• English Language & Literature Teaching
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• v.17 no.1
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• pp.37-52
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• 2011

The purposes of this study were to review developmental stages of acculturation, to establish dimensions and components of intercultural communicative competence, and to suggest teaching methods in the elementary school based on the dimensions and the components of the stages. In order to achieve these purposes, theoretical research on the nature of intercultural communicative competence and teaching methods of intercultural dimensions and components was carried out in terms of developmental stages of acculturation. The stages of acculturation have relation to cognitive domain, affective domain, and cultural awareness. In the domain of cognitive development, the models such as Cummins (1981), Wong-Fillmore (1983), and Ausubel (1968) were presented. In the affective domain of second language research, the models of Gardener and Lambert (1972), Maslow (1954), and Bloom (1974) were argued. Modifying the models of Ausubel, Cummins, Wong-Fillmore, the dimensions and components of intercultural communicative competence were established. In addition, it was suggested that cultural syllabus and lesson plan based on tourist and survivor stage should be considered.

• Phonetics and Speech Sciences
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• v.2 no.2
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• pp.27-36
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• 2010

The purpose of this study is to investigate the features of Korean infants' vocalizations according to the stages models. A total 88 infants, whose ages range from 1 to 18 months, participated in this study. This age is a critical period for vocal development. However, the study of infants' vocalizations has typically focused on children over the age of two. Because of restrictions related to the study of younger infants, from birth to the age of two, it is usually difficult to investigate what are the major features of their vocal development. Therefore, this study provides documentation and analysis of the features of infant vocalization and their vocal development stages. The results shows that the stages model of Oller & Lynch (1992) might be adapted for Korean infants' vocal development. Furthermore, the features of the infants' vocalization are not linearly appeared one stage to the next stage, but are overlapped (Koopmans-van Beinum & van der Stelt, 1986; Nathani et al., 2006; Oller, 1980; Stark, 1980; Vihman, 1996).

• Korean Journal of Child Studies
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• v.33 no.3
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• pp.131-148
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• 2012

This study examines the scientific concept development of young children in terms of the day-night cycle. The subjects consisted of 180 three-, four-, and five-year-old children from two kindergartens and one children's center located in Seoul and Jeju. Individual interviews were conducted to collect verbal and pictorial responses on the day-night cycle. The scientific concepts on the day-night cycle are classified five stages including : no recognition, egocentric concept, initial mental models, synthetic mental models, and scientific mental models. Using two-way ANOVA, scores for the types of concept on the day-night cycles were then analyzed according to both the ages and genders of the children. The results reveal the existence of significant differences in terms of the types of concept of young children according to age. Most three-year-olds children had no recognition. Most three, four, and five-year-old children revealed egocentric concepts. Four-year-old children revealed that were in the initial stages of experiencing the mental models and synthetic mental models of the day-night cycle. Five-year-old children revealed that they were in the early stages of experiencing the initial, synthetic, scientific mental models of the day-night cycle. The results suggest appropriate ways of science education for young children based on the development of scientific concepts of the day-night cycle.

• Journal of KIBIM
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• v.9 no.4
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• pp.41-50
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• 2019

Digital models for a cable-stayed bridge are defined considering data-driven engineering from design to construction. Algorithms for digital object generation of each component of the cable-stayed bridge were developed. Using these algorithms, Level-3 BIM practices can be realized from design stages. Based on previous practices, digital object library can be accumulated. Basic digital models are modified according to given design conditions by a designer. Once design models are planned, various applications using the models are linked the models such as estimation, drawings and mechanical properties. Federated bridge models are delivered to construction stages. In construction stage, the models can be efficiently revised according to the changed situations during construction phases. In this paper, measured coordinates are imported to the model generation algorithms and revised models are obtained. Augmented reality devices and their applications are proposed. AR simulations in construction site and in office condition are tested. From this pilot test of digital models, it can be said that Level-3 BIM practices can be realized by using in-house modeling algorithms according to different purposes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.73-80
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• 1994

Sequentiality in decision making is an inherent characteristic of the R&D Process, Conceptual changes are noted during the Course of the Project which represent a continuous improvement in the quality of the data available during the various project stages. In this paper, Eight characteristic types of project evaluation models have been developed economic index models, portfolio models, decision theory models, risk analysis models, frontier models, scoring models, profile models and checklists. Each of these will be critically reviewed and appraised.

• Journal of the Korean Institute of Educational Facilities
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• v.25 no.6
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• pp.35-44
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• 2018

The purpose of this study is to predict more accurate construction costs and to support efficient decision making in the planning and design stages of smart education facilities. The higher the error in the projected cost, the more risk a project manager takes. If the manager can predict a more accurate construction cost in the early stages of a project, he/she can secure a decision period and support a more rational decision. During the planning and design stages, there is a limited amount of variables that can be selected for the estimating model. Moreover, since the number of completed smart schools is limited, there is little data. In this study, various artificial intelligence models were used to accurately predict the construction cost in the planning and design phase with limited variables and lack of performance data. A theoretical study on an artificial neural network and deep learning was carried out. As the artificial neural network has frequent problems of overfitting, it is found that there is a problem in practical application. In order to overcome the problem, this study suggests that the improved models of Deep Neural Network and Deep Belief Network are more effective in making accurate predictions. Deep Neural Network (DNN) and Deep Belief Network (DBN) models were constructed for the prediction of construction cost. Average Error Rate and Root Mean Square Error (RMSE) were calculated to compare the error and accuracy of those models. This study proposes a cost prediction model that can be used practically in the planning and design stages.

• Korean Management Science Review
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• v.11 no.1
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• pp.107-115
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• 1994

Stochastic manufacturing systems are generally formulated as performance models of discrete event systems. In this paper, logical models(as opposed to performance models) of kanban systems are presented which are deterministic and untimed but not stochastic and timed. As a result, the first and second order properties of kanban systems are showed which can be fruitfully applied to the analysis and design of kanban systems.

• Computers and Concrete
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• v.32 no.5
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• pp.513-525
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• 2023

Recently, research on predicting the behavior of reinforced concrete (RC) columns using machine learning methods has been actively conducted. However, most studies have focused on predicting the ultimate strength of RC columns using a regression algorithm. Therefore, this study develops a successive machine learning process for predicting multiple nonlinear behaviors of rectangular RC columns. This process consists of three stages: single machine learning, bagging ensemble, and stacking ensemble. In the case of strength prediction, sufficient prediction accuracy is confirmed even in the first stage. In the case of displacement, although sufficient accuracy is not achieved in the first and second stages, the stacking ensemble model in the third stage performs better than the machine learning models in the first and second stages. In addition, the performance of the final prediction models is verified by comparing the backbone curves and hysteresis loops obtained from predicted outputs with actual experimental data.

• Smart Structures and Systems
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• v.6 no.1
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• pp.17-27
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• 2010

The approach to damage detection and localization adopted in this paper is based on a statistical comparison of models built from the response time histories collected at different stages during the structure lifetime. Some of these time histories are known to have been recorded when the structural system was undamaged. The consistency of the models associated to two different stages, both undamaged, is first recognized. By contrast, the method detects the discrepancies between the models from measurements collected for a damaged situation and for the undamaged reference situation. The damage detection and localization is pursued by a comparison of the SSE (sum of the squared errors) histograms. The validity of the proposed approach is tested by applying it to the analytical benchmark problem developed by the ASCE Task Group on Structural Health Monitoring (SHM). In the paper, the results of the benchmark studies are presented and the performance of the method is discussed.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.54-60
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• 1998

PSC box bridges by MSS construction method in high-speed railway may not be cast in place at one step. Web and bottom flange(U member) in the cross section are cast in place at first, then top flange will be cast in place later with some time lag. In this section, stress distributions of U member and top flange are different with those in generally complete cast in place cross section. In the composite section composed of two different aged members, the redistribution of stresses takes place. This results from time-dependent strain characteristics of concrete and the effects of forces applied at the various stages. For comparison in the present paper, two models, one with the composite cross section and the other with generally complete cast in place cross section, are analyzed. The longitudinal stress differences of two models on considering construction stages are compared. As the analysis results show the considerable differences in the stresses of cross section between two models, the composition of cross section is considered for rational design of PSC box girder bridge.