• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.624-627
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• 2005

This paper presents a new data classification method using the Robbins Monro stochastic approximation algorithm k-nearest neighbor and distribution analysis. To cluster the data set, we decide the centroid of the test data set using k-nearest neighbor algorithm and the local area of data set. To decide each class of the data, the Robbins Monro stochastic approximation algorithm is applied to the decided local area of the data set. To evaluate the performance, the proposed classification method is compared to the conventional fuzzy c-mean method and k-nn algorithm. The simulation results show that the proposed method is more accurate than fuzzy c-mean method, k-nn algorithm and discriminant analysis algorithm.

• Proceedings of the KSR Conference
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• 2009.05b
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• pp.341-347
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• 2009

In high speed railway, event recorder system stores a train speed and the related data for train operation in real time. Using those information, we can analysis the train operation and the reason of train accident. Analysis software gets the stored data from Event Recorder and shows the status of various signals related with train operation. Using it, also we can analysis the train operation before and after the given time. In this paper we propose the analysis software to show and analysis the operation of high speed train. The method of transferring the stored data from Event Recorder into Analysis Software is proposed. We develop the efficient procedure to store the transferred data into analysis system. Also the effective method to show the store data and to analysis them is studied for finding the cause of train accident.

• 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.

• Korean Parent-Child Health Journal
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• v.14 no.1
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• pp.1-8
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• 2011

Purpose: This study was aimed to classify the major subjects and theme and to analyze the data collection and analysis method in research papers published in the Korean Parent-Child Health Journal of the Academic Society of Parent-Child Health since 1998. Methods: A total 152 studies published from the first edition to volume 12, number 2 were reviewed using structured analysis criteria developed by researchers; research type, research design, research subjects, research theme, data collection and analysis method. Research theme was founded 4 nursing domains. Data collection and analysis method of papers were limited to quantitative and qualitative researches. Results: One hundred papers conducted quantitative research; 79.0% used survey design. Most of the data collection and analysis method in quantitative research were self-reported questionnaire (69.4%) and parametric statistics respectively. The research subjects of sixty three papers were parent with well or child. The common domain studies was human related concepts such as raring. Conclusion: The findings of this study suggest that published studies have been improved and diversified, however, detailed and clear evaluation tool that assess study process and method should be developed as a way to further improve the quality of published papers in the Korean Parent-Child Health Journal.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Journal of Korean Society for Atmospheric Environment
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• v.2 no.1
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• pp.41-54
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• 1986

Methods used for averaging PH's of rainwater and site representation have been studied, Statistical analysis was attempted regarding effects of ionic components on PH's utilizing 847 data altogether obtained in two years, 1984 and 1985. The outcome of the study may be assumarized as follows: 1. Methods for Averaging PH Volume weighted method is considered to be acceptable providing that precipitation is measured at the same time when the samples are taken. Without precipitation data a simple averaging method should be the next choice. 2. Site Representation A statistical method used for optimizing a monitoring newtork was applied using the data collected. Because of a limited number of data, no discernible conclusion can be reached suggesting that the method can serve as a good guide when the data base becomes more reliable. 3. A good correlation appears to exist betwen conductivities and ionic components in rainwater. It would, therefore, be possible to certain extend to estimate ionic concentrations from conductivity measurements by correlation equations. 4. The acidity of rainwater is effected by $SO_4^{2-}, NO_3^-, Cl^- and NH_4^+ with SO_4^{2-}$ being the most significant as demonstrated by standardized regression analysis.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1179-1189
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• 2017

In this study, we propose an alternative method for discriminant analysis using a multivariate empirical distribution function to express multivariate data as a simple one-dimensional statistic. This method turns to be the estimation process of the optimal threshold based on classification accuracy measures and an empirical distribution function of data composed of classes. This can also be visually represented on a two-dimensional plane and discussed with some measures in ROC curves, surfaces, and manifolds. In order to explore the usefulness of this method for discriminant analysis in the study, we conducted comparisons between the proposed method and the existing methods through simulations and illustrative examples. It is found that the proposed method may have better performances for some cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1538-1542
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• 2005

This study is to secure more accurate data of the discharge on the measurement by gaining a reliable hydrological data through the comparison the present method of measuring them and the other way that is based ISO. This study suggests the applicable measurement method of the discharge that has reliance through general elements and the analysis of uncertainty by comparing and assaying the data of the Hyung San River that is measured by the present standard. The result of this study makes us realize that we should complement the measurement method of the discharge securing the reliable and accurate hydrological data Hydrological data is very important things to perform domestic river works or install some structure in river or coast. Securing reliable and accurate hydro-data and making a thesis should go on in other to do any construction in river or coast.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.131-138
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• 1998

In usual statistical data analysis, we describe statistical data by exact values. However, in modem complex and large-scale systems, it is difficult to treat the systems using only exact data. In this paper, we define these data as fuzzy data(ie. Linguistic variable applied to make the member-ship function.) and Propose a new method to get an analysis of fuzzy survey data based on the maximum entropy Principle. Also, we propose a new method of discrimination by measuring distance between a distribution of the stable state and estimated distribution of the present state using the Kullback - Leibler information. Furthermore, we investigate the validity of our method by computer simulations under realistic situations.