• Journal of Biosystems Engineering
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• 제38권1호
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• pp.55-63
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• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• Journal of Power Electronics
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• 제12권1호
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• pp.1-9
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• 2012

This study investigates an application of the Hamming network-dual extended Kalman filter (DEKF) based on pattern recognition for high accuracy state-of-charge (SOC)/capacity estimation and state-of-health (SOH) prediction at various temperatures. The averaged nine discharging/charging voltage-temperature (DCVT) patterns for ten fresh Li-Ion cells at experimental temperatures are measured as representative patterns, together with cell model parameters. Through statistical analysis, the Hamming network is applied to identify the representative pattern that matches most closely with the pattern of an arbitrary cell measured at any temperature. Based on temperature-checking process, model parameters for a representative DCVT pattern can then be applied to estimate SOC/capacity and to predict SOH of an arbitrary cell using the DEKF. This avoids the need for repeated parameter measuremet.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권6호
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• pp.417-422
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• 2005

This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

• Smart Structures and Systems
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• 제8권1호
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2290-2292
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• 1998

This paper introduces Two-stage neural network that is capable of recognizing spatio-temporal patterns. First stage takes a spatio-temporal pattern as input and compress it into sparse spatio-temporal pattern. Second stage is for temporal pattern recognition with nonuniform inhibitory connections and different cell sizes. These are basic properties for detecting a embeded pattern in a larger pattern. The network is evaluated by computer simulation.

• 한국지능시스템학회논문지
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• 제13권2호
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• pp.154-162
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• 2003

셀룰라 신경회로망의 연상 메모리를 이용하여 시각적인 입력 데이터의 연산을 통하여 영상 패턴의 분류와 인식을 수행한다. 셀룰라 신경회로망은 일반적인 신경회로망과 같이 비선형 데이터의 실시간 처리가 가능하고, 세포자동자와 같이 이 격자구조의 셀로 이루어져 인접한 셀과 직접 정보를 주고받는다. 응용 분야로는 최적화, 선형/비선형화, 연상 메모리, 패턴인식, 컴퓨터 비전 등에 적용할 수 있다. 영상의 이미지 픽셀을 셀룰라 신경회로망의 셀에 대응하여 전체 이미지 영상을 모든 셀룰라 신경회로망의 셀에서 동시에 병렬로 처리할 수 있어 2-D 이미지 처리에 적합하다. 본 논문은 셀룰라 신경회로망에 의한 연상 메모리 구조를 설계하고, 학습된 하중값 메모리에서 가장 적당한 하중값을 선택하여 학습된 영상과 정확히 일치하는 출력을 얻는 방법을 제시한다. 학습을 통한 연상 메모리 구현에는 각각의 뉴런에서 일정하지 않은 다른 템플릿을 사용한다. 각각의 템플릿은 뉴런들 간의 연결 하중값을 나타내고 학습에 따라 갱신된다. 학습방법으로는 템플릿 하중값 학습에 뉴런들 간의 연결 하중값을 조정하는 가장 단순한 규칙인 Hebb의 학습방법이 사용되었고 분류값 학습에 LMS 알고리즘이 사용되었다.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2006년도 Proceedings of The Convention
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• pp.103-115
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• 2006

$\beta$-Glucan is a glucose polymer that has linkage of $\beta$-(1,3), -(1,4) and -(1,6). As exclusively found in fungal and bacterial cell wall, not in animal, $\beta$-glucans are recognized by innate immune system. Dendritic cells (DC) or macrophages possesses pattern recognition molecule (PRM) for binding $\beta$-glucan as pathogen-associated molecular pattern (PAMP). Recently $\beta$-glucan receptor was cloned from DC and named as dectin-l which belongs to type II C-type lectin family. Human dectin-1 is consisted of 7 exons and 6 introns. The polypeptide of dectin-1 has 247 amino acids and has cytoplasmic, transmembrane, stalk and carbohydrate recognition domains. Dectin-1 could recognize variety of beta-1,3 and/or beta-1,6 glucan linkages, but not alpha-glucans. In our macrophage cell line culture system, dectin-1 mRNA was detected in RA W264.7 cells by reverse transcription-polymerase chain reaction (RT-PCR). Dectin-1 was also detected in the murine organs of spleen, thymus, lung and intestines. Treatment of RA W264.7 cells with $\beta$-glucans of Ganoderma lucidum (GLG) resulted in increased expression of IL-6 and TNF-$\alpha$ in the presence of LPS. However, GLG alone did not increase IL-6 nor TNF-$\alpha$. These results suggest that receptor dectin-1 cooperate with CD14 to activate signal transduction that is very critical in immunoresponse.

• 한국약용작물학회:학술대회논문집
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• 한국약용작물학회 2006년도 Proceedings of The Convention of The Korean Society of Applied Pharmacology
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• pp.103-115
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• 2006

[ ${\beta}-Glucan$ ] is a glucose polymer that has linkage of ${\beta}-(1,3)$, -(1,4) and -(1,6). As exclusively found in fungal and bacterial cell wall, not in animal, ${\beta}-glucans$ are recognized by innate immune system. Dendritic cells (DC) or macrophages possesses pattern recognition molecule (PRM) for binding ${\beta}-glucans$ as pathogen-associated molecular pattern (PAMP). Recently ${\beta}-glucans$ receptor was cloned from DC and named as dectin-l which belongs to type II C-type lectin family. Human dectin-l is consisted of 7 exons and 6 introns. The polypeptide of dectin-l has 247 amino acids and has cytoplasmic, transmembrane, stalk and carbohydrate recognition domains. Dectin-l could recognize variety of beta-l,3 and/or beta-l,6 glucan linkages, but not alpha-glucans. In our macrophage cell line culture system, dectin-l mRNA was detected in RA W264.7 cells by reverse transcription-polymerase chain reaction (RT-PCR). Dectin-l was also detected in the murine organs of spleen, thymus, lung and intestines. Treatment of RA W264.7 cells with ${\beta}-glucans$ of Ganoderma lucidum (GLG) resulted in increased expression of IL-6 and $TNF-{\alpha}$ in the presence of LPS. However, GLG alone did not increase IL-6 nor $TNF-{\alpha}$ These results suggest that receptor dectin-l cooperate with CD14 to activate signal transduction that is very critical in immunoresponse.

• International Journal of Oral Biology
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• 제33권3호
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• pp.77-82
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• 2008

Innate immune response is initiated by the recognition of unique microbial molecular patterns through pattern recognition receptors (PRRs). The purpose of this study is to dissect the expression of various PRRs in gingival epithelial cells of differentiated versus undifferentiated states. Differentiation of immortalized human gingival epithelial HOK-16B cells was induced by culture in the presence of high $Ca^{2+}$ at increased cell density. The expression levels of various PRRs in HOK-16B cells were examined by realtime reverse transcription polymerase chain reaction (RTPCR) and flow cytometry. In addition, the expression of human beta defensins (HBDs) was examined by real time RT-PCR and the amounts of secreted cytokines were measured by enzyme linked immunosorbent assay. In undifferentiated HOK-16B cells, NACHT-LRR-PYDcontaining protein (NALP) 2 was expressed most abundantly, and toll like receptor (TLR) 2, TLR4, nucleotide-binding oligomerization domain (NOD) 1, and NOD2 were expressed in substantial levels. However, TLR3, TLR7, TLR8, TLR9, ICE protease-activating factor (IPAF), and NALP6 were hardly expressed. In differentiated cells, the levels of NOD2, NALP2, and TLR4 were different from those in undifferentiated cells at RNA but not at protein levels. Interestingly, differentiated cells expressed the increased levels of HBD-1 and -3 but secreted reduced amount of IL-8. In conclusion, the repertoire of PRRs expressed by gingival epithelial cells is limited, and undifferentiated and differentiated cells express similar levels of PRRs.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.182-187
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• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for similar model of fifth cell among the twelve cell for automatic test and assemblig in S company.