• Proceedings of the Computational Structural Engineering Institute Conference
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• pp.159-168
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• 1999

In seismic analysis, there are two main ways - uniform load method and dynamic analysis, dynamic analysis can be divided into response spectrum analysis and time history analysis. In case of which get the complexion of the vibration with 3-axis of coordinate direction in each mode of free vibration mode happened owing to complication of the shape, 3-dimensional dynamic analysis is recommended to perform as multi-mode spectral analysis in standard specification for highway bridge. The purpose of this study is to understand the dynamic behavior by performing multi-mode seismic analysis according to responses analysis and time history anal)'sis in using record of earthquake. In accordance with the criterion of seismic design as defined in standard specification for highway bridge by using modified records of the El Centre and Coyote Lake earthquake, response spectrum was constructed by using the tripartite logarithmic plot. The 3-span continuous space truss bridge was selected as model of numerical analysis. As the result performed time history analysis and analysis of response spectrum for the model of numerical analysis, the result of time history analysis was slightly larger than that of response spectrum analysis. This coincide with the tendency of the result came from the analysis when using a jagged response spectrum analysis, This coincide with the tendency of the result came from the analysis when using a jagged response spectrum for a single excitation. In the Process of performing these two analysis. response spectrum analysis is more effective than time history analysis in saving times in analyzing data.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.115-130
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• 1999

The price structure of housing market varies depending upon market price policy rather than low or high price policy because of IMF. The object of this study is to develop an analysis system for analyzing housing market and its demand. The analysis system consists of four major categories: macro index analysis, market decision analysis, housing market analysis, and consumer analysis. We model each category by using a variety of techniques such as generalized linear model, categorical analysis, bubble analysis, drill-down analysis, price sensitivity meter analysis, optimum price index analysis, profit index measurement analysis, correspondence analysis, conjoint analysis, and multidimensional scaling analysis. Seoul apartment data is analyzed to demonstrate the practical usefulness of the system.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.114-122
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• 2015

In a fire hazard analysis (FHA) for nuclear power plant, various electrical circuit analyses are performed in the parts of fire loading analysis, fire modeling analysis, separation criteria analysis, associated circuit analysis, and multiple spurious operation analysis. Thus, electrical circuit analyses are very important areas so that reliability of the analysis results should be assured. This study is to establish essential electrical elements for each analysis for verification of the reliability of the electrical circuit analyses in the fire hazard analysis for nuclear power plants. Applying the results derived by the study to domestic nuclear power plants, it is expected to determine the adequacy of the fire hazard analysis report and contribute to the reliability of the fire hazard analysis of those plants.

• Proceedings of the KIEE Conference
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• pp.2130-2131
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• 2011

Electric fire breaks out by various causes such as electric short, overload(over current), leakage current, poor contact, static electricity, insulation deterioration, partial disconnection and etc. In this paper, we studied analysis technique for scientific and systematic judgment for distinction of electricity fire existence and nonexistence, and described about electricity fire cause analysis process for collecting physical evidences. We handled external form analysis, Substance extension analysis, X-ray transmission analysis, cross-section analysis, thermal analysis, chemical structure analysis, surface structure analysis, component analysis, electrical properties analysis, and circuit analysis by analysis technique for electricity fire cause judgment. We expect that analysis technic elevation and correct cause of fire analysis of scene of a fire investigators and analysts through this paper which see help.

• Korean Journal of Clinical Laboratory Science
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• v.45 no.2
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• pp.60-65
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• 2013

Data from repeated measurements are accomplished through repeatedly processing the same subject under different conditions and different points of view. The power of testing enhances the choice of pertinent analysis methods that agrees with the characteristics of data concerned and the situation involved. Along with the clinical example, this paper compares the analysis of the variance on ex-post tests, gain score analysis, analysis by mixed design and analysis of covariance employable for repeating measure. Comparing the analysis of variance on ex post test, and gain score analysis on correlations, leads to the fact that the latter enhances the power of the test and diminishes the variance of error terms. The concluded probability, identified that the gain score analysis and the mixed design on interaction between "between subjects factor" and "within subjects factor", are identical. The analysis of covariance, demonstrated better power of the test and smaller error terms than the gain score analysis. Research on four analysis method found that the analysis of covariance is the most appropriate in clinical data than two repeated test with high correlation and ex ante affects ex post.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.1-14
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• 2000

The methods of sensitivity analysis for linear programming can be classified in two types: sensitivity analysis using an optimal solution, and sensitivity analysis using an approximate optimal solution. As the methods of sensitivity analysis using an optimal solution, there are three sensitivity analysis methods: sensitivity analysis using an optimal basis, positive sensitivity analysis, and optimal partition sensitivity analysis. Since they may provide different characteristic regions under degeneracy, it is not easy to understand and apply the results of the three methods. In this paper, we propose a generalized sensitivity analysis that can integrate the three existing methods of sensitivity analysis. When a right-hand side or a cost coefficient is perturbed, the generalized sensitivity analysis gives different characteristic regions according to the controlling index set that denotes the set of variables allowed to have positive values in optimal solutions to the perturbed problem. We show that the three existing sensitivity analysis methods are special cases of the generalized sensitivity analysis, and present some properties of the generalized sensitivity analysis.

• Journal of Korea Technology Innovation Society
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• v.5 no.3
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• pp.260-276
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• 2002

Technology Analysis is advanced by the development of the analysis of technological information such as technological bibliometric analysis and patent analysis. Also, the advance of technology analysis has led the development of the family of techno-market analysis such as cost-benefit analysis, analysis for new item development, and the valuation of technology and technology business. Technology analysis mostly based on technological information analysis is confronted by new challenges from the development of information science and technology such as text mining.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.529-535
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• 2018

Data is explosively growing, but many companies are still using data analysis only for descriptive analysis or diagnostic analysis, and not appropriately for predictive analysis or enterprise technology strategy analysis. In this study, we analyze the structured & unstructured patent data such as IPC code, inventor, filing date and so on by using big data analysis techniques such as network analysis and TF-IDF. Through this analysis, we propose analysis process to understand the core technology and technology distribution of competitors and prove it through data analysis.

• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.57-61
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• 1994

Performance of panelists trained for cooked rice quality was evaluated using analysis of variance, correlation analysis, and principal component analysis. Each method offered different information. Results showed that panleists with high F ratios (p=0.05) did not always have high correlation coefficient (p=0.05) with mean values pooled from whole panel. The results of analysis of variance for the panelists whose performance were extremely good or extremely poor were consistent with those of correlation analysis. Outliers designated by principal component analysis were different from the panelists whose performance was defined as extremely good or extremely poor by analysis of variance and correlation analysis. The results of principal component analysis descriminated the panelists with different scoring range more than different scoring trends depending on the treatments. Our study suggested combination of analysis of variance and correlation analysis provided valid basis for screening panelists.

• Management Science and Financial Engineering
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• v.10 no.2
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• pp.103-118
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• 2004

$\epsilon$-sensitivity analysis is a kind of methods for performing sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. Although $\epsilon$-sensitivity analysis was proposed several years ago, there have been no studies on its relationship with other sensitivity analysis methods. In this paper, we discuss the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using an optimal basis. First. we present a property of $\epsilon$-sensitivity analysis, from which we derive a simplified formula for finding the characteristic region of $\epsilon$-sensitivity analysis. Next, using the simplified formula, we examine the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using optimal basis when an $\epsilon$-optimal solution is sufficiently close to an optimal extreme solution. We show that under primal nondegeneracy or dual non degeneracy of an optimal extreme solution, the characteristic region of $\epsilon$-sensitivity analysis converges to that of sensitivity analysis using an optimal basis. However, for the case of both primal and dual degeneracy, we present an example in which the characteristic region of $\epsilon$-sensitivity analysis is different from that of sensitivity analysis using an optimal basis.