• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.111-119
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• 2022

The purpose of this paper is to examine the change in perception of 3D virtual fashion before and after COVID-19 using big data analysis. The data collection period is from January 1, 2017, before the outbreak of COVID-19, to October 30, 2022, after the outbreak. Big data was collected for key words related to 3D virtual fashion extracted from social media such as Naver, Daum, Google, and YouTube using Textom. After the collected words were refined, word cloud, word frequency, connection centrality, network visualization, and CONCOR analysis were performed. As a result of extracting and analyzing 32,461 words with 3D virtual fashion as a keyword, the frequency and centrality of fashion, virtual, and technology appeared the highest, and the frequency of appearance of digital, design, clothing, utilization, and manufacturing was also high. Through this, it was found that 3D virtual fashion is being used throughout the industry along with the development of technology. In particular, the key words that stand out the most after COVID-19 are metaverse and 3D education, which are in high demand in the fashion industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.33-42
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• 2016

Recently, the investment and study competition regarding machine running is accelerating mainly with Google, Amazon, Microsoft and other leading companies in the field of artificial intelligence. The security weakness of virtualization technology security structure have been a serious issue continuously. Also, in most cases, the internal data security depend on the virtualization security technology of platform provider. This is because the existing software, hardware security technology is hard to access to the field of virtualization and the efficiency of data analysis and processing in security function is relatively low. This thesis have applied user significant information to machine learning algorithm, created security authentication vector able to learn to provide with a method which the security authentication can be conducted in the field of virtualization. As the result of performance analysis, the interior transmission efficiency of authentication vector in virtualization environment, high efficiency of operation method, and safety regarding the major formation parameter were demonstrated.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.397-419
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• 2020

Business analytics is a management tool for achieving significant business performance improvements. Many organizations fail to or only partially achieve their business objectives and goals from business analytics. Business analytics adoption is a multi-stage complex activity consisting of evaluation, adoption, and assimilation stages. Several research papers have been published in the field of business analytics, but the research on multi-stage BA adoption is fewer in number. This study contributes to the scant literature on the multi-stage adoption model by identifying the critical themes for evaluation, adoption, and assimilation stages of business analytics. This study uses the thematic content analysis of peer-reviewed published academic papers as a research technique to explore the key themes of business analytics adoption. This study links the critical themes with the popular theoretical foundations: Resource-Based View (RBV), Dynamic Capabilities, Diffusion of Innovations, and Technology-Organizational-Environmental (TOE) framework. The study identifies twelve major factors categorized into three key themes: organizational characteristics, innovation characteristics, and environmental characteristics. The main organizational factors are top management support, organization data environment, centralized analytics structure, perceived cost, employee skills, and data-based decision making culture. The major innovation characteristics are perceived benefits, complexity, and compatibility, and information technology assets. The environmental factors influencing BA adoption stages are competition and industry pressure. A conceptual framework for the multi-stage BA adoption model is proposed in this study. The findings of this study can assist the practicing managers in developing a stage-wise operational strategy for business analytics adoption. Future research can also attempt to validate the conceptual model proposed in this study.

• Journal of Korean Home Economics Education Association
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• v.36 no.1
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• pp.39-54
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• 2024

This study analyzed Naver, Daum, Google, YouTube, and Twitter using TEXTOM for two years and four years as of January 18, 2020. The results are as follows. First, the total number and volume of keyword search data related to youth and diet were slightly higher after COVID-19, showing that interest increased due to COVID-19. Second, as a result of frequency analysis, 'education' was the highest before COVID-19, and 'health' was the highest after COVID-19, showing that interest in health is increasing due to the increased importance of health and immunity due to COVID-19. Third, as a result of frequency weight analysis of the top 50 keywords, 'education' showed the highest frequency before COVID-19, and 'acne' after COVID-19. Fourth, the results visualized using word cloud showed that the keywords 'education' before COVID-19 and 'health' after COVID-19 appeared the largest and boldest, showing the highest frequency and importance. As a result of the above results, we were able to use the text mining method to apply it to eating habits, and we used materials visualized as a highly readable word cloud in units such as eating problems in adolescence and balanced meal planning and selection in the home economics curriculum to improve the teaching of the class. The direction of proper eating habits education, including using it as a medium, was presented.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.15-29
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• 2021

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.23-34
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• 2017

During Khmer Rouge Regime, Cambodian pop music was completely forgotten since 90% of artists were killed. After recovering from war since 1979, the music started to grow again in 1990. However, Cambodian popular music dynamic and flows are observably directed by the multifaceted socioeconomic, political and creative forces. The major problems are the plagiarism and piracy which have been prevailing for years in the industry. Recently, the consciousness of the need to preserve Khmer original songs from both fans and artist have been increased and become a new trend for Cambodia young population. Still, the music quality is in the limit state. To increase the mind-set, the feedbacks and inspiration are needed. The study suggested a music ranking website using sentiment analysis which data were collected from Production Companies Facebook Pages' posts and comments. The study proposed an algorithm which translates from Khmer to English, doing sentiment analysis and generate the ranking. The result showed 80% accuracy of translation and sentiment analysis on the proposed system. The songs that rank high in the system are the songs which are original and fit the occasion in Cambodia. With the proposed ranking algorithm, it would help to increase the competitive advantage of the musical productions as well as to encourage the producers to compose the new songs which fit the particular activities and event.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.59-87
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• 2014

In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.