• 한국환경과학회지
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• 제28권1호
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.58-61
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• 2000

In this paper, we propose a new performance comparison method of various Interpolation methods for image enlargement The conventional methods employs PSNR and edge characteristic evaluation for performance comparison of interpolation methods. The proposed performance comparison method uses the position Information for each difference pixel's value and the frequency characteristic information between original image and Interpolated image. The proposed methods might be useful for performance comparison of various Interpolation methods through the computer simulation.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 학술발표대회 논문집 제17권 2호
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• pp.339-342
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• 1998

In this paper, we proposed various speaker adaptation methods and studied the performance of these methods. Methods which were studied in this paper are MAPE(Maximum A Posteriori Probability Estimation), ARTMAP. In order to evaluate the performance of these methods, we used Korean isolated digits as the experimental data, the hybrid speaker adaptation method, which unfied MAPE, linear spectral estimating and outpur probability of SCHMM, showed the better recognition result than those which performed other methods. And the method using ARTMAP showed the similar result to above hybrid method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제7권1호
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• pp.7-14
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• 2003

The main concern of this paper is to develop a new class of quasi-newton methods. These methods are intended for use whenever memory space is a major concern and, hence, they are usually referred to as limited memory methods. The methods developed in this work are sensitive to the choice of the memory parameter ${\eta}$ that defines the amount of past information stored within the Hessian (or its inverse) approximation, at each iteration. The results of the numerical experiments made, compared to different choices of these parameters, indicate that these methods improve the performance of limited memory quasi-Newton methods.

• 응용통계연구
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• 제25권6호
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• pp.1049-1058
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• 2012

Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

• 충청수학회지
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• 제29권4호
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• pp.663-676
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• 2016

In this paper we propose a new family of eighth order optimal methods for solving nonlinear equations by using weight function methods. The methods of the family require three function and one derivative evaluations per step and has order of convergence eight, and so they are optimal in the sense of Kung-Traub hypothesis. Precise analysis of convergence is given. Some members of the family are compared with several existing methods to show their performance and as a result to confirm that our methods are as competitive as compared to them.

• 응용통계연구
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• 제22권1호
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• pp.89-106
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• 2009

There have been many new advances in the development of improved clustering methods for microarray data analysis, but traditional clustering methods are still often used in genomic data analysis, which maY be more due to their conceptual simplicity and their broad usability in commercial software packages than to their intrinsic merits. Thus, it is crucial to assess the performance of each existing method through a comprehensive comparative analysis so as to provide informed guidelines on choosing clustering methods. In this study, we investigated existing clustering methods applied to microarray data in various real scenarios. To this end, we focused on how the various methods differ, and why a particular method does not perform well. We applied both internal and external validation methods to the following eight clustering methods using various simulated data sets and real microarray data sets.

• 대한인간공학회지
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• 제30권4호
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• pp.465-472
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• 2011

Objective: The aim of this paper is to introduce ergonomic evaluation methods for agricultural work. Background: Work-related Musculoskeletal Disorders(WMSDs) became a major problem in agriculture industry recently. A number of ergonomics evaluation methods have been developed in order to evaluate the work load for preventing WMSDs. The workload evaluation methods were developed for manufacturing industry. Therefore, these ergonomic evaluation methods were used carefully in agriculture industry because work type in agriculture different from work type in manufacturing. Method: Various references of ergonomic evaluation methods such as OWAS, REBA, RULA, NLE and Snook table have been reviewed for agricultural work. Results: This paper presents the characteristics, the selection and application procedure of ergonomic evaluation methods for agricultural work. Application: These results can be used to provide baseline information for ergonomic evaluation methods.

• 한국멀티미디어학회논문지
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• 제23권6호
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• pp.738-746
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• 2020

In this paper, we propose an indirect PIN entry method that provides enhanced security against smudge, recording, and thermal attacks. Conventional mobile PIN entry methods use on-screen numeric keypad for both use of display and entry. Thus These methods are vulnerable to aforementioned attacks. In our method, passcode is same as that of the conventional PIN entry methods, and that is user-friendly way for mobile device users. Therefore, our method does not reduce user convenience which is one of the advantages of the conventional methods. In addition, our method is not a method of directly touching the on-screen numeric keypad for entering passcode like the conventional PIN methods. Unlike the conventional methods, our method uses an indirect passcode entry method that applied a passcode indicating key. According to the performance comparison result, proposed method provides user convenience similar to the conventional methods, and also provides a higher level of security and safety against recording, smudge, and thermal attacks than the conventional methods.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.