scholarly journals Validation of Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) Data in Wonorejo Reservoir, Indonesia

2021 ◽  
Vol 930 (1) ◽  
pp. 012042
Author(s):  
S Wahyuni ◽  
D Sisinggih ◽  
I A G Dewi
Keyword(s):  
Data Quality ◽  
Measurement Data ◽  
Strong Relationship ◽  
Precipitation Data ◽  
Quality Test ◽  
Validity Test ◽  
Precipitation Measurement ◽  
Study Results ◽  
Stationary Test ◽  
Corrected Data

Abstract This study aims to test the validation of precipitation data from CHIRPS compared to measurement data. The study location is Wonorejo Reservoir, Indonesia. The methods in this research were 1) data quality test with the consistency test and stationary test, and 2) validity test with parameters of NSE value and correlation. The study results show that 1) The data quality test shows that the precipitation data from CHIRPS are consistent and homogeneous; 2) The validity test is carried out in two stages, for uncorrected data and corrected data. According to NSE value, the validity of test results on uncorrected data shows that CHIRPS’s precipitation data are unsatisfactory. When viewed from the correlation, the precipitation data from CHIRPS has a very strong relationship to precipitation measurement data. The next step is to test the validity of the corrected data. The validation test of corrected data shows that precipitation data from CHIRPS is satisfactory according to NSE value. Moreover, the precipitation data from CHIRPS strongly correlates with the precipitation measurement data. This study indicates that the precipitation data from CHIRPS can be utilized as alternative precipitation data if measurement data are limited.

Marketing China to U.S. travelers through electronic word-of-mouth and destination image: Taking Beijing as an example

2021 ◽  
pp. 135676672098786
Author(s):  
Li Ran ◽  
Luo Zhenpeng ◽  
Anil Bilgihan ◽  
Fevzi Okumus
Keyword(s):  
Quantitative Research ◽  
Behavioral Control ◽  
Strong Relationship ◽  
Tourism Industry ◽  
Destination Image ◽  
Perceived Behavioral Control ◽  
Online Data ◽  
Mediating Role ◽  
Study Results ◽  
The Impact

The tourism industry in China has grown significantly over the last two decades. Most of the growth, however, is fueled by domestic tourism. As one of the biggest tourism markets in the world, U.S. tourists might be reluctant to travel to China due to reasons such as unfamiliarity, cultural differences, visa requirements, and long flights. Building on the Theory of Planned Behavior (TPB) with relevant constructs, this research proposes that building a strong destination image via eWOM may influence the attitude and intention of U.S. travelers to visit Beijing. More specifically, the current research aims to examine the impact of eWOM and destination image on travel intention of tourists. This study used a quantitative research method and online data collection was conducted through Qualtrics. A total of 413 valid responses from U.S. residents were collected. The statistical software SPSS 21.0 and Mplus 7.0 were used to analyze the data. Study results show a strong relationship between eWOM utilitarian function and eWOM credibility, and eWOM credibility has a significant influence on destination image. Although there was no direct impact of destination image on tourists’ future travel intention, destination image plays a mediating role between eWOM credibility and perceived behavioral control (and tourists’ attitudes as well). Finally, perceived behavioral control and tourists’ attitudes mediate the impact of destination image on travel intention.

Preliminary analysis and main problems of instrumental measurement complex at the Vernadsky Antarctic Station

2021 ◽  
Author(s):  
Denys Pishniak ◽  
Svitlana Krakovska ◽  
Anastasia Chyhareva ◽  
Sergii Razumnyi
Keyword(s):  
Measurement Data ◽  
Bias Reduction ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Monthly Precipitation ◽  
Polar Regions ◽  
Indirect Methods ◽  
Precipitation Measurement ◽  
Precipitation Gauge ◽  
The Antarctic

<p>Measurements of precipitation has always had well known difficulties that caused inaccuracies. This is especially acute in Polar regions where prevailing solid precipitation is accomplished with strong winds. Alternatively some indirect methods of precipitation measurements still in development and numerous meteorological instruments have been created on their basis.</p><p>The Akademik Vernadsky station is located in the Antarctic Peninsula region with a large amount of precipitation and  the problem of its measuring has always been relevant here. Although the data of monthly precipitation have been found for Vernadsky (Faraday) station since 1964, the first standard Tretyakov precipitation gauge was set up there only in 1997. But in recent years, several new instruments for indirect precipitation measurement have been installed at the meteorological site. The consistency of their data are the subject for this study. </p><p>Direct comparison of all measurement devices as well as investigation of their estimations dependencies from other meteorological parameters are analysed and will be presented for the period 2019-2020. Originally various instruments showed huge differences in precipitation estimates. Deep analysis and correction of the measurement results according to weather conditions is obviously needed for bias reduction. But the local features of the extremely heterogeneous underlying surface of the region affect the vertical component of the wind, and can cause the natural small scale precipitation variability. </p><p>The advantages of indirect methods for precipitation measuring is a high sensitivity to registering even individual falling precipitation particles and, hence, the really high temporal resolution of the data. Therefore, it can be used for investigation of physical atmospheric processes. As an example, the case study of a cyclone with precipitation phase transition over Vernadsky station on December 5-6, 2020 is investigated and will be presented. A comparison of the measurement data of various devices (Tretyakov Precipitation Gauge, Snow Stick, Vaisala PWD22, Lufft WS100, METEK MRR-PRO) and the ERA-5 reanalysis was carried out. A vertical radar MRR-PRO is of special interest as a measuring instrument for polar regions because it can ignore surface snow transport and has proved reliability in the Antarctic environment recently. In Marine Antarctica this device can identify the height of precipitation melting and also show a number of other useful parameters. This complex of precipitation measurement instruments is planned to be used in the frames of the forthcoming YOPP-SH field campayne.</p>

A Methodology to Assure Measurement Data Quality for Key Engineering Materials

2010 ◽  
Vol 108-111 ◽  
pp. 972-978
Author(s):  
Ying Su ◽  
Jing Hua Huang ◽  
Latif Al-Hakim
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Measurement Data ◽  
Limited Attention ◽  
Decision Making Process ◽  
Precision Determination ◽  
Accuracy And Precision ◽  
Process Documentation ◽  
Engineering Materials

Purpose – Only limited attention has been paid to the issue of Measurement Data Quality (MDQ) in a metrology context. To address this critique of the literature a methodology to assure MDQ was proposed. Methodology – The study proposes a methodology which consists of four steps can be used to 1 identify the importance of a measurement (identification), 2 determine accuracy and precision (determination), 3 evaluate the criticality of the measurement to its impact on the final result (evaluation) and 4 record the facts that influenced the decision making process (documentation). Findings –When followed and properly documented, these four steps can help ensure our measurements are valid and worthwhile. Identifying the important measurements that are made, determining the level of accuracy required and then using the proper tools to make the measurements will yield valid, useful results.

scholarly journals Quality-Based Combination of Multi-Source Precipitation Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1709 ◽  
Author(s):  
Anna Jurczyk ◽  
Jan Szturc ◽  
Irena Otop ◽  
Katarzyna Ośródka ◽  
Piotr Struzik
Keyword(s):  
Spatial Resolution ◽  
Flash Flood ◽  
Radar Data ◽  
Rain Gauge ◽  
Quality Information ◽  
Precipitation Data ◽  
Spatial Error ◽  
Rain Gauges ◽  
Precipitation Measurement ◽  
Temporal And Spatial

A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their very high temporal and spatial resolution. Other sources of precipitation data, such as telemetric rain gauges and satellite observations, are also included in the QPE. All of the used data are characterized by different temporal and spatial error structures. Therefore, a combination of the data should be based on quality information quantitatively determined for each input to take advantage of a particular source of precipitation measurement. The presented work on multi-source QPE, being implemented as the RainGRS system, has been carried out in the Polish national meteorological and hydrological service for new nowcasting and hydrological platforms in Poland. For each of the three data sources, different quality algorithms have been designed: (i) rain gauge data is quality controlled and, on this basis, spatial interpolation and estimation of quality field is performed, (ii) radar data are quality controlled by RADVOL-QC software that corrects errors identified in the data and characterizes its final quality, (iii) NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short Range Forecasting) products for both visible and infrared channels are combined and the relevant quality field is determined from empirical relationships that are based on analyses of the product performance. Subsequently, the quality-based QPE is generated with a 1-km spatial resolution every 10 minutes (corresponding to radar data). The basis for the combination is a conditional merging technique that is enhanced by involving detailed quality information that is assigned to individual input data. The validation of the RainGRS estimates was performed taking account of season and kind of precipitation.

scholarly journals Economic Aspects of the Missing Data Problem – the Case of the Patient Registry

2017 ◽  
Vol 65 (5) ◽  
pp. 1779-1791
Author(s):  
Hatice Uenal ◽  
David Hampel
Keyword(s):  
Missing Data ◽  
Data Quality ◽  
Quality Analysis ◽  
Quality Of Data ◽  
Quality Costs ◽  
Missing Data Problem ◽  
Study Results ◽  
The Cost ◽  
Cost Factors

Registries are indispensable in medical studies and provide the basis for reliable study results for research questions. Depending on the purpose of use, a high quality of data is a prerequisite. However, with increasing registry quality, costs also increase accordingly. Considering these time and cost factors, this work is an attempt to estimate the cost advantages of applying statistical tools to existing registry data, including quality evaluation. Results for quality analysis showed that there are unquestionable savings of millions in study costs by reducing the time horizon and saving on average € 523,126 for every reduced year. Replacing additionally the over 25 % missing data in some variables, data quality was immensely improved. To conclude, our findings showed dearly the importance of data quality and statistical input in avoiding biased conclusions due to incomplete data.

scholarly journals A REVIEW OF DATA GOVERNANCE MATURITY LEVEL IN HIGHER EDUCATION

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Hanung Nindito Prasetyo
Keyword(s):  
Higher Education ◽  
Quality Management ◽  
Data Quality ◽  
Measurement Data ◽  
Measurement Model ◽  
Activity Measurement ◽  
Maturity Level ◽  
Data Governance ◽  
Data Quality Management ◽  
Measurement Mechanism

Data governance in organization is unique. Every organization has a form of data governance in accordance with their respective needs. In some literature most of the industry, build data governance program based on the needs of data quality in achieving the company's goals. Some research have shown that data quality management is the foundation of data governance development in the industry. Although the data quality management is an important foundation, but in the development of the industry show the form of data governance that vary according to the needs and interests of the company. To see the effectiveness that data governance has been implemented well in an organization, it is needed a measurement mechanism of maturity level. However, to determine whether the measurements were carried out in accordance with the organization's goals, it will be require a clear base in determining the dimensions of the measurement. This research tried to describe the dimensions of which will be used during the activity measurement data governance maturity level within an organization. The measurement model used as a reference is the IBM data governance and DAMA International.

scholarly journals Quality Control of Precipitation Measurement for Selected Stations in Iraq

2020 ◽  
Vol 30 (4) ◽  
pp. 10
Author(s):  
Ali Jawad Jaafar ◽  
Alaa Motar Al-Lami
Keyword(s):  
Quality Control ◽  
The Other ◽  
Research Quality ◽  
Data Series ◽  
Control Procedure ◽  
Precipitation Data ◽  
Homogeneity Tests ◽  
Significance Level ◽  
Pettitt Test ◽  
Precipitation Measurement

In this research, quality control and homogeneity tests were performed for 20 surface meteorological stations records in Iraq. For this purpose, the annual precipitation data series at the stations of Iraqi meteorological organizations and seismology for the period (1981-2010) were considered. Quality control procedure involving outlier detection using Mandel’s k method. Homogenization were analyzed by using four absolute methods tests namely SNH test, Pettitt test, BR test and VNR test, these tests were chosen to detect the inhomogeneity in data, the results of each test were evaluated at significance level 0.05. Results of Mandel’s K methodwere classified into four categories (Normal, Abnormal 1, Abnormal 2 and Extreme) and represented in GIS software.The results showed that 5% of station classified as Normal, 20% of stations classified as Abnormal 1, 25% of stations classified as Extreme and 50% of stations were classified as Abnormal 2. The homogeneity tests results displayed that 5% of station assigned as “doubtful” class with break years found in (1998) for (Pettitt and BR) tests, 50% of stations assigned as “useful” class , and the other stations which represent 45% assigned as “suspect” class with break years detected for (Pettitt, SNH and BR) tests most found in (1998 ad 1999) were represents 28% of break years, 21% of break years found in (1997) and other break years found between (1991-2004).

scholarly journals Deep Learning Semantic Segmentation for Water Level Estimation Using Surveillance Camera

2021 ◽  
Vol 11 (20) ◽  
pp. 9691
Author(s):  
Nur Atirah Muhadi ◽  
Ahmad Fikri Abdullah ◽  
Siti Khairunniza Bejo ◽  
Muhammad Razif Mahadi ◽  
Ana Mijic
Keyword(s):  
Deep Learning ◽  
Water Level ◽  
River Water ◽  
Correlation Coefficient ◽  
Rank Order ◽  
Measurement Data ◽  
Strong Relationship ◽  
Semantic Segmentation ◽  
Water Levels ◽  
Surveillance Systems

The interest in visual-based surveillance systems, especially in natural disaster applications, such as flood detection and monitoring, has increased due to the blooming of surveillance technology. In this work, semantic segmentation based on convolutional neural networks (CNN) was proposed to identify water regions from the surveillance images. This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. Overall, both networks attained high accuracy when compared to the measurement data but the DeepLabv3+ network performed better than the SegNet network, achieving over 90% for overall accuracy and IoU metrics, and around 80% for boundary F1 score (BF score), respectively. When predicting new images using both trained networks, the results show that both networks successfully distinguished water regions from the background but the outputs from DeepLabv3+ were more accurate than the results from the SegNet network. Therefore, the DeepLabv3+ network was used for practical application using a set of images captured at five consecutive days in the study area. The segmentation result and water level markers extracted from light detection and ranging (LiDAR) data were overlaid to estimate river water levels and observe the water fluctuation. River water levels were predicted based on the elevation from the predefined markers. The proposed water level framework was evaluated according to Spearman’s rank-order correlation coefficient. The correlation coefficient was 0.91, which indicates a strong relationship between the estimated water level and observed water level. Based on these findings, it can be concluded that the proposed approach has high potential as an alternative monitoring system that offers water region information and water level estimation for flood management and related activities.

scholarly journals The relationship between sprint performance and both lower and upper extremity explosive strength in young soccer players

2021 ◽  
Vol 25 (1) ◽  
pp. 10-14
Author(s):  
Gürken Diker ◽  
Sürhat Müniroğlu ◽  
Sadi Ön ◽  
Hüseyin Özkamçı ◽  
Abdulkerim Darendeli
Keyword(s):  
Upper Extremity ◽  
Team Sports ◽  
Strong Relationship ◽  
Sprint Performance ◽  
Soccer Players ◽  
Training Experience ◽  
Jump Performance ◽  
Explosive Strength ◽  
Study Results ◽  
The Relationship

Background and Study Aim. Sprint performance plays a major role in success of field-based team sports such as soccer. The aim of this study was to evaluate the relationship between sprinting performance and both lower and upper extremity explosive strength in young soccer players. Material and Methods. One hundred forty-seven soccer players (mean±SD; age 11.6±1.66 years, height 143.2±11.8 cm, body mass 37.1±10.2 kg and training experience 1.11±1.5 years) voluntarily participated in this study. The sprinting performance of each player was determined using their 5, 10, 20 and 30m single sprint times. The lower and upper extremity explosive strength were evaluated by standing long jump and medicine ball throwing tests respectively. Prior to the study, each of the players was given detailed information about the risks and injuries they could encounter during the study, and parental consent was obtained by their signatures on informed voluntary consent forms since the subjects were under the age of 18. Permission to conduct the study was obtained from Ankara University Medical Faculty’s Surgical and Medical Research Ethics Committee. Results. The results indicated a strong relationship between sprinting performance and horizontal jump performance (r=-.671 ̶ -.764; p=0.001) and also a large relationship between sprinting performance and upper extremity strength (r=-.633  ̶  -.703; p=0.001). The sprint performance (n=147) also significantly correlated with body weight (r=-.345  ̶  -.373; p=0.001) and height (r=-.445  ̶  -.505; p=0.001). Conclusions. The study results suggest that upper extremity strength is as important as the lower extremity strength for sprinting performance and that trainers should emphasize lower and upper extremity strength in training intended to improve sprinting performance.

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