• Journal of Smart Tourism
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• 제1권3호
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• pp.31-44
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• 2021

The emergence of the digital economy and easy accessibility to Web 2.0 tools has seen an expansion of the influencer ecosystem within the travel and tourism industry. Founded on the principles of reference groups and peer reference there is a growing trend amongst industry practitioners who are now opting to move away from many of the traditional approaches used to market their products and services and are instead taking advantage of the concept of e-word-of-mouth (eWOM). Whilst there is a growing body of academic literature addressing the notion of influencer marketing, there is little understanding of influencer marketers themselves. Consequentially, this study addresses this gap in the literature through the quantitative examination of those who promote products, services, or companies by distributing eWOM through their online digital channels and presence; otherwise known as travel influencers. A quantitative research approach involving an online survey yielded 255 responses from travel influencers. The research findings indicate that those who work in this field prefer not to be awarded the label "travel influencer," focusing instead on their specific method of influencing, such as blogging and vlogging or sharing Instagram updates. The research also demonstrates how the new influencers have a strong role in generating travel urge and desire. The research contributes to the wider body of academic literature and travel industry practitioners by establishing the general profile of influencers and their increasingly specialized role in tourism and hospitality marketing.

• 한국게임학회 논문지
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• 제21권2호
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• pp.123-138
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• 2021

본 연구는, 블록체인기술을 접목하여 개발된 게임들이 NFT 기반 게임아이템의 상호 운용성(Interoperability)을 통해 게임서비스의 성과증대와 신 모델 창출 등 비즈니스모델 혁신을 만들어 낼 수 있다는 점을 '플레이댑' 플랫폼에 대한 실증사례 분석을 통해 확인하고자 하였다. 연구를 통해, 블록체인게임의 기술적 혁신성은, 사회경제적, 산업생태계적인 거시적 관점에서 긍정적인 영향력이 있음을 알 수 있었다. 또한 게임 내 자산의 소유권 확보 및 이를 통한 새로운 사업모델의 창출을 통해, 참여개발사 와 플랫폼 제공사 등 기업의 차별화 및 고객편익 증대 부분에서 명확한 영향력을 만들어 내고 있음을 알 수 있었다.

• 디지털산업정보학회논문지
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• 제19권1호
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• 디지털산업정보학회논문지
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• 제19권4호
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• pp.45-52
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• 2023

With the advent of deep learning, Artificial Intelligence (AI) technology has experienced rapid advancements, extending its application across various industrial sectors. However, the focus has shifted from the independent use of AI technology to its dispersion and proliferation through the open AI ecosystem. This shift signifies the transition from a phase of research and development to an era where AI technology is becoming widely accessible to the general public. However, as this dispersion continues, there is an increasing demand for the verification of outcomes derived from AI technologies. Causal AI applies the traditional concept of causal inference to AI, allowing not only the analysis of data correlations but also the derivation of the causes of the results, thereby obtaining the optimal output values. Causal AI technology addresses these limitations by applying the theory of causal inference to machine learning and deep learning to derive the basis of the analysis results. This paper analyzes recent cases of causal AI technology and presents the major tasks and directions of causal AI, extracting patterns between data using the correlation between them and presenting the results of the analysis.

• 한국농림기상학회지
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• 제11권2호
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• pp.72-78
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• 2009

관측밀도가 동일한 조건에서 단위격자점의 크기를 줄일 경우 PRISM 방식에 의해 추정된 강수량 분포 가 단위격자점의 크기를 줄이기 전에 비해 개선되는지 확인하기 위해 PRISM 코드를 수정하여 $270m{\times}270m$ 격자점 단위로 구동할 수 있도록 하였다. 남한 전역의 지형자료를 270m DEM으로부터 준비하고 432개 기상청 자동기상관측소의 2007년 월별 적산강수량 자료를 입력자료로 하여 각 격자점의 PRISM 회귀식을 도출하였다. 회귀모형과 DEM 고도에 의해 각 격자점의 월별 적산강수량을 추정한 다음, 추정된 강수량분포도로부터 한국수자원공사 우량관측소 166개소에 해당하는 격자점의 자료를 추출하여 해당관측소의 실측값과 비교하였다. 동일한 강수자료를 이용하되 이번에는 5km 격자점의 PRISM 회귀모형을 유도하여 강수량 분포도를 작성하고 166개 지점 추정강수량을 추출하여 실측자료와의 차이를 RMSE로 표현하였다. 5km 대신 270m 분해능의 DEM을 사용할 경우 월 강수량이 100mm 이상인 경우 평균 10%의 오차 감소효과가 확인되었다.

• Journal of Platform Technology
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• 제9권4호
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• pp.10-31
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• 2021

최근 구글 세라고 지칭되는 디지털 세가 OECD 제31차 총회(2021. 10. 08)에서 136개국의 전폭적인 지지로 최종 합의되어 2023년부터 시행될 예정이다. 본 연구의 목적은 OECD가 글로벌 MNE를 대상으로 마련한 디지털 세에 대하여 분석하고 국내 산업에 미치는 파급효과와 우리나라의 대응 방안을 제시하는 것이다. 첫 번째 연구로 디지털 세에 대한 국제합의 내용을 분석한 결과, 글로벌 MNE가 해외 국가에 사업장을 설치하지 않더라도 매출과 이익이 발생하면 초과이익금의 25%를 세금으로 부담하고(필라1), 모든 국가에서 사업을 수행하면 최소 15%의 세금을 부담하는 것이다(필라 2). 이것은 세계 각 국가가 글로벌 MNE가 향후 자국 시장을 쉽게 잠식할 것을 예상하여 자국 기업을 보호하는 최소한의 대응책을 마련하기 위한 것으로 판단된다. 두 번째 연구는 글로벌 MNE는 왜 그렇게 강력한가? 에 대한 이유를 찾기 위해서 구글과 B2B SaaS 기업을 중심으로 동향을 분석하였다. 분석 결과, 글로벌 MNE는 디지털플랫폼 파트너십 생태계를 구축하여 해외 국가에 쉽게 진입하고 신속히 확장해 나가는 것을 발견하였다. 결론에서 우리의 대응 방안으로 산업육성정책을 창업 기업, 산업 그리고 국가 수준으로 각각 구분하여 제시하였다.

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.770-778
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• 2007

Fish schooling or group moving in cyber underwater is a part of beautiful and familiar ecosystem. It is not so easy to present the behavior of fish crowd naturally as a computer animation. Thanks to development of computer graphics in entertainment industry, the numbers of digital films and animations is increased and the scenes of numerous crowd are shown to us. Though there are many studies on the techniques to process the behavior of crowd effectively and the developments of crowd behavioral systems, there is not enough study on the development for an efficient crowd behavioral simulator. In this' paper, we smartly present the types offish behavior in cyber underwater and make up for the weak points of time and cost. We develop the fish schooling behavior simulator for the contents of cyber underwater, automating fish behavioral types realistically and efficiently.

• 전기학회논문지P
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• 제62권4호
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• pp.192-197
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• 2013

Road traffic noise barriers being used to reduce the noise, but the city surroundings inhibition, ecosystem disturbance, and it is difficult to maintain. Can enhance or complement the existing noise barrier performance, so that it is necessary to develop an electronic noise-reduction system In this paper, we proposed an electronic road noise reduction devices to reduce road noise for a DSP-based signal processing and analog signal input-output controller. In order to verify the control performance, we performed noise reduction experimentation of ANC by filtered-X LMS algorithm and traffic noise signal injection. The controller is equipped with noise reduction algorithms were tested on the characteristics of directional and omnidirectional speaker.

• 한국IT서비스학회지
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• 제21권3호
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• pp.1-25
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• 2022

The financial MyData service has implemented in January 2022 and launched 45 services by banks, securities, credit cards and fintech companies. This study applied the Q methodology, to identify the user types of MyData services and compared the perceptions of employees of financial institutions who plan and develop the MyData services. There are three types of MyData service users: active users, limited users who focus on consumption and asset status inquiry, and sensitive users for personal information. There were two types of recognition of financial company employees. One is the active user support other is the sensitive user for personal information support. The analysis of subjective perceptions can be used as a reference for establishing a company's MyData service marketing strategy and establishing related policies to improve the MyData ecosystem.

• Journal of Information Technology Applications and Management
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• 제29권3호
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• pp.75-93
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• 2022

The purpose of this study is to compare and analyze each government's ICT SME support policies to cope with changes in the ICT ecosystem paradigm. In particular, the core policies and policy trends of the Moon's government are presented through keyword network analysis and cognitive map analysis. As a result, core technologies such as ICT(Information Communication Technology), AI(Artificial Intelligence), Big Data, and 5G, which have high values of betweenness centrality and closeness centrality, are major keywords with high propagation power. The cognitive map analysis shows that the opportunity factors for the 4th industrial revolution are being activated through the ICT infrastructure circulation process, the domestic market circulation process, and the global market circulation process. This study is meaningful in terms of cognitive map analysis and utilization based on scientific analysis.