• 한국고분자학회지:고분자과학과기술
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• 제26권2호
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• pp.126-139
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• 2015

• 한국의류산업학회지
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• 제24권5호
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• pp.577-592
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• 2022

This study aims to confirm which factors related to technology acceptance affect generation MZ's use of luxury fashion platforms. For this purpose, Internet self-efficacy and technology readiness were added as new exogenous and moderating variables using extended UTAUT. Then, performance expectancy, effort expectancy, social influence, and facilitating condition as a factor of UTAUT were set as mediating factors. Response data were collected through questionnaires for generation MZ with experience in using luxury fashion platforms, and a factor analysis, reliability analysis, correlation analysis, and path analysis were conducted using the SPSS and AMOS statistical programs. According to the results, the Internet self-efficacy of generation MZ significantly affected on performance expectancy, effort expectancy, social influence, and facilitating conditions on the luxury fashion platform. Moreover, performance expectancy and social influence had a significant effect on the use intention of luxury fashion platforms, but effort expectancy and facilitating condition did not have a significant effect on use intention and use behavior. Additionally, as the moderating effect of technology readiness affects only the relationship between social influence and behavioral intention, it was confirmed that social influence is an important variable with the characteristics of MZ consumers. Therefore, it is deemed necessary to recognize the importance of social influence when trying to use new technologies targeting generation MZ in the fashion industry.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.149-160
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• 2024

For examining Web3.0 video streaming (VS) platforms in terms of the decentralized technology, tokenization and decentralized autonomous organization (DAO), we look at four platforms like DLive, DTube, Livepeer, and Theta Network (Theta). As a result, DLive which firstly partnered with Medianova for CDN and with Theta for peer to peer (P2P) network and migrates to Tron blockchain (BC), receives no commission from what creators earn, gives rewards to viewers by measuring engagement, and incentivizes participation by allowing 20% of donation & fees for funding development, 5% to BitTorrent Token (BTT) stakeholders (among these 5%, 20% to partners, 80% to other BTT stakeholders). DTube on its own lower-layer BC, Avalon, offers InterPlanetary File System (IPFS), gives 90% of the created value to creators or curators, and try to empower the community. Livepeer on Ethereum BC offers decentralized CDN, P2P, gives Livepeer Token (LPT) as incentive for network participants, and delegators can stake their LPT to orchestrators doing good. Theta on its native BC pulls streams from peering caching nodes, creates P2P network, gives Theta utility token, TFUEL for caching or relay nodes contributors, and allows Theta governance token, THETA as staking token. We contribute to the categorization of Web3.0 VS platforms: DLive and DTube reduce the risk of platform censorship, promote the diverse content, and allow the community to lead to more user-friendly environments. On the other hand, Livepeer and Theta provide new methods to stream content, but they have some differences. Whereas Livepeer focuses on the transcoding layer, Theta concentrates both on the video application layer and content delivery layer. It means, Theta tries to deliver value to all participants by enhancing network quality, reducing CDN cost, and rewarding users in utility tokens for the storage and bandwidth they provide.

• International Journal of Advanced Culture Technology
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• 제7권4호
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• pp.289-294
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• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

• 한국인공지능학회지
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• 제10권2호
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• pp.19-24
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• 2022

Metaverse refers to a world that transcends reality. Metaverse is a compound word of meta (transcendence) and universe (universe). The impact of the corona pandemic has provided an opportunity to rapidly grow the metaverse based on realistic content along with online and non-face-to-face environments. Various content and service platforms reflecting the concepts of metaverse and digital twin are rapidly spreading around the world in line with the pandemic situation. As their needs accelerate in response to the COVID-19 situation, the technology of metaverse and digital twin is attracting attention again as an indispensable condition for business, culture and art, national industry, and public services. In particular, the metaverse requires the balanced development of ecosystem components based on various advanced convergence technologies. In this paper, the concept of metaverse and digital twin, types of platforms, and development status are examined, and trends of key element technologies are investigated and analyzed. As these key element technologies, XR sensory technology, avatar technology, and other XR devices and parts were examined. Through this, we want to clearly pinpoint the direction in which the metaverse will develop through future technologies, services, and follow-up research.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.288-294
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• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• 한국BIM학회 논문집
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• 제13권2호
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• pp.16-28
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• 2023

The concept of the Metaverse has been around not only for play but also for daily use. The interest in Metaverse is increasing, and various industries such as medicine, media, and financial started to use the new technology for diverse purposes. In addition, interest in the Metaverse is increasing in the architectural industry, but not much research has been done yet. Recently, some studies started to study focusing on the architectural design of Metaverse and the technological characteristics of Metaverse. However, there are limited studies about the utilization of the Metaverse in the architectural design process or construction process. From this perspective, the study aims to analyze the applicability of the Metaverse in the architectural design process through Metaverse case studies. In order to accomplish the research goal, the study classified user experience and technology of Metaverse in the literature review and Metaverse use in other industries such as commercial, medical, media entertainment, and construction industry. Then, this study analyzes six representative Metaverse platforms according to the application of Metaverse in the architectural design process. Finally, this study discussed the future direction and potential of Metaverse application in the Architectural design process.

• 센서학회지
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• 제33권3호
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• pp.139-146
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• 2024

Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10^-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.

• Structural Engineering and Mechanics
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• 제30권3호
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• pp.331-350
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• 2008

A framework for multi-platform analytical and multi-component hybrid (testing-analysis) simulations is described in this paper and illustrated with several application examples. The framework allows the integration of various analytical platforms and geographically distributed experimental facilities into a comprehensive pseudo-dynamic hybrid simulation. The object-oriented architecture of the framework enables easy inclusion of new analysis platforms or experimental models, and the addition of a multitude of auxiliary components, such as data acquisition and camera control. Four application examples are given, namely; (i) multi-platform analysis of a bridge with soil and structural models, (ii) multiplatform, multi-resolution analysis of a high-rise building, (iii) three-site small scale frame hybrid simulation, and (iv) three-site large scale bridge hybrid simulation. These simulations serve as illustrative examples of collaborative research among geographically distributed researchers employing different analysis platforms and testing equipment. The versatility of the framework, ease of including additional modules and the wide application potential demonstrated in the paper provide a rich research environment for structural and geotechnical engineering.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.110-110
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• 2017

Biological systems offer unique principles for the design and fabrication of engineering platforms (i.e., popularly known as "Biomimetics") for various applications in many fields. For example, the lotus leaves exhibit unique surfaces consisting of evenly distributed micro and nanostructures. These unique surfaces of lotus leaves have the ability of superhydrophobic property to avoid getting wet by the surrounding water (i.e., Lotus effect). Inspired by the surface topographies of lotus leaves, the artificial superhydrophobic surfaces were developed using various micro- and nanoengineering. Here, we propose new platforms that can control hydrophilic and hydrophobic property of surfaces by mimicking micro- and nanosurfaces of various natural leaves such as common camellia, hosta plantaginea, and lotus. Using capillary force lithography technology and polymers in combination with biomimetic design principle, the unique micro- and nanostructures mimicking natural surfaces of common camellia, hosta plantaginea, and lotus were designed and fabricated. We also demonstrated that the replicated polymeric surfaces had different hydrophilic and hydrophobic properties according to the mimicking the natural leaf surfaces, which could be used as a simple, but powerful methodology for design and fabrication of controlled hydrophilic and hydrophobic platforms for various applications in the field of agriculture and biological engineering.