• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.2
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• pp.135-147
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• 2015

With the miniaturization and digitalization of electronics industry, demand for Multi-Layer Ceramic Capacitor(MLCC) has increased steadily because of its various applications such as DC Blocking, Decoupling and Filtering etc. The modeling techniques of MLCC has been studied for a long time but most of these modeling method can only be applied after measurement and this has some losses of material, time in both production stage and measurement stage. This paper proposes the modeling method which can predict the frequency characteristics of MLCC from structure data and material data in design stage. The impedance of N-Layer Capacitor can be expressed in differential mathematical form based on coupled transmission line equations. By using this formula, we can predict the impedance of MLCC. As a result, proposed modeling is correspond with simulation, and it takes much less time to obtain the result than the simulation.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.672-679
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• 2018

This paper describes a methodology for shape design using an optimal design system, whereas generally a three dimensional analysis is required for such designs. An automatic finite element mesh generation technique, which is based on fuzzy knowledge processing and computational geometry techniques, is incorporated into the system, together with a commercial FE analysis code and a commercial solid modeler. Also, with the aid of multilayer neural networks, the present system allows us to automatically obtain a design window, in which a number of satisfactory design solutions exist in a multi-dimensional design parameter space. The developed optimal design system is successfully applied to evaluate the structures that are used. This study used a stress gauge to measure the maximum stress affecting the parts of the side housing bracket which are most vulnerable to cracking. Thereafter, we used a tool to interpret the maximum stress value, while maintaining the same stress as that exerted on the spot. Furthermore, a stress analysis was performed with the typical shape maintained intact, SM490 used for the material and the minimizing weight safety coefficient set to 3, while keeping the maximum stress the same as or smaller than the allowable stress. In this paper, a side housing bracket with a comparably simple structure for 36 tons was optimized, however if the method developed in this study were applied to side housing brackets of different classes (tons), their quality would be greatly improved.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.475-480
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• 2014

In the fields of researches associated with plant layout optimization, the main goal is to minimize the costs of pipelines for connecting equipment. However, what is the lacking of considerations in previous researches is to handle the multi floor processes considering the safety distances for domino impacts on a complex plant. The mathematical programming formulation can be transformed into MILP (Mixed Integer Linear Programming) problems as considering safety distances, maintenance spaces, and economic benefits for solving the multi-floor plant layout problem. The objective function of this problem is to minimize piping costs connecting facilities in the process. However, it is really hard to solve this problem due to complex unequality or equality constraints such as sufficient spaces for the maintenance and passages, meaning that there are many conditional statements in the objective function. Thus, it is impossible to solve this problem with conventional optimization solvers using the derivatives of objective function. In this study, the PSO (Particle Swarm Optimization) technique, which is one of the representative sampling approaches, is employed to find the optimal solution considering various constraints. The EO (Ethylene Oxide) plant is illustrated to verify the efficacy of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1727-1731
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• 2008

수자원의 효율적인 관리를 위해서는 신뢰성 있는 유량자료의 획득이 대단히 중요하다. 우리나라는 양질의 유량자료를 획득하기 위해 매년 많은 시간과 돈을 투자하고 있으나 자료의 질적인 면에서 만족할 만한 성과를 얻지 못하고 있다. 현재까지 우리나라의 유량자료는 댐의 수문자료와 수량관리 부처인 건교부에서 운영하는 수위표 지점의 수위-유량곡선에서 산출된 자료에 의존하고 있다. 그러나 수위-유량 관계식을 보정하기 위한 유량측정사업이 지속적이지 못하며, 이 관계식은 유량이 적은 저수기 및 갈수기에는 부정확하다는 한계가 있다. 또한, 국립환경과학원 낙동강물환경연구소에서 오염총량관리를 위한 낙동강수계 유량측정사업을 실시하고 있지만, 목적은 낙동강수계의 오염총량관리 단위유역 말단 47개 지점에서 유량측정을 효율적으로 실시하여 수질정책의 기초자료를 제공하는데 있다. 이 자료 역시 오염총량관리를 위하여 유량측정을 실시하여 수자원의 효율적인 관리를 위한 일 유량을 알 수가 없는 한계점을 가지고 있다. 따라서 저수기 및 갈수기에 수질정책의 기초자료를 제공하기 위해서 하천을 포함한 유역의 정확한 강우-유출특성의 파악이 필요하다. 그러나 강우-유출특성 또한 유역 내 강우의 시 공간적 분포가 다르며 그 자가 비선형성이 강하고 여러 변동성을 포함하므로, 강우로부터 하천의 유출량의 정확한 해석이 불가능하다. 그러나 최근 인공지능 분야에서 신호처리, 지능제어 및 패턴인식 등의 수단으로 사용되고 있는 신경망은 학습이라는 최적화 과정을 통해 입력과 출력으로 구성되는 하나의 시스템을 비선형적으로 구축할 수 있으며 이러한 이점을 활용하여 수자원 분야에서 다양하게 적용되고 있다. 본 연구의 목적은 강우-유출자료 및 댐 방류량 자료의 비선형적인 특정을 가장 잘 반영할 수 있는 신경망모형을 적용하여 수질정책의 기초자료를 제공하기 위하여 신뢰성 있는 유량자료를 산정하는 모형을 개발하는 것이다. 이를 위해서 낙동강물환경연구소에서 오염총량관리를 위한 낙동강수계 유량측정 지점 상류의 댐 방류량의 일 방류량자료와 강우자료를 입력 자료로 하여 유량을 예측할 수 있는 유량예측 신경망 모형 FFBN(Flow Forecasting By Neural)을 개발하였다. 그리고 입력 자료로서 장기유출모형인 SWAT의 모의결과를 입력 자료로 추가한 FFBNS(Flow Forecasting By Neural and SWAT)을 개발하였다. 신경망 모형의 구조는 입력층과 출력층 사이에 하나의 은닉층이 존재하는 다층 신경망으로 구성하였으며, 학습단계에서는 오류 역전파 알고리듬 학습방법 중 모멘텀법을 사용하였다. 예측된 유출량을 실측치와의 비교를 위하여 낙본D지점과 낙본 E지점에 대하여 $2005{\sim}2006$년까지의 모의 결과를 낙동 수위측정지점과 구미 수위측정지점의 실측치 통하여 복잡한 비선형성을 가지는 유출 시계열 자료에 대한 효과적인 최적의 신경망모델을 개발하여 유량을 예측하고 적용 가능성을 검토하고자 한다. 모의 결과는 수질정책의 기초자료 제공에 기여할 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• Fire Science and Engineering
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• v.24 no.6
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• pp.1-6
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• 2010

A smoldering ground fire can be a probable cause of reignition of surface fire when transmitted from Fermentation layer to Humus layer with temperature higher than that of ignition. Purpose of this paper is to identify experimental methodology on the potential risk of a smoldering ground fire, which is similar to the real surface fuel bed, and its combustion characteristics. The fuel model designed in this study is composed of 3 layers such as Litter layer, Fermentation layer and Humus layer and 8 Thermocouples are set through 3 layer at each boundary and in between to detect the temperature change and duration of smoldering and propagation velocity. As a result, it was observed that ignition conditions in the boundary between L layer and F layer determined transmission and non-transmisstion to F-H layer. In addition, range of critical humidity at which a smoldering ground fire was transmitted in a material layer was 33~44% and when temperature exceeds $350^{\circ}C$, likelihood of transmission of a smoldering ground fire was high. In the research, the experimental model for multi-layer smoldering ground fire is suggested and information about propagation of smoldering fire, possibility of reignition according to moisture content, propagation velocity and temperature change are obtained, Also, the built-up methods were established to help analyze basic characteristics of smoldering ground fire.

• International Journal of Highway Engineering
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• v.2 no.1
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• pp.135-145
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• 2000

A new procedure needs to be developed to predict the dynamic layer properties under moving truck loads. In this study, a computer code to evaluate layer moduli of asphalt concrete pavement from measured interior deflections at various depths were developed and verified from numerical model tests. Interior deflections of the pavement are measured from Multi-Depth Deflectometer(MDD). It was found that errors between the given and backcalculated moduli in numerical analysis were less than 0.32% for several numerical models tested. When impact loads were used, a technique to determine the depth to virtual rigid base was proposed through the analysis of compressive wave velocity and impulse loading durations. It was found that errors between the given and backcalculated moduli in numerical analysis were less than 0.114% when virtual rigid base was considered in numerical analysis. The pavement behavior must be evaluated under various vehicle speeds when determining the dynamic interaction between the loading vehicle and pavement system. To evaluate the dynamic behavior on asphalt concrete pavement under various vehicle speeds, truck moving tests were carried out. From the test results with respect to vehicle speed, it was found that the vehicle speed had significant effect on actual response of the pavement system. The lower vehicle speed generates the higher interior deflections, and the lower dynamic modulus.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.2
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• pp.77-84
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• 2012

This study suggested the planting model of Zelkova serrata communities in the areas with the warmth index of both 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. Warmth index was calculated with 449 weather points using inverse distance weighted interpolation method. The planting species were selected by correlation analysis between Z. serrata and each species of four or more frequency among the 36 relev$\acute{e}$ surveyed for this study. The result of this study is summarized as follows : Warmth index of Z. serrata communities was among $74{\sim}118^{\circ}C{\cdot}month$. Results of the correlation analysis between Z. serrata and each species observed that the Z. serrata belongs to the tree layer with warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. On the other hand, the species of Carpinus laxiflora, Quercus serrata, Prunus sargentii and Platycarya strobilacea appeared only in the tree layer with warmth index of $80{\sim}100^{\circ}C{\cdot}month$. Z. serrata and Styrax japonica appeared in the subtree layer with the warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$, while Acer pseudosieboldianum, Lindera erythrocarpa, Acer mono, Quercus serrata, etc. appeared in the subtree layer with the warmth index of $80{\sim}100^{\circ}C{\cdot}month$. Z. serrata, Ligustrum obtusifolium, Lindera obtusiloba, Callicarpa japonica and Zanthoxylum schinifolium all appeared in the shrub layer with the warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. Lindera erythrocarpa, Orixa japonica, Staphylea bumalda, Akebia quinata and Sorbus alnifolia appeared in the shrub layer with the warmth index of $80{\sim}100^{\circ}C{\cdot}month$ and Styrax japonica and Stephanandra incisa appeared in the shrub layer with the warmth index of $100{\sim}120^{\circ}C{\cdot}month$, The numbers of each species planted in a $100m^2$ area of the Z. serrata community were suggested as follows : five in tree layer, five in subtree layer and nine in shrub layer. The average area of canopy are suggested to be about $86m^2$ for tree layer, $34m^2$ for subtree layer and $34m^2$ for shrub layer.

• Informatization Policy
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• v.22 no.2
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• pp.3-18
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• 2015

We explore the issues on online political participation study in Korea compared with international one. More specifically, we characterize Korea's study trends as focusing on "who" is participating while international studies center on what the new "forms" of online political participation are. In other words, domestic studies try to show that online media play a role as a factor promoting bottom-up model of civic participation. Moreover, this function of online media is stimulated by the rapid growing of civic participation during democratization and citizens' deep disapproval of political institutions since then. However, previous studies are more interested in the expansion of participants, in particular, ordinary people. Therefore, the themes on conceptualizing and categorizing the online political participation seem to have been treated lightly. In this perspective, we need to view online political participation in a more multidimensional manner. In addition, we should pay attention to "those who do not participate" as well as "those who participate" in politics. Because the current media environment more tends to provoke citizens' political indifference than ever before. If it comes to that, we will be likely to face the circumstances worrying the democratic divide beyond the digital divide.