• Journal of the Korean Solar Energy Society
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• v.24 no.3
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• pp.9-17
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• 2004

Nowadays, a concern of building environment has been arousing. Furthermore, according to this trend, the social concern has expended continuously. Especially, the right of daylight is essential for both the pleasant life and building maintenance. In this reason, it has dealt as like property right. Therefore, the Infringement on the right of daylight can be applicable to the infringement of property right. However, few un-notarized calculation methods have been used without careful examination about daylight duration calculation methods which can be used for determine sunshine infringement as the dispute solution, therefore. In this thesis We analyzed and concluded the differentiations of two calculation methods which are using nowadays.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.132-134
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• 2003

The likelihood ratio, logistic regression and artificial neural networks methods are applied and verified for analysis of landslide susceptibility in Yongin, Korea using GIS. From a spatial database containing such data as landslide location, topography, soil, forest, geology and land use, the 14 landsliderelated factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression and artificial neural network methods. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the methods. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The v erification results showed satisfactory agreement between the susceptibility map and the exis ting data on landslide locations.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.57-65
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• 2017

Six soil subsampling methods were evaluated with explosive compounds-contaminated soils to quantify the variance associated with each method. The methods include modified grab sampling, simplified ripple splitting, fractional shoveling, coning & quatering, degenerate fractional shoveling, and rolling & quatering. All the methods resulted in significantly lower CV (coefficient of variation) of 1~5%, compared to common grab sampling that gave 8~98% of CV, possibly due to the reduction of grouping and segregation errors described by Gy sampling theory. Among the methods, simplified ripple splitting tends to result in lower explosive compounds concentrations, while the rolling & quatering gave the opposite result. Fractional shoveling method showed the least variance and the highest reproducibility in the analysis.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.71-76
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• 2023

In order to achieve this goal, we consider the following issues: a retrospective analysis of the concepts of "giftedness", "intellectually gifted personality"; the experience of working with gifted youth abroad is analyzed; features of work with gifted student youth are revealed; educational and methodological support and practical work with gifted students are analyzed; an empirical study was conducted to determine the attitude of gifted youth to organizational forms of work with them; developed a scientific circle as a form of work with intellectually gifted student youth. A set of methods is used, in particular: theoretical methods: comparison, analysis, synthesis and generalization; empirical methods: analysis of documentation and results of pedagogical activity, observation.

• Advances in nano research
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• v.14 no.3
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Journal of the Korean association of regional geographers
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• v.14 no.6
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• pp.736-751
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• 2008

Although a growing number of studies have commonly used a simple areal weighting interpolation method to quantify demographic characteristics of impacted areas in environmental equity analysis, the results obtained are inevitably imprecise because of the method's unrealistic assumption that population is evenly distributed within a census enumeration unit. Two alternative areal interpolation methods such as intelligent areal weighting and regression methods can account for the distributional biases in the estimation of impacted populations by making use of additional information about the geographic distribution of population. This research explores five areal interpolation methods for estimating the population characteristics of impacted areas in environmental equity analysis and evaluates the sensitivity of the outcomes of environmental equity analysis to areal interpolation methods. This study used GIS techniques to allow areal interpolation to be informed by the distribution of land cover types, as inferred from a satellite image. in both the source and target units. Independent samples t-test statistics were measured to verify the environmental equity hypothesis while coefficients of variation were calculated to compare the relative variability and consistency in the socioeconomic characteristics of populations at risk over different areal interpolation methods. Results show that the outcomes of environmental equity analysis in the study area are not sensitive to the areal interpolation methods used in estimating affected populations, but the population estimates within the impacted areas are largely variable as different areal interpolation methods are used. This implies that the use of different areal interpolation methods may to some degree alter the statistical results of environmental equity analysis.

• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.81-87
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• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

• Genomics & Informatics
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• v.5 no.3
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• pp.129-132
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• 2007

arraylmpute is a software for exploratory analysis of missing data and imputation of missing values in microarray data. It also provides a comparative analysis of the imputed values obtained from various imputation methods. Thus, it allows the users to choose an appropriate imputation method for microarray data. It is built on R and provides a user-friendly graphical interface. Therefore, the users can easily use arraylmpute to explore, estimate missing data, and compare imputation methods for further analysis.

• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.13-25
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• 2000

This paper reviews and classify fault-tree analysis methods developed since 1960 for system safety and reliability. Fault-tree analysis is a useful analytic tool for the reliability and safety of complex systems. The literature on fault-tree analysis is, for the most part, scattered through conference proceedings and company reports. This paper classify the literature according to system definition, fault-tree construction, qualitative evaluation, quantitative evaluation, and available computer codes for fault-tree analysis.

• Wind and Structures
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• v.1 no.1
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• pp.25-42
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• 1998

Improvements to the Gumbel method of extreme value analysis of wind data made over the last two decades are reviewed and illustrated using sample data for Jersey. A new procedure for extending the Gumbel method to include M-th highest annual extremes is shown to be less effective than the standard method, but leads to a method for calibrating peak-over-threshold methods against the standard Gumbel approach. Peak-over-threshold methods that include at least the 3rd highest annual extremes, specifically the modified Jensen and Franck method and the "Method of independent storms" are shown to give the best estimates of extremes from observations.