• Journal of Plant Biotechnology
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• v.34 no.3
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• pp.201-205
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• 2007

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts of higher plants is applied to discriminate plants genetically, leaf samples of eight cultivars of Catharanthus roseus were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR fingerprint region data were analyzed by principal component analysis (PCA). Major peaks as biomarkers were identified as the most significant contributors to distinguish samples by using genetic programming. A hierarchical dendrogram based on the results from PCA separated the eight cultivars into two major groups in the same manner as the dendrograms based on genetic fingerprinting methods such as RAPD and AFLP. A slight difference between the dendrograms was found only in branching pattern within each subgroup. Therefore, we conclude that the hierarchical dendrogram based on PCA of the FT-IR data represents the most probable chemotaxonomical relationship between cultivars, which is in general agreement with the genetic relationship determined by conventional DNA fingerprinting methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.249-254
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• 2014

We have studied on the possibility of railway stability system using RFID tag. UHF RFID tag was desinged, manufactured and tested. Proposed UHF tag antenna has PIFA type structure and inset feed multi matching technique was attempted for impedance matching of antenna. The impedance bandwidth (VSWR < 3) of the proposed tag antenna covers 917~923 MHz. Measured peak gain is 3.225 dBi and UHF band with an omni-directional radiation pattern. RFID reader and tag installed in motor car and track, respectively. Then, tag recognition rate according to velocity of car (under 45 km/h) represented 100 %.

• BMB Reports
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• v.50 no.2
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• pp.55-57
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• 2017

Toll-like receptor 4 (TLR4) together with MD2, one of the key pattern recognition receptors for a pathogen-associated molecular pattern, activates innate immunity by recognizing lipopolysaccharide (LPS) of Gram-negative bacteria. Although LBP and CD14 catalyze LPS transfer to the TLR4/MD2 complex, the detail mechanisms underlying this dynamic LPS transfer remain elusive. Using negative-stain electron microscopy, we visualized the dynamic intermediate complexes during LPS transfer-LBP/LPS micelles and ternary CD14/LBP/LPS micelle complexes. We also reconstituted the entire cascade of LPS transfer to TLR4/MD2 in a total internal reflection fluorescence (TIRF) microscope for a single molecule fluorescence analysis. These analyses reveal longitudinal LBP binding to the surface of LPS micelles and multi-round binding/unbinding of CD14 to single LBP/LPS micelles via key charged residues on LBP and CD14. Finally, we reveal that a single LPS molecule bound to CD14 is transferred to TLR4/MD2 in a TLR4-dependent manner. These discoveries, which clarify the molecular mechanism of dynamic LPS transfer to TLR4/MD2 via LBP and CD14, provide novel insights into the initiation of innate immune responses.

• The Journal of Korean Medicine
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• v.27 no.2 s.66
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• pp.134-144
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• 2006

Tongue diagnosis is an important diagnostic method in traditional Oriental medicine. It has been especially accepted that quantitative analysis of tongue images allows the accurate diagnosis of the exterior-interior and cold-heat patterns of a patient. However, to ensure stable and reliable results, the color reproduction of such images must first be error-tree. Moreover, tongue diagnosis is much influenced by the surrounding illumination and subjective color recognition, so it has to be performed objectively and quantitatively using a digital diagnostic machine. In this study, 457 tongue images of outpatients were collected using the Digital Tongue Inspection System. Through statistical analysis, the result shows that the heat and cold patterns can be distinguished clearly based on the hue value of the tongue images. The average hue value (1.00) of the tongue's image in the cold pattern is higher than that in the heat pattern (0.99).

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.243-260
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• 2018

Detection of damages in fibre reinforced plastic (FRP) composite structures is important from the safety and serviceability point of view. Usually, damage is realized as a local reduction of stiffness and if dynamic responses of the structure are sensitive enough to such changes in stiffness, then a well posed inverse problem can provide an efficient solution to the damage detection problem. Usually, such inverse problems are solved within the framework of pattern recognition. Support Vector Machine (SVM) Algorithm is one such methodology, which minimizes the weighted differences between the experimentally observed dynamic responses and those computed using the finite element model- by optimizing appropriately chosen parameters, such as stiffness. A damage detection strategy is hereby proposed using SVM which perform stepwise by first locating and then determining the severity of the damage. The SVM algorithm uses simulations of only a limited number of damage scenarios and trains the algorithm in such a way so as to detect damages at unknown locations by recognizing the pattern of changes in dynamic responses. A rectangular fiber reinforced plastic composite plate has been investigated both numerically and experimentally to observe the efficiency of the SVM algorithm for damage detection. Experimentally determined modal responses, such as natural frequencies and mode shapes are used as observable parameters. The results are encouraging since a high percentage of damage cases have been successfully determined using the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.747-752
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• 2011

HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.

• Journal of Korean Academy of Nursing
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• v.39 no.2
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• pp.217-228
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• 2009

Purpose: Guided by Newman's theory of health as expanding consciousness, this study was done to explore the health experience of adolescents having depression. Methods: The researcher engaged in six to eight in-depth interviews with six adolescents. To begin the dialog, the researcher asked each participant to recount the first important memory he/ she had. All the narrative and diagram sharing between the researcher and participants were summarized according to recognized patterns and later elaborated in following interviews based on Newman's praxis methodology. Results: The significant individual pattern of early health experience was during the binding stage. At the turning point, individual patterns for participants revealed a personal journey of self-discovery and then emergence of reflecting behaviors. After the turning point, the participants changed as they evolved from the initial period of disruption and disorganization to organization at a higher level. The results suggest that adolescents who are depressive find new ways of relating to friends, family, healthcare providers, and the community by expanding their consciousness. Conclusion: Newman's praxis methodology is a good way of helping and studying adolescents with depression because it emphasizes participant-nurse/researcher partnership and pattern recognition as nursing practice.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.13-21
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• 1995

In this paper, we improve an image classifier algorithm based on neural network learning. It consists of two steps. The first is input pattern generation and the second, the global neural network implementation using an improved back-propagation algorithm. The feature vector for pattern recognition consists of the codebook data obtained from self-organization feature map learning. It decreases the input neuron number as well as the computational cost. The global neural network algorithm which is used in classifier inserts a control part and an address memory part to the back-propagation algorithm to control weights and unit-offsets. The simulation results show that it does not fall into the local minima and can implement easily the large-scale neural network. And it decreases largely the learning time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.407-412
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• 2009

Recently, in Weld Processing field, unmanned and automatic system construction has experienced the rapid growth, and diverse signal processing has been employed in order to translate the exact weld pattern. In this paper, We will suggest the effective neural network which can decide the weld quality in arc weld and monitoring system in real time. In addition, We will present the pre-processing for selecting the study data, and the method to evaluate the wave of weld more precisely and accurately through known Neural Network.

• BMB Reports
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• v.41 no.1
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• pp.23-28
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• 2008

The altered amino acid (AA) levels as neurotransmitter closely correlate to neurodegenerative conditions including Alzheimer's disease (AD). Target profiling analysis of nineteen AAs in brain cortex samples from three Tg2576 mice as AD model and three littermate mice as control model was achieved as their N(O,S)-ethoxycarbonyl/tert-butyldimethylsilyl derivatives by gas chromatography. Subsequently, star pattern recognition analysis was performed on the brain AA levels of AD mice after normalization to the corresponding control median values. As compared to control mice, $\gamma$-aminobutyric acid among ten AAs found in brain samples was significantly reduced (P < 0.01) while leucine was significantly elevated (P < 0.02) in AD mice. The normalized AA levels of the three AD mice were transformed into distorted star patterns which was different from the decagonal shape of control median. The present method allowed visual discrimination of the three AD mice from the controls based on the ten normalized AA levels.