• The Korean Journal of Ecology
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• v.16 no.3
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• pp.317-327
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• 1993

Stands profiles, yearly changes in growth of annual rings, age and diameter structure, and spatial distribution pattern of individuals in the Pinus densiflora stands around the Yeocheon industrial complex were investigated. Growth of annual ring in Pinus densiflora, which survived when vegetation of this area was damaged by air pollutants, was suppressed for about 10 years since 1974 when factories in this area began to operate, but since then such suppressed growth tended to be recovered. It was supposed that the suppresed growth was originated from air pollution and that improvement of growth since the suppressed period was due to the release from competition with them by death of neighbouring trees and the resuction of the amount of air pollutants. Physiognomy of Pinus densiflora stands showed mosaic pattern composed of different patches. Spatial distribution pattern of individuals an stand profiles were similar to those of Pinus densiflora stands regenerated after natural and artificial disturbances. In an age distribution diagram, age of Pinus densiflora population ranged from 1 to 33 years, Among these individuals were recrited corresponded to the suppresed period of growth of annual ring in Pinus densiflora survived when the vegetation was damaged by air pollution. On the other hand, from the result of analysis of frequency distribution diagram of diameter, it was postulated that even if whis Pinus densiflora community can be maintained as it is for the time being, it might be changed to Quercus community with the lapse of time. Regeneration; Pinus densiflora; Air pollution; Annual ring; Age structure; Diameter structure; Quercus spp. In these analyses, factors for individual recognition and species recognition were suggested.

• International Journal of Industrial Entomology and Biomaterials
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• v.4 no.1
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• pp.31-36
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• 2002

Peptidohlycan recognition protein (PGRP) is one of the pattern recognition proteins in innate immunity of insect. We isolated differentially expressed two cDNAa, BTL-LPI and BTL-LP2, in the fat body of Bombyx mori larvae injected with bacteria by subtractive hybridization method. These two clones showed amino acid sequence divergence of 30.4%. In the comparison with other insect PGRP genes, BTL-LP2 showed 48.8% and 45.2% of sequence homology to the known PGRP genes of Bombyx mori and Tricoplusia ni, respectively, and BTL-LP2 was 31.8% and 30.9% , respectively. Phylogenetic analysis showed relatively close relationship of the BTL-LP2 to the known insect PGRP, unlike BTL-LPI, which was equidistant both to insect and mammals, suggesting a divergent relationships of the two newly cloned B. mori PGRP genes. Northern blot analyses confirmed an induction of the expression of BTL-LP2 by the bacterial infection in the Int body of B. mori, suggesting the involvement of the gene in the insect immunity.

• Structural Engineering and Mechanics
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• v.75 no.3
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• pp.295-309
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• 2020

The construction of Reinforced Concrete (R/C) buildings with unreinforced masonry infills is part of the traditional building practice in many countries with regions of high seismicity throughout the world. When these buildings are subjected to seismic motions the presence of masonry infills and especially their configuration can highly influence the seismic damage state. The capability to avoid configurations of masonry infills prone to seismic damage at the stage of initial architectural concept would be significantly definitive in the context of Performance-Based Earthquake Engineering. Along these lines, the present paper investigates the potential of instant prediction of the damage response of R/C buildings with various configurations of masonry infills utilizing Artificial Neural Networks (ANNs). To this end, Multilayer Feedforward Perceptron networks are utilized and the problem is formulated as pattern recognition problem. The ANNs' training data-set is created by means of Nonlinear Time History Analyses of 5 R/C buildings with a large number of different masonry infills' distributions, which are subjected to 65 earthquakes. The structural damage is expressed in terms of the Maximum Interstorey Drift Ratio. The most significant conclusion which is extracted is that the ANNs can reliably estimate the influence of masonry infills' configurations on the seismic damage level of R/C buildings incorporating their optimum design.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.327-330
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• 2004

Because of its effectiveness for the PD(partial discharge) pattern recognition, PSA(Pulse Sequence Analysis) has been considered as a new analytic method instead of conventional PRPDA(Phase Resolved Partial Discharge Analysis). However, PSA has a big problem that can misanalyze patterns in case of data missing resulting from poor sensitivity because it analyses the correlation between sequential pulses, which leads to hesitate to apply it to on-site. Therefore, in this paper, the problems of PSA such as data missing and noise adding cases were investigated. For the purpose, PD data obtained from various defects including noise adding data were used and analysed, The result showed that both cases can cause fatal errors in recognizing PD patterns. In case of the data missing, the error depends on the kinds of defect and the degree of degradation. Also, it could be noticed that the error due to adding noises was larger than that due to some data missing.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.5
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• pp.484-489
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• 2005

Because of its effectiveness for the PD(Partial Discharge) pattern recognition, PSA(Pulse Sequence Analysis) has been considered as a new analytic method instead of conventional PRPDA(Phase Resolved Partial Discharge Analysis). However, it is generally thought that PSA has some possibility to misjudge patterns in case of data-missing resulting from poor sensitivity because it analyses the correlation between sequential pulses, which leads to hesitate to apply it to on-site. Therefore, in this paper, the problems of PSA such as data-missing and noise-adding cases were investigated. for the purpose, PD data obtained from various defects including noise-adding data were used and analyzed. As a result, it was shown that both cases could cause fatal errors in recognizing PD patterns. In case of the data missing, the error was dependant on the kinds of defect and the degree of degradation Also, it could be noticed that the error due to adding noises was larger than that due to some data missing.

• YAKHAK HOEJI
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• v.49 no.1
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• pp.74-79
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• 2005

Metabonomic analysis has been recognized as a powerful approach for characterizing metabolic changes in biofluids due to toxicity, disease process or environmental influences. To investigate the possibility of relating metabolic changes with $^{1}H-NMR$ spectra, urine samples from Sprague-Dawley rats treated with various dietary restrictions or toxic substances (nicotine) were analysed using $^{1}H-NMR$ spectroscopy and pattern recognition techniques. Dietary restrictions-given to male rats were normal diet and high fat diet and fasting. The nicotine urine samples were collected from SD rats administered with nicotine (25 mg/kg) at the various time intervals. $^{1}H-NMR$ spectra of all urine samples were acquired at 400 MHz on a VARIAN spectrometer. To establish the presence of any intrinsic class-related patterns or clusters in each NMR data, methods of PCA (principal component analysis) and soft independent modeling of class analogy (SIMCA) analysis were used, and the results from these analyses were compared to each other. In all cases of dietary conditions and nicotine treatment, SIMCA analysis gave better results for the discrimination of NMR spectra of urine samples than PCA.

• 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.

• Natural Product Sciences
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• v.25 no.4
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• pp.334-340
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• 2019

Cuscuta chinensis Lam. and Cuscuta japonica Choisy are parasitic plants. C. chinensis seeds were traditionally used for treatment of kidney and liver deficiencies. C. japonica seeds were used as tonic medicine to improve liver function and strengthen kidneys, treatment of high blood pressure, chronic diarrhea, and sore eyes. Cuscutae Semen are seeds of only C. chinensis in Korean Herbal Pharmacopoeia (K.H.P.). The developed HPLC-PDA method easily, accurately, and sensitively quantified using eight marker compounds [hyperoside (1), astragalin, (2), quercetin (3), kaempferol (4), chlorogenic acid (5), 3,4-di-O-caffeoylquinic acid (6), 1,5-di-O-caffeoylquinic acid (7), and 4,5-di-O-caffeoylquinic acid (8)]. In addition, the method may be used to distinguish seeds between C. chinensis Lam. and C. japonica Choisy. Furthermore, the result from the current study was applied to clarify samples between steam processed and unprocessed samples of C. chinensis by pattern analysis.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.507-517
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• 2003

Self-organizing map (SOM) has been developed mainly by T. Kohonen and his colleagues as a unsupervised learning neural network. Because of its topological ordering property, SOM is known to be very useful in pattern recognition and text information retrieval areas. Recently, data miners use Kohonen´s mapping method frequently in exploratory analyses of large data sets. One problem facing SOM builder is that there exists no sensible criterion for evaluating goodness-of-fit of the map at hand. In this short communication, we propose valid evaluation procedures for the Kohonen SOM of any size. The methods can be used in selecting the best map among several candidates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4763-4775
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• 2020

This research aims to develop a deep learning-based method that automatically detects and segments the defects on railroad surfaces to reduce the cost of visual inspection of the railroad. We developed our segmentation model by modifying a fully convolutional network model [1], a well-known segmentation model used for machine learning, to detect and segment railroad surface defects. The data used in this research are images of the railroad surface with one or more defect regions. Railroad images were cropped to a suitable size, considering the long height and relatively narrow width of the images. They were also normalized based on the variance and mean of the data images. Using these images, the suggested model was trained to segment the defect regions. The proposed method showed promising results in the segmentation of defects. We consider that the proposed method can facilitate decision-making about railroad maintenance, and potentially be applied for other analyses.