• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.839-842
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• 2004

We present a fast-switching electro-optical device based on flexoelectro-optic effect in short pitch cholesterics oriented in uniform lying helix texture. The device has two operating modes: amplitude and phase modulation mode. The amplitude modulation mode is a fast in-plane switching of the device optic axis that enables to achieve a high percent of modulation of the transmitted light intensity whereas the phase mode gives a continuous change of the refractive index and thus of the phase shift of the transmitted light. By using a small concentration of diacrylate monomer and selecting the illumination conditions we have been able to create a inhomogeneous polymeric network mostly localized at both substrate surfaces and stabilize the two switching modes.

• Bulletin of the Korean Chemical Society
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• v.12 no.1
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• pp.87-92
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• 1991

A dual capillary column system is described for the simultaneous measurement of retention index (RI) and area ratio (AR) values of each peak on two capillary columns of different polarity, DB-5 & DB-1701. Both capillary columns were connected to a common splitless injector via a deactivated fused-silica capillary tubing of 1 m length and a 'Y' splitter, the dead volume effect of which was found to be negligible. RI and AR were measured with high reproducibility(${\leq}$0.05% RSD) and with high accuracy (<10% RE), respectively. When applied to the test samples of the organic acid mixture, each acid was positively identified by the combined computer RI library search-AR comparison.

• Bulletin of the Korean Chemical Society
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• v.14 no.2
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• pp.250-255
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• 1993

A dual capillary column system is described for the simultaneous analysis of a given sample and measurement of retention index (RI) and area ratio (AR) values of each peak on two capillary columns of different polarity, DB-5 & DB-1701 from a single injection. Both capillary columns were connected to either a splitless injector or an on-column injector via a deactivated fused-silica capillary tubing of 1 m length and a 'Y' splitter. Both injection modes allowed to measure RI and AR values with high reproducibility (<0.01% RSD) and high accuracy (<10% RE), respectively with the exception that the trace and high boiling solutes required the on-column mode for the accurate quantification and AR comparison. When the dual capillary column system in on-column injection mode was applied to the blind samples containing organic acids, each acid was positively indentified by the combined computer RI library search-AR comparison.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.12
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• pp.897-905
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• 2013

In this study, sorption coefficients (${\log}K_{OC}$, n) for the binding of phenanthrene (PHE) to soil humins, insoluble fraction of soil humc substances (HS), were determined and relationship between the sorption coefficients and structural characteristics of the soil humins were investigated. The soil humins used in the present study were isolated from 7 different soils including 5 domestic soils, an IHSS standard and a peat soil, and characterized by elemental analysis and CPMAS $^{13}C$ NMR method. $^{13}C$ NMR spectral features indicate that the soil humins are mainly made up of aliphatic carbons (57.1~72.3% in total carbon) with high alkyl-C moiety, and the alkyl-C contents ($C_{Al-H,C}$, %) was in order of granite soil Hu (26~42%) > volcanic ash soil, HL Hu (23.9%) > Peat Hu (14.0%). The results of correlation study show that a positive relationship ($r^2$ = 0.77, p < 0.05) between organic carbon normalized-sorption coefficients ($K_{OC}$, mL/g) and alkyl-C contents($C_{Al-H,C}$, %), while negative relationship ($r^2$ = (-)0.74, p < 0.05) between Freundlich sorption parameter (n) and H,C-substituted aromatic carbon contents ($C_{Ar-H,C}$, %). The magnitude of $K_{OC}$ values are also negatively well correlated with polarity index (e.g., PI, N + O)/C) ($r^2$ = (-)0.74, p < 0.1). These results suggest that the binding capacity (e.g., $K_{OC}$) for PHE is increased in soil humin molecules having high contents of alkyl-C or lower polarity, and nonlinear sorption for PHE increased as the H,C-substituted aromatic carbon contents ($C_{Ar-H,C}$, %) in the soil humins increased. The PHE sorption characteristics on soil humins are discussed based on the dual reactive mode of sorption model.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.75-94
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• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Journal of the Korean Magnetic Resonance Society
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• v.18 no.2
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• pp.58-62
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• 2014

Human transmembrane proteins (hTMPs) are closely related to transport, channel formation, signaling, cell to cell interaction, so they are the crucial target of modern medicinal drugs. In order to study the structure and function of these hTMPs, it is important to prepare reasonable amounts of proteins. However, their preparation is seriously difficult and time-consuming due to insufficient yields and low solubility of hTMPs. We tried to produce large amounts of Syndecan-4 transmembrane domain (Syd4-TM) that is related to the healing wounds and tumor for a long time. In this study, we performed the structure determination of Syd4-TM combining the Polarity Index at Slanted Angle (PISA) wheel pattern analysis based on $^{15}N-^1H$ 2D SAMPI-4 solid-state NMR of expressed Syd4-TM and Molecular Dynamics (MD) simulation using Discovery Studio 3.1.

• Journal of the Korean Magnetic Resonance Society
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• v.20 no.4
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• pp.129-137
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• 2016

Transmembrane(TM) proteins are closely related to transport, channel formation, signaling, cell to cell interaction, so they are the crucial target of modern medicinal drugs. In order to study the structure and function of these TM proteins, it is important to prepare reasonable amounts of proteins. However, their preparation is seriously difficult and time-consuming due to insufficient yields and low solubility of TM proteins. We tried to produce large amounts of Syndecan-4 containing TM domain(SDC4-TM) that is related to the wound healing and tumor. Also, mutated SDC4-TM was studied to investigate structural change by modification of dimerization motif. We performed the structure determination by the Polarity Index at Slanted Angle (PISA) wheel pattern analysis based on $^{15}N-^1H$ 2D SAMPI-4 solid-state NMR of SDC4-TM and computational modeling using Discovery Studio 2016.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.23 no.1
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• pp.3-7
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• 2012

Objectives : The early onset of mood symptoms in bipolar disorder has been associated with poor outcomes in many studies. However, aspects of the clinical course of bipolar disorder in children and adolescents are controversial. The goal of this article is to review the clinical characteristics and longitudinal course of children and adolescents with bipolar disorders. Methods : Searches were conducted in MedLine, PsycINFO, KISS, and RISS using the terms phenomenology, clinical course, outcome, BPD, pediatric, children and adolescents. Twenty-one reports were selected : either original articles reporting symptoms and clinical characteristics of subjects (ages 5-18 years), or published articles in reviewed journals about bipolar disorder in children and adolescents. Results : Approximately 70% of subjects with bipolar disorder recovered from their index episode, and 50% had at least 1 syndromal recurrence, particularly depressive episodes. For 60% of the follow-up time, subjects had syndromal or subsyndromal symptoms with numerous changes in symptoms and shifts of polarity. Approximately 20% of BP-II subjects converted BP-I. Conclusion : Bipolar disorders in children and adolescents are characterized by episodic illness with subsyndromal and syndromal episodes with mainly depressive and mixed symptoms and rapid mood changes. Extensive follow-up time is needed to evaluate the continuity of bipolar disorder symptoms from childhood to adulthood.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.81.2-81.2
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• 2016

Many signals in the nature have power-law behaviors, namely they are "scale-free". The method of detrended fluctuation analysis (DFA), as one of the popular methods (e.g., Rescaled range analysis and Spectral analysis) for determining scale-free nature of time series, has a very important advantage that the DFA can be applied to both stationary and non-stationary signals. The analysis of time series using the DFA has been broadly used in physiology, finance, hydrology, meteorology, geology, and so on. We performed the DFA of 16 Spaceweather HMI Active Region Patch (SHARP) parameters for 38 HMI Active Region Patches (HARPs) obtained by Solar Dynamics Observatory (SDO) from May 2010 to June 2014. The main results from this study are as follows. (1) The most of the time series data are non-stationary. (2) The DFA scaling exponents of "mean vertical current density" for 38 HARPs have a negative correlation coefficient (-0.41) with flare index. (3) The DFA scaling exponents of parameters such as "Sum of the absolute value of net currents per polarity", "Absolute value of the net current helicity", and "Mean photospheric excess magnetic energy density" for the most active HARPs having more than 10 major flares, have positive correlation coefficients (0.64, 0.59, and 0.53, respectively) with the ratio of "the number of CMEs associated with major flares" to "the number of major flares". Physical interpretations on our results will be discussed.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.