• International Journal of Concrete Structures and Materials
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• v.10 no.1
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• pp.39-46
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• 2016

In this study, different proportions of glass beads used for road marking were added into the concrete samples to reduce the temperature gradient through the concrete pavement thickness. It is well known that decreasing the temperature gradient reduces the risk of thermal cracking and increases the service life of concrete pavement. The extent of alkali-silica reaction (ASR) produced with partial replacement of fine aggregate by glass bead was investigated and compressive strength of concrete samples with different proportion of glass bead in their mix designs were measured in this study. Ideal results were obtained with less than 0.850 mm diameter size glass beads were used (19 % by total weight of aggregate) for C30/37 class concrete. Top and bottom surface temperatures of two different C30/37 strength class concrete slabs with and without glass beads were measured. It was identified that, using glass bead in concrete mix design, reduces the temperature differences between top and bottom surfaces of concrete pavement. The study presented herein provides important results on the necessity of regulating concrete road mix design specifications according to regions and climates to reduce the temperature gradient values which are very important in concrete road design.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.3
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• pp.166-173
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• 2007

A numerical study was conducted to have the effect of $CO_2$ addition to fuel on the chemical reaction mechanism with the change of the initial concentration of $CO_2$ and the axial velocity gradient. From this study, it was found that there were two serious effects of $CO_2$ addition on a non-premixed flame ; a diluent effect by the reactive species reduction and chemical effect of the breakdown of $CO_2$ by the third-body collision and thermal dissociation. Especially, the chemical effect was serious at the lower velocity gradient of the axial flow. It was certain that the mole fraction profile of $CO_2$ was deflected and CO was increased with the initial concentration of $CO_2$. It was also ascertained that the breakdown of $CO_2$ would cause the increasing of CO mole fraction at the reaction region. It was also found that the addition of $CO_2$ did not alter the basic skeleton of $H_2-O_2$ reaction mechanism, but contributed to the formation and destruction of hydrocarbon products such as HCO. The conversion of CO was also suppressed and $CO_2$ played a role of a dilution in the reaction zone at the higher axial velocity gradient.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.9-15
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• 2003

To improve the performance of PID controller of high order systems by model reduction, we proposed two model reduction methods. One, Original model with two point $({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$ in Nyquist curve used gradient base method and genetic algorithm. The other, Original model without two point$({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$in Nyquist curve used to add very small dead time. This method has annexed very small dead time on the base model for reduction, and we remove it after getting the reduced model, and , we improved Smith-predictor for a dead-time compensator using genetic algorithms. This method considered four points$({\angle}G(jw)=0,\;-\pi/2,\;-\pi,\;-3\pi/2)$ in the Nyquist curve to reduce steady state error between original and reduced model. It is shown that the proposed methods have more performance than the conventional method.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.366-369
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• 2002

Subsurface biobarrier technology has potential applications to contain contaminated groundwater and/or to degrade toxic pollutants in groundwater. Most biobarrier studies were conducted under aerobic condition, however there were several obstacles to make aerobic condition. Thus, In this study, we examined biobarrier formation under denitrifying condition by using nitrate as an electron acceptor. Experiments were performed with a sand column inoculated with activated sludge from the nearby WWTP. The substrate medium was pumped to the sand column in an upflow mode. During the low substrate loading rate period, the extent of reduction rate in hydraulic conductivity was found similar throughout the column, and permeability became relatively stable after couple of days. However, during the high substrate loading rate period, the column demonstrated a gradient of permeability reduction, with the greatest reduction in sections nearest the column inlet. Rapid growth of microorganisms near the column inlet resulted in the unbalanced reduction of hydraulic conductivity throughout the sand column. As a result, at this denitrifying condition the thickness of biobarrier could be controlled by adjusting the medium conditions of microbial growth.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.619-625
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• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.17-24
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• 2011

TMED(Transmission Mounted Electric Device) parallel hybrid configuration can realize EV(Electric Vehicle) mode by disengaging the clutch between an engine and a transmission-mounted motor to improve efficiencies of low load driving and regenerative braking. In the EV mode, however, jerk can be induced since there are insufficient damping elements in the drive-train. Though the jerk gives demoralizing influence upon driving comport, adding a physical damper is not applicable due to constraints of the layout. This study suggests the jerk reduction control, composed of active damping method and torque profiling method, to suppress the jerk without hardware modification. The former method creates a virtual damper by generating absorbing torque in the opposite direction of the oscillation. The latter method reduces impulse on the mated gear teeth of the drive-train by limiting the gradient of traction torque when the direction of the torque is reversed. To validate the effectiveness of the suggested strategy, a series of vehicle tests are carried out and it is observed that the amplitude of the oscillation can be reduced by up to 83%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1064-1073
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• 2015

In this study, we introduce the pedestrian detection system by using the feature of HOG-PCA and RBFNNs pattern classifier. HOG(Histogram of Oriented Gradient) feature is extracted from input image to identify and recognize a object. And a dimension is reduced for improving performance as well as processing speed by using PCA which is a typical dimensional reduction algorithm. So, the feature of HOG-PCA through the dimensional reduction by using PCA leads to the improvement of the detection rate. FCM clustering algorithm is used instead of gaussian function to apply the characteristic of input data as well and connection weight is used by polynomial expression such as constant, linear, quadratic and modified quadratic. Finally, INRIA person database known as one of the benchmark dataset used for pedestrian detection is applied for the performance evaluation of the proposed classifier. The experimental result of the proposed classifier are compared with those studied by Dalal.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.41-48
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• 2021

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.1-9
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• 2008

Thanks to the multimedia technology development, it is possible to show image representations in high quality and to process images in various ways. Anisotropic diffusion as an effective diffusion filtering among many image preprocessing methods and postprocessing methods is used in reduction of speckle noises of ultrasound images, image restoration, edge detection, and image segmentation. However, the conventional anisotropic diffusion based on a cross-kernel causes the following problems. The problem is the concentration of edges in the vertical or horizontal directions. In this paper, a new anisotropic diffusion transform based on directions of gradient is proposed. The proposed method uses the eight directional square-kernel which is an expanded form of the cross-kernel. The proposed method is to select directions of small gradient based on square-kernel. Therefore, the range of proposed diffusion is selected adaptively according to the number of the directions of gradient. Experimental results show that the proposed method can decrease the concentration of edges in the vertical or horizontal directions, remove impulse noise. The image in high quality can be obtained as a result of the proposed method.