Mitigating the Impact of Azimuthal Sampling on the Strength of Radar-Observed Circulations

2020 ◽  
Vol 37 (6) ◽  
pp. 1103-1116
Author(s):  
Feng Nai ◽  
Sebastián Torres ◽  
Christopher Curtis
Keyword(s):  
Computational Complexity ◽  
Rotational Velocity ◽  
Real Data ◽  
Radar Data ◽  
Sampling Interval ◽  
Severe Thunderstorms ◽  
Key Factor ◽  
Data Points ◽  
Circulation Velocity ◽  
The Impact

AbstractSevere thunderstorms and their associated tornadoes pose significant threats to life and property, and using radar data to accurately measure the rotational velocity of circulations in thunderstorms is essential for appropriate, timely warnings. One key factor in accurately measuring circulation velocity is the azimuthal spacing between radar data points, which is referred to as the azimuthal sampling interval. Previous studies have shown that reducing the azimuthal sampling interval can aid in measuring circulation velocity; however, this comes at the price of increased computational complexity. Thus, choosing the best compromise requires knowledge of the relationship between the radar azimuthal sampling interval and the accuracy of the circulation strength as measured from the radar data. In this work, we use simulations to quantify the impact of azimuthal sampling on the strength of radar-observed circulations and show that the improvements get progressively smaller as the azimuthal sampling interval decreases. Thus, improved characterization of circulations can be achieved without using the finest possible sampling grid. We use real data to validate the results of the simulations, which can be used to inform the selection of an appropriate azimuthal sampling interval that balances the accuracy of the radar-observed circulations and computational complexity.

scholarly journals Impact of the Environmental Low-Level Wind Profile on Ensemble Forecasts of the 4 May 2007 Greensburg, Kansas, Tornadic Storm and Associated Mesocyclones

2012 ◽  
Vol 140 (2) ◽  
pp. 696-716 ◽  
Author(s):  
Daniel T. Dawson II ◽  
Louis J. Wicker ◽  
Edward R. Mansell ◽  
Robin L. Tanamachi
Keyword(s):  
Wind Profile ◽  
Radar Data ◽  
Ensemble Forecasts ◽  
Microphysics Scheme ◽  
Low Level ◽  
Severe Thunderstorms ◽  
Probabilistic Forecasts ◽  
Forecast Lead Time ◽  
Wind Profiles ◽  
The Impact

The early tornadic phase of the Greensburg, Kansas, supercell on the evening of 4 May 2007 is simulated using a set of storm-scale (1-km horizontal grid spacing) 30-member ensemble Kalman filter (EnKF) data assimilation and forecast experiments. The Next Generation Weather Radar (NEXRAD) level-II radar data from the Dodge City, Kansas (KDDC), Weather Surveillance Radar-1988 Doppler (WSR-88D) are assimilated into the National Severe Storms Laboratory (NSSL) Collaborative Model for Multiscale Atmospheric Simulation (COMMAS). The initially horizontally homogeneous environments are initialized from one of three reconstructed soundings representative of the early tornadic phase of the storm, when a low-level jet (LLJ) was intensifying. To isolate the impact of the low-level wind profile, 0–3.5-km AGL wind profiles from Vance Air Force Base, Oklahoma (KVNX), WSR-88D velocity-azimuth display (VAD) analyses at 0130, 0200, and 0230 UTC are used. A sophisticated, double-moment bulk ice microphysics scheme is employed. For each of the three soundings, ensemble forecast experiments are initiated from EnKF analyses at various times prior to and shortly after the genesis of the Greensburg tornado (0200 UTC). Probabilistic forecasts of the mesocyclone-scale circulation(s) are generated and compared to the observed Greensburg tornado track. Probabilistic measures of significant rotation and observation-space diagnostic statistics are also calculated. It is shown that, in general, the track of the Greensburg tornado is well predicted, and forecasts improve as forecast lead time decreases. Significant variability is also seen across the experiments using different VAD wind profiles. Implications of these results regarding the choice of initial mesoscale environment, as well as for the “Warn-on-Forecast” paradigm for probabilistic numerical prediction of severe thunderstorms and tornadoes, are discussed.

Competition Policy under Economic Crisis

2009 ◽  
pp. 54-69 ◽  
Author(s):  
A. Shastitko ◽  
S. Avdasheva ◽  
S. Golovanova
Keyword(s):  
Division Of Labor ◽  
Economic Crisis ◽  
Industrial Policy ◽  
Competition Policy ◽  
Transition Economy ◽  
Economic Recession ◽  
Price Rigidity ◽  
Key Factor ◽  
Policy Measures ◽  
The Impact

The analysis of competition policy under economic crisis is motivated by the fact that competition is a key factor for the level of productivity. The latter, in its turn, influences the scope and length of economic recession. In many Russian markets buyers' gains decline because of the weakness of competition, since suppliers are reluctant to cut prices in spite of the decreasing demand. Data on prices in Russia and abroad in the second half of 2008 show asymmetric price rigidity. At least two questions are important under economic crisis: the 'division of labor' between pro-active and protective tools of competition policy and the impact of anti-crisis policy on competition. Protective competition policy is insufficient in transition economy, especially in the days of crisis it should be supplemented with the well-designed industrial policy measures which do not contradict the goals of competition. The preferable tools of anti-crisis policy are also those that do not restrain competition.

Designing a CRM Framework for online & offline sports footwear retailers

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Rodrigo Cueva ◽  
Guillem Rufian ◽  
Maria Gabriela Valdes
Keyword(s):  
Environmental Changes ◽  
Customer Relationship ◽  
Business Strategies ◽  
Economic Sectors ◽  
Running Shoes ◽  
Brick And Mortar ◽  
Key Factor ◽  
On Line ◽  
The Impact

The use of Customer Relationship Managers to foster customers loyalty has become one of the most common business strategies in the past years.  However, CRM solutions do not fill the abundance of happily ever-after relationships that business needs, and each client’s perception is different in the buying process.  Therefore, the experience must be precise, in order to extend the loyalty period of a customer as much as possible. One of the economic sectors in which CRM’s have improved this experience is retailing, where the personalized attention to the customer is a key factor.  However, brick and mortar experiences are not enough to be aware in how environmental changes could affect the industry trends in the long term.  A base unified theoretical framework must be taken into consideration, in order to develop an adaptable model for constructing or implementing CRMs into companies. Thanks to this approximation, the information is complemented, and the outcome will increment the quality in any Marketing/Sales initiative. The goal of this article is to explore the different factors grouped by three main domains within the impact of service quality, from a consumer’s perspective, in both on-line and off-line retailing sector.  Secondly, we plan to go a step further and extract base guidelines about previous analysis for designing CRM’s solutions focused on the loyalty of the customers for a specific retailing sector and its product: Sports Running Shoes.

Spatial Interpolators for Intra-Frame Resampling of SAR Videos: A Comparative Study Using Real-Time HD, Medical and Radar Data

2020 ◽  
Vol 15 (2) ◽  
pp. 144-196 ◽  
Author(s):  
Mohammad R. Khosravi ◽  
Sadegh Samadi ◽  
Reza Mohseni
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Video Compression ◽  
Nearest Neighbor ◽  
Radar Data ◽  
Edge Preservation ◽  
Edge Information ◽  
Video Codecs ◽  
Comparative Results ◽  
Interesting Area

Background: Real-time video coding is a very interesting area of research with extensive applications into remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14. Materials and Methods: In this article, an evaluation of some techniques with different complexity orders for video compression problem is performed. All compared techniques are based on interpolation algorithms in spatial domain. In details, the acquired data is according to four different interpolators in terms of computational complexity including fixed weights quartered interpolation (FWQI) technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They are used for the compression of some HD color videos in real-time applications, real frames of video synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample. Results: Comparative results are also described for three different metrics including two reference- based Quality Assessment (QA) measures and an edge preservation factor to achieve a general perception of various dimensions of the mentioned problem. Conclusion: Comparisons show that there is a decidable trade-off among video codecs in terms of more similarity to a reference, preserving high frequency edge information and having low computational complexity.

Correlation of Altmetric Attention Scores with Citations in Major Pharmacy Journals (Preprint)

2018 ◽  
Author(s):  
Dave L Dixon ◽  
William L Baker
Keyword(s):  
Citation Count ◽  
Cross Sectional Study ◽  
Scientific Output ◽  
Cross Sectional ◽  
Promotion And Tenure ◽  
Article Type ◽  
Key Factor ◽  
Number Of Citations ◽  
The Impact

BACKGROUND The impact and quality of a faculty members publications is a key factor in promotion and tenure decisions and career advancement. Traditional measures, including citation counts and journal impact factor, have notable limitations. Since 2010, alternative metrics have been proposed as another means of assessing the impact and quality of scholarly work. The Altmetric Attention Score is an objective score frequently used to determine the immediate reach of a published work across the web, including news outlets, blogs, social media, and more. Several studies evaluating the correlation between the Altmetric Attention Score and number of citations have found mixed results and may be discipline-specific. OBJECTIVE To determine the correlation between higher Altmetric Attention Scores and citation count for journal articles published in major pharmacy journals. METHODS This cross-sectional study evaluated articles from major pharmacy journals ranked in the top 10% according to the Altmetric Attention Score. Sources of attention that determined the Altmetric Attention Score were obtained, as well each articles open access status, article type, study design, and topic. Correlation between journal characteristics, including the Altmetric Attention Score and number of citations, was assessed using the Spearman’s correlation test. A Kruskal-Wallis 1-way analysis of variance (ANOVA) was used to compare the Altmetric Attention Scores between journals. RESULTS Six major pharmacy journals were identified. A total of 1,376 articles were published in 2017 and 137 of these represented the top 10% with the highest Altmetric Attention Scores. The median Altmetric Attention Score was 19 (IQR 15-28). Twitter and Mendeley were the most common sources of attention. Over half (56.2%) of the articles were original investigations and 49.8% were either cross-sectional, qualitative, or cohort studies. No significant correlation was found between the Altmetric Attention Score and citation count (rs=0.07, P = 0.485). Mendeley was the only attention source that correlated with the number of citations (rs=0.486, P<0.001). The median Altmetric Attention Score varied widely between each journal (P<0.001). CONCLUSIONS The overall median Altmetric Attention score of 19 suggests articles published in major pharmacy journals are near the top 5% of all scientific output. However, we found no correlation between the Altmetric Attention Score and number of citations for articles published in major pharmacy journals in the year 2017.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

scholarly journals Robust Filtering Techniques for RTK Positioning in Harsh Propagation Environments

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1250
Author(s):  
Daniel Medina ◽  
Haoqing Li ◽  
Jordi Vilà-Valls ◽  
Pau Closas
Keyword(s):  
Intelligent Transportation Systems ◽  
Robust Statistics ◽  
Real Data ◽  
Transportation Systems ◽  
Global Navigation Satellite Systems ◽  
Mixed Integer ◽  
Robust Filtering ◽  
Precise Positioning ◽  
The Impact ◽  
Filtering Techniques

Global navigation satellite systems (GNSSs) play a key role in intelligent transportation systems such as autonomous driving or unmanned systems navigation. In such applications, it is fundamental to ensure a reliable precise positioning solution able to operate in harsh propagation conditions such as urban environments and under multipath and other disturbances. Exploiting carrier phase observations allows for precise positioning solutions at the complexity cost of resolving integer phase ambiguities, a procedure that is particularly affected by non-nominal conditions. This limits the applicability of conventional filtering techniques in challenging scenarios, and new robust solutions must be accounted for. This contribution deals with real-time kinematic (RTK) positioning and the design of robust filtering solutions for the associated mixed integer- and real-valued estimation problem. Families of Kalman filter (KF) approaches based on robust statistics and variational inference are explored, such as the generalized M-based KF or the variational-based KF, aiming to mitigate the impact of outliers or non-nominal measurement behaviors. The performance assessment under harsh propagation conditions is realized using a simulated scenario and real data from a measurement campaign. The proposed robust filtering solutions are shown to offer excellent resilience against outlying observations, with the variational-based KF showcasing the overall best performance in terms of Gaussian efficiency and robustness.

scholarly journals An adaptive social distancing SIR model for COVID-19 disease spreading and forecasting

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Said Gounane ◽  
Yassir Barkouch ◽  
Abdelghafour Atlas ◽  
Mostafa Bendahmane ◽  
Fahd Karami ◽  
...  
Keyword(s):  
Mathematical Theory ◽  
Real Data ◽  
Sir Model ◽  
Epidemic Threshold ◽  
Social Distancing ◽  
Sir Epidemic ◽  
Proposed Model ◽  
Disease Spreading ◽  
The Government ◽  
The Impact

Abstract Recently, various mathematical models have been proposed to model COVID-19 outbreak. These models are an effective tool to study the mechanisms of coronavirus spreading and to predict the future course of COVID-19 disease. They are also used to evaluate strategies to control this pandemic. Generally, SIR compartmental models are appropriate for understanding and predicting the dynamics of infectious diseases like COVID-19. The classical SIR model is initially introduced by Kermack and McKendrick (cf. (Anderson, R. M. 1991. “Discussion: the Kermack–McKendrick Epidemic Threshold Theorem.” Bulletin of Mathematical Biology 53 (1): 3–32; Kermack, W. O., and A. G. McKendrick. 1927. “A Contribution to the Mathematical Theory of Epidemics.” Proceedings of the Royal Society 115 (772): 700–21)) to describe the evolution of the susceptible, infected and recovered compartment. Focused on the impact of public policies designed to contain this pandemic, we develop a new nonlinear SIR epidemic problem modeling the spreading of coronavirus under the effect of a social distancing induced by the government measures to stop coronavirus spreading. To find the parameters adopted for each country (for e.g. Germany, Spain, Italy, France, Algeria and Morocco) we fit the proposed model with respect to the actual real data. We also evaluate the government measures in each country with respect to the evolution of the pandemic. Our numerical simulations can be used to provide an effective tool for predicting the spread of the disease.

scholarly journals A Person-to-Person and Person-to-Place COVID-19 Contact Tracing System Based on OGC IndoorGML

2020 ◽  
Vol 10 (1) ◽  
pp. 2 ◽  
Author(s):  
Soroush Ojagh ◽  
Sara Saeedi ◽  
Steve H. L. Liang
Keyword(s):  
Data Model ◽  
Low Cost ◽  
Large Body ◽  
Contact Tracing ◽  
Trajectory Data ◽  
Sequential Order ◽  
Human Contact ◽  
Wide Availability ◽  
Data Points ◽  
The Impact

With the wide availability of low-cost proximity sensors, a large body of research focuses on digital person-to-person contact tracing applications that use proximity sensors. In most contact tracing applications, the impact of SARS-CoV-2 spread through touching contaminated surfaces in enclosed places is overlooked. This study is focused on tracing human contact within indoor places using the open OGC IndoorGML standard. This paper proposes a graph-based data model that considers the semantics of indoor locations, time, and users’ contexts in a hierarchical structure. The functionality of the proposed data model is evaluated for a COVID-19 contact tracing application with scalable system architecture. Indoor trajectory preprocessing is enabled by spatial topology to detect and remove semantically invalid real-world trajectory points. Results show that 91.18% percent of semantically invalid indoor trajectory data points are filtered out. Moreover, indoor trajectory data analysis is innovatively empowered by semantic user contexts (e.g., disinfecting activities) extracted from user profiles. In an enhanced contact tracing scenario, considering the disinfecting activities and sequential order of visiting common places outperformed contact tracing results by filtering out unnecessary potential contacts by 44.98 percent. However, the average execution time of person-to-place contact tracing is increased by 58.3%.

scholarly journals Exploring the Effects of Problematic Internet Use on Adolescent Sleep: A Systematic Review

2021 ◽  
Vol 18 (2) ◽  
pp. 760
Author(s):  
Ioulia Kokka ◽  
Iraklis Mourikis ◽  
Nicolas C. Nicolaides ◽  
Christina Darviri ◽  
George P. Chrousos ◽  
...  
Keyword(s):  
Internet Use ◽  
Educational Interventions ◽  
The Body ◽  
Problematic Internet Use ◽  
Affecting Factors ◽  
Physical And Mental Health ◽  
Adolescent Sleep ◽  
Key Factor ◽  
Parental Educational Level ◽  
The Impact

Adolescent suse internet via several devices to gather information or communicate. Sleep, as a key factor of adolescents’ development, contributes to their physical and mental health. Over the past decades insufficient sleep among adolescents has been wide spread, and one of its attributing factors is the increased availability of technology. This review aims to investigate the body of evidence regarding the impact of problematic internet use on adolescent sleep. Extensive search of databases was performed according to PRISMA guidelines for studies published within the last decade, regarding subjects aged 10–19. The final step of the search yielded 12 original studies. The quality of extracted data was evaluated with the AXIS tool, in order to estimate the risk of bias. All studies showed a negative correlation between adolescent sleep and problematic internet use. It was found to affect sleep quality and quantity and provoke insomnia symptoms. Interestingly, adolescent’s sex, parental educational level, type of family and use for leisure or academic reasons appeared as affecting factors of the problematic internet use-sleep relationship. Problematic internet use has several effects on adolescents’ sleep. Results of relevant studies should be embedded in educational interventions addressed to adolescents as well as parents, to eliminate the negative outcomes of problematic internet use on sleep and adolescence’s health in general.

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