• Journal of the Korean Geotechnical Society
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• v.31 no.6
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• pp.59-69
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• 2015

Recently, landslide and debris-flow disasters caused by severe rain storms have frequently occurred. Many researches related to landslide susceptibility analysis and debris-flow hazard analysis have been conducted, but there are not many researches related to mobilization analysis for landslides transforming into debris-flow in slope areas. In this study, statistical analyses such as discriminant analysis and logistic regression analysis were conducted to develop a mobilization criterion using geomorphological and geological factors. Ten parameters of geomorphological and geological factors were used as independent variables, and 466 cases (228 non-mobilization cases and 238 mobilization cases) were investigated for the statistical analyses. First of all, Fisher's discriminant function was used for the mobilization criterion. It showed 91.6 percent in the accuracy of actual mobilization cases, but homogeneity condition of variance and covariance between non-mobilization and mobilization groups was not satisfied, and independent variables did not follow normal distribution, either. Second, binomial logistic analysis was conducted for the mobilization criterion. The result showed 92.3 percent in the accuracy of actual mobilization cases, and all assumptions for the logistic analysis were satisfied. Therefore, it can be concluded that the mobilization criterion for debris-flow using binomial logistic regression analysis can be effectively applied for the prediction of debris-flow hazard analysis.

• Sleep Medicine and Psychophysiology
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• v.19 no.2
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• pp.77-83
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• 2012

Objectives: Recent studies have reported a correlation between obstructive sleep apnea syndrome (OSA) and depression. In attempt to verify the suggestion that eveningness is related to depression, we examined the effect of morningness-eveningness on their depressive mood in patinets with OSA. Methods: The examination was based on the medical records and polysomnography reports of 211 OSA patients. Information was gathered from the patients who filled out the H$\ddot{o}$rne and Ostberg questionnaire (HOQ), profile of mood states-Korean version (K-POMS), and Epworth sleepiness scale (ESS). We compared mean values of K-POMS total, subscales of K-POMS, ESS, and OSA severity variables among the 3 morningness-eveningness groups (morningness, eveningness, and neither groups). Partial correlation analysis was performed between variables and ANCOVA was performed among the 3 groups after adjustment with age and weight. Results: There were significant negative correlations between HOQ and the followings : K-POMS total, POMS-T (tension-anxiety), POMS-D (depression-dejection), POMS-A (anger-hostility), POMS-F (fatigue-inertia), POMS-C (confusion-bewilderment), spontaneous arousal index, average O2 saturation. There were significant positive correlations between HOQ and the followings : POMS-V (vigor-activity), apnea-hypopnea index, respiratory arousal index, snore time. There were significant negative correlations between POMS-D and the followings : HOQ, POMS-V, stage 1 sleep (%), AHI, TAI (total arousal index), oxygen desaturation index, respiratory arousal index, neck circumference, average O2 desaturation, snore time (%). There were significant positive correlations between POMS-D and K-POMS total, POMS-T, POMS-A, POMS-F, POMS-C, sleep latency, stage 2 sleep (%), heart rate, spontaneous arousal index. There were significant differences in K-POMS total, POMS-T, POMS-D, POMS-F, POMS-C, spontaneous arousal index among the three HOQ groups in ANCOVA. Conclusion: The depressive correlates of OSA patients might be affected, not by excessive daytime sleepiness or OSA severity indexes, but by eveningness circadian characteristics. It would be important to take into account the morningness-eveningness tendency when we manage the depressive mood of OSA patients.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.325-338
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• 2016

This research aimed to setup the innovativeness, dependability of information, reliability, and sufficiency of information of a mobile eating out application as the precedence factor, and also aimed to present useful information regarding the mobile eating out application by verifying the effect on the continuous use satisfaction levels and long-term orientation for this mobile eating out application. The data collection carried out from February 1 to February 28, 2016, with 441 questionnaires collected from a total distribution of 500 copies, of which 396 were retained. SPSS 22.0 was employed for factor analysis and the reliability verification, while AMOS 22.0 was used for the covariance structure analysis meant to verify the presented research hypothesis. The results are as follows. First, there was found a significant positive effect (+) on continuous use from innovativeness and dependability. On the other hand, sufficiency and reliability appeared not to have a significant effect. Second, there was a positive increase in long-term orientation as continuous use increased. Third, long-term orientation increased in relation to innovativeness. On the other hand, sufficiency, dependability and reliability appeared not to have a significant effect on long term orientation. Accordingly, the useful implications for the eating out application based on the analysis results has been presented.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.99-107
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• 2021

We live in a myriad of data. Various data are created in all situations in which we work, and we discover the meaning of data through big data technology. Many efforts are underway to find meaningful data. This paper introduces an analysis technique that enables humans to make better choices through the trend and prediction of time series data as a principal component analysis technique. Principal component analysis constructs covariance through the input data and presents eigenvectors and eigenvalues that can infer the direction of the data. The proposed method computes a reference axis in a time series data set having a similar directionality. It predicts the directionality of data in the next section through the angle between the directionality of each time series data constituting the data set and the reference axis. In this paper, we compare and verify the accuracy of the proposed algorithm with LSTM (Long Short-Term Memory) through cryptocurrency trends. As a result of comparative verification, the proposed method recorded relatively few transactions and high returns(112%) compared to LSTM in data with high volatility. It can mean that the signal was analyzed and predicted relatively accurately, and it is expected that better results can be derived through a more accurate threshold setting.

• Management & Information Systems Review
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• v.35 no.2
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• pp.221-254
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• 2016

With increasing interest of health due to population aging, medical device industry is highlighted as a promising industry. However, Korea medical device industry is not enough market competitiveness compared to global company due to a narrow domestic market and a small company structure. In order to retain the national competitiveness, it is necessary that we have to derive a central technology and its trend. This study has predicted a central technology for medical device industrial using patent network analysis. The central technology is defined as a key technology that is connected to most other technologies and that significantly affects them. For the empirical study, we conducted social network analysis using covariance and correlation coefficient between IPC codes extracted from medical device patents, introduced by Jun(2012). A social network is a social structure of diverse items as well as of human beings. In this study, we set each medical device as a node in an SNA and analyze the Degree values between them. Also, Korea health industrial statistics system are utilized for verification of selected central technology. As a result, we found that the central technology is located on the medical device items, which are listed higher the amount of production. The central technology selected through the proposed methodology will provide a inspiration for establishment of R&D policy.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.416-416
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• 2019

육상 담수는 대기중 이산화탄소($CO_2$) 배출의 중요한 발생원으로 주목되고 있다. 하천 및 강에서 대기중으로 배출되는 $CO_2$는 전 세계 탄소순환의 핵심요소이며, 대부분의 하천과 강은 $CO_2$로 과포화 되어있다. 세계적으로 하천 및 강의 $CO_2$ 배출량은 호수 및 저수지의 배출량보다 약 5배 많은 것으로 보고되고 있으나, 국내연구에서는 연구사례가 드물다. 따라서 본 연구의 목적은 낙동강 중하류에 위치해있는 강정고령보(GGW), 달성보(DSW), 합천창녕보(HCW), 창녕함안보(CHW)에서 발생되는 순 대기 배출 플럭스(Net Atmospheric Flux, NAF)의 동적 변동 특성을 분석하고, 데이터마이닝 기법을 적용하여 쉽게 수집할 수 있는 물리적 및 수질 변수로 $CO_2$ NAF를 추정하는데 사용할 수 있는 간략한 예측 모델을 개발하는데 있다. $CO_2$ NAF는 대기-수면 경계면에서의 $CO_2$ 부분압($pCO_2$)의 차에 기체전달속도를 곱하여 산정하였으며, 기체전달속도는 Cole and Caraco(1998)가 제안한 식을 사용하였다. 담수와 해수의 탄산염 시스템에서 열역학적 화학평형을 모두 고려한 $CO_2$SYS 프로그램을 사용하여 수중의 $pCO_2$를 산정하였고, $CO_2$ NAF는 Henry의 법칙과 Fick의 1차 확산법칙을 사용하여 계산하였다. $CO_2$ NAF의 시간적 변동성에 영향을 미치는 환경요인을 평가하기 위해서 상관분석, 주성분분석(Principal Component Analysis; PCA), 단계적다중회귀모델(Step-wise Multiple Linear Regression; SMLR), 랜덤포레스트(Random Forest; RF)방법을 사용하였다. SMLR 모델은 R package인 olsrr, RF 모델은 R package인 caret, randomForest를 이용하여 분석하였다. 연구 결과, 4개 보 상류 하천구간은 조류의 성장이 활발한 일부 기간을 제외한 대부분의 기간에서 $CO_2$를 대기로 배출하는 종속영양시스템(Heterotrophic system)을 보였다. $CO_2$ NAF의 중위값은 HCW에서 최소 $391.5mg-CO_2/m^2day$, DSW에서 최대 $1472.7mg-CO_2/m^2day$였다. 모든 보에서 NAF는 pH와 강한 음의 상관관계를 보였으며, $pCO_2$와 Chl-a도 음의 상관관계를 보였다. 이는 조류가 수중에서 $CO_2$를 소비하고 pH를 증가시키기 때문이다. PCA 분석 결과, NAF와 $pCO_2$가 높은 공분산을 보였으며, pH와 Chl-a는 반대 방향으로 군집되어 상관분석과 동일한 결과를 보였다. 이 연구를 통해 개발된 SMLR 모델과 RF 모델의 Adj. $R^2$ 값은 모든 보에서 0.77 이상으로 나왔으며, $pCO_2$ 측정 데이터가 없더라도 하천의 $CO_2$ NAF를 추정하는 방법으로 사용될 수 있을 것으로 평가된다.

• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.811-817
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• 2012

This study aims to empirically identify how job embeddedness which is consisted of links, fit, and sacrifice affects seafarers' turnover intention via organizational commitment. The results of covariance structure analysis on the questionnaire data collected from 362 seafarers are as follows. First, as job embeddedness increases, the seafarers' organizational commitment also increases. Second, organizational commitment seems to have negative relationship with seafarers' turnover intention at the marginally significant level, since links and fit have direct negative relationship with turnover intention.

• Korea Journal of Hospital Management
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• v.13 no.4
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• pp.76-100
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• 2008

The purpose of this research is to identify causalities among service quality, service value, customer satisfaction and customer loyalty and to compare the causalities between in-patients and out-patients. A multi-group structural equation model was used to test the hypothesis of conceptual model. Empirical results indicate that two factors such as assurance and empathy have direct impact on service value and customer satisfaction in both the patients. In the results of multi-group comparison test, however, the path coefficients from service value to customer loyalty and from customer satisfaction to customer loyalty were different across the two groups. In out-patients, customer loyalty is more positively related with service value. In in-patients, customer loyalty is more positively related with customer satisfaction. It is proven that service quality influences customer loyalty. Therefore To compete successfully in today's volatile & competitive medical markets, the hospital needs to manage the service quality, considering the type of patients.

• Proceedings of the Korean Association for Survey Research Conference
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• 2007.11a
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• pp.55-65
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• 2007

In this research, it will be examined on mathematical model of AMOS software program that ues for Covariance Structure Analysis. if we have not understood to mathematical model of Covariance Structure, we fail to understand Structural equation modeling. Similarly If We were not understand to mathematical model of AMOS Software, we do not use Software adequately. Therefore we examine two sorts of Software that be designed for Structural equation modeling or Covariance Structure Analysis. In this research, We will focus on 8 assumption of Structural equation modeling and compare AMOS(Analysis of MOment Structure) program with LISREL(Linear Structure RELation) program. We found that A Program of AMOS Software have materialized with RAM(Reticular Action Model).

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.829-836
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• 2011

This study aims to empirically identify how the antecedents of seafarers' social identity(i.e., socialization, social support, perceived organizational support, status in organization) affect turnover intention via social identity. In order to achieve this objective, this study conducted covariance structure analysis on the questionnaire data collected from 362 seafarers. The main results are as follows: First of all, as social identity of seafarers increases, their turnover intention decreases. Secondly, as socialization, social support, and perceived organizational support increases, seafarers' social identity also increases. Finally, while socialization and social support decrease turnover intention only through social identity, perceived organizational support decreases turnover intention both directly and indirectly via social identity.