• 해양환경안전학회지
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• 제24권7호
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• pp.907-915
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• 2018

다양한 산업분야에서 중금속의 사용이 증가할수록, 중금속으로 인한 환경오염과 생물학적 위해성에 대한 우려의 목소리가 커지고 있다. 통계 지수는 배경농도 값과의 비교를 통해 중금속 오염농도를 정규화 시킴으로써 토양 오염의 정도를 수치화하고, 단계 별로 오염 정도를 판단 할 수 있어 많이 사용된다. 본 연구에서는 농축인자(Enrichment factor, EF), 축적 계수(accumulation index), 잠재적 생물학적 위험 지표(potential ecological risk index)등을 이용하여 중공업 근처 토양 내 중금속 오염가능성을 평가하였다. 연구결과, 중금속의 오염 정도는 정부 가이드라인에 비하여 낮은 수준이었으나, 특정 위치에서 아연, 구리, 납 등의 중금속 오염이 관찰 되었다. 농축인자, 축적계수, 생물학적 위험 지표를 통해 일부 토양 내 중금속 오염이 우려할 수준이며, 주변에 존재하는 인위적 오염원에 의한 오염가능성이 있음을 확인하였다. 연구대상지의 추가 시료채취 및 추정되는 오염원의 시료 확보 후, 동위원소 분석 및 x-ray 기반 분석을 통해 오염원 추적연구가 필요할 것으로 판단된다.

• 산업경영시스템학회지
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• 제33권4호
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• pp.187-192
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• 2010

Korean railway has run about 110 years since 1989 and played a great role of industrialization in Korea. It is known that rail transport systems have many advantages of being more safe, energy-efficient, and environment-friendly, as compared to other transportation systems. However, railway incidents are often attributed to the failure of safety management and critical to the efficiency of railroad industry. This study reviewed economic, financial, and general statistical information on Korea Railroad. Based on the statistical data, the effect of accidents on railroad management was analyzed. Correlation analysis revealed that railway accident had a negative effect on the gross profit of Korea Railroad. In order to reduce potential risks and incident rate, some recommendations are proposed. Actual or potential applications of this research include safety guidelines for improving efficiency of railroad industry.

• Journal of Periodontal and Implant Science
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• 제45권1호
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• pp.2-7
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• 2015

A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

• 대한인간공학회지
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• 제16권2호
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• pp.15-27
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• 1997

Brain potential is described using the mesocolumnar activity defined by averaged firings of excitatory and inhibitory neuron of neocortex. Lagrangian is constructed based on SMNI(Statistical Mechanics of Neocortical Interaction) and then Euler Lagrange equation is obtained. Excitatory neuron firing is assumed to be amplitude- modulated dominantly by the sum of two modes of frequency .omega. and 2 .omega. . Time series of this neuron firing is calculated numerically by Euler Lagrangian equation. I .omega. L related to low frequency distribution of power spectrum, I .omega. H hight frequency, and Sd(standard deviation) were introduced for the effective extraction of the dynamic property in the simulated brain potential. The relative behavior of I .omega. L, I .omega. H, and Sd was found by parameters .epsilon. and .gamma. related to nonlinearity and harmonics respectively. Experimental I .omega L, I .omega. H, and Sd were obtained from EEG of human in rest state and of canine in deep sleep state and were compared with theoretical ones.

• Journal of Microbiology and Biotechnology
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• 제22권12호
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• pp.1767-1775
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• 2012

The Cr(VI) removal capability of Acinetobacter junii VITSUKMW2 isolated from the Sukinda chromite mine site was evaluated and enhanced using statistical design techniques. The removal capacity was evaluated at different pH values (5-11) and temperatures ($30-40^{\circ}C$) and with various carbon and nitrogen sources. Plackett-Burman design was used to select the operational parameters for bioremediation of Cr(VI). Three parameters (molasses, yeast extract, and Cr(VI) concentration) were chosen for further optimization using central composite design. The optimal combination of parameters was found to be 14.85 g/l molasses, 4.72 g/l yeast extract, and 54 mg/l initial Cr(VI), with 99.95% removal of Cr(VI) in 12 h. A. junii VITSUKMW2 was shown to have significant potential for removal of Cr(VI).

• 터널과지하공간
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• 제8권4호
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• pp.351-358
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• 1998

현장에서 측정된 절리 trace 길이에 의거하여 영속성을 산정할 수 있는 통계적 분석법을 개발하였다. 이 방법에서는 잠재적 키블록과 불연속면의 상대적인 규모에 따라 절리 trace 기링 또는 원형절리의 직경에 대한 확률밀도분포를 이용한다. 대규모 지하공동의 설계 및 안전적 굴착에 대한 개발된 분석법의 활용성을 설명하기 위하여 규모 및 영속성이 다른 잠재적 키블록의 안정성을 고찰하였다.

• Transactions on Control, Automation and Systems Engineering
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• 제2권4호
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• pp.268-273
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• 2000

Plasma models are crucial to equipment design and process optimization. A radial basis function network(RBFN) in con-junction with statistical experimental design has been used to model a process plasma. A 2$^4$ full factorial experiment was employed to characterized a hemispherical inductively coupled plasma(HICP) in characterizing HICP, the factors that were varied in the design include source power, pressure, position of shuck holder, and Cl$_2$ flow rate. Using a Langmuir probe, plasma attributes were collected, which include typical electron density, electron temperature. and plasma potential as well as their spatial uniformity. Root mean-squared prediction errors of RBEN are 0.409(10(sup)12/㎤), 0.277(eV), and 0.699(V), for electron density, electron temperature, and Plasma potential, respectively. For spatial uniformity data, they are 2.623(10(sup)12/㎤), 5.704(eV) and 3.481(V), for electron density, electron temperature, and plasma potential, respectively. Comparisons with generalized regression neural network(GRNN) revealed an improved prediction accuracy of RBFN as well as a comparable performance between GRNN and statistical response surface model. Both RBEN and GRNN, however, experienced difficulties in generalizing training data with smaller standard deviation.

• 한국지구과학회지
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• 제25권1호
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• pp.10-21
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• 2004

Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.

• 산업공학
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• 제17권1호
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

• 지구물리
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• 제7권2호
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• pp.121-134
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and land-use, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Hwanam 2 District, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice-layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Groundwater contamination potential map was achieved as a final result by comparing modified DRASTIC potential and the amount of pollutant load logically. The result suggest the predictability of contamination potential in a specified area in the respects of hydrogeological aspect and water quality.