• Journal of Korea Water Resources Association
• /
• v.48 no.5
• /
• pp.331-343
• /
• 2015

Most nonstationary frequency models are defined as the probability models containing the time-dependent parameters. For frequency analysis of annual maximum rainfall data, the Gumbel distribution is generally recommended in Korea. For the nonstationary Gumbel models, the time-dependent location and scale parameters are defined as linear and exponential relationship, respectively. The exponentially time-varying scale parameter of nonstationary Gumbel model is generally used because the scale parameter should be positive. However, the exponential form of scale parameter occasionally provides overestimated quantiles. In this study, various forms of time-varying scale parameters such as exponential, linear, and logarithmic forms were proposed and compared. The parameters were estimated based on the method of maximum likelihood. To compare the accuracy of each scale parameter, Monte Carlo simulation was performed for various conditions. Additionally, nonstationary frequency analysis was conducted for the sites which have more than 30 years data with a trend in rainfall data. As a result, nonstationary Gumbel model with exponentially time-varying scale parameter generally has the smallest root mean square error comparing with another forms.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.9 no.2
• /
• pp.137-144
• /
• 2015

In this paper, we present an inertial sensor-based gait analysis system to measure and analyze lower-limb movements. We developed an integral AHRS(Attitude Heading Reference System) using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE(Root Mean Square Error) of 1.08 and 1.72 degree in yaw and pitch angle. In order to evaluate the performance of our the gait analysis system, we compared the joint angle for the hip, knee and ankle with those provided by Vicon system. The result shows that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limb or gait analysis during the post-stroke recovery.

• Korean Chemical Engineering Research
• /
• v.45 no.1
• /
• pp.32-38
• /
• 2007

A batch Process has a multi-way data structure that consists of batch-time-variable axis, so the statistical modeling of a batch process is a difficult and challenging issue to the process engineers. In this study, We applied a statistical process control technique to the general batch process data, and implemented a fault-detection and Statistical process control system that was able to detect, identify and diagnose the fault. Semiconductor etch process and semi-batch styrene-butadiene rubber process data are used to case study. Before the modeling, we pre-processed the data using the multi-way unfolding technique to decompose the data structure. Multivariate regression techniques like support vector regression and partial least squares were used to identify the relation between the process variables and process condition. Finally, we constructed the root mean squared error chart and variable contribution chart to diagnose the faults.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2012.05a
• /
• pp.103-103
• /
• 2012

본 연구에서는 시험포장($1276.6m^2$)에서의 지표피복 BMPs (Best Management Practices) 시나리오를 적용하여 얻은 평균 유출저감율을 HSPF 모델에 적용하여 유역차원에서의 비점원오염 저감효과를 평가하고자 한다. 본 연구에서는 별미천 유역($1.21km^2$)을 대상으로 모형의 적용을 위한 입력자료로 기상자료와 지형자료를 구축하였으며 기상자료로 수원, 양평, 이천 기상관측소 자료를 구축하였으며, 지형자료로 격자크기 2m의 DEM (Digital Elevation Model)과 토지이용도는 2006년 5월 1일 QuickBird 영상을 제공받아 기존 환경부, 건교부, USGS의 토지피복분류체계 및 현장조사를 통하여 QuickBird 영상으로부터 추출 가능한 정밀농업정보에 대한 항목을 결정하였으며, 정사보정된 QuickBird 영상을 스크린 디지타이징 기법(On-Screen Digitizing Method)을 이용하여 총 21개 토지이용항목의 정밀토지이용도를 구축하였다. 실제모니터링으로 측정된 자료를 바탕으로 수위-유량곡선 산정 및 오염부하곡선을 선정, 2011년 6월 8일부터 10월 31일 분석기간으로 HSPF 모델링을 실시하였으며 모의결과 월별 통계에 따른 적용성 분석으로 RMSE (Root Mean Square Error) 는 1.15 ~ 1.76(mm/day), $R^2$는 0.62 ~ 0.78, Nash-Sutcliffe model efficiency (NSE)는 0.62 ~ 0.76로 모의치는 실측치와 유의성이 있는 것으로 분석되었다. 또한, Sediment, T-N, T-P의 $R^2$는 각각 0.72, 0.62, 0.63으로 상관성을 보이는 것으로 분석되었다. 시험포장으로부터 얻어진 event별 볏짚을 이용한 지표피복시나리오적용 후 밭에서의 평균 유출 약 10 % 유출율 감소 조건과 실제 평균 비점원오염 저감효과 89.7 % ~ 99.4 %의 결과로부터 지표피복효과의 침투효과를 HSPF 모델로 적용하기 위해 침투량(INFILT)를 조절하여 평균유출 약 10 %가 감소되는 16.0 mm/hr 값을 선정하였다. 그 결과, Sediment. T-N, T-P의 평균 저감율은 각각 87.2 %, 28.5 %, 85.1 %로 나타났으며 이는 시험포장에서의 실제 평균 비점오염 저감효과 89.7 % ~ 99.4 %에 근접함을 알 수 있었다. 이 결과로부터 침투량 조절에 따른 지표피복(침투짚단)효과는 Sediment, T-P에서 저감효율이 80 % 이상으로 높았지만 T-N은 약 30 %로 낮은 저감율을 보임으로써 저감효과가 크지 않음을 나타냈다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.9
• /
• pp.1065-1071
• /
• 2012

Wind energy is becoming one of the most preferable alternatives to conventional sources of electric power that rely on fossil fuels. For stable electric power generation, constant rotating speed control of a wind turbine is performed through pitch control and stall control of the turbine blades. Recently, variable pitch control has been implemented in modern wind turbines to harvest more energy at variable wind speeds that are even lower than the rated one. Although wind turbine pitch controllers are currently optimized using a step response via the Ziegler-Nichols auto-tuning process, this approach does not satisfy the requirements of variable pitch control. In this study, the variable pitch controller was optimized by a genetic algorithm using a neural network model that was constructed by the Latin Hypercube sampling method to improve the Ziegler-Nichols auto-tuning process. The optimized solution shows that the root mean square error, rise time, and settle time are respectively improved by more than 7.64%, 15.8%, and 15.3% compared with the corresponding initial solutions obtained by the Ziegler-Nichols auto-tuning process.

• Wind and Structures
• /
• v.28 no.2
• /
• pp.71-87
• /
• 2019

The yaw and interference effects of blades affect aerodynamic performance of large wind turbine system significantly, thus influencing wind-induced response and stability performance of the tower-blade system. In this study, the 5MW wind turbine which was developed by Nanjing University of Aeronautics and Astronautics (NUAA) was chosen as the research object. Large eddy simulation on flow field and aerodynamics of its wind turbine system with different yaw angles($0^{\circ}$, $5^{\circ}$, $10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $45^{\circ}$) under the most unfavorable blade position was carried out. Results were compared with codes and measurement results at home and abroad, which verified validity of large eddy simulation. On this basis, effects of yaw angle on average wind pressure, fluctuating wind pressure, lift coefficient, resistance coefficient,streaming and wake characteristics on different interference zone of tower of wind turbine were analyzed. Next, the blade-cabin-tower-foundation integrated coupling model of the large wind turbine was constructed based on finite element method. Dynamic characteristics, wind-induced response and stability performance of the wind turbine structural system under different yaw angle were analyzed systematically. Research results demonstrate that with the increase of yaw angle, the maximum negative pressure and extreme negative pressure of the significant interference zone of the tower present a V-shaped variation trend, whereas the layer resistance coefficient increases gradually. By contrast, the maximum negative pressure, extreme negative pressure and layer resistance coefficient of the non-interference zone remain basically same. Effects of streaming and wake weaken gradually. When the yaw angle increases to $45^{\circ}$, aerodynamic force of the tower is close with that when there's no blade yaw and interference. As the height of significant interference zone increases, layer resistance coefficient decreases firstly and then increases under different yaw angles. Maximum means and mean square error (MSE) of radial displacement under different yaw angles all occur at circumferential $0^{\circ}$ and $180^{\circ}$ of the tower. The maximum bending moment at tower bottom is at circumferential $20^{\circ}$. When the yaw angle is $0^{\circ}$, the maximum downwind displacement responses of different blades are higher than 2.7 m. With the increase of yaw angle, MSEs of radial displacement at tower top, downwind displacement of blades, internal force at blade roots all decrease gradually, while the critical wind speed decreases firstly and then increases and finally decreases. The comprehensive analysis shows that the worst aerodynamic performance and wind-induced response of the wind turbine system are achieved when the yaw angle is $0^{\circ}$, whereas the worst stability performance and ultimate bearing capacity are achieved when the yaw angle is $45^{\circ}$.

• Journal of Korea Water Resources Association
• /
• v.55 no.9
• /
• pp.679-686
• /
• 2022

As the occurrences of flash floods have increased due to climate change, faster and more accurate precipitation observation using X-band radar has become important. Therefore, the Ministry of Environment installed two dual-pol X-band radars at Samcheok and Uljin. The radar data used in this study were obtained from two different elevation angles and composed to reduce the shielding effect. To obtain quantitative rainfall, quality control (QC), K_DP retrieval, and Hybrid Surface Rainfall (HSR) methods were sequentially applied. To improve the accuracy of the quantitative precipitation estimation (QPE) of the X-band radar, we retrieved parameters for the relationship between rainfall rate and specific differential phase, which is commonly called the R-K_DP relationship; hence, an empirical approach was developed using multiple rain gauges for those two radars. The newly suggested relationship, R = 27.4K^0.81_DP, slightly increased the correlation coefficient by 1% more than the relationship suggested by the previous study. The root mean square error significantly decreased from 3.88 mm/hr to 3.68 mm/hr, and the bias of the estimated precipitation also decreased from -1.72 mm/hr to -0.92 mm/hr for overall cases, showing the improvement of the new method.

• Journal of Intelligence and Information Systems
• /
• v.28 no.4
• /
• pp.119-133
• /
• 2022

One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.7
• /
• pp.333-341
• /
• 2008

In this paper, a new interpolation model for the head related transfer function (HRTF) was proposed. In the method herein, we assume that the impulse response of the HRTF for each azimuth angle is given by linear interpolation of the time-delayed neighboring impulse responses of HRTFs. The time delay of the HRTF for each azimuth angle is given by sum of the sound wave propagation time from the ears to the sound source, which can be estimated by using azimuth angle, the physical shape of the underlying head and the distance between the head and sound source, and the refinement time yielding the minimum mean square error. Moreover, in the proposed model, the interpolation intervals were not fixed but varied, which were determined by minimizing the total number of HRTFs while the synthesized signals have no perceptual difference from the original signals in terms of sound location. To validate the usefulness of the proposed interpolation model, the proposed model was applied to the several HRTFs that were obtained from one dummy-head and three human heads. We used the HRTFs that have 5 degree azimuth angle resolution at 0 degree elevation (horizontal plane). The experimental results showed that using only $30\sim40%$ of the original HRTFs were sufficient for producing the signals that have no audible differences from the original ones in terms of sound location.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.219-239
• /
• 2019

As the importance of providing customized services to individuals becomes important, researches on personalized recommendation systems are constantly being carried out. Collaborative filtering is one of the most popular systems in academia and industry. However, there exists limitation in a sense that recommendations were mostly based on quantitative information such as users' ratings, which made the accuracy be lowered. To solve these problems, many studies have been actively attempted to improve the performance of the recommendation system by using other information besides the quantitative information. Good examples are the usages of the sentiment analysis on customer review text data. Nevertheless, the existing research has not directly combined the results of the sentiment analysis and quantitative rating scores in the recommendation system. Therefore, this study aims to reflect the sentiments shown in the reviews into the rating scores. In other words, we propose a new algorithm that can directly convert the user 's own review into the empirically quantitative information and reflect it directly to the recommendation system. To do this, we needed to quantify users' reviews, which were originally qualitative information. In this study, sentiment score was calculated through sentiment analysis technique of text mining. The data was targeted for movie review. Based on the data, a domain specific sentiment dictionary is constructed for the movie reviews. Regression analysis was used as a method to construct sentiment dictionary. Each positive / negative dictionary was constructed using Lasso regression, Ridge regression, and ElasticNet methods. Based on this constructed sentiment dictionary, the accuracy was verified through confusion matrix. The accuracy of the Lasso based dictionary was 70%, the accuracy of the Ridge based dictionary was 79%, and that of the ElasticNet (${\alpha}=0.3$) was 83%. Therefore, in this study, the sentiment score of the review is calculated based on the dictionary of the ElasticNet method. It was combined with a rating to create a new rating. In this paper, we show that the collaborative filtering that reflects sentiment scores of user review is superior to the traditional method that only considers the existing rating. In order to show that the proposed algorithm is based on memory-based user collaboration filtering, item-based collaborative filtering and model based matrix factorization SVD, and SVD ++. Based on the above algorithm, the mean absolute error (MAE) and the root mean square error (RMSE) are calculated to evaluate the recommendation system with a score that combines sentiment scores with a system that only considers scores. When the evaluation index was MAE, it was improved by 0.059 for UBCF, 0.0862 for IBCF, 0.1012 for SVD and 0.188 for SVD ++. When the evaluation index is RMSE, UBCF is 0.0431, IBCF is 0.0882, SVD is 0.1103, and SVD ++ is 0.1756. As a result, it can be seen that the prediction performance of the evaluation point reflecting the sentiment score proposed in this paper is superior to that of the conventional evaluation method. In other words, in this paper, it is confirmed that the collaborative filtering that reflects the sentiment score of the user review shows superior accuracy as compared with the conventional type of collaborative filtering that only considers the quantitative score. We then attempted paired t-test validation to ensure that the proposed model was a better approach and concluded that the proposed model is better. In this study, to overcome limitations of previous researches that judge user's sentiment only by quantitative rating score, the review was numerically calculated and a user's opinion was more refined and considered into the recommendation system to improve the accuracy. The findings of this study have managerial implications to recommendation system developers who need to consider both quantitative information and qualitative information it is expect. The way of constructing the combined system in this paper might be directly used by the developers.