• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.717-722
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• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.

• KSCI Review
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• v.15 no.1
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• pp.191-195
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• 2007

본 논문에서는 영상으로부터 한국적 감성 데이터를 추출하고 감성 컨텐츠 프레임워크(ISC) 구축을 통해 영상데이터를 다양한 멀티미디어 데이터와 함께 사용자에게 전달하는 시스템을 제안한다. 이를 위해 먼저 영상으로부터 객체를 분리해내고 각각의 특징벡터 모델을 구축한다. 특징벡터모델은 요소인자로써 벡터공간의 데이터로 입력되고, 정규화 된 한국어 형용사 데이터와의 근접도를 비교하여 대표 감성을 표현하게 된다. 또한 감성 컨텐츠 데이터의 3층 구조를 이용하여 멀티미디어 데이터를 분류하고 대표 감성형용사와의 인자사상을 통하여 다양한 영상-감성 컨텐츠를 제공하는 프레임워크를 설계한다. 이것은 다양한 영상의 추상데이터에 대응한 감성표현을 추출하여 영상에 내포되어 있는 정확한 의미를 관찰자에게 전달할 수 있다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.4
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• pp.457-463
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• 2012

The basilar membrane (BM), one of organs of cochlea, has the specific positions of the maximum amplitude at each of related frequencies. This phenomenon is due to the geometry of BM. In this study, as the part of the research for the development of fully implantable artificial cochlea which is based on polymer membrane, parametric studies are performed to suggest the desirable artificial basilar membrane model which can detect wider range of frequency separation. The vibro-acoustic characteristics of the artificial basilar membrane are predicted through finite element analysis using commercial software Abaqus. Simulation results are verified by comparing with experimental results. Various geometric shapes of the BM and residual stress effects on the BM are investigated through the parametric study to enable a wider detectable frequency separation range.

• Journal of the Korean Institute of Gas
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• v.17 no.1
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• pp.56-66
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• 2013

The gas production plants supply the inert gas to production plants for maintaining safe operation and also supply combustible, flammable, explosive and toxic gases as functions of basic materials needed for producing chemical goods. In addition, gas plants need to be safe and reliable operation because they are operated under high temperature, high pressure, cryogenic and catalytic reactions. As these plants have a complex process in operation, there has been a risk that major industrial accidents such as a fire, explosion and toxic gas released, also risks of asphyxiations by inert gases and burns caused by high temperature and cryogenic substances. This study is to carry out the semi quantitative risk assesment method which is the generic risk analysis (GRA). This method is applied to air separation unit(ASU) to identify its initial risk, safety barriers, residual risk and elements important for safety(EIS). The result of this study, suggested the management tools and procedures of implementation for EIS management.

• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.365-370
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• 2017

This study analyze correlation between weekdays data and special days data of different power demand patterns, and builds a separate data set, and suggests ways to reduce power demand prediction error by using deep learning network suitable for each data set. In addition, we propose a method to improve the prediction rate by adding the environmental elements and the separating element to the meteorological element, which is a basic power demand prediction elements. The entire data predicted power demand using LSTM which is suitable for learning time series data, and the special day data predicted power demand using DNN. The experiment result show that the prediction rate is improved by adding prediction elements other than meteorological elements. The average RMSE of the entire dataset was 0.2597 for LSTM and 0.5474 for DNN, indicating that the LSTM showed a good prediction rate. The average RMSE of the special day data set was 0.2201 for DNN, indicating that the DNN had better prediction than LSTM. The MAPE of the LSTM of the whole data set was 2.74% and the MAPE of the special day was 3.07 %.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.397-400
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• 2010

The changing light condition of scene cause the luminance fluctuation of the captured image sequences. this artifact is called flicker, and would be easily recognized as visually unstable fluctuation. As the flicker degrades the performance of extracting useful information from image sequences, such as motion information or segmentation, it should be correction and linear flicker model. The algorithm model the flicker effects as a linear system with gain and offset parameter and estimates gain parameter with Gamma correction. The flicker reduction is performed by applying these parameters inversely th the ordinal sequences. To show the performance, we test out algorithm th the ground-truth sequences with the artificially added luminance fluctuation and real sequence with object motion.

• Journal of the HCI Society of Korea
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• v.6 no.1
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• pp.9-16
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• 2011

The previous researches of 3D object modeling have been performed in a limited environment where a target object only exists. However, in order to model an object in the real environment, we need to consider a dynamic environment, which has various objects and a frequently changing background. Therefore, this paper presents a segmentation and tracking method for a foreground which includes a target object in the dynamic environment. By using depth information than color information, the foreground region can be segmented and tracked more robustly. In addition, the foreground region can be tracked on the sequential images by referring depth distributions of the foreground region because both the position and the status in the consecutive images of the foreground region are almost unchanged. Experimental results show that our proposed method can robustly segment and track the foreground region in various conditions of the real environment. Moreover, as an application of the proposed method, it is presented a method for modeling an object extracting the object regions from the foreground region that is segmented and tracked.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.81-86
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• 2007

Hollow fiber membrane G-L contactors are widely used to remove $SO_2$ emitted from industrial facilities. In this work, the mathematical modeling and computer simulation for hollow membrane G-L contactors is carried out to analyze $SO_2$ absorption behavior in hollow fiber membranes. The model is solved with the finite element method using a commercial software. Investigated is the dependency of $SO_2$ removal efficiency and mass transfer characteristics on gas velocities, membrane mass transfer coefficients and physical properties of contactors. The membrane mass transfer coefficients are estimated by fitting the experimental data with the simulated $SO_2$ removal efficiencies. In addition, a design methodology of membrane contactors is suggested.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• Journal of the Korean Society for Advanced Composite Structures
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• v.2 no.2
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• pp.1-6
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• 2011

This study aims at predicting structural behaviors of RC (Reinforced Concrete) beams retrofitted with hybrid FRPs (Fiber Reinforced Polymers). Toward this goal, structural analysis for the RC beams retrofitted with hybrid FRPs are performed and validated using existing experimental data. For the analysis, failure models due to debonding of FRPs and concrete separation are implemented within FE (Finite Element) model, based on Smith and Teng, model, and Teng and Yao model, respectively. Nonlinear material and geometrical effects are also included in the analysis. The suggested modeling approaches are able to predict structural behaviors of RC beams retrofitted with hybrid FRPs similar to the experimental data, however, a numerical model needs to be developed in order to predict failure strength of RC beams retrofitted with hybrid FRPs accurately.