scholarly journals Uncertainty Analysis of Two Copula-Based Conditional Regional Design Flood Composition Methods: A Case Study of Huai River, China

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1872 ◽  
Author(s):  
Shiyu Mou ◽  
Peng Shi ◽  
Simin Qu ◽  
Xiaomin Ji ◽  
Lanlan Zhao ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Design Flood ◽  
Sampling Uncertainty ◽  
Composition Methods ◽  
Conditional Copula ◽  
Huai River ◽  
Composition Point ◽  
The Impact ◽  
Regional Design ◽  
Uncertainty Source

The issue of regional design flood composition should be considered when it comes to the analysis of multiple sections. However, the uncertainty accompanied in the process of regional design flood composition point identification is often overlooked in the literature. The purpose of this paper, therefore, is to uncover the sensibility of marginal distribution selection and the impact of sampling uncertainty caused by the limited records on two copula-based conditional regional design flood composition methods, i.e., the conditional expectation regional design flood composition (CEC) method and the conditional most likely regional design flood composition (CMLC) method, which are developed to derive the combinations of maximum 30-day flood volumes at the two sub-basins above Bengbu hydrological station for given univariate return periods. An experiment combing different marginal distributions was conducted to explore the former uncertainty source, while a conditional copula-based parametric bootstrapping (CC-PB) procedure together with five metrics (i.e., horizontal standard deviation, vertical standard deviation, area of 25%, 50%, 75% BCIs (bivariate confidence intervals)) were designed and employed subsequently to evaluate the latter uncertainty source. The results indicated that the CEC and CMLC point identification was closely bound up with the different combinations of univariate distributions in spite of the comparatively tiny difference of the fitting performances of seven candidate univariate distributions, and was greatly affected by the sampling uncertainty due to the limited observations, which should arouse critical attention. Both of the analyzed sources of uncertainty increased with the growing T (univariate return period). As for the comparison of the two proposed methods, it seemed that the uncertainty due to the marginal selection had a slight larger impact on the CEC scheme than the CMLC scheme; but in terms of sampling uncertainty, the CMLC method performed slightly stable for large floods, while when considering moderate and small floods, the CEC method performed better.

Stochastic simulation for determining the design flood of cascade reservoir systems

2012 ◽  
Vol 43 (1-2) ◽  
pp. 54-63 ◽  
Author(s):  
Baohong Lu ◽  
Huanghe Gu ◽  
Ziyin Xie ◽  
Jiufu Liu ◽  
Lejun Ma ◽  
...  
Keyword(s):  
Simulation Model ◽  
Stochastic Simulation ◽  
Southern China ◽  
Flow Simulation ◽  
Simulation Method ◽  
Simulation Approach ◽  
Design Flood ◽  
Design Values ◽  
Stochastic Simulation Model ◽  
The Impact

Stochastic simulation is widely applied for estimating the design flood of various hydrosystems. The design flood at a reservoir site should consider the impact of upstream reservoirs, along with any development of hydropower. This paper investigates and applies a stochastic simulation approach for determining the design flood of a complex cascade of reservoirs in the Longtan watershed, southern China. The magnitude of the design flood when the impact of the upstream reservoirs is considered is less than that without considering them. In particular, the stochastic simulation model takes into account both systematic and historical flood records. As the reliability of the frequency analysis increases with more representative samples, it is desirable to incorporate historical flood records, if available, into the stochastic simulation model. This study shows that the design values from the stochastic simulation method with historical flood records are higher than those without historical flood records. The paper demonstrates the advantages of adopting a stochastic flow simulation approach to address design-flood-related issues for a complex cascade reservoir system.

scholarly journals 1414. #Vaccine Twitter Influencers: is it Just About Reach and Followers?

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S714-S715
Author(s):  
Jean-Etienne Poirrier ◽  
Theodore Caputi ◽  
John Ayers ◽  
Mark Dredze ◽  
Sara Poston ◽  
...  
Keyword(s):  
United States ◽  
Social Media ◽  
Standard Deviation ◽  
Small Proportion ◽  
The United States ◽  
Research Support ◽  
Policy Makers ◽  
Media Messages ◽  
Social Media Platforms ◽  
The Impact

Abstract Background A small number of powerful users (“influencers”) dominates conversations on social media platforms: less than 1% of Twitter accounts have at least 3,000 followers and even fewer have hundreds of thousands or millions of followers. Beyond simple metrics (number of tweets, retweets...) little is known about these “influencers”, particularly in relation to their role in shaping online narratives about vaccines. Our goal was to describe influential Twitter accounts that are driving conversations about vaccines and present new metrics of influence. Methods Using publicly-available data from Twitter, we selected posts from 1-Jan-2016 to 31-Dec-2018 and extracted the top 5% of accounts tweeting about vaccines with the most followers. Using automated classifiers, we determined the location of these accounts, and grouped them into those that primarily tweet pro- versus anti-vaccine content. We further characterized the demographics of these influencer accounts. Results From 25,381 vaccine-related tweets available in our sample representing 10,607 users, 530 accounts represented the top 5% by number of followers. These accounts had on average 1,608,637 followers (standard deviation=5,063,421) and 340,390 median followers. Among the accounts for which sentiment was successfully estimated by the classifier, 10.4% (n=55) posted anti-vaccine content and 33.6% (n=178) posted pro-vaccine content. Of the 55 anti-vaccine accounts, 50% (n=18) of the accounts for which location was successfully determined were from the United States. Of the 178 pro-vaccine accounts, 42.5% (n=54) were from the United States. Conclusion This study showed that only a small proportion of Twitter accounts (A) post about vaccines and (B) have a high follower count and post anti-vaccine content. Further analysis of these users may help researchers and policy makers better understand how to amplify the impact of pro-vaccine social media messages. Disclosures Jean-Etienne Poirrier, PhD, MBA, The GSK group of companies (Employee, Shareholder) Theodore Caputi, PhD, Good Analytics Inc. (Consultant) John Ayers, PhD, GSK (Grant/Research Support) Mark Dredze, PhD, Bloomberg LP (Consultant)Good Analytics (Consultant) Sara Poston, PharmD, The GlaxoSmithKline group of companies (Employee, Shareholder) Cosmina Hogea, PhD, GlaxoSmithKline (Employee, Shareholder)

scholarly journals Political Polarization and Movie Ratings: Web Scraping The Brazilian Contemporary Scenario

2020 ◽  
Author(s):  
Bruno De Oliveira Chagas ◽  
Ana Paula Moritz
Keyword(s):  
Standard Deviation ◽  
Political Polarization ◽  
Web Scraping ◽  
Movie Ratings ◽  
The Impact

Our work aims to analyze the impact of political polarization on movieratings at the IMDB platform. For that we explore the concepts of Word ofMouth and Buzz marking the important role they play on polarized opinionsin movie ratings.We develop a code on python to perform web-scrapping onthe sample scope of Brazilian movies and interpret the data collected using acontroversiality index based on standard deviation. The outcome sheds somelight into the relation between Buzz and Controversiality within theframework of Brazil’s current political scenario.

scholarly journals Use of Massive Open Online Courses (MOOCs)  In the professional development of science teachers Jeddah

2019 ◽  
Vol 3 (10) ◽  
Author(s):  
Mounira Mohammed Al-Raghbi
Keyword(s):  
Professional Development ◽  
Standard Deviation ◽  
Science Teachers ◽  
Achievement Test ◽  
Impact Measurement ◽  
Continuous Training ◽  
Satisfaction Questionnaire ◽  
Distance Training ◽  
Strongly Agree ◽  
The Impact

    The current research aimed to identify the effectiveness of MOOCs as an electronic training platform for the professional development of science teachers in Jeddah. The researcher used the semi-experimental approach in a one-group design. The experiment was applied to the basic sample of research (30) Education East Jeddah Girls, who received the active learning course through direct training, were randomly selected unintentionally. The researcher used two tools to collect information and data related to the study: N of (20) paragraph tribal dish and Uday, in addition to a questionnaire to measure the sample satisfaction MOOCs as a platform for distance training, consisting of (48) paragraph. The data of this study were analyzed using the statistical packages of social programs (SPSS) according to the following statistical methods: arithmetical mean, standard deviation and t value for the pre-test and final test scores by t-test for two independent sample samples, Eta coefficient of impact measurement, Cronbach's Alpha coefficient for measurement of test stability, consistency of satisfaction criterion, and arithmetic averages and standard deviations of responses of study group members in the satisfaction questionnaire. The study reached several results, the most important of which are: -MOOCs achieved an efficiency level in the results of the achievement test with an average of (5.17) score for pre-test compared to (19.63) in the post-test. -The size of the calculated effect reached (0.99). This means that the size of the impact is great for the use of open source electronic courses (MOOCs) in the professional development of science teachers in Jeddah. -There is satisfaction with science teachers on the use of MOOCs in their professional development, where the mean is 4.37, indicating that there is satisfaction (strongly agree) on the questionnaire of satisfaction with the use of MOOCs as a distance training platform for the professional development of them -The standard deviation of the general arithmetic mean (0.119), which is a value and a sign of the great homogeneity between the responses of the members of the research sample (science parameters) on the expressions of satisfaction questionnaire In light of the results, the researcher presented a set of recommendations, the most important of which are: - To promote the culture of e-learning using electronic educational platforms MOOCs. - Provide open and continuous training programs for in-service teachers for their effectiveness and development. - Offering more training courses for electronic platforms carrying the specifications of MOOCs - Taking advantage of the current study tools, namely (the achievement test- the measure of satisfaction) to assess the   impact of professional development For science teachers in Jeddah.      

scholarly journals Uncertainty in runoff based on Global Climate Model precipitation and temperature data – Part 2: Estimation and uncertainty of annual runoff and reservoir yield

2014 ◽  
Vol 11 (5) ◽  
pp. 4579-4638 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) datasets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to approximate within-GCM uncertainty of monthly precipitation and temperature projections and assess its impact on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. To-date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2014) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), temperature (MAT) and runoff (MAR), the standard deviation of annual precipitation (SDP) and runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 world-wide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainty from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were: MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma procedure was applied to each annual runoff time-series for hypothetical reservoir capacities of 1× MAR and 3× MAR and the average uncertainty in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were: 25.1% (1× MAR) and 11.9% (3× MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1× MAR or 3× MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

scholarly journals Purwarupa Alat Deteksi Ketinggian Banjir Perbantuan SMS Gateway Dan Mikrontroler

INOVA-TIF ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 51
Author(s):  
Muhammad Ardi
Keyword(s):  
Detection System ◽  
Water Levels ◽  
Design Flood ◽  
Loss Of Life ◽  
Data Processor ◽  
Working Principle ◽  
Arduino Uno ◽  
Flood Elevation ◽  
Opening And Closing ◽  
The Impact

<em>Flood disasters still occur regularly and continuously in Indonesia. Flooding can occur due to the volume of water in the river beyond the river body. Many impacts caused by flooding, not only material losses, flooding can also cause loss of life. The impact of flooding can be reduced if people are better prepared to face the flood. One way is to quickly disseminate information on river water levels to the community. It is necessary to make a solution on how to design an automatic sluice using Arduino UNO R3 and how to monitor the water situation during floods. The working principle of this tool uses an ultrasonic sensor as a water level detector, Arduino as a data processor, servo motor as opening and closing the door bar automatically and the modem as an SMS notification. Because design based detection system is needed In this study there are two formulations of the problem (i) How to design flood altitude detection devices using Arduino uno r3 which can open and close automatically. (ii) How to test the flood altitude detection system using a wavecome modem. The research objective is divided into two parts (i) Creating a series of flood elevation devices using Arduino r3 so that it can open and close automatically (ii) Gets the results of flood elevation system testing with an sms gateway</em>

scholarly journals Impact of Planned Teaching Program on COVID- 19 Vaccination in Terms of Knowledge and Attitude among the People in Selected Rural Area of Nadiad Taluka

2021 ◽  
pp. 179-185
Author(s):  
Patel Shivangi ◽  
Pateliya Jahnvi ◽  
Makwana Pinal ◽  
Chavda Surbhi ◽  
Mahida Rajan ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Standard Error ◽  
Attitude Scale ◽  
T Test ◽  
Teaching Program ◽  
Chi Square ◽  
Rural People ◽  
Knowledge And Attitude ◽  
The Impact ◽  
Paired T Test

Introduction: Vaccination is intended to prevent diseases. Vaccines saves 2-3 million lives every year. A COVID-19 vaccine is one of the best way to provide acquired immunity against COVID -19. The study aims to assess the effectiveness of planned teaching program in terms of knowledge and attitude [1]. Objective: To assess the impact of planned teaching program on COVID- 19 vaccination in terms of knowledge and attitude among the rural people. Method: A quantitative study with one group pre test post test design was conducted at various rural places of Nadiad Taluka. A total 60 people were enrolled in to the study. A structured knowledge questionnaire and likert attitude scale was built that contained information regarding COVID 19 vaccination. The effect of teaching program was analyzed by statically Results: T-test and chi square test was used to find the association with selected demographic variables. In the knowledge regarding COVID-19 vaccination range was 8, mean was 0.849 standard deviation was 0.357, standard error mean was 0.0595. In the attitude range was 33, mean was 4.345, standard deviation was 0.797, standard error mean was 0.132. A knowledge paired t-test value was 5.30 and the attitude paired t-test value was 6.57 was. Conclusion: The planned teaching program was effective in increasing knowledge and attitude regarding COVID-19 vaccination among the rural people of Nadiad Taluka.

scholarly journals Absolute calibration method for frequency-modulated continuous wave (FMCW) cloud radars based on corner reflectors

2020 ◽  
Vol 13 (12) ◽  
pp. 6853-6875
Author(s):  
Felipe Toledo ◽  
Julien Delanoë ◽  
Martial Haeffelin ◽  
Jean-Charles Dupont ◽  
Susana Jorquera ◽  
...  
Keyword(s):  
Field Experiments ◽  
Continuous Wave ◽  
Intermediate Frequency ◽  
Absolute Calibration ◽  
Experimental Setup ◽  
Cloud Radar ◽  
Calibration Uncertainty ◽  
Radar Calibration ◽  
The Impact ◽  
Uncertainty Source

Abstract. This article presents a new cloud radar calibration methodology using solid reference reflectors mounted on masts, developed during two field experiments held in 2018 and 2019 at the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) atmospheric observatory, located in Palaiseau, France, in the framework of the Aerosol Clouds Trace gases Research InfraStructure version 2 (ACTRIS-2) research and innovation program. The experimental setup includes 10 and 20 cm triangular trihedral targets installed at the top of 10 and 20 m masts, respectively. The 10 cm target is mounted on a pan-tilt motor at the top of the 10 m mast to precisely align its boresight with the radar beam. Sources of calibration bias and uncertainty are identified and quantified. Specifically, this work assesses the impact of receiver compression, temperature variations inside the radar, frequency-dependent losses in the receiver's intermediate frequency (IF), clutter and experimental setup misalignment. Setup misalignment is a source of bias, previously undocumented in the literature, that can have an impact of the order of tenths of a decibel in calibration retrievals of W-band radars. A detailed analysis enabled the quantification of the importance of each uncertainty source to the final cloud radar calibration uncertainty. The dominant uncertainty source comes from the uncharacterized reference target which reached 2 dB. Additionally, the analysis revealed that our 20 m mast setup with an approximate alignment approach is preferred to the 10 m mast setup with the motor-driven alignment system. The calibration uncertainty associated with signal-to-clutter ratio of the former is 10 times smaller than for the latter. Following the proposed methodology, it is possible to reduce the added contribution from all uncertainty terms, excluding the target characterization, down to 0.4 dB. Therefore, this procedure should enable the achievement of calibration uncertainties under 1 dB when characterized reflectors are available. Cloud radar calibration results are found to be repeatable when comparing results from a total of 18 independent tests. Once calibrated, the cloud radar provides valid reflectivity values when sampling midtropospheric clouds. Thus, we conclude that the method is repeatable and robust, and that the uncertainties are precisely characterized. The method can be implemented under different configurations as long as the proposed principles are respected. It could be extended to reference reflectors held by other lifting devices such as tethered balloons or unmanned aerial vehicles.

Impacts of Leadership Styles on Motivations of Employees

2019 ◽  
pp. 205-217
Author(s):  
Irfan Ullah ◽  
Alina Kiran ◽  
Bin Liu
Keyword(s):  
Standard Deviation ◽  
Data Collection ◽  
Leadership Styles ◽  
Multiple Regression ◽  
Employee Motivation ◽  
Descriptive Statistics ◽  
Cronbach Alpha ◽  
The Impact ◽  
The Relationship ◽  
Survey Approach

The aim of this study to investigate the different leadership styles and impact on employee motivation. Leadership is the most important phenomena. Therefore, leadership plays a very important role, and this research study emphasizes the impact of leadership styles on motivation of employees. In this chapter, a survey approach using structured questionnaire was used for data collection. Questionnaire consists of four styles of leadership with employees' motivation. All constructs were measured using five-point Likert scale. Descriptive statistics and inferential were used. Mean and standard deviation and Cronbach alpha were used in descriptive statistics and correlation, and multiple regression was used for inferential regression. The aim of this chapter is to identify the relationship between leadership styles and motivation of employees.

Factors associated with mobility apprehension in persons with lower limb amputation

2020 ◽  
Vol 44 (4) ◽  
pp. 208-214
Author(s):  
Shannon L Mathis
Keyword(s):  
Standard Deviation ◽  
Lower Limb ◽  
Avoidance Behavior ◽  
Pain Catastrophizing ◽  
Lower Limb Amputation ◽  
Limb Amputation ◽  
Walking Ability ◽  
Factors Associated ◽  
The Mean ◽  
The Impact

Background: Factors that are related to mobility apprehension were measured in a sample of persons with lower-limb amputation. Objectives: The purpose was to determine whether intensity, interference, or catastrophizing are associated with mobility apprehension. Study design: Cross-sectional study. Methods: Persons with amputation of a lower limb who were attending a national limb loss conference were recruited to complete a survey. Subjects were administered the Tampa Scale for Kinesiophobia to measure mobility apprehension. The Brief Pain Inventory was administered to quantify the affect of pain on general activity, walking ability, and enjoyment of life. The Pain Catastrophizing Scale was administered to assess the tendency to ruminate and magnify pain sensations. A multivariable linear regression was performed to determine factors associated with mobility apprehension. Results: Fifty-three people with lower-limb amputation participated in the study. The mean (standard deviation) score for mobility apprehension was 34.2 (6.0). Mean (standard deviation) pain intensity and interference scores were 1.6 (1.7) and 2.5 (2.6), respectively. The mean (standard deviation) pain catastrophizing score was 9.1 (10). Pain catastrophizing was the only variable associated with higher mobility apprehension ( β = 0.31, p < 0.001, R2 = 0.32). Results suggest that for every one-point increase in the pain catastrophizing score, mobility apprehension will increase by 0.3 of a point. Conclusion: These preliminary results suggest that pain catastrophizing was related to mobility apprehension in this cohort of persons with lower-limb amputation. This relationship indicates that the exploration of avoidance behaviors, such as pain catastrophizing, may be useful when developing a program for physical rehabilitation. Clinical relevance Pain catastrophizing, an avoidance behavior, may be associated with higher levels of mobility apprehension in persons with major lower-limb amputation. Understanding the impact of fear-avoidance behavior will allow clinicians to identify individuals at risk for poor outcomes following amputation surgery and to develop psychological strategies to complement treatment.

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