• Title/Summary/Keyword: Sampling Errors

Search Result 341, Processing Time 0.031 seconds

RAINFALL SEASONALITY AND SAMPLING ERROR VARIATION

  • Yoo, Chul-sang
    • Water Engineering Research
    • /
    • v.2 no.1
    • /
    • pp.63-72
    • /
    • 2001
  • The variation of sampling errors was characterized using the Waymire-Gupta-Rodriguez-Iturbe multi-dimensional rainfall model(WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considered are those for using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of monthly rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather normal to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain arean than in the down stream plain area.

  • PDF

Determination of Sampling Points Based on Curvature distribution (곡률 기반의 측정점 결정 알고리즘 개발)

  • 박현풍;손석배;이관행
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • 2000.11a
    • /
    • pp.295-298
    • /
    • 2000
  • In this research, a novel sampling strategy for a CMM to inspect freeform surfaces is proposed. Unlike primitive surfaces, it is not easy to determine the number of sampling points and their locations for inspecting freeform surfaces. Since a CMM operates with slower speed in measurement than optical measuring devices, it is important to optimize the number and the locations of sampling points in the inspection process. When a complete inspection of a surface is required, it becomes more critical. Among various factors to cause shape errors of a final product, curvature characteristic is essential due to its effect such as stair-step errors in rapid prototyping and interpolation errors in NC tool paths generation. Shape errors are defined in terms of the average and standard deviation of differences between an original model and a produced part. Proposed algorithms determine the locations of sampling points by analyzing curvature distribution of a given surface. Based on the curvature distribution, a surface area is divided into several sub-areas. In each sub-area, sampling points are located as further as possible. The optimal number of sub-areas. In each sub-area, sampling points are located as further as possible. The optimal number os sub-areas is determined by estimating the average of curvatures. Finally, the proposed method is applied to several surfaces that have shape errors for verification.

  • PDF

Sampling Error Variation due to Rainfall Seasonality

  • Yoo, Chulsang
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2001.05a
    • /
    • pp.7-14
    • /
    • 2001
  • In this study, we characterized the variation of sampling errors using the Waymire-Gupta-rodriguez-Iturbe multi-dimensional rainfall model (WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considering in this study are those far using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of mentally rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather norma1 to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain area than in the down stream plain area.

  • PDF

Determination of Soil Sample Size Based on Gy's Particulate Sampling Theory (Gy의 입자성 물질 시료채취이론에 근거한 토양 시료 채취량 결정)

  • Bae, Bum-Han
    • Journal of Soil and Groundwater Environment
    • /
    • v.16 no.6
    • /
    • pp.1-9
    • /
    • 2011
  • A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

SAMPLING ERROR ANALYSIS FOR SOIL MOISTURE ESTIMATION

  • Kim, Gwang-Seob;Yoo, Chul-sang
    • Water Engineering Research
    • /
    • v.1 no.3
    • /
    • pp.209-222
    • /
    • 2000
  • A spectral formalism was applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. The lack of temporal measurements of the two-dimensional soil moisture field makes it difficult to compute the spectra directly from observed records. Therefore, the space-time soil moisture spectra derived by stochastic models of rainfall and soil moisture was used in their record. Parameters for both models were tuned with Southern Great Plains Hydrology Experiment(SGP'97) data and the Oklahoma Mesonet data. The structure of soil moisture data is discrete in space and time. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has the advantage in its general form applicable for all kinds of sampling designs. Sampling errors of the soil moisture estimation during the SGP'97 Hydrology Experiment period were estimated. The sampling errors for various sampling designs such as satedlite over pass and point measurement ground probe were estimated under the climate condition between June and August 1997 and soil properties of the SGP'97 experimental area. The ground truth design was evaluated to 25km and 50km spatial gap and the temporal gap from zero to 5 days.

  • PDF

On the Sampling and Transport of Radioactive Aerosols from Waste Thermal Process

  • Yang, Hee-Chul;Kim, Joon-Hyung;Yong Kang
    • Nuclear Engineering and Technology
    • /
    • v.29 no.4
    • /
    • pp.269-279
    • /
    • 1997
  • The errors associated with incorrect sampling and transport of radioactive aerosol from radwaste thermal process off-gas are analyzed and the conditions of representative sampling and correct transport of radioactive aerosol for off-gas system evaluation are discussed. An estimation method of sampling errors for individual radionuclides is proposed and applied to simulated vitrification melter aerosols. Prediction methods for particle deposition in sample transport tube under laminar as well as turbulent flow conditions are also described by example calculations with simulated incinerator off-gas From the results of example calculations and plots, instrumental and operational conditions of radioactive aerosol sampling system with minimized errors and correction methods for nonideal sampling and transport are recommended.

  • PDF

An Improved Second-odrer Sampling Method for Digital Beam Forming in Ultrasound Imaging Systems (초음파 영상 시스템에서 디지탈 Beam Forming을 위한 개선된 2차 샘플링 방법)

  • 조완희;안영복
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.32B no.1
    • /
    • pp.110-119
    • /
    • 1995
  • The lateral resolution in an ultrasound imaging system is one of the most important factors for quality of the image and is determined by the beam focusing. For the better lateral resolution SDF(Sampled Delay Focusing) capable of digital focusing was proposed. The second-order sampling, one of band-width sampling methods, is suggested as being the best suitable for SDF because it allows total digital processing and is simple and economical. By proving that it introduces too much error, this article shows the second-order sampling is not appropriate for sampling of the wide-band signal generally used in ultrasound imaging systems. Also, this article suggests new sampling methods that maintain the advantages and reduce the unavoidable errors of the second-order sampling method. From computer simulation it is expected that the proposed methods reduce the errors of the second-order sampling method and can be used in real applications.

  • PDF

Standardization of Sample Handling Methods to Reduce the Rate of Inadequate Sampling

  • Yo-Han Seo
    • Quality Improvement in Health Care
    • /
    • v.29 no.2
    • /
    • pp.85-93
    • /
    • 2023
  • Purpose: The predominant approach for mitigating inadequate sampling rates has primarily involved bolstering the volume of education. This study aimed to curtail inadequate sampling rates through the implementation of continuous quality improvement (CQI) activities, tailoring effective methods to the unique needs of each institution. Methods: We developed a sample handling guidebook and implemented QI activities to address this issue. Results: These measures resulted in a 4.7% decrease in inadequate sampling rates, concurrently improving knowledge of sample handling and overall nurse satisfaction. We addressed the root causes of inadequate sampling before laboratory pre-processing by: 1) focusing on systematic rather than erratic errors through CQI activities, 2) revising the sample handling guide, and 3) delivering face-to-face education based on the specific needs of the nursing department. These changes resulted in an additional 0.6% decrease in the inadequate sampling rate. Conclusion: This study demonstrates that the implementation of CQI activities based on evidence derived from a multifaceted causal analysis significantly reduced the inadequate sampling rate compared to previous studies.

Effect Analysis of Sample Size and Sampling Periods on Accuracy of Reliability Estimation Methods for One-shot Systems using Multiple Comparisons (다중비교를 이용한 샘플수와 샘플링 시점수의 원샷 시스템 신뢰도 추정방법 정확성에 대한 영향 분석)

  • Son, Young-Kap
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.15 no.4
    • /
    • pp.435-441
    • /
    • 2012
  • This paper provides simulation-based results of effect analysis of sample size and sampling periods on accuracy of reliability estimation methods using multiple comparisons with analysis of variance. Sum of squared errors in estimated reliability measures were evaluated through applying seven estimation methods for one-shot systems to simulated quantal-response data. Analysis of variance was implemented to investigate change in these errors according to variations of sample size and sampling periods for each estimation method, and then the effect analysis on accuracy in reliability estimation was performed using multiple comparisons based on sample size and sampling periods. An efficient way to allocate both sample size and sampling periods for reliability estimation tests of one-shot systems is proposed in this paper from the effect analysis results.