• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.1-15
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• 2019

One of the biggest difficulties in the vocational training field is the dropout problem. A large number of students drop out during the training process, which hampers the waste of the state budget and the improvement of the youth employment rate. Previous studies have mainly analyzed the cause of dropouts. The purpose of this study is to propose a machine learning based model that predicts dropout in advance by using various information of learners. In particular, this study aimed to improve the accuracy of the prediction model by taking into consideration not only structured data but also unstructured data. Analysis of unstructured data was performed using Word2vec and Convolutional Neural Network(CNN), which are the most popular text analysis technologies. We could find that application of the proposed model to the actual data of a domestic vocational training institute improved the prediction accuracy by up to 20%. In addition, the support vector machine-based prediction model using both structured and unstructured data showed high prediction accuracy of the latter half of 90%.

• Journal of the Korea Institute of Building Construction
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• v.20 no.2
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• pp.155-162
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• 2020

Since the third industrial revolution has been started in the 1980s, the form of buildings has been varied and atypical by the development of building technology. Such free-form building has a curved shape unlike the existing standard buildings, and to realize this, it is necessary to manufacture the free-from panel. The shape of the free-form panel must satisfy a limited error ratio compared with the design shape, and the technology to produce free-form panels is very difficult. However, there are many problems such as enormous cost and construction waste generation when implementing free-from construction. Therefore, the development of free-form panel manufacturing technology should be made to solve the problems caused by the free-form construction. In this study, the error rate analysis of the mixed mortar panel was conducted by selecting the proper mixing ratio of the mixed mortar for the shape of the free-form panel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1199-1205
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• 2021

In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.378-378
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• 2022

상수도시스템의 과정 중 최종 단계인 급수단계에서 지역전반에 수질문제가 발생할 경우, 직간접적인 피해의 해결은 장기간 지속될 수 있다. 본 연구에서는 실시간 비정형정보의 빅데이터 분석을 통해 상수도시스템에서 수질사고 문제의 파급력과 2차 피해 등의 연결 관계 변화 추적을 위한 기초적 분석을 수행하였다. 과거 대규모 수질사고가 발생된 바 있는 인천광역시 유충발생 사고를 대상으로 뉴스 기사 웹크롤링 절차를 정립하고, 그 결과를 분석하였다. '인천 유충'이 최초 보도되었던 2020년 7월 13일 부터 이후 1년을 대상으로 네이버 통합검색에 의해 표출되는 뉴스기사를 웹크롤링하였으며, 프로그래밍을 통한 불용어 제거 및 관련성 검토를 통해 총 920건의 기사를 분석하였다. 수질사고의 전개양상에 따라 사고발생, 확산, 수습, 그리고 보상의 4단계로 임의 구분하여 분석하였다. 의미분석을 위한 토픽모델링 기법은 잠재 디리클레 할당(Latent Dirichlet Allocation, LDA) 방법을 적용하였으며, 긍부정 감정분석은 KNU 한국어 감성사전(KNU sentiment lexicon)을 활용하여 수행하였다. 토픽 모델링 결과, 사고 발생에서부터 확산, 수습, 보상의 단계에 맞춰 적절한 주제어의 조합에 따른 기사들이 도출되었으며, 단계별 긍부정 기사 비율역시 사고의 전개단계에 따라 적절히 나타남을 확인하였다. 제시된 수질사고 관련 비정형정보 분석 방법론과 결과는 과거 사고 사례 분석을 통한 검색 및 긍부정 키워드 확정, 키워드 발생 비율 변동(사고전과 후)에 따른 상황판단 기준설정 등에 활용이 가능하다.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.14-26
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• 2017

With the development of computer technology, many different kinds of digital design tools have been developed and used. In the circumstance, methodologies of digital process have more been researched. Despite various atypical forms, there have been limits to the application and practical use of the mobile technology for approaches to the creation of architectural forms and various circumstances. Therefore, this study tries to analyze previous studies and actual conditions of mobile application in order to recognize the research necessity and suggest the possibility of the atypical form creation in the mobile environment. In short, the purpose of this study is to recognize the necessity of the smart mobile application for making idea & learning tools, suggest the process based selective application method (not analytical application) of smart mobile application technology to make possible atypical form creation in the initial step of architectural design processes, and propose a new method of mobile application.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1243-1248
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• 2022

A mobile platform that can robustly operate in unstructured environments such as construction sites is an essential problem for smart construction technology development. In this paper, we introduce a mobile robot platform that can be applied to the unstructured environment to support the collection of geographical information at construction sites. The proposed mobile platform is designed to cope with not only vertical slopes but also side slopes, and the performance of overcoming the step difference of the proposed platform was analyzed through simulation experiments.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.715-720
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• 2020

In Big data analysis, text data is mostly unstructured and large-capacity, so analysis was difficult because analysis techniques were not established. Therefore, this study was conducted for the possibility of commercialization through verification of usefulness and problems when applying the big data word cloud technique, one of the text data analysis techniques. In this paper, the limitations and problems of this technique are derived through visualization analysis of the "President UN Speech" using the R program word cloud technique. In addition, by proposing an improved model to solve this problem, an efficient method for practical application of the word cloud technique is proposed.

• Knowledge Management Research
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• v.23 no.4
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• pp.69-89
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• 2022

As we enter a super-aged society, senior citizens' health issues are affecting a variety of fields, including medicine, economics, society, and culture. In this study, we intend to draw implications from unstructured data analysis such as text mining and social network analysis in order to apply digital health care service design for improving the cognitive ability of senior citizens. The research procedure of this study improved the service design methodology into a process suited to the analysis of unstructured data, and six steps were applied. Related keywords that exist on social media, focusing on cognitive improvement and healthcare for senior citizens, were collected and analyzed, and based on these results, the direction of healthcare service design for improving on the cognitive abilities of senior citizens was derived. The results of this study are expected to have academic and practical implications for expanding the scope of the use of big data analysis methods and improving existing healthcare service development methodologies.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1337-1341
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• 2007

최근의 이상기후 등에 의해 도시유역에서의 강우가 증가하게 되면, 홍수유출량의 증가를 야기하고 이로 인하여 하천이 월류하거나 제방이 붕괴되고, 배수시스템을 통한 배수가 불량하게 되어 침수피해가 발생하게 된다. 도시지역 홍수피해는 주거지역으로 확장되어 주택을 파손시키고 경우에 따라서는 인명손실을 일으키기도 한다. 특히 도시지역에서는 인구와 각종 시설들이 집중되어 있기 때문에 일단 침수가 발생하게 되면 막대한 피해가 발생한다. 이러한 도시홍수 피해를 줄이기 위해서, 홍수 범람에 대한 예측이 반드시 필요하다. 본 연구에서는 Link와 Node로 구성된 개개의 요소가 해당지점을 대표하도록 구성되는 비정형 격자기반의 침수해석 모형을 개발하였고, 비정형 격자기반 침수해석모형의 적용성을 검증하기 위해 일방향 경사유역 및 DEM기반 침수해석 모형과 비교하였다. DEM기반 침수해석 모형과의 비교를 위해 SWMM 모형을 이용하여 배수시스템에서 월류되는 유량을 산정하였고, 월류된 유량이 전파되어 가는 과정을 해석하기 위하여 먼저 흐름을 수로형과 위어형 흐름으로 구분하였다. 다음으로 내부의 위상관계를 분석하여 각 Link와 Node에 고유번호를 지정하고 각 Link에 연결된 Node번호들을 지정하여 침수해석을 실시하였다. DEM기반 침수해석 모형과 비정형 격자기반 침수해석 모형을 적용한 침수해석 결과에 대하여 GIS Tool을 이용하여 대상유역에 대한 입력자료를 구축하고, 모의 결과를 도시함으로써 두 침수해석 모형의 비교 및 분석을 실시하였다.