• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.135-142
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• 2020

The purpose of this study is to analyze the effectiveness of university convergence curriculum using CIPP model. With 758 data surveys of professors and students participating in K University's convergence education, the analysis of differences according to group characteristics and the factors affecting performance recognition and course satisfaction were analyzed. As a result of analysis, first, class activity(CA) was the highest (M=3.85), and coursework design(CD) was the lowest (M=3.35), and there were significant differences in the course objectives, course content, and class activities according to the characteristics of the group. Second, the factors affecting the performance recognition and course satisfaction of the convergence curriculum were needs analysis, coursework design, learner activity, performance recognition, and course satisfaction. In conclusion, it suggests that from the planning stage, it should be designed to reflect the needs of professors and students, and to improve satisfaction and performance recognition with novel contents and active teaching and learning activities. This study can be used as basic data for improving the quality of the convergence curriculum.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.181-188
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• 2009

This paper discusses the covariance structures of data collected from an experiment with a nested design structure, where a smaller experimental unit is nested within a larger one. Due to the nonrandomization of repeated measures factors to the nested experimental units, compound symmetry covariance structure is assumed for the analysis of data. Treatments are given as the combinations of the levels of random factors and fixed factors. So, a mixed-effects model is suggested under compound symmetry structure. An example is presented to illustrate the nesting in the experimental units and to show how to get the parameter estimates in the fitted model.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1275-1279
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• 2008

도시지역은 도시형 수해발생, 갈수시의 급수안전도 저하, 평시 하천유량의 감소, 공공수역의 수질악화, 지하수 오염 등 여러가지 문제에 직면하고 있다. 개발로 인한 수환경의 피해를 최소화하기 위한 대안적인 설계방안이 필요하며, 이를 위해서는 개발 전후 물순환 환경 변화에 대한 정량적인 해석이 가장 우선적으로 수행되어야 한다. 본 연구에서는 우리나라와 일본에서 도시유역에의 적용이 활발한 물리적 개념의 분포형 수문모형인 WEP(Water and Energy transfer Process) 모형을 통해 행정중심복합도시 개발 전후의 물순환 변화를 해석하였다. 정밀한 해석을 위해 대상유역을 100m 크기의 정방형 격자로 구분하고 기상 조건, 지표면 조건, 하천, 토양, 지하대수층, 농업용수 이용 등 물순환에 관련된 광범위한 입력자료는 기존 측정 자료 및 관련 문헌, 현장 조사를 통해 각각 구축하였다. 모의의 전 후처리는 WEP+를 통해 수행되었는데, WEP+는 WEP 모형의 방대한 양의 입력자료를 효과적으로 구축하고, 다양한 시계열 및 공간분포 출력자료를 효과적으로 분석할 수 있는 인터페이스를 지닌 전 후처리 프로그램이다. 개발로 인한 물순환 변화는 절성토로 인한 지형 및 토양 조건 변화, 토지이용 및 용수이용 변화에 대한 개발 계획을 모형 입력자료로 구축한 후, 개발전과 동일한 기상조건과 초기 모의조건 하에서 각각 11년간 모의하여 수문 요소 변화를 비교하는 방법을 사용하였다. 물순환 해석 결과는 개발 전후 모의에 대해 유황곡선 및 물수지, 수문요소 공간분포 비교를 통해 수행하였다.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.335-345
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• 2017

It is necessary for an instructor to understand the student's team building behavior for an effective guidance of team activities. In this study, we developed an agent-based computational model for simulating the student's self-controlled behavior. We validated the model by comparing the actual behavior. Through the simulation, we found that the time to stabilization of team formation and the ratio of the students having no team are decreasing as the population of the student increases. However, we also found that over a certain amount of population, the time and the ratio do not show much progress in the difference. The simulation also shows that the more heterogeneity between the students the higher chance of delaying the team formation and increasing the ratio. We expect to use the model as a tool for guiding and supporting students' team activities.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.111-121
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• 2007

A transit assignment model can forecast the behaviors of transit users. thereby playing an important role In the evaluation of transit policies. Most existing transit assignment models are based on the models for passenger cars; therefore they cannot reflect the specific characteristics of transit modes. In addition most of the existing models are based on a single transit mode (bus or rail), and they cannot forecast the behaviors of transit users in a changing mass transportation system. The goal of this study is to overcome these problems with the exiting models and to develop a more realistic model. The newly developed model is based on mixed transit modes and is a stochastic model that can reflect the different preferences of each transit user for travel time and transfering. Data gathered from the Seoul metropolitan area's smart card are used to calibrate this model. This study is expected to be used for the evaluation of transportation policies and to attribute the development of transit revitalization strategies.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.382-392
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• 2016

This study organize a self-directed learning in complex structures. And based on this, It was developed self-directed learning scale for university students. It was a analyzing literature and reviewing previous studies for developed scale. Therefore, Self-directed learning model was configured into motives, performance behaviors, and learning management behaviors. On the basis of this, the present study constructed 19 sub-factors and developed 114 scale items. First, a preliminary scale was developed and its reliability was assessed by administering the scale to 128 students attending A university. The result showed that the reliability of every sub-factor was good and, therefore, the scale was developed with no item removed. To verify the validity of the scale, this study evaluated reliability and construct validity by administering the scale to 674 students going to A university. The reliability and validity of all sub-factors were found to be good. A confirmatory factor analysis was performed to verify construct validity and the result revealed that the first model was not an appropriate model. For this reason, the first model was modified once by taking the model modification index into account and it was found that ${\chi}^2$ (563.254), CFI=.963, NFI=.951, RMSEA=.064. Thus, the model was verified as a valid model. The results of this study imply that it is possible to point out learners' weaknesses and strengths by measuring activities taking place in the learning process in detail.

• Journal of Digital Convergence
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• v.13 no.7
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• pp.349-357
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• 2015

Giant character used various SF movies and games in media convergence ages, and is essential for giant character in success contents. It This study defined giant character of SF movies and games, it analysed the eight of external characteristics and internal characteristics of giant character in SF movies and games. The external characteristics defined shape, silhouette, size and color, the internal characteristics defined fear, satanism, image and story focus, playfulness. Above, it was structured positioning model of giant character based eight characteristics and analyzation of example of SF movies and games. The elements of positioning model of giant characters are darkness, huge, abnormal, human, animal, fear, satanism, story focused, image focused and playfulness, and this study was proposed these model of elements of eight in SF movies and games.

• Journal of Korea Water Resources Association
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• v.52 no.4
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• pp.301-312
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• 2019

The importance of the dual drainage system model has increased as the urban flood damage has increased due to the increase of local storm due to climate change. The dual drainage model is a model for more accurately expressing the phenomena of surface flow and conduit flow. Surface runoff and pipe runoff are analyzed through the respective equations and parameters. And the results are expressed visually in various ways. Therefore, inundation analysis results of dual drainage model are used as important data for urban flood prevention plan. In this study, the applicability of the COBRA model, which can be interpreted by combining the dual drainage system with the natural watershed and the urban watershed, was investigated. And the results were compared with other dual drainage models (XP-SWMM, UFAM) to determine suitability of the results. For the same watershed, the XP-SWMM simulates the flooding characteristics of 3 types of dual drainage system model and the internal flooding characteristics due to the lack of capacity of the conduit. UFAM showed the lowest inundation analysis results compared with the other models according to characteristics of consideration of street inlet. COBRA showed the general result that the flooded area and the maximum flooding depth are proportional to the increase in rainfall. It is considered that the COBRA model is good in terms of the stability of the model considering the characteristics of the model to simulate the effective rainfall according to the soil conditions and the realistic appearance of the flooding due to the surface reservoir.

• Composites Research
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• v.17 no.2
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• pp.1-8
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• 2004

The present paper is concerned with the optimum design of taper spring, in which the static spring rate of the fiber-reinforcement composite material spring is fitted to that of the steel leaf spring. The thickness and width of springs were selected as design variables. The object functions of the regression model were obtained through the analysis with a common analytic program. After regression coefficients were calculated to get functions of the regression model, optimal solutions were calculated with DOT. E-glass/epoxy and carbon/epoxy were used as fiber reinforcement materials in the design, which were compared and analyzed with the steel leaf spring. The result of the static spring rates show that optimized composite leaf springs agree with steel leaf spring within 1%.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.217-229
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• 2018

This paper aims at applying the data mining such as decision tree, neural network, and logistic regression to an unsold apartment complex in Wirye new town and developing the model forecasting the result of initial sale contract by house unit. Raw data are divided into training data and test data. The order of predictability in training data is neural network, decision tree, and logistic regression. On the contrary, the results of test data show that logistic regression is the best model. This means that logistic regression has more data adaptability than neural network which is developed as the model optimized for training data. Determinants of initial sale are the location of floor, direction, the location of unit, the proximity of electricity and generator room, subscriber's residential region and the type of subscription. This suggests that using two models together is more effective in exploring determinants of initial sales. This paper contributes to the development of convergence field by expanding the scope of data mining.