• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.478-484
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• 1990

An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2047-2051
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• 2009

In this paper, we propose the localization method on WSN(Wireless Sensor Network) using fuzzy model and Kalman filter. The proposed method is as follows: First, we estimate the distance of RSSI(Receive Signal Strength Index) by using fuzzy model in order to minimize the distance error. Second, we use a triangulation measurement for estimating the localization. And then, we minimize the localization error using a Kalman filter. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.359-364
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• 2005

This paper considers a specification test of conditional Poisson regression model for time series count data. Although conditional models for count data have received attention and proposed in several ways, few studies focused on checking its adequacy. Motivated by the test of martingale difference assumption, a specification test via Ljung-Box statistic is proposed in the conditional model of the time series count data. In order to illustrate the performance of Ljung- Box test, simulation results will be provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3730-3744
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• 2020

This study proposes a deep learning-based evolutionary recommendation model for heterogeneous big data integration, for which collaborative filtering and a neural-network algorithm are employed. The proposed model is used to apply an individual's importance or sensory level to formulate a recommendation using the decision-making feedback. The evolutionary recommendation model is based on the Deep Neural Network (DNN), which is useful for analyzing and evaluating the feedback data among various neural-network algorithms, and the DNN is combined with collaborative filtering. The designed model is used to extract health information from data collected by the Korea National Health and Nutrition Examination Survey, and the collaborative filtering-based recommendation model was compared with the deep learning-based evolutionary recommendation model to evaluate its performance. The RMSE is used to evaluate the performance of the proposed model. According to the comparative analysis, the accuracy of the deep learning-based evolutionary recommendation model is superior to that of the collaborative filtering-based recommendation model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.295-298
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• 1995

We performed a research to improve the performance of active bar model which is used in tracking algorithm. Active bar model is a simplified model of snake model. If we used the sctive bar model, the numerical procedure for real time tracking problem can be carried out faster than snake model. However the demerit of active bar algorithms is that we can't used the provious image data because each time it has to reconstruct the active bar. In this paper we proposed advanced algorithm for active bar model. The proposed model can improve tracking abilities by preserving the active bar during the process and changing the energy functional.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.2
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• pp.94-110
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• 1997

In the present study, a mean torque predictive model has been proposed and experimentally validated. It includes induction air mass model, fuel delivery model and mean production mode. Air induction and fuel delivery model considering dynamic behaviors of air induction and fuel delivery were proposed to predict the air-fuel ratio excursions under transient condition. Torque function model reflects thermal efficiency, volumetric efficiency, friction and effect of spark timing. In the spark timing model, knock limit and acceleration retard are included. Experiments were carried out to validate the simulation model for the step changes of throttle at constant engine speed. The results show reasonable agreements between simulation and experiment at fully warmed condition. Using this model, fueling strategies are varied with fast throttle open and it can predict air-fuel ratio excursion and IMEP.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.42-47
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• 2003

In Part 2 of this paper, the dynamic cutting force model, thermal behavior model, and feed drive model used in the development of a virtual machine tool (VMT) are briefly described. Some results are presented to verify the proposed models. Experimental data agreed well with the predicted results fer each model. A comprehensive software environment to integrate the models into a VMT is also proposed.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.157-167
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• 1992

This paper presents a new two-stage randomized response model to protect greater privacy of respondents for the sensitive characters. The conditions when the proposed model will be more efficient than Warner model, Liu-Chow's multiple trial model and Mangat-Singh model have been obtained for the case when the respondents are truthful in their answer, and the efficiency of the proposed model is also compared with Warner model, Liu-Chow's multiple trial model and Mangat-Singh model.

• ETRI Journal
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• v.44 no.4
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• pp.599-612
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• 2022

This study focuses on improving a word embedding model to enhance the performance of downstream tasks, such as those of dialog systems. To improve traditional word embedding models, such as skip-gram, it is critical to refine the word features and expand the context model. In this paper, we approach the word model from the perspective of subword embedding and attempt to extend the context model by integrating various sentence models. Our proposed sentence model is a subword-based skip-thought model that integrates self-attention and relative position encoding techniques. We also propose a clustering-based dialog model for downstream task verification and evaluate its relationship with the sentence-model-based subword embedding technique. The proposed subword embedding method produces better results than previous methods in evaluating word and sentence similarity. In addition, the downstream task verification, a clustering-based dialog system, demonstrates an improvement of up to 4.86% over the results of FastText in previous research.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.1-10
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• 2016

OBJECTIVES : Currently, the market for carbon emissions trading has been increasing. In Korea, it is known that traffic mode rate in bike transportation is low. However, if bike transportation system is encouraged and the traffic mode rate is increased, it would be possible to reduce carbon emissions through the trading market. In this study, a practical policy to activate the bike transportation system in Korea will be proposed and verified. METHODS : Past studies regarding bike transportation system in international and domestic metropolitan cities were analyzed. Moreover, detailed reviews on recent carbon emissions trading market were performed. In particular, SWOT analysis on the bike transportation system in Korea and policy topology analysis were conducted. RESULTS : Based on the literature reviews and SWOT analysis, a new bike transportation policy was proposed. Several actual plans to adopt in Korea were proposed. In addition, a new bike transportation policy was analyzed using policy typology model, and a business model related to the cost of implementing the system and CERs were also proposed. CONCLUSIONS : It is concluded that the proposed bike transportation activation policy and several practical plans to connect CERs and a business model including bus, subway, T-money and bike riders to give some incentive were effective and reasonable. It is desired that this study will help Korea to get CERs through bike transportation activation in the future.