• The Journal of Engineering Geology
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• v.18 no.1
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• pp.1-6
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• 2008

Precipitation and groundwater level data sets from Kum river watershed were analyzed and compared. The correlation between groundwater level and the moving average of precipitation was analyzed. Moving averaging technique is stochastic method and that was used to consider the effect of precipitation events on groundwater level fluctuation. Groundwater level generally follows seasonal precipitation pattern and low level occurs from early December to late April. Relatively high groundwater level is appeared in wet spell (July and August). The correlation between groundwater level and the moving average of precipitation to consider precedent precipitation events was analyzed with minimum two-year data sets. When the precipitation and groundwater level data set pair was selected the precipitation gauge station is closely located to groundwater level gauge station in the upstream direction to minimize the non-homogeneous precipitation distribution effect. The maximum correlation was occurred when the averaging periods were from 10 days to 150 days with Kum river watershed data. The correlation coefficients are influenced by data quality, missing data periods, or snow melt effect, etc. The maximum coefficient was 0.8886 for Kum river watershed data.

• Korean Journal of Mathematics
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• v.17 no.4
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• pp.419-428
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• 2009

We show the existence of at least one nontrivial solution of the homogeneous mixed type nonlinear elliptic problem. Here mixed type nonlinearity means that the nonlinear part contain the jumping nonlinearity and the critical growth nonlinearity. We first investigate the sub-level sets of the corresponding functional in the Soboles space and the linking inequalities of the functional on the sub-level sets. We next investigate that the functional I satisfies the mountain pass geometry in the critical point theory. We obtain the result by the mountain pass method, the critical point theory and variational method.

• Journal of International Academy of Physical Therapy Research
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• v.2 no.1
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• pp.260-266
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• 2011

The purpose of this study was to investigate the effects of meditation music with lumbar stabilization exercise on balance, concentration and muscle activation. Participants are divided into Group A and Group B. Group A listened to meditation music while doing 4 sets of lumbar stabilization exercise. Group B did not listen to meditation music while doing 4 sets of lumbar stabilization exercise. Surface EMG data was obtained rectus abdominis, external oblique, erector spinae, multifidus muscle during lumbar stabilization exercise. To examine the effect of before-after experiment for concentration and balance, paired t-test was adopted. Changes in EMG data of each muscles were analyzed by independence t-test. There were statistically significant increasing at concentration level and balance level in Group A. But significant difference was not shown in muscle activation. The clinical effect of the meditation music with lumbar stabilization exercise was investigated in this study with more excellent results in concentration and balance. In conclusion, these results suggest that meditation music and lumbar stabilization exercise may be useful in elderly people.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.575-584
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• 2016

Considering the randomness and uncertainty of wind power, a reliability model of WTGs is established based on the combination of the Weibull distribution and the Markov chain. To analyze the failure mode quickly, we use the switch-section partitioning method. After defining the first-level load zone node, we can obtain the supply power sets of the first-level load zone nodes with each WTG. Based on the supply sets, we propose the dynamic division strategy of island operation. By adopting the fault analysis method with the attributes defined in the switch-section, we evaluate the reliability of the distribution network with WTGs using a sequential Monte Carlo simulation method. Finally, using the IEEE RBTS Bus6 test system, we demonstrate the efficacy of the proposed model and method by comparing different schemes to access the WTGs.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.405-414
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• 2012

In this paper, we propose a reliability estimation method for DI&C systems. At the system level, a fault tree model is suggested and Boolean algebra is used to obtain the minimal cut sets. At the component level, an exponential distribution is used to model hardware failures, and Bayesian estimation is suggested to estimate the failure rate. Additionally, a binomial distribution is used to model software failures, and a recently developed software reliability estimation method is suggested to estimate the software failure rate. The overall system reliability is then estimated based on minimal cut sets, hardware failure rates and software failure rates.

• KOGO NEWS
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• v.6 no.1
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• pp.29-33
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• 2006

Gene set analysis is a new concept and method. to analyze and interpret microarray gene expression data and tries to extract biological meaning from gene expression data at gene set level rather than at gene level. Compared with methods which select a few tens or hundreds of genes before gene ontology and pathway analysis, gene set analysis identifies important gene ontology terms and pathways more consistently and performs well even in gene expression data sets with minimal or moderate gene expression changes. Moreover, gene set analysis is useful for comparing multiple gene expression data sets dealing with similar biological questions. This review briefly summarizes the rationale behind the gene set analysis and introduces several algorithms and tools now available for gene set analysis.

• Asia Marketing Journal
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• v.22 no.2
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• pp.1-18
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• 2020

We estimate a choice-based aggregate demand model accounting for consumers' consideration sets, and study its implications on market structure. In contrast to past research, we model and estimate consumer demand using aggregate-level consumer browsing data in addition to aggregate-level choice data. The use of consumer browsing data allows us to study consumer demand in a realistic setting in which consumers choose from a subset of products. We calibrate the proposed model on both data sets, avoid biases in parameter estimates, and compute the price elasticity measures. As an empirical application, we estimate consumer demand in the camcorder category and study its implications on market structure. The proposed model predicts a limited consumer price response and offers a more discriminating competitive landscape from the one assuming universal consideration set.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.6
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• pp.850-853
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• 1999

Angus postweaning daily gain (PWDG) was analyzed to investigate effects of the heterogeneous variance and the genotypes by sex interaction on prediction of EBVs with data sets of various environmental levels. A whole data (16,239 records) was divided into six data sets according to averages of the best linear unbiased estimator (BLUE) of herd environment. The results comparing prediction models showed that single-trait model is adequate for most of the data sets except for the data set of poor environment for both of the bulls and the heifers where the heterogeneity of variance and the genotypes by sex interaction exists. In the prediction with the data set of the low environment level, the bull's EBVs by single-trait models had high product moment correlations with male EBVs of the bulls by the multitrait model. Whereas the heifer's EBVs had moderate correlations with female EBVs by the multitrait model. This moderate correlation seems to be resulted by the heterogeneity of variance and low heritability of the heifer's PWDG. The prediction models with heterogeneity of variance had little effect on the prediction of EBVs for the data sets with moderate to high genetic correlations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.71-85
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• 2011

Saltwater intrusion effects of coastal aquifers in Korea peninsula were analyzed through trend analysis with groundwater level, seawater level, seawater temperature, and electrical resistivity(EC) data sets. Groundwater level and EC data sets from 27 coastal regions were collected and analyzed. Groundwater level was stable for all the regions however EC data showed stable or changing trends (9 increasing, 10 stable, and 8 decreasing regions). Seawater temperature was collected and analyzed for 14 regions and they are increasing for most regions (12 increasing and 2 stable regions). Seawater level was also collected and analyzed for 24 regions and is rising for most regions (18 rising, 3 stable, and 3 falling regions). Especially, west cost regions have stronger increasing tendencies of seawater level, seawater temperature, and EC than eastern and southern coastal regions. Therefore the saltwater intrusion problem can be serious for west cost regions in Korea peninsula and it is necessary to establish a plan to minimize the damages from saltwater intrusion.

• Journal of Korea Water Resources Association
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• v.46 no.10
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• pp.977-987
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• 2013

This study aims to develop a multiple criteria decision making (MCDM) approach for flood vulnerability assessment which considers uncertainty. The flood vulnerability assessment procedure consists of three steps: (1) use the Delphi process to determine the criteria and their corresponding weights-the adopted criteria represent the social, economic, and environmental circumstances related to floods, (2) construct a fuzzy data matrix for the flood vulnerability criteria using fuzzification and standardization, and (3) set priorities based on the number of assessed vulnerabilities. This study uses a modified fuzzy TOPSIS method based on ${\alpha}$-level sets which considers various uncertainties related to weight derivation and crisp data aggregation. Further, Spearman's rank correlation analysis is used to compare the rankings obtained using the proposed method with those obtained using fuzzy TOPSIS with fuzzy data, TOPSIS, and WSM methods with crisp data. The fuzzy TOPSIS method based on ${\alpha}$-cut level sets is found to have a higher correlation rate than the other methods, and thus, it can reduce the difference of the rankings which uses crisp and fuzzy data. Thus, the proposed flood vulnerability assessment method can effectively support flood management policies.