• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.556-558
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• 2010

Most of the domestic educational mobile contents are concentrated on learning foreign languages like English and it's common to provide contents with mobile cellphone under partnership between mobile and education companies. In recently, the trend is that the mobile platform of educational contents is changing according to development of various smart phones like I-phone and Google-phone. In this paper, so, we implement listening contents for Korean education to support learning Korean as foreign language effectively. In detail, we implement the operation of contents based on android OS of Google open-type platform of smart phone.

• Korean Journal of Optics and Photonics
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• v.31 no.1
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• pp.26-30
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• 2020

First, if we want to design and construct a robotic camera, we need to understand the parallax errors between adjacent images, caused by rotation and movement of the robotic camera system. In this paper, we try to derive the mathematical formulation of parallax error and connect it to a conventional lens system, to obtain a useful, generalized, analytic algebraic expression for the parallax error. Utilizing this expression, we can structurally design a robotic camera, and study the Google ART camera as an example of a robotic camera.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.469-472
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• 2012

최근 IT 분야의 화두로 '빅 데이터'가 떠오르고 있으며 많은 기업들이 이를 분석하여 이익을 증대하기 위한 노력을 하고 있다. 이에 구글은 초기에 맴리듀스라고 하는 대용량 분산처리 프레임워크 기술을 확보하여 이를 기반으로 한 서비스를 제공하고 있다. 그러나 스마트 단말 및 소설미디어 등의 출현으로 다양한 디지털 정보들이 그래프로 표현되는 추세가 강화되고 있으며 기존의 맵리듀스로 이를 처리하는 데에 한계를 느낀 구글은 Pregel 이라는 그래프 형 자료구조에 최적화된 또 다른 분산 프레임워크를 개발하였다. 본 논문에서는 일반적인 그래프 형 데이터가 갖는 특성을 분석하고, 대용량 그래프 데이터를 처리하는데 있어 맵리듀스가 갖는 한계와 Pregel은 어떤 방식으로 이를 극복하고 있는지를 소개한다. 또한 실험을 통하여 데이터의 특성에 따른 적절한 프레임워크의 선택이 대용량 데이터를 처리하는 데에 있어서 얼마나 큰 영향을 미치는지 확인한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.559-560
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• 2016

Modern was also the era that can go quickly and easily, as well as overseas travel domestic travel. Whereby the two grew more and more people enjoying the trip. In the first place, but if you been easy to get lost overseas will receive help if not the ability to speak local languages and also to develop a tool that is easy to find your way in the first place because been difficult. Previously, became the drone that was used for military purposes now enjoy easy and convenient operation and safety of the public. Drones are using this time because of the wide application field width should also try to develop a drone navigation to find your way. If you set the destination using Google Maps it aims to make the user want to go to fly toward the destination while keeping the user with a certain distance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.117-118
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• 2019

본 논문에서는 스마트 폰의 GPS 센서와 구글 맵 기반의 음식점 정보제공 연동이 자유로운 어플리케이션을 설계하고 구현한다. 이 어플리케이션은 안드로이드 내장 센서를 이용하여 현재 사용자의 위치를 기준으로 반경 30m 안의 음식점 정보는 초록색 반원에서 확인할 수 있다. 그리고 구글 맵에서 마커는 메뉴별로 다르게 하여 카테고리마다 마커가 다르게 표시된다. 또한, 상단에 메뉴를 선택할 수 있게 하여 메뉴별로 필터를 가능하게 함으로써 크게 한식, 양식, 일식, 중식, 분식, 후식, 패스트푸드 등으로 분류되어 사용자 주위에 있는 음식집을 빠르게 선택할 수 있도록 구현한다.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.511-518
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• 2020

In the pandemic situation due to corona 19, we examined the satisfactory level of students' between non-face-to-face and online classes in the first year of radiology. In the case of online non-face classes related to radiation majors, it is considered better to conduct real-time lectures than recorded lectures, which allows students to understand difficult radiation majors throughout real-time questions and answers, and at the same time allows them to sympathize with difficult subjects such as intimacy and bonds between students. As a result of the analysis of the answers to questionnaires, the coefficient of answer correlation between first and second grade students is P>0.05, and there is no answer correlation between grades, and it can be seen that the higher the grade, the higher the demand for face-to-face classes was.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.147-157
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• 2018

Since Google launched a prediction service for influenza-like illness(ILI), studies on ILI prediction based on web search data have proliferated worldwide. In this regard, this study aims to build short-term predictive models for ILI in Korea using ILI and web search data and measure the performance of the said models. In these proposed ILI predictive models specific to Korea, ILI surveillance data of Korea CDC and Korean web search data of Google and Naver were used along with the ARIMA model. Model 1 used only ILI data. Models 2 and 3 added Google and Naver search data to the data of Model 1, respectively. Model 4 included a common query used in Models 2 and 3 in addition to the data used in Model 1. In the training period, the goodness of fit of all predictive models was higher than 95% ($R^2$). In predictive periods 1 and 2, Model 1 yielded the best predictions (99.98% and 96.94%, respectively). Models 3(a), 4(b), and 4(c) achieved stable predictability higher than 90% in all predictive periods, but their performances were not better than that of Model 1. The proposed models that yielded accurate and stable predictions can be applied to early warning systems for the influenza pandemic in Korea, with supplementary studies on improving their performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.756-759
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• 2015

As the struggle to get a job becomes increasingly ferocious year after year, the website offering a range of employment information have continued to gain popularity. Those website, however, are not of much help when it comes to an interview to face the interviewer. Furthermore, many people suffer depression due to the heavy stress they are under while making preparations for employment or working for an organization. The current employment website do not have a team of professionals to deal with such issues. In an effort to solve those problems, the present study made arrangements to allow users to put in an enormous amount of employment information based on Google App Engine(GAE) and Google Web Toolkit(GWT) and upload interview videos. In addition, a Q&A board was created to help those who prepare for employment or current workers relieve their stress and provide them with access to a team of counseling professionals.

• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.443-458
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• 2011

There has been a lively discussion on improving Korean students' academic achievement and the imbalance in their recognition of the value of mathematics. In this context, there is a need for a program that enables the majority students who regards mathematics as a subject for the entrance examination to recognize the practicality and historicity of mathematics. Educational books on mathematics in everyday life or the history of mathematics are also expected to serve as an effective tool. In addition, Web 2.0 Map is another means of representing mathematics in everyday life and the history of mathematics in connection with the practical context. The active storytelling process in which mathematics in the practical context in mathematical educational books is represented in Web 2.0 Map is expected to help to understand in depth the practicality and historicity of mathematics. Nevertheless, mathematical educational books and Web 2.0 Map may lead to a considerable variety of outcomes and speeds if carrying out tasks depending on the student's competence and may have practical difficulties in being operated in class. These concerns, however, can be resolved through the creative activity programs adopted in conformance with the 2009 revised curriculum. Therefore, this study intends to develop a program for creating mathematical story maps through mathematical educational books and the Mashup of Web 2.0 Map in accordance with the process of developing activity programs. This study also intends to determine its effectiveness in enabling students to recognize the practical and historical values of mathematics.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.