• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.877-889
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• 2006

This paper introduces a simple but effective method for recognizing vehicle models corresponding to each maker by information and images for moving vehicles. The proposed approach is implemented by combination of the breadth detection mechanism using the vehicle's pressure, exact height detection by a laser scanning, and license plate recognition for classifying specific vehicles. The implemented system is therefore capable of robust classification with real-time vehicle's moving images and established sensors. Simulation results using the proposed method on synthetic data as well as real world images demonstrate that proposed method can maintain an excellent recognition rate for moving vehicle models because of image acquisition by 2-D CCD and various image processing algorithms.

• BMB Reports
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• v.39 no.6
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• pp.703-708
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• 2006

During infection, the common respiratory tract pathogen Streptococcus pneumoniae encounters several environmental conditions, such as upper respiratory tract, lung tissue, and blood stream, etc. In this study, we examined the effects of blood on S. pneumoniae protein expression using a combination of highly sensitive 2-dimensional electrophoresis (DE) and MALDI-TOF MS and/or LC/ESI-MS/MS. A comparison of expression profiles between the growth in THY medium and THY supplemented with blood allowed us to identify 7 spots, which increased or decreased two times or more compared with the control group: tyrosyl-tRNA synthetase, lactate oxidase, glutamyl-aminopeptidase, L-lactate dehydrogenase, cysteine synthase, ribose-phosphate pyrophosphokinase, and orotate phosphoribosyltransferase. This global approach can provide a better understanding of S. pneumoniae adaptation to its human host and a clue for its pathogenicity.

• Korean Chemical Engineering Research
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• v.45 no.5
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• pp.415-423
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• 2007

Photocatalytic water splitting (PWS) is the most promising technology to produce $H_2$ energy directly from renewable water and solar light. In spite of the remarkable progress made in the last decade, there are still many technical challenges remaining particularly in finding new photocatalytic materials with high efficiency and durability. This article discusses the application of nanocomposite materials in search of new photocatalytic materials for solar hydrogen production from water. It has been demonstrated that smart combination and modification of known materials and functions could be fruitful approach for the purpose.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11B
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• pp.1020-1029
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• 2008

This paper proposes an high speed pattern matching algorithm and its implementation. The pattern matcher is used to check patterns from realtime input packet. The proposed algorithm can find exact string, range of string values, and combination of string values from input packet at high speed. Given string and rule set are modelled as a state transition graph which can find overlapped strings simultaneously, and the state transition graph is partitioned according to input implicants to reduce implementation complexity. The pattern matcher scheme uses the transformed state transition graph and input packet as an input. The pattern matcher was modelled and implemented in VHDL language. Experimental results show the proprieties of the proposed approach.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.326-330
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• 2008

The study on combining multiple classifiers in the field of pattern recognition has mainly focused on how to combine multiple classifiers, but it has gradually turned to the study on how to select multiple classifiers from a classifier pool recently. Actually, the performance of multiple classifier system depends on the selected classifiers as well as the combination method of classifiers. Therefore, it is necessary to select a classifier set showing good performance, and an approach based on information theory has been tried to select the classifier set. In this paper, a classifier set candidate is made by the selection of classifiers, on the basis of mutual information between classifiers, and the classifier set candidate is compared with the other classifier sets chosen by the different selection methods in experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.182-185
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• 2003

This paper presents a new design algorithm for the combination with the fuzzy classifier and the Bayesian classifier. Only few attempts have so far been made at providing an effective design algorithm combining the advantages and removing the disadvantages of two classifiers. Specifically, the suggested algorithms are composed of three steps: the combining, the fuzzy-set-based pruning, and the fuzzy set tuning. In the combining, the multi-inputs and multi-outputs (MIMO) fuzzy model is used to combine two classifiers. In the fuzzy-set-based pruning, to effectively decrease the complexity of the fuzzy-Bayesian classifier and the risk of the overfitting, the analysis method of the fuzzy set and the recursive pruning method are proposesd. In the fuzzy set tuning for the misclassified feature vectors, the premise parameters are adjusted by using the gradient decent algorithm. Finally, to show the feasibility and the validity of the proposed algorithm, a computer simulation is provided.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.2
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• pp.142-146
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• 2005

Thirty-two germplasms of Korean adlay landraces were examined to analyse the genetic relationship through the amplified fragment length polymorphism (AFLP) approach. Total number of AFLP products generated by 12 selective primer combinations was 882. The number of polymorphic fragments by each primer combination greatly varied from 4 to 51 with a mean of 20.3, bands visible on the polyacrylamide gel. A genetic similarity coefficient was used for cluster analysis following UPGMA (unweighted pair grouping method of averages) method. The resulting clusters were represented in the form of a dendrogram. The clustering was not tight in the dendrogram. There was generally no clear grouping of the adlay according to the geographic regions in which germplasms were collected. The present AFLP analysis imply that although Korean adlay displayed a larger amount of AFLP variation within germplasms, the variation was shown independently without reflecting a clinal variation. This study demonstrated that AFLP method can be used to examine the genetic relationships among different germplasms of adlay.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• The Plant Pathology Journal
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• v.36 no.2
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• pp.157-169
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• 2020

Two lactic acid bacteria (LAB) designated J02 and J13 were recovered from fermented vegetables based on their ability to suppress soft rot disease caused by Pectobacterium carotovorum subsp. carotovorum (Pcc) on radish. J02 and J13 were identified as Lactobacillus pentosus and Leuconostoc fallax, respectively. The ability of J02 and J13 to suppress plant diseases is highly dependent on chitosan. LAB alone has no effect and chitosan alone has only a moderate effect on disease reduction. However, J02 or J13 broth cultures plus chitosan display a strong inhibitory effect against plant pathogens and significantly reduces disease severity. LAB strains after being cultured in fish surimi (agricultural waste) and glycerol or sucrose-containing medium and mixed with chitosan, reduce three cruciferous vegetable diseases, including cabbage black spot caused by Alternaria brassicicola, black rot caused by Xanthomonas campestris pv. campestris, and soft rot caused by Pcc. Experimental trials reveal that multiple applications are more effective than a single application. In-vitro assays also reveal the J02/chitosan mixture is antagonistic against Colletotrichum higginsianum, Sclerotium rolfsii, and Fusarium oxysporum f. sp. rapae, indicating a broad-spectrum activity of LAB/chitosan. Overall, our results indicate that a synergistic combination of LAB and chitosan offers a promising approach to biocontrol.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.195-200
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• 2008

The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.