• Plant Biotechnology Reports
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• v.3 no.2
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• pp.147-155
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• 2009

Oryza grandiglumis Chitinase IVa (OgChitIVa) cDNA encoding a class IV chitinase was cloned from wild rice (Oryza grandiglumis). OgChitIVa cDNA contains an open reading frame of 867 nucleotides encoding 288 amino acid residues with a predicted molecular weight of 30.4 kDa and isoelectric point of 8.48. Deduced amino acid sequences of OgChitIVa include the signal peptide and chitin-binding domain in the N-terminal domain and conserved catalytic domain. OgChitIVa showed significant similarity at the amino acid level with related monocotyledonous rice and maize chitinase, but low similarity with dicotyledoneous chitinase. Southern blot analysis showed that OgChitIVa genes are present as two copies in the wild rice genome. It was shown that RNA expression of OgChitIVa was induced by defense/stress signaling chemicals, such as jasmonic acid, salicylic acid, and ethephon or cantharidin and endothall or wounding, and yeast extract. It was demonstrated that overexpression of OgChitIVa in Arabidopsis resulted in mild resistance against the fungal pathogen, Botrytis cinerea, by lowering disease rate and necrosis size. RT-PCR analysis showed that PR-1 and PR-2 RNA expression was induced in the transgenic lines. Here, we suggest that a novel OgChitIVa gene may play a role in signal transduction process in defense response against B. cinerea in plants.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.851-858
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• 2009

Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.26-39
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• 2021

This study investigated the characteristics of the watershed and pollutants in the Seonakdong River basin in the lower stream of the Nakdong River Water System, and evaluated the areas vulnerable to nonpoint pollution by subwatershed according to the TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution) method. The selection method consists of selection of evaluation factors, calculation of weights and selection of areas vulnerable to non-point pollution through evaluation factors and weights. The entropy method was used as the weight calculation method and TOPSIS, a multi-criteria decision making(MCDM) method was used as the evaluation method. Indicator data were collected as of 2018, and national pollution source survey data and national statistics were used. Most of the vulnerable watersheds were highly urbanized had a large number of residents and were evaluated as having a large land area among industrial facilities and site area rate. Through this study, it is necessary to approach a variety of weighting methodologies to assess the vulnerability of non-point pollution with high reliability, and scientific analysis of the factors that affect non-point pollution sources and consideration of the effects are necessary.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.267-274
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• 2023

In this paper, a method for estimating the illuminant chromaticity of a scene for an input image is proposed. The illuminant chromaticity is estimated using the illuminant reference region. The conventional method uses a certain number of reference lighting information. By comparing the chromaticity distribution of pixels from the input image with the chromaticity set prepared in advance for the reference illuminant, the reference illuminant with the largest overlapping area is regarded as the scene illuminant for the corresponding input image. In the process of calculating the overlapping area, the weights for each reference light were applied in the form of a Gaussian distribution, but a clear standard for the variance value could not be presented. The proposed method extracts an independent reference chromaticity region from a given reference illuminant, calculates the characteristic values in the r-g chromaticity plane of the RGB color coordinate system for all pixels of the input image, and then calculates the independent chromaticity region and features from the input image. The similarity is evaluated and the illuminant with the highest similarity was estimated as the illuminant chromaticity component of the image. The performance of the proposed method was evaluated using the database image and showed an average of about 60% improvement compared to the conventional basic method and showed an improvement performance of around 53% compared to the conventional Gaussian weight of 0.1.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.1-12
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• 2009

Mobbing is going the rounds through a society rapidly and Military is not exception. Because mobbing of military is expressed not only psychology exclusion that is mobbing pattern of adult society but also sometimes psychologic and physical mobbing, is possible to join serious military discipline like a suicide and outrageous behavior. Specially military try to protect occurrence of victims that is public service through various rules and management plan but victims is going on happen. It means importance of grasp not only current mobbing victims but also potential mobbing victims better than preparation of various rules and management plans. Therefore this paper extracts seven factors and fifty attributes that are related to this matter mobbing. Next, by using Gunwoo's Social Network Service that is made for oneself and expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function(Dice's coefficient) to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and propose Mobbing Value(MV) Algorithm through this total summation. Finally through this algorithm which will contribute to efficient personnel management, we can grasp mobbing victims and tentative mobbing victims.

• Information Systems Review
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• v.19 no.1
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• pp.147-168
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• 2017

We investigated perceptual similarity and the difference between client and vendor in information technology (IT) outsourcing projects. Specifically, we focused on each player's perception of how the fit of governance and peripheral knowledge affects the performance of IT project outsourcing. For 107 IT projects, we surveyed both client and vendor in the same IT projects and compared the responses of each side. Through a dyadic analysis, we first found that both client and vendor put more weight on the vendor's peripheral knowledge than that of the client as a positive influencer of project performance. However, regarding the governance style of an IT project, client and vendor showed completely different perspectives. The client believed that the vendor's peripheral knowledge positively contributes to the performance of IT project under the governance of outcome control. However, the vendor showed that its peripheral knowledge creates synergy effects under the governance of process control. Our interpretation of the perceptual similarity and difference between client and vendor delivers managerial implications for businesses that process IT projects.

• International Journal of Industrial Entomology and Biomaterials
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• v.15 no.1
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• pp.83-85
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• 2007

A glycine and proline-rich antibacterial protein was cloned from larvae of a beetle, Protaetia brevitarsis. The DNAs encoded a deduced propeptide of 127 amino acid residues with predicted molecular weight of 14.0 kDa and PI of 7.89. Structural analysis of this protein indicated the presence of a recognition sequence for the cleavage site within the constitutive secretory pathway(Arg-Xaa-Lys/Arg-Arg), suggesting that mature portion(72 amino acid residues) is produced by cleavage of signal peptide and propeptide from 127 amino-acid-long precursor protein. Mature portion sequence of this protein showed 72% similarity to that of Oryctes rhinoceros Rhinocerosin and 91% to that of Holotrichia diomphalia holotricin 2. The mRNA expression was reached the highest level at 4 hrs after E. coli injection and then declined gradually.

• Journal of Microbiology and Biotechnology
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• v.11 no.4
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• pp.636-643
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• 2001

Bacillus sp. AIR-5, a strain from soil, produced an extracellular maltopentaose-forming amylase from amylose and soluble starch. This bacterium produced 8.9 g/l of maltopentaose from 40 g/l of soluble starch in a batch fermentation and the maltopentaose made up 90 % of the maltooligosaccharides produced (from maltose to maltoheptaose). The culture supernatant was concentrated using a 30 K molecular weight cut-off membrane and purified by DEAE-Cellulose and Sephadex G-150 column chromatographies. The purified protein showed one band on a native-PAGE and its molecular mass was estimated as 250 kDa. The 250-kDa protein was composed of tetramers of a 63-kDa protein. the isoelectric point of the purified protein was pH 6.9, and the optimum temperature for the enzyme activity was $45^{\circ}C$. The enzyme was quickly inactivated above $55^{\circ}C$, and showed a maximum activity at pH 8.5 and over 90% stability between a pH of 6 to 10. The putative N-terminal amino acid sequence of AIR-5 amylase, ATINNGTLMQYFEWYVPNDG, showed a 96% sequence similarity with that of BLA, a general liquefying amylase.

• Journal of Microbiology and Biotechnology
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• v.8 no.5
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• pp.501-508
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• 1998

An alkalophilic mi.croorganism (strain YB380), which produces yeast cell wall hydrolase extracellulary, was isolated from Korean soil. The rod-shaped cells were 0.3~0.4 by 2~4${\mu}{\textrm}{m}$ long, motile, aerobic, gram-positive, and spore-forming. The color of the colony was light yellow. The temperature range for growth at pH 9.0 was 25 to $45{\circ}C, with optimum growth at $35{\circ}C. The pH range for growth at $35{\circ}C was 8 to 11 with an optimum pH of 9.0. Therefore, the strain YB380 is an obligate alkalophile. The 16S rRNA of strain YB380 has a 99% sequence similarity with that of Bacillus alcalophilus. On the basis of physiological properties, cell wall fatty acid composition, and phylogenetic analysis, we propose that the isolated strain is Bacillus alcalophilus. The yeast cell wall hydrolase from Bacillus alcalophilus subsp. YB380 has been purified and partially characterized. The molecular weight was estimated to be 27,000 daltons with an optimum temperature and pH of $60{\circ}C and 9.0, respectively. The N-terminal amino acid sequence of the enzyme was analyzed as Gln- Thr- Val- Pro- Trp- Gly- Ile- Asn- Arg- Val.