• Information Systems Review
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• v.25 no.1
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• pp.27-46
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• 2023

Research on restaurant recommender systems has been proposed due to the development of the food service industry and the increasing demand for restaurants. Existing restaurant recommendation studies extracted consumer preference information through quantitative information or online review sensitivity analysis, but there is a limitation that it cannot reflect consumer semantic preference information. In addition, there is a lack of recommendation research that reflects the detailed attributes of restaurants. To solve this problem, this study proposed a model that can learn the interaction between consumer preferences and restaurant attributes by applying deep learning techniques. First, the convolutional neural network was applied to online reviews to extract semantic preference information from consumers, and embedded techniques were applied to restaurant information to extract detailed attributes of restaurants. Finally, the interaction between consumer preference and restaurant attributes was learned through the element-wise products to predict the consumer preference rating. Experiments using an online review of Yelp.com to evaluate the performance of the proposed model in this study confirmed that the proposed model in this study showed excellent recommendation performance. By proposing a customized restaurant recommendation system using big data from the restaurant industry, this study expects to provide various academic and practical implications.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.2
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• pp.197-205
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• 2016

This study is intended to look into the effects of project leader's core competencies(intellectual ability, management ability, emotional ability) on the Critical success factors(job satisfaction, organizational commitment, group cohesion) of project by environmental variables of organization. The results of this study were summarized as follows. First, the intellectual ability, management ability and emotional ability had a significant effect on the job satisfaction, organizational commitment and group cohesion. Second, the functional organization and project organization had a partial effect on project leader's core competencies. But the individual-centered organization had no moderating effect. For the project organization, all intellectual ability, management ability and emotional ability had a moderating effect on the organizational commitment. Consequently, project leader's core competencies are mechanisms to improve the job satisfaction, organizational commitment and group cohesion, and they have a different moderating effect according to the type of organization.

• Science of Emotion and Sensibility
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• v.9 no.4
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• pp.307-319
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• 2006

Problematic behaviors have been among adolescent population in school and home. Problematic behavior manifested in childhood and adolescence is reported to be a good predictor for adult criminal behavior although no clear factor to cause was identified. Based on literature review on this subject, our hypotheses that delinquency and aggressive behaviors are associated with brain information processing and emotionality in adolescents was developed and this study aimed to test these hypotheses. 1,479 male and female middle school students were selected and given the Trait Meta-Mood Scale, Korea Youth Self Report-Child Behavior Check List and Brain Preference Indicator Test. The main results are as follows: 1) Subjects with problematic behavior compared to average students showed a significant difference in sub-variables of emotionality ant the characteristics of brain information processing. 2) Young adolescent's emotionality and brain information processing characteristics have effects on problematic behaviors. 3) However, the effect on aggression and delinquency was different by gender.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.717-724
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• 2020

Due to the important role played by emotion in human interaction, affective computing is dedicated in trying to understand and regulate emotion through human-aware artificial intelligence. By understanding, emotion mental diseases such as depression, autism, attention deficit hyperactivity disorder, and game addiction will be better managed as they are all associated with emotion. Various studies for emotion recognition have been conducted to solve these problems. In applying machine learning for the emotion recognition, the efforts to reduce the complexity of the algorithm and improve the accuracy are required. In this paper, we investigate emotion Electroencephalogram (EEG) feature reduction and classification using Stack AutoEncoder (SAE) and Long-Short-Term-Memory/Recurrent Neural Networks (LSTM/RNN) classification respectively. The proposed method reduced the complexity of the model and significantly enhance the performance of the classifiers.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1171-1180
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• 2019

Emotion is a psycho-physiological process that plays an important role in human interactions. Affective computing is centered on the development of human-aware artificial intelligence that can understand and regulate emotions. This field of study is also critical as mental diseases such as depression, autism, attention deficit hyperactivity disorder, and game addiction are associated with emotion. Despite the efforts in emotions recognition and emotion detection from nonstationary, detecting emotions from abnormal EEG signals requires sophisticated learning algorithms because they require a high level of abstraction. In this paper, we investigated LSTM hyperparameters for an optimal emotion EEG classification. Results of several experiments are hereby presented. From the results, optimal LSTM hyperparameter configuration was achieved.

• Journal of the Korean Society of Costume
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• v.57 no.3 s.112
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• pp.23-36
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• 2007

It is important that ubiquitous technology changes paradigm of thought, not simple definition in the 21st digital era. Characteristics of ubiquitous computing are pervasive, disappearing, invisible, calm through environment. As IT Technology develops, designers, computer scientists, chemists, performance artists cooperate in order to find out the best way to make desirable digital clothing in the future, with the merit of each part. Digital clothing defines clothes of new generation equipped computer, digital installations. Digital clothing design demands intercept of electromagnetic waves, light-weight and esthetic appearance, for it is attached high-technology equipment near body. The purpose of this study is to analyze design features of digital clothing according to ubiquitous characteristics. The methods of this study are documentary research of previous study and case study. In the theoretical study, ubiquitous characteristics are function-intensive by convergence, interactivity, embedded mobility and human & emotion-oriented attributes. Based on ubiquitous characteristics, digital clothing design classified function-intensive design by convergence, design for Interactivity and multi-sensible & emotion-oriented design, because embedded mobility is a basic element of ubiquitous environment. The early days digital clothing design is function-intensive design, and have esthetic appearances and design for interactivity increasingly. Recently digital clothing design is expressed multi-sensible and emotion-oriented design.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.145-150
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• 2021

This thesis attempted to examine the mechanization of humans, humanization of machines, and coexistence through dance works. The dance works were reviewed by partial excerpts from Oscar Schlemer's <3 Chord Ballet>, Felindrome Dance Company's , and . Also, I looked at the dance work , which has an inherent form of coexistence. Through the above work, robot-like science and technology and fusion. It was found that various dance performances that coexist in complex forms provide continuous creativity to humans, and various forms of sensibility and creative movements based on data make it possible to produce rich performances for humans. This researcher expects numerous works that accept and reflect the changes of the times through the embodied interaction of dance performances with science and technology.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.33-42
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• 2024

With the recent rapid development of artificial intelligence (AI) technology, its use is gradually expanding to include creative areas and building new content using generative AI solutions, reaching beyond existing data analysis and reasoning applications. Content creation using generative AI faces challenges owing to technical limitations and other aspects such as copyright compliance. Nevertheless, generative AI may increase the productivity of experts and overcome barriers to creative work by allowing users to easily express their ideas as digital content. Thus, various types of applications will continue to emerge. As images and videos can be created using text input on a prompt, generative AI allows to create and edit digital assets quickly. We present trends in generative AI technology for images, videos, three-dimensional (3D) assets and scenes, digital humans, interactive content, and interfaces. In addition, the prospects for future technological development in this field are discussed.

• Korean journal of communication and information
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• v.31
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• pp.85-111
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• 2005

This paper aims at dealing with the communication of Korean gong sound. It is based on 'music-spirit theory' of Han-Gi Choi and Mead's 'symbolic interactionism', and does this by interpreting the message of gong sound that is mentioned in Korean literature. The gong sound brings out the message of symbolizing evaporation of Korean people's joy and regrettable matters in the playing yard by regulating of breathing according to the steps. By the novel "Gong Sound" of Sun-Tae Moon Korean gong sound has a message of people's joy, anger, avarice, anxiety and sorrow. In Jeong-Rae Jo's novel "Arirang" the Korean Gong Sound includes a message of evaporation of people's regret and raises the national spirit during the Japanese Imperialism. By Jeong-Ja Yoo's collection of poems, "The sound of flower breathing carried by gong sound", the Korean gong sound carries a message of a roar of spirit and breathing of the spring flower. In conclusion, the Korean gong sound is a sublime sound of sky which carries the message of symbolizing evaporation of people's joy and regrettable matters through the sound communication in the open space, and awakes us to a method of breathing with sky.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1114-1121
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• 2009

1990 년대 후반 이후 스마트 의류 연구는 기능성 및 인간 친화적인 측면으로의 접근 필요성이 증가됨에 따라 기능 및 사용자 중심의 연구로 진행되어 오고 있다. 이에 따라 최근 스마트 의류의 발달은 사용자 애플리케이션을 중심으로 세분화되어 개발되고 있다다변하는 의류 시장에서 스마트 의류 상품기획은 기존의 의류 상품기획과 같이 소비자 트렌드 중심의 경향과 함께 소비자의 특성을 파악하는 연구의 필요성이 대두되어 그 중요성은 날로 부상하고 있다. 그러나, 기존의 스마트 의류의 연구는 기능성, 사용성 기반의 연구자 중심의 개발이 이루어지고 있어, 소비자 중심, 마켓 중심의 연구가 미비한 실정이다. 따라서 본 연구에서는 스마트 의류 기획에 있어 가장 밀접한 관련이 예상되는 의복 및 의복행동 라이프 스타일과 디지털 라이프 스타일을 중심으로 라이프 스타일의 유형을 분석하고, 라이프 스타일에 따른 스마트 의류 수용도와 인지도를 조사하고자 하였다. 본 연구는 추후 스마트 의류의 수요가 가장 높을 것으로 예상되는 20 대, 30 대를 중심으로 이루어졌으며, 라이프 스타일에 따른 스마트 의류의 수용도와 인지 여부 및 스마트 의류의 선호도를 조사하여 그 결과를 제시하였다.그 결과 소비자 라이프스타일은 유행추구형, 감각적 정보추구형, 실용적 기능추구형의 세 유형으로 도출되었으며, 유행추구형 집단이 스마트 의류에 대한 인지도가 가장 높은 것으로 나타났다. 유행추구형은 엔터테인먼트 의류군을 선호하였으며, 스마트 의류 속성 중 외관을 다른 집단에 비해 중시하는 경향을 보였다. 감각적 정보추구형은 감성교감의류 및 생체 신호 측정의류의 선호도 및 필요성을 높게 인지하고 있었으며, 실용적 기능 추구형은 생체 신호 측정의류 및 환경과의 상호작용 하는 의류에 대해 선호하는 경향을 나타내며, 스마트 의류의 필요성을 다른 집단에 비해 높게 느끼고 있는 것으로 나타났다. 본 연구는 스마트 의류의 인식 및 선호도 등 상품화에 실질적인 평가 자료를 제시함으로써, 추후 스마트 의류의 상용화에 있어 시장 가능성 및 상품화를 위한 스마트 의류 기획 방향을 제시한 것에 의의가 있다.