• 유통과학연구
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• 제20권10호
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• pp.105-117
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• 2022

Purpose: The digital healthcare business is rapidly growing due to the COVID-19 pandemic, and the medical service platform business based on smartphone apps is globally expanding. This study targeted medical information online to offline (O2O) platform users in the medical service field. It verified the effect relationship revealed in the continuous use intention of the platform with the mediation of platform quality components, namely perceived benefits, flow experience, and use satisfaction. Research design, data and methodology: Based on previous studies, three medical information O2O platform quality components, namely system quality, information quality, and service quality, were defined. And the questionnaire survey was carried out targeting 359 leading medical information O2O platform users in Korea. Results: As a result of the analysis, it was confirmed that system quality and service quality had a positive (+) effect on satisfaction and continuous use intention with the mediation of perceived benefits and flow experience. Meanwhile, information quality had a negative effect (-) on perceived benefits and flow experience and did not affect use satisfaction and continuous use intention. Conclusions: Consequently, it was ascertained that the system quality and service quality affecting user behavior and experience were more significant factors than information quality to medical information O2O platform users from the medical service aspect.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.475-486
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• 2015

Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the specific bias of the individual study. However, integrating several data sets from different studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classification that the platform of a testing sample is different from the platform of a training set, and suggested a simple classification method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.

• 융합정보논문지
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• 제7권5호
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• pp.177-182
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• 2017

IoT, 클라우드 컴퓨팅, 빅데이터와 같은 주요 ICT 기술이 제조 분야에 적용되기 시작하면서 스마트 공장 구축이 본격화 되고 있다. 스마트 공장 구현의 핵심은 공장 내외부의 데이터 확보 및 분석력에 있다. 따라서 빅데이터 분석 플랫폼에 대한 필요성이 증가하고 있다. 본 연구의 목적은 제조 공정 빅데이터 분석을 위한 플랫폼을 구성하고, 분석을 위한 통합 메소드를 제안하는데 있다. 제안하는 플랫폼은 대량의 데이터 셋을 분산 처리하기 위해 분석도구 R과 하둡을 통합한 RHadoop 기반 구조로서 자동화 시스템의 단위 공정 및 공장 내에서 수집되는 빅데이터를 하둡 HBase에 직접 저장 및 분석이 가능하다. 또한 기존 RDB 기반 분석의 한계점을 보완하였다. 이러한 플랫폼은 스마트 공장을 위한 단위 공정 적합성을 고려하여 개발되어야 하며, 제조 공정에 스마트 공장을 도입하고자 하는 중소기업에 IoT 플랫폼 구축의 가이드가 될 수 있을 것으로 전망된다.

• 한국컴퓨터정보학회논문지
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• 제24권7호
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• pp.45-52
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• 2019

With the popularity of mobile Internet and smart phones, the domestic digital music access platform has entered a period of rapid development. Existing studies in the academic circle have shown that experience has a positive impact on user perception and loyalty. However, the research on the relationship between brand loyalty, user perception and user experience of Internet products has not received much attention. Starting from the brand loyalty theory and user experience theory, this paper explores the mechanism of user experience, user perception and brand loyalty of digital music access platform. Based on the development status of digital music access platform in China, the purpose is to explore how the user experience of the mainstream digital music access platform can affect Usefulness Perception, Epidemic Perception. And to explore how the Usefulness Perception, Epidemic Perception can affect users' brand loyalty. also further explore the role of users' perception in this process to understand the relationship between brand and user experience. In practical operations, 398 formal questionnaires were issued online to collect first-hand data, and reliability analysis, factor analysis, correlation analysis and hypothesis analysis were carried out successively on the data in the later stage. Through research, it is found that the user experience of digital music access platform has a partial significant impact on the perception and loyalty of applications. The visual presentation and emotional feelings of digital music access platform are positively correlated with the perceived usefulness of applications. The visual presentation and emotional feelings of digital music access platform are positively correlated with the perceived popularity of applications. The e perceived usefulness and perceived popularity of the digital music access platform are positively correlated with the loyalty of the application. Through this research, it has certain guiding significance to the promotion of digital music access platform's brand loyalty degree.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2005년도 학술발표회 논문집
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• pp.269-276
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• 2005

A web-based platform for nonlinear earthquake analysis on SDOF systems has been developed in the research. The proposed web-based platform is a 2-tier system composed of client and server sides. Smart Client is applied for the client side to improve the handling speed and UI compatible to the stand alone systems. For the server side, MSSQL is used as a storage for the web. XML WebService is adpoted for the networking between client and server. To examine the efficiency of the developed web-based platform, a trial study on a SDOF nonlinear structural system under earthquake excitation has been carried out.

• 한국정보통신학회논문지
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• 제18권1호
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• pp.50-56
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• 2014

최근 위치 기반 서비스를 사용하는 안드로이드 앱이 널리 사용되고 있다. 안드로이드 플랫폼에서 지원되는 여러 위치 제공자 중 GPS (Global Positioning System) 위치 제공자의 동작에 대한 이해는 관련 안드로이드 개발자에게 중요한 과제이다. 본 고는 안드로이드 플랫폼의 GPS 서브시스템 소스를 분석하여, GPS 위치 제공자의 동작을, 주요 쓰레드를 중심으로 그리고 초기화 단계부터 최종 위치 보고 단계까지 단계별로 일목요연하게 제시하고자 한다.

• 한국의상디자인학회지
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• 제22권1호
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• pp.33-44
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• 2020

The purpose of this study is to guide the research direction for securing the competitiveness of the textile industry by analyzing the trends of patent technology development for flexible materials and platform technologies of domestic and overseas textiles used for wearable devices. The study is based on patents from Korea (KIPO), USA (USPTO), Japan (JPO), Europe (EPO), PCT (WO), and China (SIPO), which were registered as of December 31, 2017. The analysis utilized 3,643 patents acquired from the WINTELIPS search DB. The technology classification system for patent analysis was divided into evangelist-based textile technology developments: human body (AA), fiber attachment patch development (AB), and service platform development (AC). The analysis findings are as follows: 1. The development of flexible materials and platform technologies for textile-based wearable devices has increased since 2000. In particular, China (SIPO) had the most patents. 2. In China, Japan, and Korea, most patent applicants are applied for by natives, but the US has a high proportion of foreigners applying for patents. 3. As for the amount of development of the evangelist-based textile technology (AA) was the most common with 1,203 (33%) cases. As a result of the above IP historical analysis, it can be seen that as a result of the global competition, domestic companies need to acquire IRP and standard technology, and promote commercialization by applying their products to smart wearables devices and other products.

• 한국IT서비스학회지
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• 제19권3호
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• pp.151-163
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• 2020

This paper describes a study on the FRACAS(Failure Reporting Analysis and Corrective Action System)-based dependability control platform for domestic urban railway trains. There are more demands for the verification of the dependability of trains as it becomes a regulation for train manufacturers to verify the dependability recently. Train manufacturers as well as railway operators need a effective FRACAS solution to perform the verification of the dependability. Yet current FRACAS solutions have limitations to support the verification processes effectively. This paper addresses the issues of current FRACAS solutions and suggests a FRACAS framework designed for the domestic urban railway trains. Service failure scenarios are standardized using the proposed availability model to implement a more user-friendly and reliable platform. A new FRACAS-based platform for the dependability control (SCARF^®) has been developed to implement the suggested framework. The detail interfaces and functions of the platform are explained. The SCARF^® platform is expected to engage the increasing demands for the dependability control successfully enhancing the reliability, maintainability, availability and safety of domestic urban railway trains eventually.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.100-106
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• 2023

We developed a crawler-based driving platform that can perform harvesting, transportation, pest control, and rotary operation by equipping it with various implements, and analyzed its performance. This single platform was developed to perform as pepper harvester, peanut harvester, and transporter with a 46-kW engine. A simulation model was developed to study the specifications of the platform, and the accuracy was also analyzed. The absolute percentage error ranged from 0.2 to 5.9%, which made it possible to predict the platform performance using simulation model. In T-test, both torque and speed on field and asphalt showed a significant difference (1%). Driving torque required differed depending on the nature of the field, and the speeds also changed based on soil load. The developed platform has the advantage of being equipped with a variety of working tools, expected to be used to harvest root crops in the future.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.