• Genomics & Informatics
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• v.8 no.3
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• pp.142-149
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• 2010

In recent years, genome-wide association (GWA) studies have successfully led to many discoveries of genetic variants affecting common complex traits, including height, blood pressure, and diabetes. Although GWA studies have made much progress in finding single nucleotide polymorphisms (SNPs) associated with many complex traits, such SNPs have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. This is partly due to that fact that most current GWA studies have relied on single-marker approaches that identify single genetic factors individually and have limitations in considering the joint effects of multiple genetic factors on complex traits. Joint identification of multiple genetic factors would be more powerful and provide a better prediction of complex traits, since it utilizes combined information across variants. Recently, a new statistical method for joint identification of genetic variants for common complex traits via the elastic-net regularization method was proposed. In this study, we applied this joint identification approach to a large-scale GWA dataset (i.e., 8842 samples and 327,872 SNPs) in order to identify genetic variants of obesity for the Korean population. In addition, in order to test for the biological significance of the jointly identified SNPs, gene ontology and pathway enrichment analyses were further conducted.

• Journal of Information Science Theory and Practice
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• v.6 no.4
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• pp.28-38
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• 2018

Wikipedia is composed of millions of articles, each of which explains a particular entity with various languages in the real world. Since the articles are contributed and edited by a large population of diverse experts with no specific authority, Wikipedia can be seen as a naturally occurring body of human knowledge. In this paper, we propose a method to automatically identify key entities and relations in Wikipedia articles, which can be used for automatic ontology construction. Compared to previous approaches to entity and relation extraction and/or identification from text, our goal is to capture naturally occurring entities and relations from Wikipedia while minimizing artificiality often introduced at the stages of constructing training and testing data. The titles of the articles and anchored phrases in their text are regarded as entities, and their types are automatically classified with minimal training. We attempt to automatically detect and identify possible relations among the entities based on clustering without training data, as opposed to the relation extraction approach that focuses on improvement of accuracy in selecting one of the several target relations for a given pair of entities. While the relation extraction approach with supervised learning requires a significant amount of annotation efforts for a predefined set of relations, our approach attempts to discover relations as they occur naturally. Unlike other unsupervised relation identification work where evaluation of automatically identified relations is done with the correct relations determined a priori by human judges, we attempted to evaluate appropriateness of the naturally occurring clusters of relations involving person-artifact and person-organization entities and their relation names.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Fashion & Textile Research Journal
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• v.16 no.5
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• pp.756-765
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• 2014

Customer-company (C-C) identification is the perceived fit between the identities of a consumer and an organization. If a consumer identifies with a company that places a high priority on being socially responsible, a consumer who also values social responsibility may support and patronize that business because of the link between something that is important to both them and the company. Because C-C identification may explain the success of cause-related marketing (CRM) in the fashion industry, we investigated the effect of an image resulting from CRM on ratings of brand attributes (e.g., distinctiveness, credibility, attractiveness), identification with the brand, attitude toward the brand, and customer loyalty. Participants also responded to open-ended questions reflecting their rationale for their ratings of brand attributes. Data were collected from a convenience sample of undergraduates (n = 228) enrolled at Midwestern University in the U.S. Structural equation modeling revealed that as ratings of the social responsibility of the cause-related marketing effort increased so did perceptions of the brand's distinctiveness, credibility, and attractiveness. Participants identified with a brand when they rated the brand as attractive. Participants' identification with a brand had a significant impact on attitudes toward the brand and customer loyalty (e.g., purchase intention, willingness to spread positive word-of-mouth). Content analyses of open-ended responses supported the idea that brand images stemming from CRM exert an important influence on consumer's ratings of brand attributes. Fashion marketers interested in cause-related marketing will find success with efforts that increase customer identification.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.555-563
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• 2016

Science and technology contents (research papers, patents, reports) are the most common reference material for researchers involved in research and development in the fields of science and technology. Based on various search elements (title, abstract, keyword, year of publication, name of journal, name of author, publisher, etc.), many services are available for users to search science and technology contents and bibliographic information owned by libraries. Authority data on organization name can be useful as an element for author identification and as an element to search for results produced by specific organizations. However, organization name is not taken into account by current search services for domestic academic information and bibliographic records. This study analyzes organization name data contained in the metadata of science and technology contents, which are the basis of the establishment of authority data, and proposes a method and system based on string containment and exact string matching.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.1-10
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• 2019

The purpose of this study is to verify the effect of the compaction and virtue experienced by police officers in the organization on positive emotion and, second, to demonstrate the effect of positive emotion on the organization uniformity, which is subordinate variable. Third, we intend to verify the mediated effect of positive emotion in the relationship between compassion and organization uniformity, and fourthly, to demonstrate the coordination effect of collective self-esteem in the relationship between positive emotion and organization identicalness. Sampling of this study was conducted on 353 male and female police officers working at police stations belonging to the National Police Agency and used these samples for hypothesis testing. Studies have confirmed that the compaction and virtue experienced by police officers have a positive effect on positive emotion, and that positive emotion has a positive effect on the phenomenon of tissue co-ordination. And it has been shown that positive emotion plays a full role in the relationship between compassion, virtue and organizational co-ordination, and that positive emotion and collective self-esteem plays a controlling role in the relationship with organizational co-ordination. The theoretical implications of this study will contribute to creating a positive organizational culture by maintaining a strict hierarchical relationship and spreading the compaction and virtuous behavior to police organizations with high task stress.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.496-505
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• 2011

The purpose of this study was to research the relationships among ethical climate, trust, organizational identification and turnover intention of employees in travel agency. Ethical climates the prevailing perceptions of typical organizational practices and procedures that have ethical content. Ethical climate involves the perceptions of rightness or wrongness present in the organization's work environment, and establishes the norms for acceptable and unacceptable behavior within the company. To accomplish this study, it was determined that the analysis derived from a hypothesis and literature reviews and data collected from 231 employees in travel agency. The results of empirical analysis showed as follows. First, Perceived ethical climate has a significant effect on trust, organizational identification and turnover intention. Second, Organizational identification has a significant effect on turnover intention while trust has no relationship with it. In addition, the mediating role of organizational identification is examined in the relationship between ethical climate and turnover intention. Based on these findings, the implications and limitations of the study were presented including some directions for future studies.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.583-591
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• 2017

The purpose of this study was empirically to reveal the structure relationship between ethical management of ski resort employee, organizational identification and customer orientation. For the research, survey of 200 people working in domestic ski resorts was conducted. The survey was composed of three variables(ethical management, organizational identification and customer orientation). The following results were obtained by confirmatory analysis, reliability analysis, correlation analysis and structural equation model analysis. First, ski resort employee's ethical management had a positive correlation with organizational identification. Second, ski resort employee's ethical management had a positive correlation with customer orientation. Third, ski resort employee's organizational identification had a positive correlation with customer orientation. This study suggested that the ethical management of ski resorts had positive effects on the attitudes and behaviors of the employees who regarded the organization as a common fate and provided high quality service considering the customer's position.

• Analytical Science and Technology
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• v.34 no.3
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• pp.99-114
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• 2021

Substance identification is the first step in implementing chemical legislation, such that subsequent hazard and risk assessments can be accurately followed. Based on the web page and related guidance documents of the European Chemicals Agency and available consortia information, the procedure for substance identification carried out in Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) is surveyed. In this study, the importance of substance identification and substance sameness check, as well as the necessity of generating a substance identity profile (SIP) are considered. In addition, the SIPs of several substance types are presented, which focused on information utilization in the instrumental analysis results and organization of information to generate the SIP. Analytical science can contribute to the accurate and effective implementation of chemical regulation at the starting stage of substance identification. However, understanding of the regulation and consequent final wrap-up of analytical results as a SIP should be followed for communication among registrants in Substance Information Exchange Forum (SIEF) as well as with related authorities.

• 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.