• Korean Journal of Optics and Photonics
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• v.24 no.3
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• pp.135-142
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• 2013

Two white light emitting diodes(LEDs) were fabricated by using two kinds of yellow phosphor, YAG:Ce and $(Sr,Ba)_2SiO4:Eu$, and their spectroscopic properties were analyzed as a function of temperature from room temperature to $80^{\circ}C$. The asymmetric double sigmoidal function was applied to both blue and yellow peaks of the emitting spectrum to obtain the center wavelength, the amplitude, the half width, and the skewness parameters. According to this analysis, the center wavelength of the blue peak shifted to longer wavelength while that of the yellow peak shifted to shorter wavelength. In addition, some of the skewness parameters were found to increase upon heating, which indicates that spectrum asymmetry becomes enhanced at higher temperatures. The changes in the color coordinates and the luminous efficacy were larger for the case of silicate-based white LED. These results suggest that the silicate-based white LED is inferior to the YAG-based white LED from the viewpoint of color stability, efficacy and color rendering index.

• Korean Journal of Optics and Photonics
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• v.24 no.2
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• pp.64-70
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• 2013

In this paper, two white light emitting diodes(LEDs) were manufactured by using two kinds of yellow phosphor, YAG:Ce and $(Sr,Ba)_2SiO_4:Eu$, and their spectroscopic properties were compared and analyzed. We found that the asymmetric double sigmoidal function can be applied to both white LEDs to obtain the center wavelength, the half width, and the skewness parameters. According to this analysis, the half width of the emitting spectrum of silicate phosphor was smaller than that of YAG phosphor, indicating smaller color rendering index. However, the silicate phosphor exhibited better color stability depending on the driving current than the YAG phosphor. The current dependence of the luminous efficacy of both white LEDs was investigated, which showed that efficacy decreased monotonically with current. The efficacy of the silicate-based white LED was lower than that of the YAG-based LED by about 10~12 lm/W.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.153-168
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• 2017

Recent studies focus on the role of investor attention and transparency in stock-related information in explaining stock return and trading volume. Moreover, recent literatures predict that firm opacity will increase the likelihood of future stock price crashes. In this paper, we investigate, using Naver Trend, the relation between portal search intensity and stock price crash. Using various alternative measures of stock price crash risk and search intensity, we demonstrate that stocks with larger volume of portal search are less likely to experience stock price crashes. These results are consistent with our hypothesis that accumulated firm opacity cause future stock price crash. Finally, our results still hold even after we control for the potential effect of endogeneity in the regression specifications.

• International Area Studies Review
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• v.12 no.2
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• pp.3-26
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• 2008

This article investigates the usefulness of the skewed Student-t distribution in modeling the long memory volatility property that might be present in the daily returns of two Australian financial series; the ASX200 stock index and AUD/USD exchange rate. For this purpose we assess the performance of FIGARCH and FIAPARCH Value-at-Risk (VaR) models based on the normal, Student-t, and skewed Student-t distribution innovations. Our results support the argument that the skewed Student-t distribution models produce more accurate VaR estimates of Australian financial markets than the normal and Student-t distribution models. Thus, consideration of skewness and excess kurtosis in asset return distributions provides appropriate criteria for model selection in the context of long memory volatility models in Australian stock and foreign exchange markets.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.365-392
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• 2021

In order to assess the state of library and information science (LIS) research in Korea, the study analyzed bibliometric data of papers published in past 18 years in Korea Citation Index (KCI) and Social Science Citation Index (SSCI) journals. The analysis of study data, which consisted of 6,301 KCI journal papers with 26,474 citations and 86,727 SSCI journal papers with 1,196,961 citations from 2002 to 2020, involved comparison of research productivity and impact, collaboration trends, and key areas of research between domestic and international LIS scholars with normalizations by units of analysis for size differences. Even with size normalization, the study found a marked difference in citation patterns between domestic and international LIS research. Korean LIS authors were twice as productive as international LIS authors but a little over a half as impactful. The results also showed a much higher level of skewness in international research, where a fraction of top authors, institutions, and journals received a lion's share of citations. The trend of increasing co-authorship was much more pronounced among international publication, where the recent popularity of larger collaboration groups suggests multi-disciplinary and increasingly complex nature of modern LIS research in the world stage. The keyword analysis revealed a much more diverse subject area in international than domestic LIS research with a recent shift towards technology, such as big data, blockchain, and altmetrics. Keywords in SSCI journals also exhibited a less connection between popularity and impact than KCI keywords, where popular keywords did not necessarily correspond to impactful keywords.

• 대한공업교육학회지
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• v.36 no.2
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• pp.111-130
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• 2011

The purpose of this study was to identify a causal relationship among commitment to change, needs of technology education innovation, communication and self-efficacy of technology teachers. A total of 300 copies of questionnaires were used for data analysis except for 117 copies like the one where insincerely responds to any question was found. To ensure the reliability and validity of questions, I performed technical statistics like average, standard deviation, skewness, and kurtosis via PASW 18.0, item-total correlation and the totality, and reliability analysis. I undertook a confirmatory factor analysis via AMOS 7.0 to ensure the validity of items together with a structural analysis to perform a path analysis among variables and assess the suitability of model. The major finding of this study were as follows: First, because fit index of hypothetical model generally met standards in this study, a hypothetical model was judged appropriately. Second, needs of technology education innovation had a positive effect on communication and commitment to change of technology teachers. And, communication among technology teachers had a positive effect on commitment to change of technology teachers. This result means that communication among technology teachers is important to activation of technology education. Third, self-efficacy had a positive effect on commitment to change of technology teachers. This result means that it needs to raise self-efficacy level through teacher education.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• Journal of Korea Port Economic Association
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• v.30 no.3
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• pp.1-14
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• 2014

This paper aims at measuring how new information is incorporated into volatility estimates. Various GARCH models are compared and estimated with daily BDI(Baltic Dry Index) data. While most researchers agree that volatility is predictable, they differ on how this volatility predictability should be modelled. This study, hence, introduces the asymmetric or leverage volatility models, in which good news and bad news have different predictability for future. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. From the Ljung-Box test statistic for twelfth-order serial correlation for the level we do not find any significant serial correlation in the unpredictable BDI. The coefficients of skewness and kurtosis both indicate that the unpredictable BDI has a distribution which is skewed to the left and significantly flat tailed. Furthermore, the Ljung-Box test statistic for twelfth-order serial correlations in the squares strongly suggests the presence of time-varying volatility. The sign bias test, the negative size bias test, and the positive size bias test strongly indicate that large positive(negative) BDI shocks cause more volatility than small ones. This paper, also, shows that three leverage models have problems in capturing the correct impact of news on volatility and that negative shocks do not cause higher volatility than positive shocks. Specifically, the GARCH model successfully reveals the shape of the news impact curve and is a useful approach to modeling conditional heteroscedasticity of daily BDI.

• 한국노년학
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• v.29 no.1
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• pp.117-134
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• 2009

The purpose of this study was designed to develop an questionnaire for healthy aging. The subjects of this study were total 335 people who participated in regular exercise and went to welfare centers in Seoul. The validity and reliability were tested for verifying the developed questionnaire for healthy aging. The data were collected between June 12, 2006 and October 27, 2006. The mean, standard deviation, kurtosis, skewness, reliability, exploratory factor analysis and confirmatory factor were analyzed for statistical purpose using by SPSS-Win 12.0 program. The results were as follows; First, to obtain content validity, the results of previous research and the value system responses were submitted to a judgement group. Second, the results of the factor analysis of the 20 items making up the questionnaire were classified into the following 3 factors; physiological health(6 items), cognitive-mental health(6 items), social-support health(8 items). Third, the reliability of the questionnaire for healthy aging was 0.891(Cronbach's alpha). In the factor analysis Cronbach's alpha correlations for the 4 factors ranged from 0.642 to 0.885. Fourth, the results of confirmatory factor analysis, all the index values(NFI, RFI, CFI, Delta 2 IFI) were close to 1. Thus, this questionnaire demonstrated good reliability and validity and therefore it was an appropriate measurement of healthy aging.