• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.101-115
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• 2020

In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.65-74
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• 2003

Location-based service is an important spatiotemporal database application area that provides the location-aware information of wireless terminals via positioning devices such as GPS. With the rapid advances of wireless communication systems, the requirement of mobile application areas including traffic, mobile commerce and supply chaining management became the center of attention for various research issues in spatiotemporal databases. In this paper we present the A-Quadtree, an efficient indexing method for answering location-based queries where the movement vector information (e.g., speed and velocity) is not presented. We implement the A-Quadtree with an index structure for object identifiers as a.Net component to apply the component to multiplatforms. We present our approach and describe the performance evaluation through various experiments. In our experiments, we compare the performance with previous approaches and show the enhanced efficiency of our method.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.76-85
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• 2015

We have developed a software to predict failure time of the rock slope based on analysis of the data from real time displacement measurements with respect to time. The software consists of four modules that play roles in analytical methods such as inverse velocity method, log time-log velocity method, log velocity-log acceleration method and nonlinear least square method to estimate failure time. VisualBasic.NET on the MS Visual Studio platform was utilized as a development tool to efficiently implement the modules and the graphical user interface of the software. Displacement data obtained from laboratory physical model studies of plane sliding were used to explore the applicability of the software, and to evaluate the possibility of predicting potential slope failure. It seems possible to estimate failure time using developed software for sliding plane having exponential type of deformability.

• Smart Media Journal
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• v.9 no.3
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• pp.41-45
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• 2020

Recently, artificial intelligence (AI) and the Internet of things (IoT), which are represented by machine learning and deep learning among IT technologies related to the Fourth Industrial Revolution, are applied to our real life in various fields through various researches. In this paper, IoT and AI using object recognition technology are applied to classify clothing. For this purpose, the image dataset was taken using webcam and raspberry pi, and GoogLeNet, a convolutional neural network artificial intelligence network, was applied to transfer the photographed image data. The clothing image dataset was classified into two categories (shirtwaist, trousers): 900 clean images, 900 loss images, and total 1800 images. The classification measurement results showed that the accuracy of the clean clothing image was about 97.78%. In conclusion, the study confirmed the applicability of other objects using artificial intelligence networks on the Internet of Things based platform through the measurement results and the supplementation of more image data in the future.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.274-287
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• 2022

Competition in the broadcasting market is intensifying as OTT services are spreading. And Korea is positioned as a competent international contents supply base. This can be helpful for the domestic contents production industry. However, it can result in being incorporated as a subcontractor in the global video industry. Therefore, it is necessary for Korean OTT operators to expand their market upto overseas and maintain competitiveness by linking content competitiveness to the sales expansion. This study was conducted to reduce the risk and encourage implementation through feasibility analysis of overseas business of domestic OTT operators. The North American market was selected as a region with high potential through in-depth interviews with experts and literatures review. And it was confirmed that the partnership with local platform is effective. Then, the sales and input costs were estimated, and business was evaluated using the net present value method. Totally 18 scenarios were created using multiple estimates for copyright cost, subscribers, and rate, which are highly uncertain. From the analyses, 8 scenarios were found to be acceptable. And copyright cost has the greatest impact on business success, followed by rates and subscribers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.474-484
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• 2019

In this age, where the social environment is changing rapidly and unpredictably, interest in safety from crime is increasing in Korean society. As the desire to live a life free from the fear of crime increases, interest in the construction of safe cities is also rising nationwide. To meet the national demand, the Korean government is promoting a project to link public disaster safety systems by involving municipalities, 112, 119, and other emergency services and institutions through the Smart City Integrated Platform in order to construct a smart safety net. This study investigates the linking of theSmart City Integrated Platform and theIntelligent Security Project. The results are as follows. 1. The linkage's objective is clear. 2. The system sector can provide information to accident-related organizations. 3. The scenario area can be expanded to a crime-prevention sector, and a long-term urban information integration infrastructure can be created. 4. Product testing is enabled by a smart city road map and through continuous consultation with relevant organizations. 5. Project diffusion to other local governments can be promoted with the continued addition of commercial products.

• Journal of Korea Game Society
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• v.20 no.1
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• pp.133-142
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• 2020

Digital educational game market is growing as it expands to smart platforms such as smart phones and tablet PCs. As games have become digital in the classroom evolving to two-ways. In this paper, it designed that enables elementary students to acquire musical knowledge related to musicians through digital board games. By collecting achievement cards of musicians associated with. Elementary students repeatedly gain relevant musical knowledge in the end. The developed game was simulated using Petri net to check the gameplay flow.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.59-72
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• 2016

The main objective of this study is to provide the behavioral model of co-creation by customers and explorer influential factors of participation from the customer's perspective. To achieve the research goals, we employed grounded theory and conducted intensive interviews of 8 customers who had writing product reviews experiences with Beauty Net. The study results indicate that the most important influential factors of participation from the customer's perspective are: (1) Co-creation platform; (2) Co-creation policy; and (3) Individual characteristics.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.130.2-130.2
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• 2011

지상의 관측소에서 특정 인공위성을 찾아내기 위해서는 위성의 정밀궤도 계산이 필요하다. 궤도상의 인공위성의 위치는 시간에 따라 계속 변하므로 이러한 위성의 위치를 실시간으로 추적하기 위해서는 컴퓨터를 이용한 계산이 필수적이다. 정밀한 계산 결과를 얻기 위하여 태양과 지상 관측소의 위치는 Astronomical Almanac과 지구 타원체 모델을 이용하여 계산 하였다. 인공위성의 궤도는 미공군 북미방공사령부(NORAD)에서 발표하는 TLE를 초기값으로 이용하여 J2 섭동효과를 포함한 위성의 위치 및 속도의 변화를 계산하여 SkyView로 나타내었다. 이렇게 나타낸 SkyView의 결과를 실제 위성의 궤적과 비교하여 위성의 궤도를 검증하였으며, 시간에 따른 위성의 광도 곡선 변화 계산 루틴을 작성하여 실제 위성을 찾아내기 위한 기초자료로 활용이 가능하도록 하였다. 모든 계산을 위한 프로그램을 Visual Studio.net 2010 환경에서 C++ 언어를 이용하여 작성하였으며, 결과를 나타내기 위하여 Nokia 사의 Cross Platform 라이브러리인 Qt를 이용하여 UI 제작 및 Visualization을 수행하였다. Qt 라이브러리는 C++ 언어를 기반으로 작성된 플랫폼 독립적인 GUI 라이브러리로써 MS Windows, Linux, MacOS 환경에서 사용이 가능하다. 이를 통해 운영체제에 관계없이 모든 컴퓨터 환경에서 동일한 유저 인터페이스를 이용하여 계산을 할 수 있다. 본 연구는 향후 우주물체탐색에 있어 독자적인 운영을 위한 프로그램으로 활용할 예정이다.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.53-58
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• 2013

온라인 소비자들은 amazon.com과 같은 온라인 상점 플랫폼에 상품 평가(리뷰: review) 글을 남김으로써 대상 상품에 대한 의견을 표현한다. 이러한 상품 리뷰는 다른 소비자들의 구매 결정에도 큰 영향을 끼친다는 관점에서 볼 때, 매우 중요한 정보원이라고 할 수 있다. 사람들이 남긴 의견 정보(opinion)를 자동으로 추출하거나 분석하고자 하는 연구인 감성 분석(sentiment analysis)분야에서 과거에 진행된 대다수의 연구들은 크게는 문서 단위에서 작게는 상품의 요소(aspect) 단위로 사용자들이 남긴 의견이 긍정적 혹은 부정적 감정을 포함하고 있는지 분석하고자 하였다. 이렇게 소비자들이 남긴 의견이 대상 상품 혹은 상품의 요소를 긍정적 혹은 부정적으로 판단했는지 여부를 판단하는 것이 유용한 경우도 있겠으나, 본 연구에서는 소비자들이 '어떤 관점'에서 대상 상품 혹은 상품의 요소를 평가했는지를 자동으로 추출하는 방법에 초점을 두었다. 본 연구에서는 형용사의 대표적인 성질 중 하나가 자신이 수식하는 명사의 속성에 값을 부여하는 것임에 주목하여, 수식된 명사의 속성을 추출하고자 하였고 이를 위해 WordNet을 사용하였다. 제안하는 방법의 효과를 검증하기 위해 3명의 평가자를 활용하여 실험을 하였으며 그 결과는 본 연구 방향이 감성분석에 있어 새로운 가능성을 열기에 충분하다는 것을 보여주었다.