• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.15-20
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• 1999

This paper presents a climate change information system that provides the data and information about climate change. The system shows the meteorologic data observed, climate change research institutes, and research programs. As the result of analyzing the meteorologic data, it also provides users with the climate change information using the graphic and multimedia data. The terminology retrieval and dictionary facility in the climate change can be useful to the users who are interested in the climate change.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.123-139
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• 1999

Recently, implementing ERP(Enterprise Resource Planning) systems has been one of major concerns of many companies. Despite the trend in the business area, few theoretical researches about the ERP have been published to date. The primary propose of current study, therefore, lies in examining the effects of change management characteristics on ERP performance. Top management support, user participation, and consulting support were selected as change management characteristics. Additionally, ERP implementation characteristics were considered as contingency variables which may moderate the relationships between change management characteristics and ERP performance. Two ERP implementation characteristic variables introeuced in this study were ERP implementation approach and ERP implementation strategy. Hypotheses concerning the relationships among those variables of change management characteristics. ERP performance and ERP implementation characteristics were empirically tested. The findings show that change management characteristics are strongly correlated with ERP performance, and ERP implementation characteristics have contingency effects, partially at least, on the relationship between change management characteristics and ERP performance.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.543-556
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• 2001

This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.5
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• pp.46-52
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• 2003

In this work we developed the closed-loop model of a paper machine during grade change with the intention to provide a reliable dynamic model to be used in the model-based grade change control scheme. During the grade change, chemical and physical characteristics of paper process change with time. It is very difficult to represent these characteristics on-line by using physical process models. In this work, the wet circulation part and the drying section were considered as a single process and closed-loop identification technique was used to develop the grade change model. Comparison of the results of numerical simulations with mill operation data demonstrates the effectiveness of the model identified.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2362-2367
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• 2005

This paper reports a technique for discriminating double talk and echo path change using the stochastic characteristics of power change for an adaptive noise canceller. The causes of rapid error increasing are double talk and echo path change. When the echo path is changed, the system corrects the impulse response in order to reduce the error. However, in the case of double talk, the system has to suspend the updating impulse response in order to maintain the quality of the voice signal. In the conventional system, it was difficult to discriminate between the two situations. In this research, the stochastic characteristics of the voice power change in the double talk period were experimentally verified to be different from the power change during echo path changing. Based on the results, a new double talk detection method is proposed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.466-469
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• 2004

In this paper, real-time voice change method using pitch change technique is proposed to change one's voice to the other voice. For this purpose, sampling rate change method using DFT (Discrete Fourier Transform) method and time scale modification method using SOLA (Synchronized Overlap and Add) method is combined to change pitch. In order to evaluate the performance of the proposed method, voice transformation experiments were conducted. Experimental results showed that original speech signal is changed to the other speech signal in which original speaker's identity is difficult to find. The system is implemented using TI TMS320C6711DSK board to verify the system runs in real time.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.641-651
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• 2003

This study suggests the hybrid models for interest rate forecasting using structural changes (or change points). The basic concept of this proposed model is to obtain significant intervals caused by change points, to identify them as the change-point groups, and to reflect them in interest rate forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in the U. S. Treasury bill rate dataset. The second phase is to forecast the change-point groups with data mining classifiers. The final phase is to forecast interest rates with backpropagation neural networks (BPN). Based on this structure, we propose three hybrid models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported model, (2) case-based reasoning (CBR)-supported model, and (3) BPN-supported model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the prediction ability of hybrid models to reflect the structural change.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.1-1
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result,the annual change pattern of precipitation days in Korea is classified into 8 types from A to e,in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC,into detail, 41 regions from I no to IIICl.

• Journal of Environmental Science International
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• v.4 no.5
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• pp.387-402
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result, the annual change pattern of precipitation days in Korea is classified into 8 types from A to e, in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC, into detail, 41 regions from I no to IIICl.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.12-14
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• 2006

This paper presents a novel scene change detection method using intra prediction mode and edge direction in H.264/AVC. When scene change occurs, there are less temporal correlation between frames, most of macro-blocks encoded in intra mode. Using this property, the method calculates the percentage of intra mode blocks in each predictive frame in order to get candidates of scene change frame. To further find scene change, we obtain edge histogram of each candidates by using eight prediction direction of intra prediction mode in H.264/AVC. We detect scene change frames with $\iota^1$-norm of edge histograms. The experimental results show that the method is efficient and robust.