• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2941-2946
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• 2007

A model of the cardiovascular system coupling cell, hemodynamics and autonomic nervecontrol function is proposed for analyzing heart mechanics. We developed a comprehensive cardiovascular model with multi-physics and multi-scale characteristics that simulates the physiological events from membrane excitation of a cardiac cell to contraction of the human heart and systemic blood circulation and ultimately to autonomic nerve control. Using this model, we delineatedthe cellular mechanism of heart contractility mediated by nerve control function. To verify the integrated method, we simulated a 10% hemorrhage, which involves cardiac cell mechanics, circulatory hemodynamics, and nerve control function. The computed and experimental results were compared. Using this methodology, the state of cardiac contractility, influenced by diverse properties such as the afterload and nerve control systems, is easily assessed in an integrated manner.

• Korean Journal of Cognitive Science
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• v.7 no.3
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• pp.37-60
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• 1996

From the biopsychological point of view,learning could be defined as the processes to transfer the information that we obtain from environment to the neural circuits in the brain.In the studies to determine the biological substrates of learning and memory,there was a remarkable effort to identify neural circuits related with a specific type of learning and to describe the mechanixm of neural plasticity of learning and memory,under the assumption that the memory orinformation may be stored as a modificationof neural synapes in the central nerviys system.On the other hand,there was a different kind of tendency to analyze the mechanism of interactions between neural substrates involved in learning and memory,under the assumption that a specific information may be represented in the patterns of comples neural network of the central nervous system.The present review,in the former position.focused on the research methods and the chracteristics and finding of the investigations employing animal model systems to indentify the essential site of engram for learning and memory.Specifically,the review presents major advances in ourunderstanding of the memory trace circuit for a specific type of learning,with the use of animal model system,the detemination of the critical lodi of neuaral plastic chabges In learing abd memory,and the neurophysiological an biocemical mechanixms of the neural modifia by learint.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.95-98
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• 2009

본 연구는 주관 감성에 따른 생리 데이터의 패턴을 분류하고, 임의의 생리 데이터의 패턴을 확인하여 각성-이완, 쾌-불쾌의 감성을 추론하기 위해 베이지안 이론(Bayesian learning)을 기반으로 한 추론 모델을 제안하는 것이 목적이다. 본 연구에서 제안하는 모델은 학습데이터를 분류하여 사전확률을 도출하는 학습 단계와 사후확률로 임의의 생리 데이터의 패턴을 분류하여 감성을 추론하는 추론 단계로 이루어진다. 자율 신경계 생리변수(PPG, GSR, SKT) 각각의 패턴 분류를 위해 1~7로 정규화를 시킨 후 선형 관계를 구하여 분류된 패턴의 사전확률을 구하였다. 다음으로 임의의 사전 확률 분포에 대한 사후 확률 분포의 계산을 위해 베이지안 이론을 적용하였다. 본 연구를 통해 주관적 평가를 실시하지 않고 다중 생리변수 인식을 통해 감성을 추론 할 수 있는 모델을 제안하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.153-156
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• 2007

인간의 시각 시스템은 선택적 주의 집중에 의해 시각 수용체로 도달되는 많은 물체들 중에서 필요한 정보만을 추출하여 원하는 작업을 수행한다. Itti와 Koch는 시각적 주의를 제어할 수 있는, 신경계를 모방한 계산적 모델을 제안하였으나 조명환경에 고정적인 saliency map을 구성하였다. 따라서, 본 논문에서는 영상에서 ROI(region of interest)을 탐지하기 위한 조명환경에 적응적인 saliency map 모델을 구성하는 기법을 제시한다. 변화하는 환경에서 원하는 특징을 부각시키기 위하여 상황에 적응적인 동적 가중치를 부여한다. 동적 가중치는 conspicuity map에 S.K. Chang이 제안한 PIM(Picture Information Measure)을 적용시켜 정보량을 측정한 후, 이에 따라 정규화된 값을 부여함으로써 구현한다. 제안하는 조명환경에 강인한 적응적인 saliency map 모델 구현의 성능을 얼굴검출 실험을 통하여 검증하였다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.189-192
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• 2000

본 논문에서는 청각 장애인의 보다 향상된 보청 환경을 조성하고자 청각손실을 심리음향 모델을 적용하여 감음 신경성 난청을 보정하는 알고리즘을 제안한다. 제안한 알고리즘에서는 난청의 유형은 내이에서부터 중추 뇌에 걸친 감음계와 신경계의 장애에서 비롯되는 감음신경성 난청(sensorineural hearing loss)으로 주파수 영역상에서 MTH(minimum hearing threshold)가 균일하지 않게 상승하게되어 가청영역이 좁아지는 문제점을 해결하기 위한 방법으로 각각의 주파수 밴드마다 멀티밴드 압축 알고리즘을 적용하였다. 그러나 이 경우 각각의 주파수 밴드에 따른 서로 다른 가청 영역의 영향에 의한 변형된 스펙트럼 모양으로 인해 spectral contrast reduction과 변형된 마스킹 특성으로 인해 음성 변별력에 제한을 가하게 된다. 이것은 주변 주파수 성분들에 의한 마스킹 효과에 의한 것으로, 신호에 대한 난청인이 느끼는 지각 영역(perceptual domain)에서의 해석과 심리음향 모델 파라미터를 통한 보청기의 개발이 이루어져야 하며, 본 논문에서 그 알고리즘을 적용하였다.

• Proceedings of the Ginseng society Conference
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• 1984.09a
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• pp.233-249
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• 1984

To find out the effects of ginsenosides to some parameters of the haemodynamic and gas exchange depending to the autonomic nervous system - and to border it against the psychosomatic nervous ways was the idea of these studies. The lot of the effects are very differentiated, so that we have to find out the special ginsenoside receptors in that system.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.452-460
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• 1994

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading To automatically extract a road map directly from more complicated topographical maps, a very complicated algorithm is needed, since the image generally involves such complicated patterns as symbols, characters, residential sections, rivers, railroads, etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• Progress in Medical Physics
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• v.10 no.3
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• pp.141-149
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• 1999

This research analyzed the HRV signals by using wavelet transform to observe the activities of autonomous nervous system in a sleep state. This research also restructured the HRV signals from electrocardiogram and by using coefficient which was obtained through wavelet transform, analyzed the signals by frequency bandwidth. Then compared the analyzed results with existing frequency analyzing method using AR model techniques. The suggested wavelet coefficient from power spectrum component in the study shows a similar tendency with the results from FFT or AR model technique. Therefore, it can be found that power spectrum analyzing method by wavelet coefficient is a useful as a tool for analyzing autonomous nervous system activities using HRV signals. Since the suggested method able to clearly depict the progression of change in time zone, which was once impossible with the existing methods, it is presumed that it will be useful in other physiological signals.

• Therapeutic Science for Rehabilitation
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• v.1 no.1
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• pp.39-56
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• 2012

Introduction : Animal studies cannot be applied directly to Occupational Therapy(OT) intervention protocol. However, animal models still provide essential evidences and knowledge to improve OT practice and to develop OT theories as well as human studies do. The purpose of this scholarly paper is to explore the potential of animal models to inform OT theory and practice particularly as it relates to neuroscience. Body : The animal models provide related knowledge for a better understanding of the mechanism of diseases and related neural networks. Based on this knowledge, researchers can test their hypothesis of neural disease. In addition, accumulated animal studies contribute to introduce the new approaches to human diseases and to improve the effectiveness of treatment. Conclusions : Animal models of neurological disease are critical and have the potential to improve OT practice and theory in many ways. Therefore, OT researchers need to pay more attention to animal models in addition human studies.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.543-549
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• 2013

Motion artifacts of central and autonomic nervous system signals degrades the performance of the bio-signal based human factor analysis. Firstly, we propose a defining method of motion artifact section by analyzing successive image frames. Motion artifact section is defined when the amount of motion is greater than the pre-defined threshold. In here, the amount of motion is estimated by first derivation of image frames at temporal domain. Secondly, we propose another defining method of motion artifact section through designing 2D Gaussian probability density function model by analyzing feature vectors of one cycle of signal such as length and amplitude. The defined motion artifact sections are interpolated on the basis of 1D Gaussian function. At result of applying the method into photoplethysmography signal, we confirmed that the calculated heartbeat rate from the restored photoplethysmography came up to the one from electrocardiography. Also, we found that the video based method generated relatively more false acceptance of motion artifact section and the probability density function based method generated relatively more false rejection of motion artifact section.