• Title/Summary/Keyword: root-mean-square error

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Estimation of Atmospheric Turbulent Fluxes by the Bulk Transfer Method over Various Surface (다양한 지표면 위에서 총체 전달 방법에 의한 대기 난류 플럭스 추정)

  • Kim, Min-Seong;Kwon, Byung-Hyuk;Kang, Dong-Hwan
    • Journal of Environmental Science International
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    • v.23 no.6
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    • pp.1199-1211
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    • 2014
  • The momentum flux and the sensible heat flux were measured with the scintillometers and ultrasonic anemometers at 6 sites of which surface characteristics like roughness length and zero-displacement are different each other. We estimated the momentum flux and the sensible heat flux based on the bulk transfer method with the drag coefficient and the heat transfer coefficient calculated from the temperature and wind speed at two heights. The variation of bulk transfer coefficients showed a remarkable difference depending on the atmospheric stability which is less influenced by the zero-displacement than the roughness length. The estimated sensible heat fluxes were in good agreement with those measured at 3 m, showing 23.7 $Wm^{-2}$ of the root mean square error that is less than 10% of its maximum. Since the estimated momentum flux is not only effected by drag coefficient but also by wind speed square, the determination of wind speed in the bulk transfer method is critical.

Effect of Grandmother-Mother Relationship on Grandmother-Grandchildren Ties: Focusing on the Mediating Effect of Coparenting (조모-어머니 관계질이 조모-손자녀 유대감에 미치는 영향: 공동양육의 매개효과를 중심으로)

  • Choi, Hye-Jeong;An, Jeong-Shin
    • Human Ecology Research
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    • v.58 no.2
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    • pp.149-161
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    • 2020
  • This study showed that the association between grandmother-mother relationship and grandmother-grandchildren ties is mediated by the coparenting. Participants consisted of 329 grandmothers who were rearing preschool aged grandchildren in the Seoul and Gyeonggido area. SPSS 23.0 performed descriptive statistical analysis and correlation analysis. The structural equation model was estimated with AMOS 23.0. Parameters were estimated using the maximum likelihood method. Model fit index used the chi-square statistic, the goodness of fit index (GFI), the Turker-Lewis index (TLI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA). The mediation effect analysis followed a two-step verification process; direct and indirect effect. In addition, statistical significance of the indirect effect was examined using a bootstrapping procedure. The results are as follows. First, a positive correlation was found between the grandmother-mother relationship, grandmother-grandchildren ties, and coparenting. Second, the association between grandmother-mother relationship and grandmother-grandchildren ties is mediated by coparenting. The results of this study suggest that the quality of the grandmother's relationship with mothers and cooperative coparenting is important to building relationships with grandchildren. In addition, coparenting can be an important mechanism for grandmother-mother relationships and grandmother-grandchild ties. Based on the results of this study, we discussed ways to improve the grandmothers' relationship quality with the mother and strengthen parenting ability.

Design and performance evaluation of portable electronic nose systems for freshness evaluation of meats II - Performance analysis of electronic nose systems by prediction of total bacteria count of pork meats (육류 신선도 판별을 위한 휴대용 전자코 시스템 설계 및 성능 평가 II - 돈육의 미생물 총균수 예측을 통한 전자코 시스템 성능 검증)

  • Kim, Jae-Gone;Cho, Byoung-Kwan
    • Korean Journal of Agricultural Science
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    • v.38 no.4
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    • pp.761-767
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    • 2011
  • The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

Accuracy of Data-Model Fit Using Growing Levels of Invariance Models

  • Almaleki, Deyab A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.157-164
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    • 2021
  • The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘2) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.

Spatio-temporal soil moisture estimation using water cloud model and Sentinel-1 synthetic aperture radar images (Sentinel-1 SAR 위성영상과 Water Cloud Model을 활용한 시공간 토양수분 산정)

  • Chung, Jeehun;Lee, Yonggwan;Kim, Sehoon;Jang, Wonjin;Kim, Seongjoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.28-28
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    • 2022
  • 본 연구는 용담댐유역을 포함한 금강 유역 상류 지역을 대상으로 Sentinel-1 SAR (Synthetic Aperture Radar) 위성영상을 기반으로 한 토양수분 산정을 목적으로 하였다. Sentinel-1 영상은 2019년에 대해 12일 간격으로 수집하였고, 영상의 전처리는 SNAP (SentiNel Application Platform)을 활용하여 기하 보정, 방사 보정 및 Speckle 보정을 수행하여 VH (Vertical transmit-Horizontal receive) 및 VV (Vertical transmit-Vertical receive) 편파 후방산란계수로 변환하였다. 토양수분 산정에는 Water Cloud Model (WCM)이 활용되었으며, 모형의 식생 서술자(Vegetation descriptor)는 RVI (Radar Vegetation Index)와 NDVI (Normalized Difference Vegetation Index)를 활용하였다. RVI는 Sentinel-1 영상의 VH 및 VV 편파자료를 이용해 산정하였으며, NDVI는 동기간에 대해 10일 간격으로 수집된 Sentinel-2 MSI (MultiSpectral Instrument) 위성영상을 활용하여 산정하였다. WCM의 검정 및 보정은 한국수자원공사에서 제공하는 10 cm 깊이의 TDR (Time Domain Reflectometry) 센서에서 실측된 6개 지점의 토양수분 자료를 수집하여 수행하였으며, 매개변수의 최적화는 비선형 최소제곱(Non-linear least square) 및 PSO (Particle Swarm Optimization) 알고리즘을 활용하였다. WCM을 통해 산정된 토양수분은 피어슨 상관계수(Pearson's correlation coefficient)와 평균제곱근오차(Root mean square error)를 활용하여 검증을 수행할 예정이다.

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A Study for The Accuracy Assessment Method of Satellite Sensor Modeling (위성영상 센서모형화의 정확도 평가방법에 관한 연구)

  • Ko, Hyun-Soo;Choi, Chul-Soon;Hong, Jae-Min;Yoon, Chang-Rak
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.2 s.32
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    • pp.79-84
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    • 2005
  • Recent researches about the accuracy assessment of the satellite sensor modeling usually focused on the quantitative analysis of errors. Quantitative error analysis contains its limitation that the distribution property of error can not be analyzed. The numerical evaluation of result of the satellite sensor modeling drop its confidence because of the absence of the distribution property of error. This study can be presented the distribution property of error to calculate RMSE and direction-coefficient of error. Moreover, Direction-coefficient which is closed to 1 s contains systematic errors. On the contrary, direction-coefficient which is closed to the zero contains random errors. To analyse the direction of errors, we will indicate that a formula is reduced the error.

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Phase Error Decrease Method for Target Direction Detection Improvement (표적 방향 탐지 향상을 위한 위상 오차 감소 방법)

  • Lee, Min-Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.1
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    • pp.7-13
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    • 2021
  • This paper proposes a method to minimize the target's direction detection error using RADAR. The radar system cannot accurately detect the target direction due to the phase error of he received signal. The proposed method of this study obtains a phase by applying an root mean square to each antenna incident signal, and reduces the phase error by using an optimal signal to noise ratio. In the simulation result, the probability of detecting the target direction is the best when the antenna spacing is half wavelength. The conventional method of direction detection probability 10-1.7 and the proposed method is 10-3.3. The target detection direction of the existing method represents [-8°,8°] with an error of 2 degrees. The target detection direction of the proposed method is shown in [-10°,10°], and all target directions are accurately detected. In the future, There is need for a method to reduce the phase error even though the resolution decrease.

Optimization of Soil Contamination Distribution Prediction Error using Geostatistical Technique and Interpretation of Contributory Factor Based on Machine Learning Algorithm (지구통계 기법을 이용한 토양오염 분포 예측 오차 최적화 및 머신러닝 알고리즘 기반의 영향인자 해석)

  • Hosang Han;Jangwon Suh;Yosoon Choi
    • Economic and Environmental Geology
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    • v.56 no.3
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    • pp.331-341
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    • 2023
  • When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.

A Ku-Band 5-Bit Phase Shifter Using Compensation Resistors for Reducing the Insertion Loss Variation

  • Chang, Woo-Jin;Lee, Kyung-Ho
    • ETRI Journal
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    • v.25 no.1
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    • pp.19-24
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    • 2003
  • This paper describes the performance of a Ku-band 5-bit monolithic phase shifter with metal semiconductor field effect transistor (MESFET) switches and the implementation of a ceramic packaged phase shifter for phase array antennas. Using compensation resistors reduced the insertion loss variation of the phase shifter. Measurement of the 5-bit phase shifter with a monolithic microwave integrated circuit demonstrated a phase error of less than $7.5{\circ}$ root-mean-square (RMS) and an insertion loss variation of less than 0.9 dB RMS for 13 to 15 GHz. For all 32 states of the developed 5-bit phase shifter, the insertion losses were $8.2{\pm}1.4$dB, the input return losses were higher than 7.7 dB, and the output return losses were higher than 6.8 dB for 13 to 15 GHz. The chip size of the 5- bit monolithic phase shifter with a digital circuit for controlling all five bits was 2.35 mm ${\times}$1.65 mm. The packaged phase shifter demonstrated a phase error of less than $11.3{\circ}$ RMS, measured insertion losses of 12.2 ${\pm}$2.2 dB, and an insertion loss variation of 1.0 dB RMS for 13 to 15 GHz. For all 32 states, the input return losses were higher than 5.0 dB and the output return losses were higher than 6.2 dB for 13 to 15 GHz. The size of the packaged phase shifter was 7.20 mm${\times}$ 6.20 mm.

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A Feasibility Test on the DGPS by Correction Projection Using MSAS Correction

  • Yoon, Dong Hwan;Park, Byungwoon;Yun, Ho;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
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    • v.3 no.1
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    • pp.25-30
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    • 2014
  • Differential Global Positioning System-Correction Projection (DGPS-CP) algorithm, which has been suggested as a method of correcting pre-calculated position error by projecting range-domain correction to positional domain, is a method to improve the accuracy performance of a low price GPS receiver to 1 to 3 m, which is equivalent to that of DGPS, just by using a software program without changing the hardware. However, when DGPS-CP algorithm is actually realized, the error is not completely eliminated in a case where a reference station does not provide correction of some satellites among the visible satellites used in user positioning. In this study, the problem of decreased performance due to the difference in visible satellites between a user and a reference station was solved by applying the Multifunctional Transport Satellites (MTSAT) based Augmentation System (MASA) correction to DGPS-CP, instead of local DGPS correction, by using the Satellite Based Augmentation System (SBAS) operated in Japan. The experimental results showed that the accuracy was improved by 25 cm in the horizontal root mean square (RMS) and by 20 cm in the vertical RMS in comparison to that of the conventional DGPS-CP.