• Journal of the Korean Society of Costume
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• v.51 no.2
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• pp.105-120
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• 2001

The purpose of this study is to identify the relationship of self-efficacy, which is a kind of the self concept about one's own ability, to the decision-making process, which is the key part of consumer behavior. The subjects in this study were 985 male and female undergraduates of a university located in the city of Kyongsan, the north Kyongsang province. The collected data were statistically processed by MANOVA and ANOVA. For post test, Scaffle and $\chi$$^2$-test were employed. The followings are findings of this study : 1. Concerning incentive to buying, the group having the weaker general self-efficacy is stimulated more highly by the incentives of self-display, fashion pursuit and economic utility than the group having the stronger general self-efficacy does. 2. Regarding information sources. the factor of observation is frequently used by the group having the weaker general and social self-efficacies more than the group having the stronger general and social self-efficacies. 3. As to the evaluative criteria of clothes, the group having the stronger general and social self-efficacies put a higher value on functional and economical points than the group having the weaker general and social self-efficacies does. 4. As for the evaluative criteria of store the group having the stronger general self-efficacy lays stress on store atmosphere, store attributes and convenient shopping condition, while the group having the weaker general self-efficacy puts emphasis on brand and fashion. 5. In buying apparels, the group having the stronger general and social self-efficacies makes more planned purchase.

• Journal of the Korean Society of Costume
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• v.64 no.7
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• pp.128-142
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• 2014

In the new media age, the importance of personal style is highlighted, as the fashion recipients independently create their own images by transforming and recombining the fashion information gathered from the fashion blogs - the most representative form of social networks. The study aims to identify the types and styles of imaginary ego-images represented on the personal fashion blogs as a new space of self-expression, based on Lacan's gaze; the imaginary of the unconscious world and the ego-concept. According to literature search, the imaginary ego-image is classified as narcissism, regression, identification, and virtuality. In the case study, Narcissism is represented mostly as bloggers' satisfaction and beliefs about their fashion styles. The degeneration represents childhood images including a mother, as well as retro and vintage images that recreate the fashions of bygone eras - such as medieval, $19^{th}$ or 20th century fashion. Identification is the connection with the various areas of culture and art, especially movies and music. Virtuality represents hypothetical situations of mythical, fairy tale-like, surreal, or dreamlike atmospheres and hypothetical bodies that appear removed, disassembled, or crooked. The imaginary ego-images emerged on the personal fashion blogs are also classified into specific style depending on the attributes of the ego images-such as kidult style, retro style, ethnic style, and surreal style.

• Journal of Microbiology and Biotechnology
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• v.22 no.8
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• pp.1054-1058
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• 2012

In order to predict biologically significant attributes such as function from protein sequences, searching against large databases for homologous proteins is a common practice. In particular, BLAST and HMMER are widely used in a variety of biological fields. However, sequence-homologous proteins determined by BLAST and proteins having the same domains predicted by HMMER are not always functionally equivalent, even though their sequences are aligning with high similarity. Thus, accurate assignment of functionally equivalent proteins from aligned sequences remains a challenge in bioinformatics. We have developed the FEP-BH algorithm to predict functionally equivalent proteins from protein-protein pairs identified by BLAST and from protein-domain pairs predicted by HMMER. When examined against domain classes of the Pfam-A seed database, FEP-BH showed 71.53% accuracy, whereas BLAST and HMMER were 57.72% and 36.62%, respectively. We expect that the FEP-BH algorithm will be effective in predicting functionally equivalent proteins from BLAST and HMMER outputs and will also suit biologists who want to search out functionally equivalent proteins from among sequence-homologous proteins.

• Quality Improvement in Health Care
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• v.8 no.2
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• pp.146-159
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• 2001

Background : To propose effective strategies for successful implementation of QI in health care institutions, by identifying facilitating factors and barriers to conducting QI programs. Methods : In order to examine empirical evidence on the success factors or barriers to QI implementation in hospitals, a literature study was performed on the basis of MEDLINE search. Among the identified literature. 13 provided reliable findings and basis comprehensive discussion on this issue and thus were selected for in-depth analysis. A mailed questionnaire survey was conducted for hospital CEOs and QI directors of hospitals with 400 beds or greater to investigate what attributes of their organizations they perceived as success factors or obstacles to QI implementation. Result : The analysis of selected literature and survey results presented that the primary factors considered to be most important as successful implementation of QI were: strong support from hospital CEOs, setting higher priority for QI activities, continuous and persistent efforts in QI activities, and active participation of clinical staffs. The barriers identified in this study were : the lack of orientation and understanding of QI concepts, low level of interest and participation of physician in QI programs, the lack of evaluation and rewarding system for QI activities. Conclusion : By identifying factors that affect facilitation of QI, the study results will be of great use for either institutions being in the early stage of evolving QI or those looking for better strategies to achieve more active and persistent QI implementation in their institutions.

• The Journal of the Korea Contents Association
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• v.8 no.6
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• pp.261-268
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• 2008

An author of a paper is represented as his/her personal name in a bibliographic record. However, the use of names to indicate authors may deteriorate recall and precision of paper and/or author search, since the same name can be shared by many different individuals and a person can write his/her name in different forms. To solve this problem, it is required to disambiguate same-name author names into different persons. As features for author resolution, previous studies have exploited bibliographic attributes such as co-authors, titles, publication information, etc. This study attempts to apply email addresses of authors to disambiguate author names. For this, we first handle the extraction of email addresses from full-text papers, and then evaluate and analyze the effect of email addresses on author resolution using a large-scale test set.

• Korean Journal of Cognitive Science
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• v.20 no.4
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• pp.535-554
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• 2009

Information collected on mobile devices might be utilized to support user's memory, but it is difficult to effectively retrieve them because of the enormous amount of information. In order to organize information as an episodic approach that mimics human memory for the effective search, it is required to detect important event like landmarks. For providing new services with users, in this paper, we propose the prediction model to find landmarks automatically from various context log information based on attributed Bayesian networks. The data are divided into daily and weekly ones, and are categorized into attributes according to the source, to learn the Bayesian networks for the improvement of landmark prediction. The experiments on the Nokia log data showed that the Bayesian method outperforms SVMs, and the proposed attributed Bayesian networks are superior to the Bayesian networks modelled daily and weekly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.451-458
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• 2011

In order to provide the optimal location based services such as the optimal moving path search or the scheduling pattern prediction, the extraction of significant moving pattern which is considered the temporal and spatial properties of the location-based historical data of the moving objects is essential. In this paper, for the extraction of significant moving pattern we propose the location generalization method which translates the location attributes of moving object into the spatial scope information based on $R^*$-tree for more efficient patterning the continuous changes of the location of moving objects and for indexing to the 2-dimensional spatial scope. The proposed method generates the moving sequences which is satisfied the constraints of the time interval between the spatial scopes using the generalized spatial data, and extracts the significant moving patterns using them. And it can be an efficient method for the temporal pattern mining or the analysis of moving transition of the moving objects to provide the optimal location based services.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.595-598
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• 2007

Vast amount of XML documents raise interests in how they will be used and how far their usage can be expanded. This paper has two central goals: 1) easy and fast retrieval of XML documents or relevant elements; and 2) efficient and stable management of large-size XML documents. The keys to develop such a practical system are how to segment a large XML document to smaller fragments and how to store them. In order to achieve these goals, we designed SCOF(Service-centric Object Fragmentation) model, which is a semi-decomposition method based on conversion rules provided by XML database managers. Keyword-based search using SCOF model then retrieves the specific elements or attributes of XML documents, just as typical XML query language does. Even though this approach needs the wisdom of managers in XML document collection, SCOF model makes it efficient both retrieval and management of massive XML documents.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.453-462
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• 2006

Discovering sequential patterns is an important problem for many applications. Existing algorithms find sequential patterns in the sense that only items are included in the patterns. However, for many applications, such as business and scientific applications, quantitative attributes are often recorded in the data, which are ignored by existing algorithms but can provide useful insight to the users. In this paper, we consider the problem of mining sequential patterns with quantities. We demonstrate that naive extensions to existing algorithms for sequential patterns are inefficient, as they may enumerate the search space blindly. Thus, we propose hash filtering and quantity sampling techniques that significantly improve the performance of the naive extensions. Experimental results confirm that compared with the naive extensions, these schemes not only improve the execution time substantially but also show better scalability for sequential patterns with quantities.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.45-69
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• 2007

This paper is divided into two parts. The first part elaborates on four Information Retrieval (IR) models: a traditional IR model and three more recent, user-oriented models of It interaction presented by Belkin, Ingwersen, and Saracevic. The strengths and limitations of each model are discussed. The second part, based on an analysis of the previous models, presents the author's interactive model, namely, the Iceberg Model. The rationales that are given to explain the design of this model are associated with the following: a greater specificity of system attributes; more concrete interplays among different components of IR interaction; and, the increased role of the Human Information Intermediary (HII). In sum, the new model presents a framework that can evolve in varying information-seeking contexts.