• English Language & Literature Teaching
• /
• v.10 no.1
• /
• pp.153-178
• /
• 2004

The purpose of the present study is to develop several types of English teaching/learning models in view of cross-curricular approach in Korean elementary school. Brewster(1992)' model is suitable for younger children as well as the 1st or 2nd graders. For 3rd or 4th graders, Halliwel1(1997)' model seems more proper type in Korean EFL situation. There has been studying for cross-curricular approach in elementary English education. Many studies has recently focused the characteristics of elementary students by cognitive and psychological perspectives. Among them, Park(1996)'s research talks about the elementary school students. Han(1996)'s research based on the notion of applied to other subjects. Kim(1999)'s also emphasized the importance of linking other subjects. Kim(2003) argued the need of integrating English with other subjects. The elementary education as the National Common Basic Curriculum(NCBC) has the essence of cross-curricular approach, so the English education will be linked with other subject matters more and more, not just as for Communicative function based English education but as both content and function based subject matter.

• Journal of Mechanical Science and Technology
• /
• v.14 no.11
• /
• pp.1225-1231
• /
• 2000

This paper proposes a V-shaped Lyapunov function approach for the model-based control of flexible-joint robots, in which a new model-based nonlinear control scheme is designed based on a V-shaped Lyapunov function. The proposed control guarantees global asymptotic stability for link trajectory control while keeping all internal signals bounded. Since joint flexibility is used as a control parameter, the proposed control is not restricted by the degree of joint flexibility and be applied to flexibility-joint, partly-flexibility, or rigid-joint robots without modification. the effectiveness of the proposed control has been by computer simulation.

• Journal of Information Technology Applications and Management
• /
• v.31 no.1
• /
• pp.1-9
• /
• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Communications for Statistical Applications and Methods
• /
• v.24 no.4
• /
• pp.339-351
• /
• 2017

Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.

• Journal of Korean Society of Transportation
• /
• v.12 no.2
• /
• pp.47-63
• /
• 1994

The purposes of this study are to identify Traffic Flow characteristics and to develop approach delay model of unsignalized intersection based on the travel speed in the conflicting area. The results of this study are as following ; 1. The cumulative frequency distributions of Left-turning speed show a few differences among approaches and they are distributed to lower range of speeds. On the other hand, those of through speed show obvious differences among bounds. The similar results also show in the analysis of Percentile speed. 2. The effectiveness of conflicting movements to travel speed in the conflicting area are analyzed using regression analysis. Left-turning speed model shows that Left-and Right-Conflicting speed. Through-speed model is also developed, when approaching through volume is less than 420vph. 3. Since the lost time due to the acceleration stop, and decelerlation is occured in the conflicting area, approach delay model is delivered using the travel speed models under the condition of small queuing delay.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.2
• /
• pp.240-245
• /
• 2012

A 160 MW drum-type boiler-turbine system is developed in the present research through a multi-multivariable dynamic matrix control (DMC) scheme and a multi-multivariable model approach. A novel intelligence-based decision mechanism (IBDM) is realized to support both model approach and control scheme. In such case, the responsibility of the proposed IBDM is to identify the best multivariable model of the system and the corresponding multivariable DMC scheme to cope with the system at each instant of time in an appropriate manner.

• Communications for Statistical Applications and Methods
• /
• v.24 no.1
• /
• pp.67-80
• /
• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• Korean Journal of Computational Design and Engineering
• /
• v.5 no.1
• /
• pp.12-22
• /
• 2000

Network and Internet technology opens up another domain for building future CAD/CAM environment. The environment will be global, network-centric, and spatially distributed. In this paper, we present an approach for network-centric feature-based modeling in a distributed design environment. The presented approach combines the current feature-based modeling technique with distributed computing and communication technology for supporting product modeling and collaborative design activities over the network. The approach is implemented in a client/server architecture, in which Web-enabled feature modeling clients, neutral feature model server, and other applications communicate with one another via a standard communication protocol. The paper discusses how the neutral feature model supports multiple views and maintains naming consistency between geometric entities of the server and clients. Moreover, it explains how to minimize the network delay between the server and client according to incremental feature modeling operations.

• MALSORI
• /
• no.62
• /
• pp.97-112
• /
• 2007

The speech recognizer in general operates in noisy acoustical environments. Many research works have been done to cope with the acoustical variations. Among them, the multiple-HMM model approach seems to be quite effective compared with the conventional methods. In this paper, we consider a multiple-model approach combined with the model compensation method and investigate the necessary number of the HMM model sets through noisy speech recognition experiments. By using the data-driven Jacobian adaptation for the model compensation, the multiple-model approach with only a few model sets for each noise type could achieve comparable results with the re-training method.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.23 no.6
• /
• pp.579-592
• /
• 2010

This paper presents a multi-phase model update approach for system identification of prestressed concrete (PSC) girders under various prestress forces. First, a multi-phase model update approach designed on the basis of eigenvalue sensitivity concept is newly proposed. Next, the proposed multi-phase approach is evaluated from controlled experiments on a lab-scale PSC girder for which forced vibration tests are performed for a series of prestress forces. On the PSC girder, a few natural frequencies and mode shapes are experimentally measured for the various prestress forces. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model which is established for the target PSC girder. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model update procedure. Based on model update results, the relationship between prestress forces and model-updating parameters is analyzed to evaluate the influence of prestress forces on structural subsystems.