• Journal of computational fluids engineering
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• v.8 no.4
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• pp.41-49
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• 2003

This study presents a numerical model to analyze dynamic thermal behavior of a hot chuck designed for flip-chip bonders. The hot chuck of concern is a heater which has been specifically developed for accomplishing high-speed and ultra-precision soldering. The characteristic features are radiative heat source and the heating tool made of a material of high thermal diffusivity. A physical modeling has been conducted for the network of heat transport. A simplified finite volume model is deviced to simulate time-dependent thermal behavior of the heating tool on which soldering is achieved. The reliability of the proposed numerical model is verified experimentally. A series of numerical tests illustrate the usefulness of the numerical model in design analysis.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.44.4-45
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• 2017

We report the first detection of RR Lyrae variable stars in the Crater II dwarf galaxy, a recently discovered ultra-faint satellite of the Milky Way. Based on B, V time series photometry obtained with the Korea Microlensing Telescope Network (KMTNet) at CTIO, Chile, we have identified ~45 fundamental-mode (ab-type) and ~2 first-overtone (c-type) RR Lyrae stars by adopting template light-curve fitting method. Our preliminary analysis suggests an Oosterhoff-intermediate classification of this galaxy from the mean period of the RRab stars, <$P_{ab}$> ${\simeq}0.63$ days, and the location of them on the period-amplitude diagram. We discuss the properties of the RR Lyare stars in this galaxy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.325-326
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• 2021

LNG는 환경규제에 따라 화석에너지에서 친환경 재생에너지로 전환되는데 중요한 역할을 하는 에너지원이다. UN산하 세계해사기구(IMO)의 MARPOL협약에 따라 선박 황산화물 배출가스규제로 LNG추진 선박에 대한 수요가 증가되고 있을 뿐만 아니라 미국의 쉐일혁명으로 LNG를 수출함에 따라 공급의 변화가 급격하게 이뤄지고 있다. 과거 국가 주도의 프로젝트 성격이 강한 LNG 운송시장은 장기정기용선계약이 대부분이었으나 수요와 공급시장의 급격한 변화로 스팟시장의 중요성이 커지고 있다. 따라서 본 논문은 LNG 운송시장에서 시장참여자들의 스팟거래에 합리적인 의사결정이 이뤄지도록 과학적인 예측방법을 제시하고자 한다. LNG 스팟운임 예측에 기계학습모델 중 인공신경망 모델을 적용할 것이며 기존의 시계열분석 방법인 ARIMA모델과 비교하여 본문에서 제시된 모델의 예측성능의 우수성을 확인하였다. 본 논문은 LNG 스팟운임을 다룬 최초의 연구로서 학문적인 차별성이 기대된다.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.89-114
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• 2018

Research on changes in research trends in academic disciplines is a method that enables observation of not only the detailed research subject and structure of the field but also the state of change in the flow of time. Therefore, in this study, in order to observe the changes of research trend in library and information science field in Korea, co-word analysis was conducted with Korean author keywords from three types of journals which were listed in the Korea Citation Index(KCI) and have top citation impact factor were selected. For the time series analysis, the 15-year research period was accumulated in 5-years units, and divided into 2003~2007, 2003~2012, and 2003~2017. The keywords which limited to the frequency of appearance 10 or more, respectively, were analyzed and visualized. As a result of the analysis, during the period from 2003 to 2007, the intellectual structure composed with 25 keywords and 8 areas was confirmed, and during the period from 2003 to 2012, the structure composed by 3 areas 17 sub-areas with 76 keywords was confirmed. Also, the intellectual structure during the period from 2003 to 2017 was crowded into 6 areas 32 consisting of a total of 132 keywords. As a result of comprehensive period analysis, in the field of library and information science in Korea, over the past 15 years, new keywords have been added for each period, and detailed topics have also been subdivided and gradually segmented and expanded.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.39-51
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• 2022

As the 4th Industrial Revolution emerged as a key to improving national competitiveness, OCR technology, one of the major technologies in the 4th industry is in the spotlight. Since characters in various images contain a lot of information, OCR technology for recognizing these characters has evolved into technology used in many industries. In this paper, trends in OCR technology were identified and predicted using thesis data published in 'RISS' and patent data by International patent classification (IPC) under the theme of Optical character recognition (OCR). For patent data 20,000 patents related to OCR technology from 2002 to 2020 were used as data, and 432 papers from 2012 to 2022 were used as data. Through time-series analysis, each patent data and thesis data were investigated since when OCR technology has developed, and various keyword analysis predicted which technology will be used in the future. Finally, the direction of future OCR technology development was presented through network association analysis with patent data and thesis data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.79-90
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• 2016

The study has purposed in evaluating experiences for achievable accuracy and precision of time series at 3-D coordinates. It has been estimated from the kinematic medium-range baseline processing of Continuously Operating Reference Stations (CORS) for the potential application of crustal displacement analysis during an earthquake event. To derive the absolute coordinates of local CORS, it is highly recommended to include some of oversea country references, since it should be compromised of an observation network of the medium-range baselines within the length range from tens of kilometers to about 1,000 kilometers. A data processing procedure has reflected the dynamics of target stations as the parameter estimation stages, which have been applied to a series of experimental analysis in this research at the end. From the analysis of results, we could be concluded in that the subcentimeters-level of positioning accuracy and precision can be achievable. Furthermore, the paper summarizes impacts of satellite ephemeris, data lengths and levels of initial coordinate constraint into the positioning performance.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.135-156
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• 2016

Recently, as the importance of user-oriented archives management is becoming increasingly, government archives try to serve interactive services using social network service (SNS) beyond one-way approaches. This study aims to analyze usage of government archives service in social media and examine users' interestedness. We especially select "National Archives of Korea" and "Presidential Archives" as target government archives and collect tweets from 2010 to 15th April 2016. Our study adopts informetric approaches and social media analysis including buzz analysis, time series analysis. We differentiate between the tweet collection posted by government archives themselves and the other collection generated by general users. Furthermore we conduct correlation analysis of tweet and social issues and propose application plan for government archives services in social media environment.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1036-1056
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• 2017

The rapid increase of ageing population and chronic disease patients cause high medical expenses, and it led an increased attention to digital healthcare. Smart car technologies for healthcare have been developing to recognize drivers' status and predict diverse driving environments. The present study aimed to understand the research trends of autonomous vehicle technologies of Korea and the United States through time series analysis, network analysis, visualization, and comparison between the two countries. The results suggest that cooperative study needs to be done in common research areas such as driver's safety and algorithms. It is also needed to conduct studies and benchmark about liking technique related to part-to-part and vehicle-to-vehicle as America's competitive advantaged area. In the US, diverse approaches of autonomous vehicle technologies have used to consider the characteristics of various age groups and passengers' health status through sensor, while in Korea, only one aspect, older drivers, is mentioned. Implications for the development direction of autonomous vehicle technologies with competitiveness in considering public health, ethics, and driver's safety and convenience are discussed in detail.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1229-1235
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• 2010

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.267-268
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• 2022

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Big data is usually in the form of sentences, and morphological analysis or understanding of the sentences is required. Accordingly, NLP, a technique for analyzing natural language, can understand the relationship of words and sentences. In this paper, we study the advantages and disadvantages of Transformers and Reformers, which are techniques that complement the disadvantages of RNN, which is a time series approach to big data.