• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.435-436
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• 2015

In order to analyze and maximize efficiency of advertise, business put more importance on SNS. Especially, keyword extraction analyses based on Hadoop receive attention. The existing keyword extraction analyses have mostly MapReduce processes. Due to that, it causes problems data base would not update in real time like SNS system. In this study, we indicate limitations of the existing model and suggest new model using Storm technique to analyze data in real time.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.17-22
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• 2008

본 논문에서는 영역별로 자동으로 개체명을 추출하기 위하여 씨앗단어를 이용하고, 웹페이지와 개체명 후보들 간의 상호 중요도를 측정하여 개체명 후보들의 순위를 정하는 방식을 제안한다. 제안된 방식은 크게 세 단계에 의해서 수행되어 지는데 먼저 씨앗단어 정보를 이용하여 웹페이지를 검색하고, 검색되어진 웹 페이지와 씨앗단어 정보를 이용하여 패턴 규칙을 추출한다. 추출된 패턴 규칙을 웹페이지에 적용하여 개체명 후보들을 추출하고 추출된 후보들과 웹페이지 사이의 상호 중요도를 재귀적으로 계산하여 최종적으로 개체명 후보들의 순위가 정해 진다. 한국어와 영어 개체명 영역에 제안된 기법을 적용하여 실험한 결과 한국어에서는 78.72%의 MAP를 얻을 수 있었고, 영어에서는 96.48%의 MAP를 얻었다. 특히 영어 개체명 인식에서의 성능은 구글에서 제공하고 있는 구글셋의 결과보다도 높은 성능을 보였다.

• Bulletin of the Korean Space Science Society
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• 2007.10a
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• pp.129-134
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• 2007

As quantity of information has been increased rapidly, the importance of efficient information analysis system has increased. This research suggests the direction of GNSS (Global Navigation Satellite System) technology strategies with information analysis on SCI Expanded DB. Exactly, it analyzes paper map and network structure between nations, between institutes and between authors. As a conclusion, it suggests strategies to take an opportunity for emerging technology and secure a leading position.

• Molecules and Cells
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• v.21 no.2
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• pp.167-173
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• 2006

The literature provides strong precedent for both pro-tumorigenic and tumor suppressor roles for the c-Jun N-terminal kinases (JNKs) in the setting of oncogenesis. Clearly, JNKs are activated by numerous oncogenes and growth factors and the literature documents a role for these MAP kinases in cell proliferation and transformation. By contrast, JNKs mediate signals from diverse stimuli that result in cell death or differentiation and a role for JNKs as tumor suppressors has emerged. This enigmatic nature of the JNKs in the setting of oncogenesis is considered herein. Further illumination of the complex and context-dependent functions of the JNKs in cancer cells is of obvious importance for the rational use of small molecule JNK inhibitors as therapeutics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1122-1140
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• 2024

The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.573-588
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• 2020

The study investigated the forest vegetation structure of Kongju National University Forests in the vicinity of Seokjangri-dong to provide the information needed for efficient use and management. It conducted a Z-M phytosociological vegetation survey in 60 quadrate plots in August 2019 and generated the actual vegetation map by analyzing the physiognomic community classification and mean importance value. The physiognomic community classification showed five vegetation community types: Quercus acutissima community, Pinus densiflora community, Quercus variabilis community, Pinus rigida community, and Quercus serrata community. The relative importance value in the Q. acutissima community was 31.4% for Q. acutissima, 9.6% for Prunus spp., and 9.0% for Q. variabilis. In the P. densiflora community, it was 24.9% for P. densiflora, 12.4% for Q. acutissima, and 11.5% for Q. serrata. In the Q. variabilis community, it was 25.3% for Q. variabilis, 9.8% for Prunus spp., and 8.5% for Q. acutissima. In the P. rigida community, it was 28.4% for P. rigida 28.4%, 10.0% for Q. acutissima, and 9.3% for P. densiflora. In the Q. serrata community, it was 27.0% for Q. serrata, 11.3% for Q. aliena, and 11.5% for Styrax japonica. The actual vegetation map based on the uppermost dominant species to identify the forest vegetation's spatial distribution characteristics indicated that the natural vegetation covered the most with 87.5%, the number of vegetation patches was 87, and the average area per patch was 1.46ha.

• Journal of the Korea Institute of Building Construction
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• v.9 no.1
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• pp.89-94
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• 2009

A study was performed the analysis for the schedule delay of the public housing. To perform this study, the first study existing research literature on the cause of the schedule delay was considered. The based on existing study, this study selected the cause of schedule delay. For check of the schedule delay, this study was compared the monthly schedule and the work diary. Survey was conducted for using the selected cause of schedule delay. And the importance was calculated for using the AHP method. In a case site, the cause of the schedule delay was analyzed. The last, the delay cause was presented the map of cause of effect the based on the delay cause of a case site.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.103-104
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• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.424-425
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• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.