Metaverse provides technology for people to connect, find communities, and grow businesses. Its sales have seen growth during the COVID-19 pandemic. In an era of metaverse, luxury brands such as Gucci, Ralph Lauren, Burberry, Balenciaga, and Dolce & Gabbana are trying to adapt to new changes. They launched NFT(Non-fungible token) goods, digital fashion, and virtual luxury goods on various metaverse platforms such as Zepeto, Roblox, and Fortnite. For example, Ralph Lauren in Zepeto provides various types of luxury items, immerses in virtual performances, and has a game plot interaction. As people immerse themselves in the Metaverse, they feel happy from various activities—such as watching advertisements, drinking juice, and playing with friends. Thus, what factors should be considered when the luxury brands manage the metaverse?

In recent years, with its amazing online interactive promotion ability, e-commerce live streaming has attracted the attention of theoretical scholars and practical experts. This study takes “co-presence (CP) ” and “social presence (SP) ”, which are the prominent features of e-commerce live streaming, as the breakthrough point to explore the mechanism of the influence of co-presence and social presence on purchase intention. In this study, consumers with e-commerce live streaming watching experience are taken as participants, and the method of structural equation modeling is used. It is found that: presence significantly impacts flow experience and consumer purchase intention, while the impact of the two kinds of presence (SP, CP) is variable. the promotion effect of the two kinds of presence (SP, CP) on consumer purchase intention is completely mediated by flow experience. The mediating effect of co-presence on consumer purchase intention through flow experience is regulated by e-commerce live streaming topicality, but social presence doesn’t.

Metaverse blends the physical and virtual worlds, transforming the customer's shopping experience. This study aims to identify the psychological mechanism in the metaverse environment and the relationship between metaverse experience and consumer happiness. To identify metaverse experiences, both behavioral and functional magnetic resonance imaging (fMRI) studies were conducted. In a behavioral study, we found that consumers' happiness increased when participants were in an immersive metaverse space. In the fMRI study, we found greater activation in the medial prefrontal cortex (MPFC) and lateral occipital cortex (LOC) regions in the high level of the immersive metaverse and found a positive relationship with consumers' happiness. This paper is the first attempt in marketing to provide an integrative brain map for the metaverse experience. This brain map helps marketers better understand the consumer experience. This study suggests that only in the immersive metaverse space where virtual and physical experiences interact can consumers become one with the virtual space and maximize customer experience values.

시리즈 애니메이션 IP들이 사업 다각화를 위해 웹툰으로 제작되어 서비스되는 경우들이 있는데, 영세한 애니 메이션 제작사들은 웹툰으로 제작할 때 발생하는 노동집약적인 작업 과정과 비용 때문에 접근이 어려운 실정 이다. 이를 위해 함께 협업한 연구실에서 인공지능을 활용하여 <Pitchfork Park> 애니메이션 시리즈의 웹툰 변 환 작업을 자동화하는 시스템을 개발하였다. 해당 시스템을 활용하면 단순 노동적으로 작업자가 일일이 수행 하던 1) 애니메이션 컷 선별, 2) 선별된 컷 재배치, 3) 말풍선 배치, 4) 대사 배치, 5) 효과선 추가 등 상당 부 분을 자동화할 수 있다. 시스템에서 출력된 작업물을 작업자가 확인하고, 후보정 작업을 거쳐 최종 결과물을 완성한다. 기존 작업 과정에서 필요한 노동력과 시간을 절약할 수 있고, 작품의 완성도도 향상시킬 수 있다. 본 연구는 기존 웹툰 작업 과정을 분석하여 인공지능을 활용한 작업 방식의 효율성을 검증하였으며, 결과적으 로 인공지능 기술을 활용한 애니메이션의 웹툰 변환 제작 파이프라인을 구축할 수 있는 토대를 확인하였다.

Patient-controlled sedation systems, in which the patient has control of sedative administration, have been shown to be effective and safe for patients undergoing minor procedures. Safety depends on the adequacy of the step-wise increase in dose of the sedative, the lockout time and patient’s ability to adjust the effective activation of the handset. While there is no patient-controlled sedation (PCS) system available domestically, we have developed a new purpose-built PCS pump, and determined its degree of precision using a microweight measuring scale. The PCS system was designed to be applied to most intravenous sedatives and work through a newly developed operating software algorithm that titrates the doses and lockout times. Our system titrates the doses through software modification, and for experimental purposes, the number of steps for handset activation by the patient was set to four, and the lockout time was set to 30 s. The degree of precision of the PCS system was tested using an electronic weighing scale. The comparison of the amount infused via the PCS system with weight on the scale showed nearly same patterns at the four infusion stages, and the difference was minimal (3% on average at each infusion step). We designed and manufactured a pilot button-type PCS pump capable of use by the patient for optimal sedation, and confirmed the precise working mechanism of the pump, thereby reducing the margin of error for infusion accuracy to 3% or less on average

본 논문은 필리핀 로컬 스페셜티 커피에 대한 소비자의 선호도를 밝히고 일반커피 대비 스페셜티 커피에 대해 소비자들이 부여하는 가치를 추정하는 것에 목적이 있다. 특히 소비자 잉여를 극대화하는 스페셜티 커피의 최적 가격을 분석하여 커피 농가를 포함한 생산자, 투자자들의 이해를 높이고자 하였다. 주 요 연구 결과는 다음과 같다. 1. 응답자들의 연령 및 성별에 따라 소비하는 커피의 형태가 다르게 나타남. 그러나 공통적으로 주로 아침에, 집에서, 습관적으로 커피를 섭취함. 가장 선호하는 커피의 맛은 단맛과 쓴맛임. 대부분의 소비자들은 양조 커피, 압착 커피를 소비함. 2. 고품질의 원두를 엄선하여 만들어지는 스페셜티 등급의 커피 한 잔에 대한 소비자의 평균 지불의사가격은 일반 커피 (42페소) 대비 271% 높은 156페소(약 3.2달러)로 분석됨. 연령이 어릴수록, 학력과 소득이 높을수록, 스페셜티 커피에 대한 사전적 인지도가 높을수록, 향후 스페셜티 커피에 대한 구매 의사가 강할수록 스페셜티 커피에 보다 높은 지불의사가격을 표현함. 3. 로컬 스페셜티 커피는 원두 구매, 가공 및 로스팅, 등급 평가 비용이 발생하여 적절한 가격 인상이 요구됨. 기존 일반 커피 가격대비 40% 인상까지 소비자 후생이 증가하는 것으로 나타나는 반면, 스페셜티 커피 가격이 일반커피 가격대비 50% 이상 인상되는 경우에는 소비자들의 후생이 감소하는 것으로 나타남. 4. 필리핀 소비자들이 지역에서 생산된 스페셜티 커피에 대한 높은 선호를 갖고 있다는 점을 고려하면 현지 스페셜티 커피에 대한 대대적인 홍보가 로컬 스페셜티 커피에 대한 인지도를 높이고 시장 확대로 이어질 수 있음. 이는 필리핀 커피 로드맵, 필리핀 농무부의 지속 가능한 발전 계획 목표 달성에 기여할 것임.

Culturally, it is wonderful that they try to integrated their ordinary life on the earth into heavenly spiritual life through their funeral rituals and song so called Yeong-Jang-Sori as same context as in the Pacific. During life, they eat traditional bread ( Bing-Teok) and drink traditional liquor (O-Me-Gi Ssol) and wear persimmon-dyeing Gal-ot healthily and they meet each other in the heaven eternally through happy dying. We are evidently sensitive to the unique cultural heritage of the island. UNESCO’s mission is the promotion of peace amongst peoples and its cultural heritage is also dedicated to working with indigenous peoples’ on their eco-friendlly knowledge of a sustainable planet. As Jeju Island is inscribed in part as both a World Heritage Site and a UNESCO Biosphere, it is important to give due consideration to the natural and cultural heritage of the island, as seen and experienced by the islanders. As such, if there is something useful we can discuss, for example the recognition of the special relationship between Jeju islanders and sacred natural sites on the island.

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.