• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.1
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• pp.89-113
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• 2020

Libraries are one of the essential living infrastructures in urban regeneration. Beyond its meaning as a basic living infrastructure, it is necessary to first understand the role, nature and forms of participation in existing urban regeneration projects in order for libraries to perform their functions and roles effectively as participants of urban regeneration. Therefore, this study investigates the contents related to libraries in the contents of the strategic plan related to urban regeneration projects, and considers them in terms of the role of the library and the form of participation. Through this, the city's library would seek to maximize its role and function as a participant in urban regeneration. As a result, the library in urban regeneration is expected to improve the quality of living environment, Urban vitality, culturally, educationally, socially/welfare role closely related to life, and the role of community as a hub. In addition, the types of library participation could be largely divided into regional and geographical libraries, hybrid libraries combined with various services, libraries based on community cooperation and linkage, and regional community hub libraries based on community participation. In the future, the library needs to promote a more active role change based on the five roles expected as participants in urban regeneration. In addition, more detailed discussions on librarians, services, and programs, which are the main subjects of library services, will be needed in developing urban regeneration plans in order for libraries to successfully fulfill their role as urban regeneration centers.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.765-776
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• 2018

Artificial Intelligence is a rapidly growing technology with the latest developments in computing technology and is considered as one of the next major technologies. Chat-Bot is a system that is designed to respond to user's input according to the rules that are set up in advance and it provides more services through simple and repetitive tasks such as counseling, ordering and others. Accordingly, the study aims to present a model of a celeb-bot using Artificial Intelligence. Celeb-Bot is a combination of Celeb, which are short for Celebrity and Chat-bot. Celeb-Bot provides a Chat-Bot service that allows people to talk to a celebrity. The celeb is the best thing to build a relationship and has the advantages of being accessible to anyone. At the same time, Artificial Intelligence is a technology that can be seen as a person, not a product. Based on this, we believe that Celeb's Characteristic and Chat-bot based on artificial intelligence technologies need to be combined, so variety of products can generate synergy. It is predicted that there will be variety of derivatives that utilize this technology, and it is going to present a celeb-bot model accordingly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.2028-2042
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• 1994

Properly defining signal and noise in a self-organizing system like ART(Adaptive Resonance Theory) neural network model raises a number of subtle issues. Pattern context must enter the definition so that input features, treated as irrelevant noise when they are embedded in a given input pattern, may be treated as informative signals when they are embedded in a different input pattern. The ATR automatically self-scales their computational units to embody context and learning dependent definitions of a signal and noise and there is no problem in categorizing input pattern that have features similar in nature. However, when we have imput patterns that have features that are different in size and nature, the use of only one vigilance parameter is not enough to differentiate a signal from noise for a good categorization. For example, if the value fo vigilance parameter is large, then noise may be processed as an informative signal and unnecessary categories are generated: and if the value of vigilance parameter is small, an informative signal may be ignored and treated as noise. Hence it is no easy to achieve a good pattern categorization. To overcome such problems, a Coupled-ART neural network capable of modularized categorization of patterns is proposed. The Coupled-ART has two layer of tightly coupled modules. the upper and the lower. The lower layer processes the global features of a pattern and the structural features, separately in parallel. The upper layer combines the categorized outputs from the lower layer and categorizes the combined output, Hence, due to the modularized categorization of patterns, the Coupled-ART classifies patterns more efficiently than the ART1 model.