• 부동산연구
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• 제27권3호
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• pp.41-50
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• 2017

변동성 모형을 이용한 국내의 주택가격에 대한 기존의 연구에서는 변동성모형을 어떻게 주택시장분석에 적용할 수 있는지를 보여주고 있지만 최근 국내의 지역주택시장들에 나타나는 유의미한 변화를 반영하는데는 한계가 존재할 수 밖에 없다. 본 연구에서는 변동성모형을 적용하여 전국의 각 지역별 주택시장을 분석하고 이를 통해 미래의 지역별 주택시장의 가격변동을 실제적으로 예측하였다. AR(1)-ARCH(1), AR(1)-GARCH(1,1), AR(1)-EGARCH(1,1,1) 모형을 통하여 지역주택시장에 ARCH 및 GARCH효과가 존재하는 것을 확인하였다. 그리고 각 지역의 예측력을 비교하여 지역별 최적예측모형을 선정하였으며, 이러한 지역별 최적모형의 선정이 실제적으로 어떻게 이용될 수 있는지를 보여주기 위하여 2017년 하반기의 각 지역주택시장의 가격변동을 선정된 지역별 최적모형을 이용하여 예측하였다.

• 한국의류학회지
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• 제46권5호
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• pp.760-771
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• 2022

This study sought to develop clothing for a companion animal that can provide stable ECG measurements. A pattern for the smart clothing of a companion dog was manufactured using the replica method to select a location and method that best suited the stable measurement of ECG and improved the clothing's fitness. The smart clothing was developed as the following three types: strap type, top type, and combined top and vest type with a detachable wireless ECG monitor. The detection abilities of these were observed using the PQRST rate taken after ECG measurements while the three companion dogs were tested while resting and moving. The results revealed that apart from using an electrode, applying a gel pad is the most effective way to achieve stable ECG measurements, and the central chest region is more reliable than the left armpit for providing steady readings. The combined top and vest type showed the highest average ECG PQRST detection number, meaning that the ECG signal measurement was steady. These results may contribute to the measurement of ECG in smartwear for U-Healthcare to measure other biometric data of a companion dog.

• 현장농수산연구지
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• 제6권1호
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• pp.143-154
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• 2004

본 실험은 기존의 난방 부하 모델식을 검토하고 문제점을 수정 보완하여 국내에 적용 가능한 모델식을 선정하고 지역별 온실내 목표온도에 따른 Degree hour 값을 결정하기 위하여 수행하였다. 국내 기상환경에 적용 가능한 모델식을 선정하기 위하여 1961년부터 2000년의 기상자료를 이용하여 온실내 목표온도를 9, 13, 16, 20℃로 설정하여 현재까지 개발된 모델식과 기본식의 지역별 DH값을 산출하였다. 지역별로 산출된 기본의 DH값을 종속변수, Mihara(6식)식, Hayashi(7식)식과 각각의 수정식인 6-1식, 7-1식을 독립변수로 하여 온실내 설정온도에 따른 수정결정상관계수를 분석한 결과 수정 Mihara(6-1)식이 기본식에 가장 근접하였다. 따라서 본 실험 조건하에서 국내적용 가능한 DH모델식은 수정 Mihara식임이 판명되었다. 수정 Mihara식을 이용하여 온실내 목표온도 9, 13, 16, 20℃ 따른 DH값 등고선 그래프를 지역별로 제시하였다.

• 한국환경보건학회지
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• 제49권3호
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• pp.149-158
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• 2023

Background: Injury is one of the major health problems in South Korea. Few studies have evaluated both intentional and unintentional injury when investigating the association between exposure to air pollutants and injury. Objectives: We aimed to explore the association between short-term exposure to ambient air pollution and years of life lost (YLLs) due to injury. Methods: Data on daily YLLs for 2002~2019 were obtained from the the Death Statistics Database of the Korean National Statistical Office. This study estimated short-term exposure to particulate matter with an aerodynamic diameter of <10 ㎛ (PM₁₀), particulate matter with an aerodynamic diameter of <2.5 ㎛ (PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). This time series study was conducted using a generalized additive model (GAM) assuming a Gaussian distribution. We also evaluated a delayed effect of ambient air pollution by constructing a lag structure up to seven days. The best-fitting lag was selected based on smallest generalized cross validation (GCV) value. To explore effect modification by intentionality of injury (i.e., intentional injury [self-harm, assault] and unintentional injury), we conducted stratified subgroup analyses. Additionally, we stratified unintentional injury by mechanism (traffic accident, fall, etc.). Results: During the study period, the average daily YLLs due to injury was 307.5 years. In the intentional injury, YLLs due to self-harm and assault showed positive association with air pollutants. In the unintentional injury, YLLs due to fall, electric current, fire and poisoning showed positive association with air pollutants, whereas YLLs due to traffic accident, mechanical force and drowning/submersion showed negative associations with air pollutants. Conclusions: Injury is recognized as preventable, and effective strategies to create a safe society are important. Therefore, we need to establish strategies to prevent injury and consider air pollutants in this regard.

• 한국물환경학회지
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• 제39권5호
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• pp.396-412
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• 2023

Species from the mayfly genus Ephemera (Order Ephemeroptera) was assessed for their physical microhabitat suitability (namely E. strigata, E. separigata, and E. orientalis-sachalinensis). Probability distribution models (Exponential, Normal, Lognormal, Logistic, Weibull, Gamma, Beta, and Gumbel) based on the data collected from 23,957 sampling units of 6,787 sites in Korea from 2010 to 2021 were used. Mode and standard deviation calculated from the best-fitting models to species distribution along a water depth gradient were 265 cm and 159 cm in E. orientalis-sachalinensis; 10 cm and 83 cm in E. strigata; 20 cm and 15 cm in E. separigata, respectively. The current velocity gradient was 22 cm/s and 40 cm/s in E. orientalis-sachalinensis; 60 cm/s and 53 cm/s in E. strigata; 82 cm/s and 25 cm/s in E. separigata, respectively. The mean diameter (phi scale) of substrate grains were -3.6 and 2.2 in E. orientalis-sachalinensis; -7.4 and 1.5 in E. strigata; -5.8 and 0.9 in E. separigata, respectively. Habitat suitability range of E. orientalis-sachalinensis was estimated to be 161~369 cm (water depth), 5~44 cm/s (current velocity), -5.2~-2.0 (mean diameter); 3~34 cm (water depth), 36~94 cm/s (current velocity), -8.1~-6.3 (mean diameter) for E. strigata; 12~32 cm (water depth), 63~96 cm/s (current velocity), -6.3~-5.2 (mean diameter) for E. separigata. In relative comparison, E. orientalis-sachalinensis was estimated to be rheophobic, eurybathophilic, and eurypsephophilic; E. strigata to be euryrheophilic, bathophobic, and lithophilic; E. separigata to be stenomesorheophilic, stenobathophobic, stenolithophilic.

• Current Optics and Photonics
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• 제8권3호
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• pp.230-238
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• 2024

The refractive index is a key material-design parameter, especially for high-refractive-index glasses, which are used for precision optics and devices. Increased demand for high-precision optical lenses produced by the glass-mold-press (GMP) process has spurred extensive studies of proper glass materials. B₂O₃, SiO₂, and multiple heavy-metal oxides such as Ta₂O₅, Nb₂O₅, La₂O₃, and Gd₂O₃ mostly compose the high-refractive-index glasses for GMP. However, due to many oxides including up to 10 components, it is hard to predict the refractivity solely from the composition of the glass. In this study, the refractive index of optical glasses based on the B₂O₃-La₂O₃-Ta₂O₅-SiO₂ system is predicted using machine learning (ML) and compared to experimental data. A dataset comprising up to 271 glasses with 10 components is collected and used for training. Various ML algorithms (linear-regression, Bayesian-ridge-regression, nearest-neighbor, and random-forest models) are employed to train the data. Along with composition, the polarizability and density of the glasses are also considered independent parameters to predict the refractive index. After obtaining the best-fitting model by R² value, the trained model is examined alongside the experimentally obtained refractive indices of B₂O₃-La₂O₃-Ta₂O₅-SiO₂ quaternary glasses.

• 한국지진공학회논문집
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• 제28권3호
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• pp.121-128
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• 2024

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f^0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune's source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

• Animal Bioscience
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• 제37권8호
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• pp.1333-1344
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• 2024

Objective: Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns. Methods: A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2nd and 3rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Results: Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4th parity and then declined. In contrast, NPL and PPL decreased until the 2nd parity and then steadily increased until the 8th parity. The 2nd and 3rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC. Conclusion: The 3rd degree polynomial model offers the most suitable description of NBA, NPL, and PPL patterns. It holds promise for applications in genetic evaluations to enhance litter size and reduce piglet loss at birth in sows. These findings highlight the importance of accounting for sow parity effects in swine breeding programs, particularly in tropical conditions, to optimize piglet production and sow performance.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.242-254
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• 2016

This paper is the forth investigation on the evaluation methods of flow characteristics in a steady flow bench. In the previous works, it was concluded that the assumption of the solid rotation might cause serious problems and both of the eccentricity and the velocity profile distort the flow characteristics when using the ISM at 1.75B plane. Also particle image velocimetry (PIV) measurement at this position showed that the real velocity profile was far from the assumption of ISM evaluation. In this paper, the planar velocity profiles were measure from 1.75B to 6.00B position by PIV and the characteristics were examined according to the valve angles and lifts for further investigations about the effect of the position on the velocity profile. The results show that $26^{\circ}$ valve angle is always an unique exceptional case in all aspects. If the valve angle is $21^{\circ}$ and below, the planar velocity profiles according to the lift and the position are similar to each other, however, the tangential velocity curves along with the radial direction have common tendencies up to $16^{\circ}$ angle. Also the well arranged swirl behaviors are generally observed at the position above 3.00B and the velocity contour lines come closer to the concentric circle as the valve lift increases. In addition, the gradient of tangential velocity along with the radial direction from the swirl center becomes stable and constant as the position goes downstream. Concurrently the velocity gradient is larger to the eccentric direction of the center. In the meantime the tangential velocity curves along with the radial direction are irregular and various at 1.75B, however, they become regular and reach higher level as the evaluation position goes downstream. At this time the curves of 4.50B are the best fitted to the ideal one. On the other hand in an exceptional case, $26^{\circ}$, the velocity contours are very complicated over 6mm valve lift regardless the position and the gradient increases to the opposite direction of the eccentric center. Also, 6.00B is a best fitting position in the geometrical cylinder center base. With respect to the swirl center, the distribution range of centers for 1.75B is different to that for the other positions and the eccentricities of this plane are larger regardless the valve angle. After 1.75B, there is no certain tendency in the center position change according to the valve angle and lift. Additionally, the eccentricities are not sufficiently small to neglecting the effect on ISM measurement.

• 정보처리학회논문지B
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• 제14B권4호
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• pp.287-294
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• 2007

실세계의 문제에서 많은 기계학습의 알고리즘들은 데이터의 클래스 불균형 문제에 어려움을 겪는다. 이러한 클래스 불균형 문제를 해결하기 위하여 데이터의 비율을 변경하거나 좀 더 나은 샘플링 전략으로 극복하려는 연구들이 제안되었다. 그러나 데이터의 비율을 변경하는 연구에서는 전체 데이터 분포의 특성을 고려하지 못하고, 샘플링 전략을 제안하는 연구에서는 여러 가지 제한 조건을 고려해야만 한다. 본 논문에서는 위의 두가지 방법의 장점을 모두 포함하는 개선된 집중 샘플링 방법을 제안한다. 제안된 방법에서는 클래스 불균형 문제를 해결하기 위해 학습에 유용한 데이터들을 샘플링하는데 스코어링에 기반한 데이터 분할 방법을 이용한다. 즉, 입력 데이터들에 대해 SOM(Self Organizing Map)의 학습 결과로 얻은 BMU(Best Matching Unit)와의 거리를 계산하고, 이 거리론 스코어라 한다. 측정된 스코어는 오름차순으로 정렬되며, 이 과정에서 입력 데이터의 분포가 재 표현되고, 재 표현된 분포는 전체 데이터의 특성을 대표하게 된다. 그 결과로 얻은 데이터들 중에서 유용하지 못한 데이터들에 대해 제거하는 과정을 수행하여 새로운 학습 데이터 셋을 얻는다. 새로운 학습 데이터 생성 과정에서는 재 표현된 분포의 결과를 두 구간(upper, lower)으로 분할하는데, 두 추간 사이의 데이터들은 유용하지 못한 패턴들로 간주되어 학습에 이용되지 않는다. 본 논문에서 제안한 방법은 클래스 불균형의 비율 감수 훈련 데이터의 크기 감소, 과적합의 방지 등 몇 가지 장점을 보인다. 제안한 방법으로 샘플링된 데이터에 kNN 을 적용하여, 분류 실험한 결과 심한 불균형이 있는 ecoli 데이터의 분류 성능이 최대 2.27배 향상되었다.