• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.335-347
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• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.87-95
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• 2020

The Incheon airport is a gateway to and from the Republic of Korea and has a great influence on the image of the country. Therefore, it is necessary to predict the number of airport passengers in the long term in order to maintain the quality of service at the airport. In this study, we compared the predictive performance of various time series models to predict the air passenger demand at Incheon Airport. From 2002 to 2019, passenger data include trend and seasonality. We considered the naive method, decomposition method, exponential smoothing method, SARIMA, PROPHET. In order to compare the capacity and number of passengers at Incheon Airport in the future, the short-term, mid-term, and long-term was forecasted by time series models. For the short-term forecast, the exponential smoothing model, which weighted the recent data, was excellent, and the number of annual users in 2020 will be about 73.5 million. For the medium-term forecast, the SARIMA model considering stationarity was excellent, and the annual number of air passengers in 2022 will be around 79.8 million. The PROPHET model was excellent for long-term prediction and the annual number of passengers is expected to be about 99.0 million in 2024.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.3
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• pp.163-172
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• 1989

In order to study spatial variability of soil physical properties accross the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs), all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil particle size distribution analysis was made at 225 intersections of $15{\times}15$ grid with 10m interval. Field capacity, bulk density and saturated hydraulic conductivity were measured in situ at 594 intersections of $33{\times}18$ grid with 2.5m interval in only $6,000m^2$ reselected from $22,500m^2$ of sampling area for particle size distribution analysis. Sampled or measured soil depths were 0 to 10cm 25 to 35cm and 50 to 60cm at each intersections. The results are summarized as follows: 1. The coefficient of variance (CV) of various physical properties ranges from 4.8 to 128.8%. Saturated hydraulic conductivity is classified into the high variation group with CV greater than 100%, while the low variation group with CV smaller than 10% consists of bulk density. Other properties belong to the medium variation group with CV between 10 and 100%. 2. The appropriate number of soil samples for the determination of various physical properties with error smaller than 10% are calculated as one for bulk density, six for field moisture capacity, 16 for silt, 19 for clay, 69 for sand and 686 for saturated hydraulic conductivity. 3. Smooth frequency distribution and fractile diagram show that saturated hydraulic conductivity is in lognormal distribution while other physical properties are in normal distribution. 4. Serial correlation analysis reveals that the soil physical properties have spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of physical properties measured between the serial grid points in the direction of south to north following section boundary shows that the zone of influence showing stationarity ranges from 7.5 to 40m. In the direction of east to west across section boundary, the autocorrelogram of many physical properties shows peaks with the periodic interval of 30m, which are similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.4
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• pp.257-264
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• 1989

In order to study spatial variability of soil chemical properties across the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs) in the experimental fie ld of the wheat and Barley Research Institute in Suwon, all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil chemical property analysis was made at 225 intersections of 15x 15 grid with 10m interval from three soil depths (0-10cm, 25-35cm, 50-60cm) in the seven patitioned fields. 1. The coefficient of variance (CV) of various chemical properties varied from 5.4 to 72.7%. Soil pH was classified into the low variation group with CV smaller than 10%, while the other chemical properties belonged to the medium variation group with C.V. between 10 and 100% 2. The approximate number of soil samples for the determination of various chemical properties with error smaller than 10% were two for pH, ten for CEC, 15 for exchangeable Ca, 32 for total nitrogen content, 39 for exchangeable Mg, 40 for exchangeable K, 61 for exchangeable Na, 82 for organic matter content, 212 for available phosphate,. 3. Smooth frequency distribution and fractile diagram showed that available phosphate was in log-normal distribution while others were in normal distribution. 4. Serial correlation analysis revaled that the soil chemical properties had spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of chemcial properties measured between the serial grid points in the direction of south to north following land-partitioned boundary showed that the zone of influence showing stationarity ranged from 20 to 50m. In the direction of east to west accross land-partitioned boundary, the autocorrelogram of many chemical properies showed peaks with the periodic interval of 30m, which were similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.