scholarly journals Sources of uncertainties and artifacts in back-projection results

2019 ◽  
Author(s):  
Zeng Hongyu ◽  
Wei Shengji ◽  
Wu Wenbo
Keyword(s):  
High Frequency ◽  
Synthetic Data ◽  
Water Layer ◽  
Focal Mechanisms ◽  
Coda Waves ◽  
Back Projection ◽  
Common Procedure ◽  
Frequency Dependent ◽  
Synthetic Test ◽  
The Impact

Summary Back-projecting high-frequency (HF) waves is a common procedure for imaging rupture processes of large earthquakes (i.e. Mw > 7.0). However, obtained back-projection (BP) results could suffer from large uncertainties since high-frequency seismic waveforms are strongly affected by factors like source depth, focal mechanisms, and the Earth's 3D velocity structures. So far, these uncertainties have not been thoroughly investigated. Here, we use synthetic tests to investigate the influencing factors for which scenarios with various source and/or velocity set-ups are designed, using either Tohoku-Oki (Japan), Kaikoura (New Zealand), Java/Wharton Basin (Indonesia) as test areas. For the scenarios, we generate either 1D or 3D teleseismic synthetic data, which are then back-projected using a representative BP method, MUltiple SIgnal Classification (MUSIC). We also analyze corresponding real cases to verify the synthetic test results. The Tohoku-Oki scenario shows that depth phases of a point source can be back-projected as artifacts at their bounce points on the earth's surface, with these artifacts located far away from the epicenter if earthquakes occur at large depths, which could significantly contaminate BP images of large intermediate-depth earthquakes. The Kaikoura scenario shows that for complicated earthquakes, composed of multiple sub-events with varying focal mechanisms, BP tends to image sub-events emanating large amplitude coherent waveforms, while missing sub-events whose P nodal directions point to the arrays, leading to discrepancies either between BP images from different arrays, or between BP images and other source models. Using the Java event, we investigate the impact of 3D source-side velocity structures. The 3D bathymetry together with a water layer can generate strong and long-lasting coda waves, which are mirrored as artifacts far from the true source location. Finally, we use a Wharton Basin outer-rise event to show that the wavefields generated by 3D near trench structures contain frequency-dependent coda waves, leading to frequency-dependent BP results. In summary, our analyses indicate that depth phases, focal mechanism variations, and 3D source-side structures can affect various aspects of BP results. Thus, we suggest that target-oriented synthetic tests, for example, synthetic tests for subduction earthquakes using more realistic 3D source-side velocity structures, should be conducted to understand the uncertainties and artifacts before we interpret detailed BP images to infer earthquake rupture kinematics and dynamics.

Global Algorithmic Capital Markets

2018 ◽  
Keyword(s):  
Public Policy ◽  
Capital Markets ◽  
Systemic Risk ◽  
High Frequency ◽  
Investor Protection ◽  
High Frequency Trading ◽  
Market Making ◽  
Market Governance ◽  
Policy Objectives ◽  
The Impact

This book illustrates and assesses the dramatic recent transformations in capital markets worldwide and the impact of those transformations. ‘Market making’ by humans in centralized markets has been replaced by supercomputers and algorithmic high frequency trading operating in often highly fragmented markets. How do recent market changes impact on core public policy objectives such as investor protection, reduction of systemic risk, fairness, efficiency, and transparency in markets? The operation and health of capital markets affect all of us and have profound implications for equality and justice in society. This unique set of chapters by leading scholars, industry insiders, and regulators sheds light on these and related questions and discusses ways to strengthen market governance for the benefit of society at large.

scholarly journals Crisis Management in Higher Education in the Time of Covid-19: The Case of Actor Training

2021 ◽  
Vol 11 (3) ◽  
pp. 132
Author(s):  
Anna McNamara
Keyword(s):  
Higher Education ◽  
Crisis Management ◽  
High Frequency ◽  
High Reliability ◽  
Actor Training ◽  
Management Actions ◽  
The Usa ◽  
The Uk ◽  
The Impact ◽  
High Frequency Words

The impact of Covid-19 placed Higher Education leadership in a state of crisis management, where decision making had to be swift and impactful. This research draws on ethea of mindfulness, actor training techniques, referencing high-reliability organisations (HRO). Interviews conducted by the author with three leaders of actor training conservatoires in Higher Education institutions in Australia, the UK and the USA reflect on crisis management actions taken in response to the impact of Covid-19 on their sector, from which high-frequency words are identified and grouped thematically. Reflecting on these high-frequency words and the thematic grouping, a model of mindful leadership is proposed as a positive tool that may enable those in leadership to recognise and respond efficiently to wider structural frailties within Higher Education, with reference to the capacity of leaders to operate with increased mindfulness, enabling a more resilient organisation that unlocks the locus of control.

scholarly journals Adversarial Data Augmentation on Breast MRI Segmentation

2021 ◽  
Vol 11 (10) ◽  
pp. 4554
Author(s):  
João F. Teixeira ◽  
Mariana Dias ◽  
Eva Batista ◽  
Joana Costa ◽  
Luís F. Teixeira ◽  
...  
Keyword(s):  
Data Augmentation ◽  
Medical Image Analysis ◽  
Synthetic Data ◽  
Breast Mri ◽  
Semantic Segmentation ◽  
Adversarial Networks ◽  
Augmentation Strategy ◽  
Magnetic Resonance Imaging Mri ◽  
Segmentation Task ◽  
The Impact

The scarcity of balanced and annotated datasets has been a recurring problem in medical image analysis. Several researchers have tried to fill this gap employing dataset synthesis with adversarial networks (GANs). Breast magnetic resonance imaging (MRI) provides complex, texture-rich medical images, with the same annotation shortage issues, for which, to the best of our knowledge, no previous work tried synthesizing data. Within this context, our work addresses the problem of synthesizing breast MRI images from corresponding annotations and evaluate the impact of this data augmentation strategy on a semantic segmentation task. We explored variations of image-to-image translation using conditional GANs, namely fitting the generator’s architecture with residual blocks and experimenting with cycle consistency approaches. We studied the impact of these changes on visual verisimilarity and how an U-Net segmentation model is affected by the usage of synthetic data. We achieved sufficiently realistic-looking breast MRI images and maintained a stable segmentation score even when completely replacing the dataset with the synthetic set. Our results were promising, especially when concerning to Pix2PixHD and Residual CycleGAN architectures.

The Obesity Paradox in Emergency General Surgery Patients

2021 ◽  
pp. 000313482096852
Author(s):  
Sean R. Maloney ◽  
Caroline E. Reinke ◽  
Abdelrahman A. Nimeri ◽  
Sullivan A. Ayuso ◽  
A. Britton Christmas ◽  
...  
Keyword(s):  
General Surgery ◽  
Multivariable Analysis ◽  
Operative Management ◽  
Chronic Obstructive ◽  
High Morbidity ◽  
Emergency General Surgery ◽  
Common Procedure ◽  
Increased Risk ◽  
Social Security Death Index ◽  
The Impact

Operative management of emergency general surgery (EGS) diagnoses involves a range of procedures which can carry high morbidity and mortality. Little is known about the impact of obesity on patient outcomes. The aim of this study was to examine the association between body mass index (BMI) >30 kg/m2 and mortality for EGS patients. We hypothesized that obese patients would have increased mortality rates. A regional integrated health system EGS registry derived from The American Association for the Surgery of Trauma EGS ICD-9 codes was analyzed from January 2013 to October 2015. Patients were stratified into BMI categories based on WHO classifications. The primary outcome was 30-day mortality. Longer-term mortality with linkage to the Social Security Death Index was also examined. Univariate and multivariable analyses were performed. A total of 60 604 encounters were identified and 7183 (11.9%) underwent operative intervention. Patient characteristics include 53% women, mean age 58.2 ± 18.7 years, 64.2% >BMI 30 kg/m2, 30.2% with chronic obstructive pulmonary disease, 19% with congestive heart failure, and 31.1% with diabetes. The most common procedure was laparoscopic cholecystectomy (36.4%). Overall, 90-day mortality was 10.9%. In multivariable analysis, all classes of obesity were protective against mortality compared to normal BMI. Underweight patients had increased risk of inpatient (OR = 1.9, CI = 1.7-2.3), 30-day (OR = 1.9, CI = 1.7-2.1), 90-day (OR = 1.8, CI 1.6-2.0), 1-year (OR = 1.8, CI = 1.7-2.0), and 3-year mortality (OR = 1.7, CI = 1.6-1.9). When stratified by BMI, underweight EGS patients have the highest odds of death. Paradoxically, obesity appears protective against death, even when controlling for potentially confounding factors. Increased rates of nonoperative management in the obese population may impact these findings.

High-Frequency and Passive Radar Designs for Homeland Security Applications

2011 ◽  
Vol 45 (3) ◽  
pp. 111-119 ◽  
Author(s):  
Magdy F. Iskander ◽  
Zhengqing Yun ◽  
Nuri Celik ◽  
Hyoungsun Youn ◽  
Nobutaka Omaki ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Homeland Security ◽  
High Frequency ◽  
Beam Steering ◽  
Antenna System ◽  
Hf Radar ◽  
Passive Radar ◽  
High Definition ◽  
Security Applications ◽  
The Impact

AbstractEmerging homeland security applications require low-cost and fast, deployable, high-frequency (HF) radar systems and the ability to operate in challenging terrain environments. With the need to cover as many border and coastal areas as possible, taking advantages of available transmitter resources to track targets using passive radar technologies is yet another area of research of considerable interest. In this paper, we describe the development of an HF radar system that meets these operational challenges, and we also highlight some recent implementation of the passive radar technology for homeland security applications. Specifically, we describe the design of a novel, electrically small HF antenna system consisting of three helical elements, one connected to the feed port while the other two are folded arms terminated with switchable loads. The antenna is 0.90-m (<3 feet) high with a small ground disk of 0.60 m (∼2 feet) diameter. The antenna is self-resonant at multiple frequencies (5.7, 16, 20.5, and 27.7 MHz) and with input impedance values that can be easily matched to a 50-Ω coaxial feed. Values of the electrical size ka range from 0.44 at 30 MHz down to 0.08 at 5.7 MHz. The achieved bandwidths range from 1.4% up to 12% and associated efficiencies range from 66.2% to 76% within the HF band (3‐30 MHz). As for the operational requirement in challenging terrain environments, a setup in a hilltop-type environment with a slope terrain and surface roughness was considered. A propagation modeling and ray-tracing approach was used to evaluate the impact of such terrain conditions on the effective interelement spacing of an HF radar antenna array and the subsequent impact on its beamforming and beam steering performance. It is shown that while the effect of the slope on the effective interelement spacing of the array could be very significant, diffraction effects from surface roughness resulted in a much smaller, but significant, error of about 18°. Results from some initial work on the implementation of passive radar technology, with focus on addressing the bandwidth requirement to ensure practical resolution values, are also described. It is shown that signals from wide-band transmitters (e.g., High Definition Television [HDTV] signals) rather than those from radio stations are required to provide acceptable range resolution. These as well as simulation and experimental results of the antenna design, and results from beamforming simulations illustrating the effect of a rough hilltop terrain on the HF radar performance are described.

scholarly journals Multi-Scale Spatiotemporal Change Characteristics Analysis of High-Frequency Disturbance Forest Ecosystem Based on Improved Spatiotemporal Cube Model

2021 ◽  
Vol 13 (13) ◽  
pp. 2537
Author(s):  
Yangcen Zhang ◽  
Xiangnan Liu ◽  
Meiling Liu ◽  
Xinyu Zou ◽  
Qian Zhang ◽  
...  
Keyword(s):  
High Frequency ◽  
Forest Ecosystems ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Anthropogenic Factors ◽  
Residential Areas ◽  
Short Term ◽  
Spatiotemporal Changes ◽  
Spatiotemporal Scales ◽  
The Impact

High-frequency disturbance forest ecosystems undergo complex and frequent changes at various spatiotemporal scales owing to natural and anthropogenic factors. Effectively capturing the characteristics of these spatiotemporal changes from satellite image time series is a powerful and practical means for determining their causes and predicting their trends. Herein, we combined the spatiotemporal cube and vegetation indices to develop the improved spatiotemporal cube (IST-cube) model. We used this to acquire the spatiotemporal dynamics of forest ecosystems from 1987 to 2020 in the study area and then classified it into four spatiotemporal scales. The results showed that the cube-core only exists in the increasing IST-cubes, which are distributed in residential areas and forests. The length of the IST-cube implies the duration of triggers. Human activities result in long-term small-scope IST-cubes, and the impact in the vicinity of residential areas is increasing while there is no change within. Meteorological disasters cause short-term, large scope, and irregular impacts. Land use type change causes short-term small scope IST-cubes and a regular impact. Overall, we report the robustness and strength of the IST-cube model in capturing spatiotemporal changes in forest ecosystems, providing a novel method to examine complex changes in forest ecosystems via remote sensing.

Does time-varying illiquidity matter for the Indian stock market? Evidence from high-frequency data

2021 ◽  
pp. 031289622110102
Author(s):  
Mousumi Bhattacharya ◽  
Sharad Nath Bhattacharya ◽  
Sumit Kumar Jha
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
High Frequency ◽  
Jel Classification ◽  
Exogenous Shock ◽  
Intraday Data ◽  
Day Of The Week ◽  
Holiday Effects ◽  
Indian Stock Market ◽  
The Impact

This article examines variations in illiquidity in the Indian stock market, using intraday data. Panel regression reveals prevalent day-of-the-week, month, and holiday effects in illiquidity across industries, especially during exogenous shock periods. Illiquidity fluctuations are higher during the second and third quarters. The ranking of most illiquid stocks varies, depending on whether illiquidity is measured using an adjusted or unadjusted Amihud measure. Using pooled quantile regression, we note that illiquidity plays an important asymmetric role in explaining stock returns under up- and down-market conditions in the presence of open interest and volatility. The impact of illiquidity is more severe during periods of extreme high and low returns. JEL Classification: G10, G12

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