• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.123-126
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• 2023

본 논문에서는 철도 인근 주거지역, 철도 건널목, 철도 터널, 철도 교량을 위험 상황으로 설정하고, 각 상황이 철도가 아닌 다른 상황에서 발생할 때와 철도에서 발생할 때와의 위험도 차이를 분석하며 철도 위험 상황에 영향을 미치는 요인들을 분석한다. 또한, 요인별 위험도의 기준을 설정하고 설정한 위험 상황과 유사한 상황에 대한 데이터 발생 시 해당 데이터를 웹 어플리케이션에 송출하여 소비자들에게 서비스를 제공한다.

• Educational Technology International
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• 제24권2호
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• pp.295-329
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• 2023

The recent development of metaverse-related technology has led to efforts to overcome the limitations of time and space in education by creating a virtual educational environment. To make use of this platform efficiently, applying learning analytics has been proposed as an optimal instructional and learning decision support approach to address these issues by identifying specific rules and patterns generated from learning data, and providing a systematic framework as a guideline to instructors. To achieve this, we employed an inductive, bottom-up approach for framework modeling. During the modeling process, based on the activity system model, we specifically derived the fundamental components of the learning analytics framework centered on learning activities and their contexts. We developed a prototype of the framework through deduplication, categorization, and proceduralization from the components, and refined the learning analytics framework into a 7-stage framework suitable for application in the metaverse through 3 steps of Delphi surveys. Lastly, through a framework model evaluation consisting of seven items, we validated the metaverse learning analytics framework, ensuring its validity.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2008년도 춘계학술발표대회
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• pp.331-334
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• 2008

현재 위피 저작도구는 위피 코드 작성의 편의성이 부족하고, 시각화를 배제한 문법 중심의 프로그래밍 도구가 대부분이다. 이로 인해 규모가 작은 위피 응용프로그램의 경우에도 직접 코딩해서 개발하고 있다. 따라서 위피 상위레벨(High level) 컴포넌트를 GUI 위젯(Widget)으로 시각화하고, 이를 모바일 레이아웃에 쉽게 적용한 후, 위피 코드로 렌더링(Rendering) 해주는 저작도구에 대한 연구가 필요하다. 본 논문에서는 위젯, 기본 위피 코드, 에뮬레이터 관리를 위해 W2PM(Widget and WIPI Platform Management)을 제안하고, 이를 시스템 기능 요구사항에 반영하여 GUI 위젯을 이용한 위피 저작도구를 설계한다. 제안한 도구는 개발자가 Look & Feel을 자유롭게 조정하고, 중.소규모의 위피 응용프로그램을 제작하는데 효율적이다.

• 급식외식위생학회지
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• 제4권2호
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• pp.42-47
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• 2023

The FoodTech industry has been developed with the rise of start-up by using AI, big data, robotics, biotechnology. In addition, sustainable development is more important with the trend of population growth, aging, and climate change. We investigated the impact of FoodTech on the foodservice industry with the cases of the global and domestic companies. The technology of AI, IoT, blockchain, robotics, automation systems are widely used to improve food safety and hygiene while as the use of diagnostic biomarkers such as blood or DNA, digital platform and app, and AI-based solutions are used in the field of personalized nutrition. With the expand of FoodTech in foodservice industry, the competencies that the managers need to develop include understanding technology, resource management, self-development, work ethics, problem-solving, and communication, therefore the support of the related education and training is required.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.191-208
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• 2024

This paper proposes the presence and importance of cultural differences to address user engagement in worldwide social media platforms. Based on Hofstede's cultural dimensions, this paper addresses their new meanings in the context of user engagement in social media. Our propositions address two research questions: (1) how do cultural dimensions, displayed on social media platforms, differ across national cultures?; (2) what different preferences the social media platforms have in terms of which cultural dimensions promote or suppress user engagement? User engagement in social media platforms is explained by the cultural differences in terms of the four cultural dimensions: individualism vs. collectivism, uncertainty avoidance, power distance, and masculinity vs. femininity. Implications are also discussed for research and practice.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.26-48
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• 2024

Data plays an ever greater part in the tourism industry. While the platform-based sharing of open public data, private-sector intermediary platforms, and the use of social media to understand consumer trends are already well recognized, more potential for innovation exists in sharing private data among organizations in Smart Tourism Destinations. Research into the factors enabling and hindering coopetition in this kind of data sharing platforms is still in the nascent stage of development. Our case study of Sapporo, a major Japanese city endeavouring to create itself as a Smart Tourism Destination, sheds light on the initial approaches to involve organizations to such a data sharing agreement. Founding on seven interviews with ten participants of Sapporo Smart City project organization (SARD), we derived enablers and impediments that promote coopetition in data sharing as part of Smart Tourism Destination development. We also present practical recommendations and future research opportunities for such initiatives.

• Asia pacific journal of information systems
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• 제31권3호
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• pp.257-276
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• 2021

This study investigates the factors that facilitate or hinder people to use mobile payment, especially drawing upon the theoretical perspectives on individual's privacy protection motivation and perceived market condition. Survey data (n = 200) were collected through a web-based platform and used to test a theoretical model. The results show that one's privacy protection power is formed by various individual and technological factors (i.e., perceived data exposure, self-efficacy, and response efficacy), and in turn it determines his/her intention to use mobile payment. Moreover, the relationship between privacy protection power and mobile payment use is conditional on the perceived market control by the service provider - with a perception of the high level of provider's market control, one uses mobile payment regardless of his/her privacy protection power, while under the low level of provider's market control, the decision depends on the degree of privacy protection power. The findings would help our understanding of why some people are more susceptible to mobile payment and others are not.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2024년도 제69차 동계학술대회논문집 32권1호
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• pp.275-276
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• 2024

본 논문에서는 고객들이 쉽게 맛집을 찾고 예약할 수 있는 서비스를 제공하기 위해 웹 플랫폼인 Wait-Wise (ver.업주)와 WPMG, 하이브리드 앱인 Wait-Wise (ver.고객)과 포스시스템인 Pos-Ting이다. Wait-Wise (ver.고객)을 통해서 예약한 정보를 Pos-Ting에서 예약자명, 인원 수, 좌석, 예약번호와 같은 유요한 정보들을 업주에게 제공해주고, 업주는 Wait-Wise (ver.업주)을 통해서 매장정보, 메뉴정보, 테이블정보 저장하여 고객에게 Wait-Wise (ver.고객)을 통해서 정보를 제공하고, 관리자는 WPMG를 통해서 메뉴정보 저장하여 Pos-Ting에 정보를 제공한다. 일반 예약 어플리케이션은 예약시간만 지정할 수 있는데 반해 본 프로젝트는 예약 테이블을 지정하여 고객에 선택의 폭을 넓혀 원하는 시간과 원하는 자리에서 식사를 할 수 있게끔 본 프로젝트를 개발하였다.

• Asia pacific journal of information systems
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• 제29권2호
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• pp.248-267
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• 2019

As merging online and offline channels into one single platform, individuals could easily and frequently switch between online and offline channels. In order for understanding such unique behaviors, this study attempts to explore why and how consumers choose their channels to search and purchase a product. We have drawn on multiple theories that have been used to explain individuals' judgment and decision making (i.e., construal level theory and regula-tory focus theory) in order to develop and tested two-way ANOVA based models of how both regulatory focus (e.g., promotion vs. prevention) and product types (e.g., experience goods vs. searching goods) including the psychological distance cue separately and jointly affect individuals' channel selection behavior (e.g., intention to use single channel vs. intention to use cross-channels). Our results have indicated that consumers with promotion-focus are more likely to use a single channel in experience goods rather than in searching goods when there exists the psychological cue. Based on our findings, the implication for both research and practice are discussed.

• Asia pacific journal of information systems
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• 제28권4호
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.