• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.186-195
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• 2010

In most self-incompatible plant species, recognition of self-pollen is controlled by a single locus, termed the S-locus. The self-incompatibility (SI) system in Brassica is controlled sporophytically by multiple alleles at a single locus, designated as S, and involves cell-cell communication between male and female. Two highly polymorphic S locus genes, SLG (S locus glycoprotein) and SRK (S receptor kinase), have been identified, both of which are expressed predominantly in the stigmatic papillar cell. Gain-of-function experiments have demonstrated that SRK solely determines S haplotype-specificity of the stigma, while SLG enhances the recognition reaction of SI. The sequence analysis of the S locus genomic region of B. campestris (syn. rapa) has led to the identification of an anther-specific gene, designated as SP11/SCR, which is the male S determinant. Molecular analysis has demonstrated that the dominance relationships between S alleles in the stigma were determined by SRK itself, but not by the relative expression level. In contrast, the expression of SP11/SCR from the recessive S allele was specifically suppressed in the S heterozygote, suggesting that the dominance relationships in pollen were determined by the expression level of SP11/SCR. Furthermore, recent studies on recessive allele-specific DNA methylation of Brassica self-incompatibility alleles demonstrate that DNA methylation patterns in plants can vary temporally and spatially in each generation. In this review, we firstly present overview of self incompatibility system in Brassica and then describe dominance relationships in Brassica self- incompatibility regulated by allele-specific DNA methylation.

• Journal of Korean Academy of Nursing
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• v.51 no.3
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• pp.265-279
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• 2021

Purpose: This study examined the impact of a drinking reduction program on drinking motivation, drinking refusal self-efficacy, and problematic drinking behaviors in college students with problematic drinking habits. Methods: This study incorporated a non-equivalent control group prepost-test design. Study participants included 58 college students who scored 12 or more in the AUDIT-K test (Alcohol Use Disorders Identification Test-Korean version) (experimental group: 30; control group: 28). The intervention consisted of eight sessions and was conducted once a week. It was designed to promote autonomy, competence, and relatedness-the three elements of basic psychological needs in self-determination theory. The participants were assessed before the intervention, immediately after, and four weeks post intervention. Data were collected from October 12 to December 31, 2017. The analysis employed the chi-square test, Fisher's exact test, independent t-test, and repeated measures ANOVA using SPSS/WIN 22.0. Results: The mean age of participants was 21.8 years. There were 30 men (51.7%) and 28 women (48.3%). The differences in drinking motivation, drinking refusal self-efficacy, and problematic drinking behaviors were statistically significant for the group by time interaction (F = 42.56, p < .001; F = 54.96, p < .001; F = 39.90, p < .001, respectively). Conclusion: The findings indicate that the intervention effectively decreases drinking motivation, increases drinking refusal self-efficacy, and decreases problematic drinking behaviors. It can be an efficient strategy for college students with problematic drinking habits to enhance their self-determination ability.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.

• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.197-201
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• 2005

It is well known that a rotating bar potential can transport angular momentum to the disk and hence cause the evolution of the disk. Such a process is particularly important in disk galaxies since it can result in fuelling AGNs and starburst ring activities. In this paper, we will present the numerical simulations to show how this mechanism works. The problem, however, is quite complicated. We classify our simulations according to the type of Lindbald resonances and try to single out the individual roles they play in the disk evolution. Among many interesting results, we emphasize the identification of the origin of the starburst rings and the dense circumnuclear molecular disks to the instability of the disk. Unlike most of the other simulations, the self-gravitation of the disk is emphasized in this study.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.368-369
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• 2011

This article suggests an online-based remote fault current mode discrimination method in order to identify the causes of the power line faults with various causes. For that, it refers to existing cause identification methods and categorizes modes by fault causes based on statistical techniques beforehand and performs the pretreatment process of fault currents by each cause acquired from the fault recorder into a topological plane in order to extract the characteristics of fault currents by each cause. After that, for the fault mode categorization, it discriminates modes by each cause using data by each cause as leaning data through utilizing RBF network based on FCM allowing self-organization in deciding the middle layer. And then it tests the validity of the suggested method as applying it to the data of the actual fault currents acquired from the fault recorder in the electric power transmission center.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.354-361
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• 2009

It is a tentative study on the influence of the consumers' motivation of charity impulse on their loyalty who donate to non-profit organizations. Based on the self-determination theory, this thesis paper analyzed the motivation of charity impulse on non-profit organizations which is the main factor influencing the donation loyalty with consumer-nonprofit identification as parametric variables.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.434-437
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• 2004

본 논문에서는 유전자 알고리즘에 기반을 둔 자기구성 다항식 뉴럴네트워크(Self-Organizing Polynomial Neural Networks： SOPNN)의 새로운 구조를 제안하고, 포괄적인 설계 방법론을 토의한다. 기존의 자기구성 다항식 뉴럴 네트워크는 확장된 GMDH 방법에 기반을 두며, 네트워크의 성장과정을 통하여 각 충의 다항식 뉴런에서 고정된 노드 입력들의 수 뿐만 아니라 다항식 차수(1차, 2차, 그리고 수정된 2차식)를 이용하였다. 더구나, 그 방법은 학습을 통해 생성된 SOPNN이 최적 네트워크 구조를 가진다는 것을 보증하지 못한다. 그러나, 제안된 GA 기반 SOPNN은 그 구조를 구조적으로 더 최적화된 네트워크가 되도록 하고, 기존의 SOPNN보다 훨씬 더 유연하고, 선호된 뉴럴 네트워크가 되도록 한다. 구조적으로 더 최적화된 SOPNN을 생성하기 위해, SOPNN의 각 단계에서의 GA기반 설계 절차는 SOPNN내에서 이용할 수 있는 다음의 최적 파라미터들- 즉 입력변수의 수, 입력변수, 및 다항식 차수-을 가진 선호된 노드들의 선택으로 이끈다. 하중계수를 가진 합성성능지수가 그 모델의 근사화 및 일반화(예측) 능력 사이의 상호 균형을 얻기 위해 제안된다. 상세 설계 절차가 상세히 토의된다.

• Molecules and Cells
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• v.25 no.2
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• pp.279-288
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• 2008

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2451-2460
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• 2000

In order to minimize straightness error of deflected shaft, a geometric adaptive straightness controller system is studied. A multi-step straightening and a three-point bending process have been developed for the geometric adaptive straightness controller. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and real-time hydraulic control methodology are studied for the three-point bending process. By deflection pattern analysis and fuzzy self-learning method in the multi-step straightening process, a straightening point and direction, desired permanent deflection and supporting condition are determined. An automatic straightening machine has been fabricated for rack bars by using the developed ideas. Validity of the proposed system is verified through experiments.

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.204-211
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• 2016

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.