context of the Comprehensive Nuclear-Test-Ban Treaty and, among other purposes, to characterize large meteoroids entering Earth's atmosphere. Anyhow, for both types of sources, the exact location and time are initially unknown and sometimes difficult to precisely estimate. In contrast, rocket launches are well-defined ground-truth events generating strong infrasonic signatures. In this study, we analyse infrasound signatures of 1001 rocket launches for space missions recorded at stations of the International Monitoring System between 2009 and mid-2020. We include all surface- or ocean-based launches within this period with known launch time, location, rocket type, and mission name; whereas launches of sounding rockets and ballistic missiles for scientific and military purposes, respectively, are excluded from our study. We characterize the infrasonic signatures of over 70 different types of rockets launched at 27 different globally distributed spaceports and are able to identify infrasound signatures from up to 73% of the launches considered. We use this unique dataset to estimate the global detectability of such events and to characterize rocket infrasound. We provide the results as a DOI-assigned ground-truth reference dataset for supporting its further use in geophysical and atmospheric research.

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Text Analysis of Project Completion Reports

10.18235/0003611 ◽

2021 ◽

Author(s):

César E. Montiel Olea ◽

Leonardo R. Corral

Keyword(s):

Text Analysis ◽

Text Documents ◽

Project Completion ◽

Analysis Tools ◽

Development Effectiveness ◽

Different Types ◽

Potential Applications ◽

Project Cycle ◽

Main Instrument ◽

Unique Dataset

Project Completion Reports (PCRs) are the main instrument through which different multilateral organizations measure the success of a project once it closes. PCRs are important for development effectiveness as they serve to understand achievements, failures, and challenges within the project cycle they can feed back into the design and execution of new projects. The aim of this paper is to introduce text analysis tools for the exploration of PCR documents. We describe and apply different text analysis tools to explore the content of a sample of PCRs. We seek to illustrate a way in which PCRs can be summarized and analyzed using innovative tools applied to a unique dataset. We believe that the methods presented in this investigation have numerous potential applications to different types of text documents routinely prepared within the Inter-American Development Bank (IDB).

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Motion estimation in vehicular environments based on Bayesian dynamic networks

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219255 ◽

2021 ◽

pp. 1-12

Author(s):

Lauro Reyes-Cocoletzi ◽

Ivan Olmos-Pineda ◽

J. Arturo Olvera-Lopez

Keyword(s):

Real World ◽

Dynamic Networks ◽

Ground Truth ◽

Change Of Direction ◽

Prediction Rate ◽

Different Types ◽

Novel Method ◽

Comparison Of The Results ◽

Multiple Obstacles ◽

Real Traffic

The cornerstone to achieve the development of autonomous ground driving with the lowest possible risk of collision in real traffic environments is the movement estimation obstacle. Predicting trajectories of multiple obstacles in dynamic traffic scenarios is a major challenge, especially when different types of obstacles such as vehicles and pedestrians are involved. According to the issues mentioned, in this work a novel method based on Bayesian dynamic networks is proposed to infer the paths of interest objects (IO). Environmental information is obtained through stereo video, the direction vectors of multiple obstacles are computed and the trajectories with the highest probability of occurrence and the possibility of collision are highlighted. The proposed approach was evaluated using test environments considering different road layouts and multiple obstacles in real-world traffic scenarios. A comparison of the results obtained against the ground truth of the paths taken by each detected IO is performed. According to experimental results, the proposed method obtains a prediction rate of 75% for the change of direction taking into consideration the risk of collision. The importance of the proposal is that it does not obviate the risk of collision in contrast with related work.

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Adjoint backtracking for the verification of the Comprehensive Test Ban Treaty

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-2-2133-2002 ◽

2002 ◽

Vol 2 (6) ◽

pp. 2133-2150 ◽

Cited By ~ 2

Author(s):

J.-P. Issartel ◽

J. Baverel

Keyword(s):

Adjoint Operator ◽

Real Data ◽

Daily Basis ◽

New Approach ◽

Comprehensive Test Ban Treaty ◽

Tracer Dispersion ◽

International Monitoring ◽

Comprehensive Test ◽

Test Ban ◽

Test Ban Treaty

Abstract. An international monitoring system is being built as a verification tool for the Comprehensive Test Ban Treaty. Forty stations will measure on a worldwide daily basis the concentration of radioactive noble gases. The paper introduces, by handling preliminary real data, a new approach of backtracking for the identification of sources after positive measurements. When several measurements are available the ambiguity about possible sources is reduced significantly. As an interesting side result it is shown that diffusion in the passive tracer dispersion equation is necessarily a self-adjoint operator.

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Infrasound station IS25 of the International Monitoring System of the Comprehensive Test Ban Treaty : from design to certification

10.5194/egusphere-egu21-15858 ◽

2021 ◽

Author(s):

thomas philippe ◽

sylvain carre

Keyword(s):

Monitoring System ◽

International Monitoring System ◽

Comprehensive Test Ban Treaty ◽

Monitoring Tools ◽

International Monitoring ◽

Deep Forest ◽

International Data ◽

Comprehensive Test ◽

Test Ban ◽

Test Ban Treaty

CEA is operating the French segment of the International Monitoring System of the Comprehensive Test Ban Treaty (CTBT). Construction of IMS stations was started on the late 90&#8217; and one last station was pending before completing commitment of France.Taking into account experience learned over the years, design was thought to combine enhanced detection capability and robustness. It gives also the opportunity to improve out monitoring tools and technics.Station run 9 sensors spread out on a deep forest in Guadeloupe; power is distributed with buried cable while data are received with optical fibre to a central facility from which frames are sent to the International Data Center to the CTBTO. Constructiion was carried out in 2019.IS25 was certified by the PTS of the CTBTO in November 2020

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Teleseismic slowness-azimuth station corrections for the International Monitoring System Seismic Network

Bulletin of the Seismological Society of America ◽

10.1785/bssa0890040989 ◽

1999 ◽

Vol 89 (4) ◽

pp. 989-1003 ◽

Cited By ~ 7

Author(s):

István Bondár ◽

Robert G. North ◽

Gregory Beall

Keyword(s):

Monitoring System ◽

Global Network ◽

Systematic Bias ◽

International Monitoring System ◽

Time Data ◽

International Monitoring ◽

Event Location ◽

Systematic Biases ◽

Predicted Values ◽

Test Ban

Abstract The prototype International Data Center (PIDC) in Arlington, Virginia, has been developing and testing software and procedures for use in the verification of the Comprehensive Test Ban Treaty. After three years of operation with a global network of array and three-component stations, it has been possible to characterize various systematic biases of those stations that are designated in the Treaty as part of the International Monitoring System (IMS). These biases include deviations of azimuth and slowness measurements from predicted values, caused largely by lateral heterogeneity. For events recorded by few stations, azimuth and slowness are used in addition to arrival-time data for location by the PIDC. Corrections to teleseismic azimuth and slowness observations have been empirically determined for most IMS stations providing data to the PIDC. Application of these corrections is shown to improve signal association and event location. At some stations an overall systematic bias can be ascribed to local crustal structure or to unreported instrumental problems. The corrections have been applied in routine operation of the PIDC since February 1998.

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Machine Learning Approach to Classify Rain Type Based on Thies Disdrometers and Cloud Observations

Atmosphere ◽

10.3390/atmos10050251 ◽

2019 ◽

Vol 10 (5) ◽

pp. 251 ◽

Cited By ~ 4

Author(s):

Wael Ghada ◽

Nicole Estrella ◽

Annette Menzel

Keyword(s):

Machine Learning ◽

Geographical Location ◽

Classification Performance ◽

Classification Methods ◽

Reference Dataset ◽

Machine Learning Classification ◽

Machine Learning Approach ◽

Different Types ◽

Microstructure Parameters

Rain microstructure parameters assessed by disdrometers are commonly used to classify rain into convective and stratiform. However, different types of disdrometer result in different values for these parameters. This in turn potentially deteriorates the quality of rain type classifications. Thies disdrometer measurements at two sites in Bavaria in southern Germany were combined with cloud observations to construct a set of clear convective and stratiform intervals. This reference dataset was used to study the performance of classification methods from the literature based on the rain microstructure. We also explored the possibility of improving the performance of these methods by tuning the decision boundary. We further identified highly discriminant rain microstructure parameters and used these parameters in five machine-learning classification models. Our results confirm the potential of achieving high classification performance by applying the concepts of machine learning compared to already available methods. Machine-learning classification methods provide a concrete and flexible procedure that is applicable regardless of the geographical location or the device. The suggested procedure for classifying rain types is recommended prior to studying rain microstructure variability or any attempts at improving radar estimations of rain intensity.

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Mirrors for Space Telescopes: Degradation Issues

Applied Sciences ◽

10.3390/app10217538 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7538

Author(s):

Denis Garoli ◽

Luis V. Rodriguez De Marcos ◽

Juan I. Larruquert ◽

Alain J. Corso ◽

Remo Proietti Zaccaria ◽

...

Keyword(s):

Far Infrared ◽

Space Missions ◽

Low Earth Orbit ◽

Electromagnetic Spectrum ◽

X Rays ◽

Space Telescopes ◽

Coating Materials ◽

Sounding Rockets ◽

Operational Life ◽

Extreme Uv

Mirrors are a subset of optical components essential for the success of current and future space missions. Most of the telescopes for space programs ranging from earth observation to astrophysics and covering the whole electromagnetic spectrum from x-rays to far-infrared are based on reflective optics. Mirrors operate in diverse and harsh environments that range from low-earth orbit to interplanetary orbits and deep space. The operational life of space observatories spans from minutes (sounding rockets) to decades (large observatories), and the performance of the mirrors within the mission lifetime is susceptible to degrading, resulting in a drop in the instrument throughput, which in turn affects the scientific return. Therefore, the knowledge of potential degradation mechanisms, how they affect mirror performance, and how to prevent them is of paramount importance to ensure the long-term success of space telescopes. In this review, we report an overview of current mirror technology for space missions with a focus on the importance of the degradation and radiation resistance of coating materials. Special attention is given to degradation effects on mirrors for far and extreme UV, as in these ranges the degradation is enhanced by the strong absorption of most contaminants.

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Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

Electronics ◽

10.3390/electronics9030462 ◽

2020 ◽

Vol 9 (3) ◽

pp. 462 ◽

Cited By ~ 1

Author(s):

Boni García ◽

Francisco Gortázar ◽

Micael Gallego ◽

Andrew Hines

Keyword(s):

Packet Loss ◽

Ground Truth ◽

Subjective Analysis ◽

Audio Quality ◽

Full Reference ◽

Opinion Score ◽

Different Types ◽

Audiovisual Quality ◽

Video And Audio

WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of different objective Full-Reference (FR) models for video and audio in WebRTC applications. FR models calculate the video and audio quality by comparing some original media reference with the degraded signal. To compute these models, we have created an open-source benchmark in which different types of reference media inputs are sent browser to browser while simulating different kinds of network conditions in terms of packet loss and jitter. Our benchmark provides recording capabilities of the impairment WebRTC streams. Then, we use different existing FR metrics for video (VMAF, VIFp, SSIM, MS-SSIM, PSNR, PSNR-HVS, and PSNR-HVS-M) and audio (PESQ, ViSQOL, and POLQA) recordings together with their references. Moreover, we use the same recordings to carry out a subjective analysis in which real users rate the video and audio quality using a Mean Opinion Score (MOS). Finally, we calculate the correlations between the objective and subjective results to find the objective models that better correspond with the subjective outcome, which is considered the ground truth QoE. We find that some of the studied objective models, such as VMAF, VIFp, and POLQA, show a strong correlation with the subjective results in packet loss scenarios.

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