• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.45-62
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• 2021

This article examines celeactor as cultural contents focused on the multi-persona in a South Korean reality show program . The celeactor is a form of celebrity and part of a celetoid. Celebrity can be categorized by three forms: ascribed form, achieved form and attributed form. In attributed form, the celetoid suddenly becomes popular through the media. The celeactor is a subcategory of the celetoid. The celeactor is defined by a virtual character that exist in temporary or institutionalized traits of popular culture. The Korean celebrity culture presents Korean intellectual factors, spiritual aspects, tastes, moral virtue, power relationships and traditional hierarchy. In order to examine the features of the Korean celeactor in cultural contents, this article focuses on the multi-persona of celebrity in South Korean popular culture through fantasy, challenge and nostalgia. This article examines the multi-persona of celebrity represented in South Korean popular culture as a negotiated response to cultural identity deconstructed and reconstructed in performance. The research methodology is to analyze a South Korean television reality show program on MBC Hangout with Yoo that represents various sub-characters performed by Jae-suk Yoo, a South Korean comedian and host. As for theoretical underpinning, this exploration joins work on Erving Goffman's (1959) notion of self-presentation and Chris Rojek's (2001) celebrity studies.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.572-577
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• 2020

일관된 발화를 생성함에 있어 인격데이터(persona)의 도입을 이용한 연구가 활발히 진행되고 있지만, 한국어 데이터셋의 부재와 데이터셋 생성의 어려움이 문제점으로 지적된다. 본 연구에서는 인격데이터를 포함하지 않고 일관된 발화를 생성할 수 있는 방법으로 다중 대화 시스템에서 사전 학습된 자연어 추론(NLI) 모델을 도입하는 방법을 제안한다. 자연어 추론 모델을 이용한 관계 분석을 통해 과거 대화 내용 중 발화 생성에 이용할 대화를 선택하고, 자가 참조 모델(self-attention)과 다중 어텐션(multi-head attention) 모델을 활용하여 과거 대화 내용을 반영한 발화를 생성한다. 일관성 있는 발화 생성을 위해 기존 NLI데이터셋으로 수행할 수 있는 새로운 학습모델 nMLM을 제안하고, 이 방법이 일관성 있는 발화를 만드는데 기여할 수 있는 방법에 대해 연구한다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.263-268
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• 1999

The most important things to the tube the of the heat exchanger are the precision of t hole position and the quality of the drill face. Nowadays, 6 and 12 spindle multi-drilling machine controlled by CNC or used to drill holes of the tube sheet. The drilling of 12 axes can offer high speover three times as fast as the drilling of axis. However, the drilling of 12 axes h difficulty in controlling many motors to d spindles and assigning a corresponded numbe accurately to each axis. In the past, conventional method to inspect the code the drilling was machining holes on a thin plate previously which resulted in the productivity because it required a h production cost by machining and weldin time. In this thesis, there are two drilling codes different from CNC code. M code is used to control many motors and S code is used to assign a correspondent number for each axis. For increasing the productivity by removing process, this paper is intended to take simulation of the drill machining c including 6 and 12 axis on the persona computer.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.281-286
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• 2023

더욱 사람같은 대화 모델을 실현하기 위해, 페르소나 메모리를 활용하여 응답을 생성하는 연구들이 활발히 진행되고 있다. 다수의 기존 연구들에서는 메모리로부터 관련된 페르소나를 찾기 위해 별도의 검색 모델을 이용한다. 그러나 이는 전체 시스템에 속도 저하를 일으키고 시스템을 무겁게 만드는 문제가 있다. 또한, 기존 연구들은 페르소나를 잘 반영해 응답하는 능력에만 초점을 두는데, 그 전에 페르소나 참조의 필요성 여부를 판별하는 능력이 선행되어야 한다. 따라서, 우리의 제안 모델은 검색 모델을 활용하지 않고 생성 모델의 내부적인 연산을 통해 페르소나 메모리의 참조가 필요한지를 판별한다. 참조가 필요하다고 판단한 경우에는 관련된 페르소나를 반영하여 응답하며, 그렇지 않은 경우에는 대화 컨텍스트에 집중하여 응답을 생성한다. 실험 결과를 통해 제안 모델이 장기적인 대화에서 효과적으로 동작함을 확인하였다.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.13-26
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• 2024

Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.