• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.101-113
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• 2010

Recently actual rainfall pattern is decreasing rainy days and increasing in rainfall intensity and the frequency of flood occurrence is also increased. To consider recent situation, Engineers use deterministic methods like a PMP(Probable Maximum Precipitation). If design storm wouldn't occur, increasing of design criteria is extravagant. In addition, the biggest structure cause trouble with residents and environmental problem. And then it is necessary to study considering probability of rainfall parameter in each sub-basin for design of water structure. In this study, stochastic rainfall patterns are generated by using log-ratio method, Johnson system and multivariate Monte Carlo simulation. Using the stochastic rainfall patterns, hydrological analysis, hydraulic analysis and 2nd flooding analysis were performed based on GIS for their applicability. The results of simulations are similar to the actual damage area so the methodology of this study should be used about making a flood risk map or regidental shunting rout map against the region.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1879_1880
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• 2009

본 논문에서는 제어상황에 따라 Type-1 Fuzzy Logic Controller가 선택적으로 rule을 사용하도록 rule 선택 알고리즘을 제안 한다. 그리고 이를 통해 연산 효율성을 높이는 방법에 관해 논한다. Type-1 Fuzzy Logic Controller는 기존의 제어기에 비해 설계하기 쉽고 성능이 더 뛰어나다. 그러나 제어 변수가 많아질수록 rule의 개수가 늘어나 연산량이 증가하게 된다. 연산량이 많아지면 고성능의 컴퓨터에서는 실시간 연산에 문제가 없으나 산업용 micro controller에서는 실시간 연산을 구현하는데 한계가 발생한다. 본 논문에서는 Type-1 Fuzzy Logic System의 논리구조에 근거하여 Type-1 Fuzzy Logic Controller의 연산량을 감소시킬 수 있는 알고리즘을 제안한다. 제안한 알고리즘은 제어상황에 따라 필요한 rule들만 선택적으로 제어값 도출을 위한 연산에 관여하도록 한다. Matlab 시뮬레이션을 통해 제안한 알고리즘의 유용성과 연산량을 실험하였다. 실험대상은 2륜 이동로봇으로 하였고 step 응답과 전/후진 시 결과를 관찰하였다. 실험 결과 제안한 알고리즘이 기존의 Type-1 Fuzzy Logic Controller에 비해 제어상황에 따라 필요한 rule들만 선택적으로 사용하는 것을 확인하였다. 결과적으로 연산 효율성이 향상되었다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.10
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• pp.70-78
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• 2009

This paper addresses the analysis and the design optimization of differential interconnects for high-speed Low-Voltage Differential Signaling (LVDS) applications. Thanks to the differential transmission and the low voltage swing, LVDS offers high data rates and improved noise immunity with significantly reduced power consumption in data communications, high-resolution display, and flat panel display. We present an improved model and new equations to reduce impedance mismatch and signal degradation in cascaded interconnects using optimization of interconnect design parameters such as trace width, trace height and trace space in differential printed circuit board (FPCB) transmission lines. We have carried out frequency-domain full-wave electromagnetic simulations, and time-domain transient simulations to evaluate the high-frequency characteristics of the differential FPCB interconnects. We believe that the proposed approach is very helpful to optimize high-speed differential FPCB interconnects for LVDS applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.761-764
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• 2007

This paper addresses the analysis and the design optimization of differential interconnects for Low-Voltage Differential Signaling (LVDS) applications. Thanks to the differential transmission and the low voltage swing, LVDS offers high data rates and improved noise immunity with significantly reduced power consumption in data communications, high-resolution display, and flat panel display. We present an improved model and new equations to reduce impedance mismatch and signal degradation in cascaded interconnects using optimization of interconnect design parameters such as trace width, trace height and πace space in differential flexible printed circuit board (FPCB) transmission lines. We have carried out frequency-domain full-wave electromagnetic simulations, time-domain transient simulations, and S-parameter simulations to evaluate the high-frequency characteristics of the differential FPCB interconnects.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.331-337
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• 2023

In this paper, we propose a deep learning model to detect lumbar 3 (L3) CT images to determine the occurrence and degree of sarcopenia. In addition, we would like to propose an optimization technique that uses oversampling ratio and class weight as design parameters to address the problem of performance degradation due to data imbalance between L3 level and non-L3 level portions of CT data. In order to train and test the model, a total of 150 whole-body CT images of 104 prostate cancer patients and 46 bladder cancer patients who visited Gangneung Asan Medical Center were used. The deep learning model used ResNet50, and the design parameters of the optimization technique were selected as six types of model hyperparameters, data augmentation ratio, and class weight. It was confirmed that the proposed optimization-based L3 level extraction model reduced the median L3 error by about 1.0 slices compared to the control model (a model that optimized only 5 types of hyperparameters). Through the results of this study, accurate L3 slice detection was possible, and additionally, we were able to present the possibility of effectively solving the data imbalance problem through oversampling through data augmentation and class weight adjustment.

• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.603-612
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• 2002

Numerical analyses have been carried out in order to check the applicability of high-strength steel to a medium-sized steel bridge. Using the yield strength of steel, Average Daily Truck Traffic (ADTT), and fatigue grade of structural detail as analytical parameters, the minimum weight sections that satisfy the limit states of the AASHTO LRFD design specification were determined through an optimization scheme. Likewise, the effects of the number of girders and span length on the applicability of high-strength steel were evaluated. Results show that high-strength steel may be employed in the steel bridge, since steel weight decreases with increasing yield strength regardless of the fatigue effect. Nonetheless, appropriate countermeasures against fatigue should be determined since it is a major factor in the effective use of high-strength steel in steel bridges.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.1
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• pp.32-39
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• 2018

Repairing timing and the extended service life with repairing are very important for cost estimation during operation. Conventionally used model for repair cost shows a step-shaped cost elevation without consideration of variability of extended service life due to repairing. In the work, RC(Reinforced Concrete) Column is considered for probabilistic evaluation of repairing number and cost. Two mix proportions are prepared and chloride behavior is evaluated with quantitative exterior conditions. The repairing frequency and cost are investigated with varying service life and the extended service life with repairing which were derived from the chloride behavior analysis. The effect of COV(Coefficient of Variation) on repairing frequency is small but the 1st repairing timing is shown to be major parameter. The probabilistic model for repairing cost is capable of reducing the number of repairing with changing the intended service life unlike deterministic model of repairing cost since it can provide continuous repair cost with time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.879-886
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• 2008

This paper addresses the analysis and the design optimization of differential interconnects for Low-Voltage Differential Signaling (LVDS) applications. Thanks to the differential transmission and the low voltage swing, LVDS offers high data rates and improved noise immunity with significantly reduced power consumption in data communications, high-resolution display, and flat panel display. We present an improved model and new equations to reduce impedance mismatch and signal degradation in cascaded interconnects using optimization of interconnect design parameters such as trace width, trace height and trace space in differential flexible printed circuit board (FPCB) transmission lines. We have carried out frequency-domain full-wave electromagnetic simulations, time-domain transient simulations, and S-parameter simulations to evaluate the high-frequency characteristics of the differential FPCB interconnects. The 10% change in trace width produced change of approximately 6% and 5.6% in differential impedance for trace thickness of $17.5{\mu}m$ and $35{\mu}m$, respectively. The change in the trace space showed a little change. We believe that the proposed approach is very helpful to optimize high-speed differential FPCB interconnects for LVDS applications.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.73-84
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• 1993

In this research, configuration design optimization of plane truss structure has been tested by using decomposition technique. In the first level, the problem of transferring the nonlinear programming problem to linear programming problem has been effectively solved and the number of the structural analysis necessary for doing the sensitivity analysis can be decreased by developing stress constraint into member stress approximation according to the design space approach which has been proved to be efficient to the sensitivity analysis. And the weight function has been adopted as cost function in order to minimize structures. For the design constraint, allowable stress, buckling stress, displacement constraint under multi-condition and upper and lower constraints of the design variable are considered. In the second level, the nodal point coordinates of the truss structure are used as coordinating variable and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, unconstrained optimal design problems are easy to solve. The decomposition method which optimize the section areas in the first level and optimize configuration variables in the second level was applied to the plane truss structures. The numerical comparisons with results which are obtained from numerical test for several truss structures with various shapes and any design criteria show that convergence rate is very fast regardless of constraint types and configuration of truss structures. And the optimal configuration of the truss structures obtained in this study is almost the identical one from other results. The total weight couldbe decreased by 5.4% - 15.4% when optimal configuration was accomplished, though there is some difference.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.