• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.513-522
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• 2021

A smartphone (SMP) includes a MEMS sensor that can record 3-components motions and has a wireless network device to transmit data in live. These features and relatively low maintenance costs are the advantage of using SMPs as an auxiliary seismic observation network. Currently, 279 SMPs are monitoring seismic motions. In this study, we compare the SMP records with the seismic station (SS) records to validate SMP records. The data used for comparison are records for five earthquakes that occurred in 2019, which are 321 SS data recorded by the Korea Meteorological Administration and the Korea Institute of Geoscience and Mineral Resources and 145 recorded by SMPs. The analysis shows that the event-term corrected average residual of the SMP MEMS sensor records is 0.59 which indicating that the peak horizontal acceleration by SMP is 1.8 factor bigger than the peak ground acceleration by SS. In addition, the residuals tend to decrease as the installation floor of the smartphone MEMS sensor increases, which is the similar trend with response spectra from SS.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.66-76
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• 2019

Recently, natural disasters such as floods and droughts are frequently occurred due to climate change and the damage is also increasing. Wetland is known to play an important role in reducing and minimizing the damage. In particular, water level variability needs to be analyzed in order to understand the various functions of wetland as well as the reduction of damage caused by natural disaster. Therefore, in this study, we fitted water level series of Upo wetland in Changnyeong, Gyeongnam province to a proper time series model and residual test was performed to confirm the appropriateness of the model. In other words, ARIMA model was constructed and its residual tests were performed using existing nonparametric statistics, BDS statistic, and Close Returns Histogram(CRH). The results of residual tests were compared and especially, we showed the applicability of CRH to analyze the residuals of time series model. As a result, CRH produced not only accurate randomness test result, but also produced result in a simple calculation process compared to the other methods. Therefore, we have shown that CRH and BDS statistic can be effective tools for analyzing residual in time series model.

• Research in Vestibular Science
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• v.17 no.4
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• pp.152-159
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• 2018

Objectives: The Korean Dizziness Handicap Inventory (KDHI), which includes 25 patient-reported items, has been used to assess self-reported dizziness in Korean patients with Parkinson disease (PD). Nevertheless, few studies have examined the KDHI based on item-response theory within this population. The aim of our study was to address the feasibility and clinimetric properties of the KDHI instrument using polytomous Rasch measurement analysis. Methods: The unidimensionality, scale targeting, separation reliability, item difficulty (severity), and response category utility of the KDHI were statistically assessed based on the Andrich rating scale model. The utilities of the orderedresponse categories of the 3-point Likert scale were analyzed with reference to the probability curves of the response categories. The separation reliability of the KDHI was assessed based on person separation reliability (PSR), which is used to measure the capacity to discriminate among groups of patients with different levels of balance deficits. Results: Principal component analyses of residuals revealed that the KDHI had unidimensionality. The KHDI had satisfactory PSR and there were no disordered thresholds in the 3-point rating scale. However, the KDHI showed several issues for inappropriate scale targeting and misfit items (items 1 and 2) for Rasch model. Conclusions: The KDHI provide unidimensional measures of imbalance symptoms in patients with PD with adequate separation reliability. There was no statistical evidence of disorder in polytomous rating scales. The Rasch analysis results suggest that the KDHI is a reliable scale for measuring the imbalance symptoms in PD patients, and identified parts for possible amendments in order to further improve the linear metric scale.

• Journal of the Korean GEO-environmental Society
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• v.22 no.2
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• pp.35-39
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• 2021

Photogrammetry using drone can produce high-resolution ortho image and acquire high-accuracy 3D information, which is useful. Therefore, this study attempted to determine the possibility of using drone-photogrammetry in park construction by producing a topographic map using drone-photogrammetry and analyzing the problems and accuracy generated during production. For this purpose, we created ortho image and DSM (digital surface model) using drone images and created topographic status map by vectorizing them. Accuracy was compared based on topographic status map by GPS (global positioning system) and TS (total station). The resulting of analyzing mean of the residuals at check points showed that 0.044 m in plane and 0.066 m in elevation, satisfying the tolerance range of 1/1,000 numerical maps, and result of compared lake size showed a difference of about 4.4%. On the other hand, it was difficult to obtain accurate height values for terrain in which existed vegetation when producing the topographic map, and in the case of underground buried objects, it is not possible to confirm it in the image, so direct spatial information acquisition was necessary. Therefore, it is judged that the topographic status map using drone photogrammetry can be efficiently constructed if direct spatial data acquisition is achieved for some terrain.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.239-254
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• 2021

This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.561-571
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• 2020

Seven techniques widely used in the geodetic transformations have been reviewed and compared to figure out their theoretical characteristics. A series of numerical tests were performed about four data sets. This was followed by result analyses in terms of transformation residuals and accuracies together with some hypothesis testings based on the student-t distribution to confirm the statistical significance of the techniques. In the case of the transformation between the geodetic frames implemented in the same system, no statistical significance was revealed in the results of the 3D transformation techniques, even if the testing area becomes large as the Asia-Oceania continent. Among the 2D transformations, it was possible for the NTv2 grid modeling technique to deliver improved transformation accuracy. Finally, it was possible from the results analyzed in this study to propose the Helmert transformation to geodetic control points and the NTv2 technique to the 2D spatial data transformation of the geodetic systems.

• Animal Bioscience
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• v.35 no.5
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.630-643
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• 2022

This study was conducted to derive the fresh weight and dry weight estimation formulas of Pinus densiflora and prepare a weight table using them. Aone-variable formula using only the diameter at breast height (DBH) and a two-variable formula using DBH and height were used to calculate the fresh and dry weight. Each equation was verified using statistics, such as fit index, standard error, and residuals. Theoptimal equation was evaluated for applicability by calculating the weight as a coefficient derived from a statistical verification. W = bD+cD² was selected for the one-variable equation, while W = aD^bH^c was selected for the two-variable equation. The fit index of the former was 0.87-0.92, while that of the latter was 0.94-0.98, both of which showed a good fit. A new weight table was prepared using the optimal estimation formula, and it was compared and analyzed with a previous weight table. Analysis results showed that Gangwon pine had higher values in the previous weight table, while pines in the central region had higher values in the newly created weight table.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.315-324
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• 2022

The conventional LESS (LEast-Squares Solution) is calculated under the assumption that there is no errors in independent variables. However, the coordinates of a point, either from traditional ground surveying such as slant distances, horizontal and/or vertical angles, or GNSS (Global Navigation Satellite System) positioning, cannot be determined independently (and the components are correlated each other). Therefore, the TLS (Total Least Squares) adjustment should be applied for all applications related to the coordinates. Many approaches were suggested in order to solve this problem, resulting in equivalent solutions except some restrictions. In this study, we calculated the normal vector of the 3D plane determined by the trace of the VLBI targets based on TLS within GHM (Gauss-Helmert Model). Another numerical test was conducted for the estimation of the Helmert transformation parameters. Since the errors in the horizontal components are very small compared to the radius of the circle, the final estimates are almost identical. However, the estimated variance components are significantly reduced as well as show a different characteristic depending on the target location. The Helmert transformation parameters are estimated more precisely compared to the conventional LESS case. Furthermore, the residuals can be predicted on both reference frames with much smaller magnitude (in absolute sense).

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.