• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.949-963
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• 2017

This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.

• Journal of Biomedical Engineering Research
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• v.41 no.3
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• pp.121-127
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• 2020

The purpose of this paper is to review the validation on the application of low frequency IMU(Inertial Measurement Unit) sensors by replacing high frequency motion analysis systems. Using an infrared-based 3D motion analysis system and IMU sensors (22 Hz) simultaneously, the gait cycle and knee flexion angle were measured. And the accuracy of each gait parameter was compared according to the statistical analysis method. The Bland-Altman plot analysis method was used to verify whether proper accuracy can be obtained when extracting gait parameters with low frequency sensors. As a result of the study, the use of the new gait assessment system was able to identify adequate accuracy in the measurement of cadence and stance phase. In addition, if the number of gait cycles is increased and the results of body anthropometric measurements are reflected in the gait analysis algorithm, is expected to improve accuracy in step length, walking speed, and range of motion measurements. The suggested gait assessment system is expected to make gait analysis more convenient. Furthermore, it will provide patients more accurate assessment and customized rehabilitation program through the quantitative data driven results.

• Atmosphere
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• v.26 no.1
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• pp.35-45
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• 2016

Initialization of the global seasonal forecast system is as much important as the quality of the embedded climate model for the climate prediction in sub-seasonal time scale. Recent studies have emphasized the important role of soil moisture initialization, suggesting a significant increase in the prediction skill particularly in the mid-latitude land area where the influence of sea surface temperature in the tropics is less crucial and the potential predictability is supplemented by land-atmosphere interaction. This study developed a new soil moisture initialization method applicable to the KMA operational seasonal forecasting system. The method includes first the long-term integration of the offline land surface model driven by observed atmospheric forcing and precipitation. This soil moisture reanalysis is given for the initial state in the ensemble seasonal forecasts through a simple anomaly initialization technique to avoid the simulation drift caused by the systematic model bias. To evaluate the impact of the soil moisture initialization, two sets of long-term, 10-member ensemble experiment runs have been conducted for 1996~2009. As a result, the soil moisture initialization improves the prediction skill of surface air temperature significantly at the zero to one month forecast lead (up to ~60 days forecast lead), although the skill increase in precipitation is less significant. This study suggests that improvements of the prediction in the sub-seasonal timescale require the improvement in the quality of initial data as well as the adequate treatment of the model systematic bias.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.325-332
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• 2006

The dynamic responses of human standing postural control were investigated when subjects were exposed to long-term horizontal vibration. It was hypothesized that the motion of standing posture complexity mainly occurs in the mid-sagittal plane. The motor-driven support platform was designed as a source of vibration. The AC Servo-controlled motors produced anterior/posterior (AP) motion. The platform acceleration and the trunk angular velocity were used as the input and the output of the system, respectively. A method was proposed to identify the complexity of the standing posture dynamics. That is, during AP platform motion, the subject's knee, hip and neck were tightly constrained by fixing assembly, so the lower extremity, trunk and head of the subject's body were individually immovable. Through this method, it was assumed that the ankle joint rotation mainly contributed to maintaining their body balance. Four subjects took part in this study. During the experiment, the random vibration was generated at a magnitude of $0.44m/s^2$, and the duration of each trial was 40 seconds. Measured data were estimated by the coherence function and the frequency response function for analyzing the dynamic behavior of standing control over a frequency range from 0.2 to 3 Hz. Significant coherence values were found above 0.5 Hz. The estimation of frequency response function revealed the dominant resonance frequencies between 0.60 Hz and 0.68 Hz. On the basis of our results illustrated here, the linear model of standing postural control was further concluded.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.603-617
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• 2023

This study aims to provide a better understanding of the turbulent flow characteristics in swash zone. A double dam-break method is employed to generate the swash zone flow. Comparing with the conventional single dam-break method, a delay between two gate opening can be controlled to reproduce various interactions between uprush and backwash. For numerical simulations, overInterDyMFoam based on OpenFOAM is adopted. Using overInterDyMFoam, interface between two immiscible fluids having different densities (i.e., air and water phases) can be tracked in a moving mesh with multiple layers. Two-dimensional Reynolds-Averaged Navier-Stokes equations are solved with a standard 𝜅-𝜖 turbulence model for momentum and continuity. Numerical model results are validated with laboratory experiment data for the time series of water depth and streamwise velocity. Turbulent kinetic energy distribution is further investigated to identify the turbulence evolution for each flow regime (i.e., uprush, backwash, and swash-swash interaction).

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.1-12
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• 2010

This paper deals with the transmission interval of vehicle data in smart highway where WAVE (Wireless Access for Vehicular Environments) systems have been installed for advanced road infrastructure. The vehicle data could be collected at every second, which is containing location information of the vehicle as well the vehicle speed, RPM, fuel consuming and safety data. The safety data such as DTC code, can be collected through OBD-II. These vehicle data can be used for valuable contents for processing and providing traffic information. In this paper, we propose a model to decide the collection interval of vehicle information in real time environment. This model can change the transmission interval along with special and time-variant traffic condition based on the 32 scenarios using microscopic traffic simulator, VISSIM. We have reviewed the transmission interval, communication transmission quantity and communication interval, tried to confirm about communication possibility and BPS, etc for each scenario. As results, in 2-lane from 1km highway segment, most appropriate transmission interval is 2 times over spatial basic segment considering to communication specification. In the future, if a variety of wireless technologies on the road is introduced, this paper considering not only traffic condition but also wireless network specification will be utilized the high value.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.348-359
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• 2017

Recently, various public transportation activation policies are being implemented in order to mitigate traffic congestion in metropolitan areas. Especially in the metropolitan area, the bus information system has been introduced to provide information on the current location of the bus and the estimated arrival time. However, it is difficult to predict the travel time due to repetitive traffic congestion in buses passing through complex urban areas due to repetitive traffic congestion and bus bunching. The previous bus travel time study has difficulties in providing information on route travel time of bus users and information on long-term travel time due to short-term travel time prediction based on the data-driven method. In this study, the path based long-term bus travel time prediction methodology is studied. For this purpose, the training data is composed of 2015 bus travel information and the 2016 data are composed of verification data. We analyze bus travel information and factors affecting bus travel time were classified into departure time, day of week, and weather factors. These factors were used into clusters with similar patterns using self organizing map. Based on the derived clusters, the reference table for bus travel time by day and departure time for sunny and rainy days were constructed. The accuracy of bus travel time derived from this study was verified using the verification data. It is expected that the prediction algorithm of this paper could overcome the limitation of the existing intuitive and empirical approach, and it is possible to improve bus user satisfaction and to establish flexible public transportation policy by improving prediction accuracy.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.4
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• pp.478-486
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• 2021

This report demonstrates a method of generating a chair-side and computer-aided template for implant surgery based on the Top-Down and restoration-driven concept. Compared to the traditional CAD-CAM process which requires multiple steps to be taken between dental clinic and laboratory, this alternative procedure, VARO guide system (VARO Guide, CAD, Pre-Guide, VARO-mill, NeoBiotech, Seoul, South Korea) enables accurate and patient-friendly implant surgery as well as immediate provisional restoration in a single visit. First, bite-registration at centric jaw relation and CBCT were taken using the Pre-Guide. The CBCT data was then reorganized directly through the chair-side CAD, and we could determine the most appropriate 3-dimensional position of implant. The STL file was extracted and put into the chair-side CAM (VARO-mill) to fabricate a VARO. This surgical guide allowed the implants to be accurately positioned into the planned sites within an hour.