• Tunnel and Underground Space
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• v.29 no.4
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• pp.243-261
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• 2019

Microseismic monitoring technologies have been recognized for its superiority over traditional methods and are used in domestic and overseas underground mines. However, the complex gangway layout of underground mines in Korea and the mixed structure of excavated space and rock masses make it difficult to estimate the microseismic propagation and to determine the arrival time of microseismic wave. In this paper, experimental studies were carried out to determine the source location according to various arrival picking methods and dimensional conditions. The arrival picking methods used were FTC (First Threshold Cross), Picking window, AIC (Akaike Information Criterion), and 2-D and 3-D source generation experiments were performed, respectively, under the 2-D sensor array. In each experiment, source location algorithm used iterative method and genetic algorithm. The iterative method was effective when the sensor array and source generation were the same dimension, but it was not suitable to apply when the source generation was higher dimension. On the other hand, in case of source location using RCGA, the higher dimensional source location could be determined, but it took longer time to calculate. The accuracy of the arrival picking methods differed according to the source location algorithms, but picking window method showed high accuracy in overall.

• Journal of Ecology and Environment
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• v.32 no.2
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• pp.103-107
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• 2009

We investigated colonization and extinction patterns in a meta population of the gold-spotted pond frog (Rana planeyi ehoseniea) near the Korea National University of Education, Chungbuk, Korea, by surveying the frogs in the nine occupied habitat patches in the study area four times per breeding season for three years (2006$\sim$2008) and recording whether the patches were occupied by frogs as well as how many frogs were calling in the patches. We then developed five a priori year-specific models using the Akaike Information Criterion (AIC). The models predicted that: 1) probabilities of colonization and local extinction of the frogs were better explained by year-dependent models than by constant models, 2) there are high local extinction and low colonization probabilities, 3) approximately 31% number of patches will be occupied at equilibrium, and 4) that considerable variation in occupation rate should occur over a 30-year period, due to demographic stochasticity (in our model, the occupation rate ranged from 0.222 to 0.889). Our results suggest that colonization is important in this metapopulation system, which is governed by mainly stochastic components, and that more constructive conservation effects are needed to increase local colonization rates.

• Journal of Korean Academy of Nursing
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• v.44 no.6
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• pp.660-671
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• 2014

Purpose: The aims of this study were to construct a hypothetical structural model which explains the premenstrual syndrome (PMS) in adolescent girls and to test the fitness with collected data. Methods: The participants were 1,087 adolescent girls from 3 high schools and 5 middle schools in B city. Data were collected from July 3 to October 15, 2012 using self-reported questionnaires and were analyzed using PASW 18.0 and AMOS 16.0 programs. Results: The overall fitness indices of hypothetical model were good (${\chi}^2$ =1555, p<.001), ${\chi}^2$/df=4.40, SRMR=.04, GFI=.91, RMSEA=.05, NFI=.90, TLI=.91, CFI=.92, AIC=1717). Out of 16 paths, 12 were statistically significant. Daily hassles had the greatest impact on PMS in the adolescent girls in this model. In addition, PMS in adolescent girls was directly affected by menarche age, Body Mass Index (BMI), amount of menstruation, test anxiety, social support, menstrual attitude and femininity but not by academic stress. This model explained 27% of the variance in PMS in adolescent girls. Conclusion: The findings from this study suggest that nursing interventions to reduce PMS in adolescent girls should address their daily hassles, test anxiety, menstrual attitude and BMI. Also, social support from their parents, friends, and teachers needs to be increased.

• Journal of Korean Academy of Nursing
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• v.44 no.3
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• pp.259-269
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• 2014

Purpose: The purpose of this study was to construct and test a structural equation modeling on burnout of clinical nurses based on CS-CF model. Methods: A survey using a structured questionnaire was conducted with 557 clinical nurses. Data were analyzed using structural equation modeling. Results: The modified hypothetical model yielded the following ${\chi}^2=289.70$, p<.001, RMSEA=.09, GFI=.93, TLI=.91, CFI=.94, PCFI=.65, AIC=363.21, SRMR=.05 or less and showed good fit indices. Nursing work environment, patient safety culture and resilience showed indirect effects on burnout while compassion fatigue and compassion satisfaction had direct effects. Conclusion: Results of this study suggest that compassion fatigue must be decreased and compassion satisfaction has to be increased, while burnout is lowered by enhancing the clinical nursing work environment, patient safety culture and resilience. In addition, more variables and longitudinal studies are necessary to validate the clear cause-and-effect relationship between the relevant variables.

• Journal of the Korean Home Economics Association
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• v.33 no.1
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• pp.169-180
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• 1995

To determine the effects of guar suksolgi on blood glucose and lipids in type-ll diabetic subjects, a piece of guar suksolgi(36.3g, 54Kcal) was administered to eight patients for 3 weeks every meal. No significant differences occured indietary intakes and body weight before and after the treatment. Fasting blood glucose levels were decreased from 132.38mg/dI to 114.75mg/dI after the treatment, but not statistically significant. Blood TG levels were increased from 159.13mg/dI to 175.00mg/dI after the treatment, but not statistically significant. Excluding one patient who had extremely high TG level, blood TG levels tended to be decreased from 148.00mg/dI to 121.00mg/dI. TC LDL-c, HDL-c levels were decreased after the treatment, but not statistically significant. HbAIC concentrations were decreased from 8.54mg/kI to 7.80mg/dI after the treatment, but not statistically significant. In the case of three patients who had had normal fasting blood glucose levels, blood glucose levels tended to be decreased at postprandial 30, 60 minutes, and blood insulin levels tended to be decreased at postprandial 30, 60, 90, 120 minutes, although none of the levels were statistically significant. Therefore, if guar suksolgi is adinistered to type-ll diabetic subjects being more hyperglycemic than our patients, their blood glucose and lipids will be decreased significantly.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.179-192
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• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.10
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• pp.1406-1418
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• 2002

The direct simulation Monte Carlo(DSMC) method is employed to calculate the etch rate on Al wafer. The etchant is assumed to be Cl$_2$. The etching process of an Al wafer in a helicon plasma etcher is examined by simulating molecular collisions of reactant and product. The flow field inside a plasma etch reactor is also simulated by the DSMC method fur a chlorine feed gas flow. The surface reaction on the Al wafer is simply modelled by one-step reaction: 3C1$_2$+2Allongrightarrow1 2AIC1$_3$. The gas flow inside the reactor is compared for six different nozzle locations. It is found that the flow field inside the reactor is affected by the nozzle locations. The Cl$_2$ number density on the wafer decreases as the nozzle location moves toward the side of the reactor. Also, the present numerical results show that the nozzle location 1, which is at the top of the reactor chamber, produces a higher etch rate.

• Knowledge Management Research
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• v.17 no.3
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• pp.45-64
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• 2016

As the digital retail environement becomes prevalent, consumers are given greater opportunities to make purchases across physical and digital boundaries. Prior research emphasizes that the attractiveness of the digital or online channel is relatively determined by spatial specifics of physical locations. The overall market trend combined with prior research suggests that understanding spatial specifics becomes a key to managing both offline and online sales performance together. In this study, we focus on geographic variation in sales performance through offline and online channels and aim to investigate the channel-level sales difference between central and subsidiary areas. To this end, we obtain sales data of skincare and makeup products from a leading cosmetic company. Next, we examine spatial autocorrelations in data and then employ the spatial error models to study the effects of spatial specifics. The empirical findings are as follows. First, there are significant differences in category-specific and channel-level sales between central and subsidiary areas. Second, Moran's I statistics demonstrate the spatial autocorrelations of each variable. Third, spatial error models outperform simple regression models with lower AIC values. Finally, spatial specifics play a greater role in understanding online sales in subsidiary areas whereas they exert greater influence on offline sales in central areas. We believe our study advances the related theory and knowledge of multi-channel retailing and also contributes practically to location-dependent multi-channel strategies and sales data analytics.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.342-345
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• 2005

This paper describes dynamics analysis of a small training boat and a new type of ship's autopilot not only to keep her course but also to reduce her roll motion. Firstly, statistical analysis through multi-variate auto regressive model is carried out using the real data collected from the sea trial on an actual small training boat Sazanami after the navigational system of the boat was upgraded. It is shown that the roll motion is strongly influenced by the rudder motion and it is suggested that there is a possibility of reducing the roll motion by controlling the rudder order properly. Based on this observation, a new type of ship's autopilot that takes the roll motion into account is designed using the muti-variate modern control theory. Lastly, digital simulations by white noise are carried out in order to evaluate the proposed system and a typical result is demonstrated. As results of simulations, the proposed autopilot had good performance compared with the original data.

• Journal of Forest and Environmental Science
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• v.34 no.2
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• pp.108-118
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• 2018

Biomass determination of species-specific in forest ecosystem by semi-destructive measures requires the development of allometric equations; predict aboveground biomass observable independent variables such as, Diameter at Breast Height, Height, and Volume are crucial role. There has not been equation of this type in mountain Chuqala natural forest. In this study two species namely, Hypericum revolutum Vahl. & Maesa lanceoleta Forssk. with tree diameter classes (15-20, 20.5-25, and 25.5-35 cm), with the purpose of conducting allometric equations were characterized. Each species assumed considered individually. For the linear model fit the two observed variable DBH, H and V were preferred for the prediction of above ground biomass. The best fitted model choose among the two formed model were identified using Akaike Information Criterion (AIC), and $R^2$ and adjacent $R^2$. Based on this the best fit model for Hypericum revolutum Vahl. was AGB=-681.015+4,494.06 (DBH), and for Maesa lanceoleta Forrsk. was. AGB=-936.96+5,268.92 (DBH).