• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.2
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• pp.236-241
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• 2004

New electrolytes of cubic L $a_2$M $o_2$-x Nbx $O_{9-}$$\delta$/(x=0, 0.05, 0.1, 0.2) were fabricated by a solid-state reaction method and their sintered densities were approximately 93％ of theoretical density. X-ray diffraction analysis and microstructure observation for the sintered specimens were performed. The at complex impedance were measured at 34$0^{\circ}C$ to 93$0^{\circ}C$ in air and fitted with a Solatron ZView program. Their impedance spectra showed big difference below and over the phase transition temperature (58$0^{\circ}C$). The electrical conductivity of L $a_2$M $o_2$ $O_{9}$ was 1.36${\times}$10$^{-2}$ S$cm^{-1}$ / at 817$^{\circ}C$. Comparing to undoped L $a_2$M $o_2$ $O_{9}$ , Nb-doped specimen showed the increase of electrical conductivity due to the aliovalent doping effect..

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.845-852
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• 2018

Mayer-Schönberger and Cukier(2013) explain why big data is important for our life, while showing many cases in which analysis of big data has great significance for our life and raising intriguing issues on the analysis of big data. The two authors claim that correlation is in many ways practically far more efficient and versatile in the analysis of big data than causality. Moreover, they claim that causality could be abandoned since analysis and prediction founded on correlation must prevail. I critically examine the two authors' accounts of causality and correlation. First, I criticize that corelation is sufficient for our analysis of data and our prediction founded on the analysis. I point out their misunderstanding of the distinction between correlation and causality. I show that spurious correlation misleads our decision while analyzing Simpson paradox. Second, I criticize not only that causality is more inefficient in the analysis of big data than correlation, but also that there is no mathematical theory for causality. I introduce the mathematical theories of causality founded on structural equation theory, and show that causality has great significance for the analysis of big data.

• Journal of the Korean Ceramic Society
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• v.35 no.1
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• pp.1-4
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• 1998

SiC whisker reinforced Al2O3-SiC composite was fabricated by reaction synthesis method whish is cost ef-fective and allows good dispersion of whiskers. Fracture strength at room temperature showed the highest value with 150$0^{\circ}C$ reaction temperature because a lot of SiC whiskers was formed. Fracture strength at 135$0^{\circ}C$ did not show big differences with reaction temperature due to agglomeration of whiskers and formation of sil-icon oxynitride during hot MO(modulus of rupture) test probably promoting grain boundary sliding.

• Journal of the Korean Society of Food Science and Nutrition
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• v.27 no.6
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• pp.1053-1058
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• 1998

Volatile flavor compounds in salt fermented big eyed herring were analyzed by vacuum simultaneous distillation solvent extraction/gas chromatography/mass spectrometry/olfactometry and aroma extract dilution anlaysis. A total of 44 volatile compounds were detected by GC/O analysis. Of these, 23 were positively identified, and composed of aldehydes(7), esters(5), ketones(4), sulfur containing compounds (3), aromatic hydrocarbons(2), alcohol(1) and nitrogen containing compound(1). Predominant odorants (Log3FD$\geq$5) in sample were ethyl butanoate(bubble gum /sweet candy-like), 3 methylbutyl butanoate (almond /nutty), 1 octen 3 one(earthy/mushroom like), (E,E) 2,6 nonadienal(roasted wheat/grainy), dimethyl trisulfide(soy sauce /cooked cabbage like), 2 acetylpyrazine(nutty/baked potato like) and unidentified compound(RI=1867, seaweed like).

• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2423-2430
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• 2014

Nitrogen-doped short tubular carbons (N-STCs) with big inner diameter have been successfully synthesized via carbonization of polydopamine (PDA) wrapped halloysite nanotubes (HNTs). The obtained N-STCs have average length of $0.3{\mu}m$ with big inner diameter (50 nm), thin wall (2-3 nm) and large surface area ($776m^2g^{-1}$), and show excellent electrochemical properties. As an example in electrochemical applications, N-STCs were used to electrochemically detect hydrogen peroxide ($H_2O_2$) and glucose. The results showed that the N-STCs modified glassy carbon (N-STCs/GC) electrode had much better analytical performance (lower detection limit and wider linear range) compared to the acid-treated carbon nanotubes (AO-CNTs) based GC electrode. The unique structure endows N-STCs the enhanced electrochemical performance and promising applications in electrochemical sensing.

• Journal of the Korean Ceramic Society
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• v.47 no.4
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• pp.308-311
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• 2010

Porous SiC samples were prepared with three types of wood (poplar, pine, big cone pine) by simply embedding the wood charcoal in a powder mixture of Si and $SiO_2$ at 1600 and $1700^{\circ}C$. The basic engineering properties such as density, porosity, pore size and distribution, and strength were characterized. The samples showed full conversion to mostly $\beta$-SiC with good retention of the cellular structure of the original wood. More rigid SiC struts were developed for $1700^{\circ}C$. They showed similar bulk density ($0.5{\sim}0.6\;g/cm^3$) and porosity (81~84%) irrespective of the type of wood. The poplar sample showed three pore sizes (1, 8, $60\;{\mu}m$) with a main size of $60\;{\mu}m$. The pine sample showed a single pore size ($20\;{\mu}m$). The big cone pine sample showed two pore sizes (10, $80\;{\mu}m$) with a main size of $10\;{\mu}m$. The bend strength was 2.5 MPa for poplar, 5.7 MPa for pine, 2.8 MPa for big cone pine, indicating higher strength with pine.

• Korean Journal of Child Studies
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• v.36 no.5
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• pp.173-188
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• 2015

The main purpose of this study was to investigate the effects of a mother's big five personality factors and playfulness on maternal parenting behavior. The participants consisted of 270 mothers with young children, aged 3-6 years old. The subjects completed questionnaires on IPIP(International Personality Item Pool), PAS(Playfulness Scale for Adults) and Parenting Behavior. The results were as follows. First, regarding the relationships of the mother'personality and parenting behavior, higher levels of neuroticism(N) in the mothers resulted in lower levels of warmth acceptance(W A) in parenting behavior. Higher levels of extroversion(E), openness(O), agreeableness(A), and conscientiousness(C) resulted in higher levels of W A. In terms of the relationships of the mother's playfulness and parenting behavior, higher levels of playfulness resulted in higher levels of W A. and lower levels of permissiveness nonintervention(P N) and rejection restriction(R R). Second, N, E, C, and a maternal sense of humor had an effect in W A. C was found to have an effect in P N and N was observed to have an effect in R R.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.335-336
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• 2019

5G를 비롯한 무선 네트워크의 발달과 인터넷의 보급이 보편화되어 가고 있다. 또한, 스마트폰 등의 모바일 기기 등이 일상화됨에 따라 방대하고 다양한 유형의 데이터들이 발생되고 있다. 이와 같은 범람하기 시작한 정보와 데이터들을 연결하여 새로운 가치를 창출하는 초지능 연결의 4차 산업혁명 시대가 도래하였다. 이러한 4차 산업혁명은 ICBM(IoT, Cloud, Big data, Mobile) 기술이 발달함에 따라 가능했으며. 그중 빅데이터는 초지능 연결의 근간이 되고 있다. 하지만, 빅데이터에서의 데이터는 다양한 목적에 의해 다양한 유형의 데이터를 모두 포함하고 있음에도 데이터 포맷 및 데이터 셋 등의 불일치에 의해 즉각적인 연결은 불가능하다. 본 논문에서는 스마트 공장을 중심으로 서로 다른 형태의 이기종 데이터를 통합하여 처리할 수 있는 빅데이터 처리 플랫폼을 제안한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.7-14
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• 2023

Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people's life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing 'heavy snow' in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.