• 패션비즈니스
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• 제25권5호
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• pp.88-98
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• 2021

In this study, the characteristics of digital anthropometric methods were determined with case studies. These methods were broadly classified into two categories: non-wearable and wearable. Then, these categories were further classified into four types: 3D Scanning, mobile app, smart clothing, and smart tool Among the non-wearable types, the "3D scanning" technique was based on the use of 3D hardware equipment. With this technique, the body shape was measured and the internal body information was obtained. Therefore, it is used in fields of healthcare and fitness. Among the wearable types, "Smart clothing" involves a special clothing that measures human body and a smartphone application. Both the components are linked to a fashion platform, which is based on the measured sizes that help shoppers. The "Smart tool" has the characteristic of measuring only with smart tools and smartphone applications; it does not involve the measurement of images. The common advantage of digital anthropometric methods are as follows: they reduce the time and cost of measurement by enabling self-measurement. Moreover, simple measurements are used to determine the size of anthropometry. Thereafter, it accumulates this data to track the continuous changes in size. From an industrial point of view, digital anthropometric technology should be used to increase sales. The on-demand market can be expanded as global consumers would throng the Korean fashion market. For the consumer, an avatar should be created to fit the user's size. This would provide a fun experience to the user.

• 한국전자통신학회논문지
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• 제17권6호
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• pp.1181-1186
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• 2022

본 연구에서는 POV(Persistence of Vision) 현상을 활용한 프로펠러 디스플레이를 제작하여 기존 디스플레이(CRT, LCD, LED 등)를 이용하는 것보다 저전력, 간단한 구성, 더 매력 있는 생김새를 가지는 고효율 디스플레이의 동작 특성을 연구하였다. Hall 센서를 사용하여 기준점을 설정한 후 앱 프로그램을 기반으로 제작한 핸드폰 애플리케이션을 통해 채널 인식 신호 및 음성인식 신호를 Bluetooth를 사용하여 디스플레이에 표시하고 전달받은 동작 명령에 따라 명령을 수행하도록 디스플레이를 설계 제작하였다. 실험 결과, 모터 속도 1,030rpm에서 원하는 정보가 디스플레이 화면상에 최적으로 표현되는 동작 특성을 확인하였다.

• 한국산업융합학회 논문집
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• 제25권6_1호
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• pp.927-939
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• 2022

This study was conducted to develop a Web-GIS based monitoring module of smart city that can effectively respond, manage and improve situation in all stages of illegal dumping management on a city scale. First, five technologies were set for the core technical elements of the module configuration. Five core technical elements are as follows; video screening technology based on motion vector analysis, human behavior detection based on intelligent video analytics technology, mobile app for receiving civil complaints about illegal dumping, illegal dumping risk model and street cleanliness map, Web-GIS based situation monitoring technology. The development contents and results for each set of core technical elements were evaluated. Finally, a Web-GIS based 'illegal dumping monitoring module' was proposed. It is possible to collect and analyze city data at the local government level through operating the proposed module. Based on this, it is able to effectively detect illegal dumpers at relatively low cost and identify the tendency of illegal dumping by systematically managing habitual occurrence areas. In the future, it is expected to be developed in the form of an add-on module of the smart city integration platform operated by local governments to ensure interoperability and scalability.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.51-56
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• 2022

It is relevant and timely for the existence and prosperity of today's tourism to build up a stock of new abilities and a set of innovations. At present, the tourism industry is experiencing a new stage in its digital transformation. The newest technologies, which are now spreading en masse and one of which is rightfully considered to be blockchain technology, enable tourists to receive tourist services directly from the producers, which not only gives the consumer the opportunity to enjoy higher quality and inexpensive products but also increases the responsibility of the producer. The article analyzes research literature on the possibility of using blockchain technology in the tourism industry. Based on an expert survey, the main problems, prospects, and advantages of the implementation of blockchain technology in the tourism industry are identified. The paper proposes and analyzes an option for the use of blockchain technology on the basis of a blockchain project with a mobile app for users and a dedicated website and public API for travel service providers.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.1674-1677
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• 2010

고객관리가 대두되면서 고객유지 및 관리를 위한 마케팅 기법 중에서 중요한 것이 마일리지 적립마케팅이며, 대표적인 방식으로 자바 카드(Java card)와 같은 스마트 카드 방식 및 스티커 또는 쿠폰, 도장을 이용한 방식을 들 수 있다. 그러나 현재 많은 업계에서 도입한 마일리지 관리가 오히려 다수의 마일리지 카드 소지로 인해 고객에게 불편함을 주고 있다. 몇몇 기업에서는 같은 계열사의 마일리지를 통합 관리하는 방식을 선보였으나, 불편함을 줄이기엔 역부족이었다. 본 논문에서는 현재 국내 및 전 세계에서 스마트폰 이용이 확산되고 있는 시점에서 스마트 폰의 한 종류인 애플사의 아이폰 어플리케이션, 즉 앱(App)을 활용하여 개인의 마일리지를 보다 효율적으로 관리할 수 있는 마일리지 통합 관리 시스템을 제안한다.

• 한국인공지능학회지
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• 제11권3호
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

• 디지털산업정보학회논문지
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• 제19권2호
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• pp.177-186
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• 2023

This study investigates customers' perceptions of untack services in the hospitality and foodservice industries based on the Technology Acceptance Model (TAM). The study first identifies Perceived Ease of Use, Perceived Usefulness, and Image as antecedents of customers' Behavioral Intention and Recommendation Intention. Second, the structural relationships among them are established and tested. The study adopts a self-administered survey method, uses SmartPLS 4.0, and applies a two-stage approach. After testing the reliability and validity of customers' 429 data on hospitality and foodservice, hypotheses were tested. The results showed that Perceived Ease of Use significantly affects Perceived Usefulness and Image. Perceived Usefulness significantly also affects Image and Behavioral Intention. The Image of untact services also significantly affects Behavioral Intention and Recommendation Intention. And Behavioral Intention significantly affects Recommendation Intention. Finally, the mediation effects are also all significant. The study's findings suggest that researchers and practitioners should consider the management of Image and Recommendation Intention in the untact service environment.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.577-578
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• 2021

최근 다양한 분야에서 인공지능 시스템이 활용되고 있다. 인공지능의 결정 알고리즘의 정확도는 학습량과 학습데이터의 정확도에 기인한다. 학습량의 경우 인공지능 성능에 결정적인 영향을 미치기 때문에 많은 양의 데이터가 필요하다. 학습데이터의 정확도는 여러 정제 단계를 거치면서 보정할 수 있으나 분석 이외의 자원 소모를 추가로 가져온다. 본 논문에서는 영유아의 체온 데이터를 기반으로 향후 나타날 수 있는 병증 및 유아의 상태 변화를 분석하는 시스템 구축을 위한 데이터 수집 시스템에 대하여 제안한다. 제안된 시스템은 기존 빅데이터 분석 및 학습 데이터 구축에서 서버 시스템의 자원 소모를 최소화할 수 있을 것으로 사료 된다.

• 유통과학연구
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• 제21권7호
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• pp.117-129
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• 2023

Purpose: With the number of COVID-19 cases declining and generational differences among how people use mobile apps, including health service apps, the goal of this research is to identify and analyze the factors that affect people's attitudes when using the Halodoc health service app during the third year of the pandemic. Research design, data, and methodology: This study proposes a quantitative analysis method based on PLS-SEM modeling. This study has used a questionnaire survey to collect randomized data from 268 Halodoc users from generations Y and Z in Jakarta. Results: Both the Y and Z generations believe there is a significant usefulness factor in the attitude toward using the application. The start of the pandemic period demonstrates that the urgency of using health service applications is no longer determined by performance expectations, effort, or social panic, but rather by these applications' usability. Conclusions: Even though a health service application is no longer considered an urgent service or a priority need, attitudes, and behaviors in using it emphasize the aspect of long-term benefits. These findings supplement other considerations and understandings in application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model in explaining attitudes and intention behaviors.

• 한국의류학회지
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• 제46권4호
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• pp.638-656
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• 2022

This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.