• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.360-360
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• 2022

토양수분과 유출 간 관계를 정량화하는 것은 수문 기작 및 유출 발생 과정의 이해를 위한 중요한 정보를 제공한다. 특히, 유출과정의 특성화는 수문 사상에 따른 불포화대 내 토양수 및 토사 손실 제어와 산사태 및 비점오염원 발생 예측을 위해 필수적이다. 유출과정과 관련된 비선형성과 복잡성을 확인하기 위해 토양수분과 유출 사이의 이력 거동이 조사되었다. 특히, 수문 과정 내 이력 현상 구체화를 위해 정성적인 시각적 분류 및 정량적 평가를 위한 이력 지수들이 개발되었다. 정성적인 시각적 분류는 시간에 따라 시계 및 반시계방향으로 다중 루프 형상을 나누는 방식으로 진행되었고, 정량적 평가의 경우 이력 고리(Hysteretic loop) 내 상승 고리(Rising limb)와 하강 고리(Falling limb)의 차이를 기준으로 한 지수로 이력 현상을 특성화하였다. 이전에 제안된 방법론들은 연구자의 판단이 들어가기 때문에 보편적이지 않고 이력 현상을 개발된 지수에 맞춤에 따라 자료 손실이 나타나는 한계가 존재한다. 자료의 손실 없이 불포화대 내 발생 가능한 대표 이력 현상을 자동으로 추출하기 위해 적합한 비지도 학습기반 기계학습 방법론의 제안이 필요하다. 우리 연구에서는 국내 산지 사면에서 강우 사상 동안 다중 깊이(10, 30, 60cm)로 56개의 토양수분 측정지점에서 확보된 토양수분 시계열 자료와 산지 사면 내 위어를 통해 확보된 유출 시계열 자료를 사용하였다. 먼저, 기존에 분류 방법을 기반으로 계절 및 공간특성에 따라 지배적으로 발생하는 토양수분-유출 간 이력 현상을 특성화하였다. 다음으로, 토양수분-유출 간 이력 패턴을 자료 손실 없이 형상화하여 자동으로 데이터베이스화하는 알고리즘을 개발하였다. 마지막으로, 비지도 학습방법을 이용하여 데이터베이스화된 실제 발현 이력 현상 내 확률분포를 최대한 가깝게 추정하는 은닉층을 반복적인 재구성 학습을 통해 구현함으로써 대표 이력 현상 패턴을 추출하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.313-314
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• 2022

The intelligent maritime traffic information service provides a service to prevent collisions and stranding of ships based on the location information of ships periodically collected from ship equipment such as LTE-Maritime transceivers and AIS installed on ships. provided in real time. However, the above service may reduce the reliability of ship location information because GPS location information for measuring the ship's location may be cut off during transmission through LTE-Maritime or AIS networks, or phenomena such as location jumps and delays may occur. This study aims to estimate reliable position information to some extent even in an abnormal section through ship position prediction based on the existing received position information using the Kalman filter, which is an optimal estimation filter based on probability.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.67-75
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• 2023

This paper deals with the operation of air taxis, which is one of the latest innovative technologies aimed at solving the issue of traffic congestion in cities. A key challenge for the successful introduction of the technology and efficient operation is a vertiport location problem. This paper employs a discrete choice model to calculate choice probabilities of transportation modes for each route, taking into account factors such as cost and travel time associated with different modes. Based on this probability, a mathematical formulation to maximize the utilization rate for air taxi is proposed. However, the proposed model is NP-hard, effective and efficient solution methodology is required. Compared to previous studies that simply proposed the optimization models, this study presents a solution methodology using the cross-entropy algorithm and confirms the effectiveness and efficiency of the algorith through numerical experiments. In addition to the academic excellence of the algorithm, it suggests that decision-making that considers actual data and air taxi utilization plans can increase the practial usability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.195-202
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• 2008

Underestimation of the capacity can have serious economic consequences, as deficient bridges must be posted, repaired or replaced. Accurate prediction of bridge behavior may allow for more bridges to remain in service with or without minor repairs. The presented research is focused on the reliability evaluation of the actual load carrying capacity of existing bridges based on the field testing. Reliability analysis is performed on 17 previously tested bridges. Bridges are first evaluated based on the code specified values and design resistance. However, after the field testing program, it is possible to apply the experimental results into the bridge reliability evaluation procedures. The girder distribution factors obtained from the tests are also applied in the reliability calculation. The results indicate that the reliability indices of selected bridges can be significantly increased due to the reduction of uncertainties without sacrificing the safety of structures, by including the result of field measurement data into calculation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.141-147
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• 2024

In this study, micro CT images were used to confirm the tensile fracture strength according to the pore distribution characteristics of 3D printed concrete. Unlike general specimens, concrete structures printed by 3D printing techniques have the direction of pores (voids) depending on the stacking direction and the presence of filaments contact surfaces. Accordingly, the pore distribution of 3D printed concrete specimens was analyzed through quantitative and qualitative methods, and the tensile strength by direction was analyzed through a finite element technique. It was confirmed that the pores inside the 3D printed specimen had directionality, resulting in their anisotropic behavior. This study aims to analyze the characteristics of 3D concrete printing specimen and correlate them with simulation-based mechanical properties to improve performance of 3D printed material and structure.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.169-178
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• 2008

Level of Service (LOS) is one of ways to evaluate operational conditions. It is very important factor in evaluation especially for the facility of highways. However, some studies proved that ${\upsilon}/c$ ratio and accident rate is appeared like a second function which has a U-form. It means there is a gap between LOS and safety of highway facilities. Therefore, this study presents a method for evaluation of a signalized intersection which is considered both smooth traffic operation (delay) and traffic safety (accident). Firstly, as a result of our research, accident rates and EPDO are decreased when it has a big delay. In that reason, it is necessary to make a new Level of Service included traffic safety. Secondly, this study has developed a negative binominal regression model which is based on the relation between accident patterns and stream. Thirdly, standards of LOS are presented which is originated from calculation between annual delay costs and annual accident cost at each intersection. Lastly, worksheet form is presented as an expression to an estimation step of a signalized intersection with traffic accident prediction model and new LOS.

• Tunnel and Underground Space
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• v.22 no.2
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• pp.106-119
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• 2012

Roughness of rock joint has generally been characterized based upon geometrical aspects of a two-dimensional surface profile. The appropriate description of joint roughness, however, should consider the features of roughness mobilization at contact areas under normal and shear loads. In this study, direct shear tests were conducted on the replicas of tensile fractured gneiss joints and the influence of the shear direction on the shear behavior and effective roughness was examined. In this procedure, a joint surface was represented as a group of triangular planes, and the steepness of each plane was characterized using the concepts of the active and inactive micro-slope angles. The contact areas at peak strength which were estimated by a numerical method showed that the locations of the contact areas were mainly dependent on the distribution of the micro-slope angle and the shear behavior of joint was dominated by only the fractions with active micro-slope angles. Therefore, a three-dimensional coefficient for the quantification of rock joint roughness is proposed based on the distribution of active micro-slope angle: active roughness coefficient, $C_r$. Comparison of the active roughness coefficient and the peak shear strength obtained from the experiment suggests that the active roughness coefficient is the effective parameter to quantify the surface roughness and estimate the shear behavior of rock joint.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.679-686
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• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.

• Journal of Environmental Impact Assessment
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• v.26 no.5
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• pp.291-302
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• 2017

The research was carried out in order to find climate factors which determine the distribution of Eurya japonica, and the potential habitats (PHs) under the current climate and climate change scenario by using species distribution models (SDMs). Four climate factors; the warmth index (WI), the minimum temperature of the coldest month (TMC), summer precipitation (PRS), and winter precipitaion (PRW) : were used as independent variables for the model. Seventeen general circulation models under RCP (Representative concentration pathway) 8.5 scenarios were used as future climate scenarios for the 2050s (2040~2069) and 2080s (2070~2099). Highly accurate SDMs were obtained for E. japonica. The model of distribution for E. japonica constructed by SDMs showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of E. japonica. The area above the $-5.7^{\circ}C$ of TMC revealed high occurrence probability of the E. japonica. Future PHs for E. japonica were projected to increase respectively by 2.5 times, 3.4 times of current PHs under 2050s and 2080s. It is expected that the potential of E. japonica habitats is expanded gradually. E. japonica is applicable as indicator species for monitoring in the Korean Peninsula. E. japonica is necessary to be monitored of potential habitats.