• Communications for Statistical Applications and Methods
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• v.14 no.2
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• pp.309-316
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• 2007

In this paper, we decompose the whole likelihood based on grouped data into conditional likelihoods and study the approximate contribution of additional inspection to the efficiency. We also combine the conditional maximum likelihood estimators to construct an approximate maximum likelihood estimator. For an exponential distribution, we see that a large inspection size does not increase the efficiency much if the failure rate is small, and the maximum likelihood estimator can be approximated with a linear function of inspection times.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.2083-2085
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• 2009

Brain Computer Interface (BCI) is a communication pathway between devices (computers) and human brain. It treats brain signals in real-time basis and discriminates some information of what human brain is doing. In this work, we develop a EEG BCI system using a feature extraction such as common spatial pattern (CSP) and a classifier using Fisher linear discriminant analysis (FLDA). Two-class EEG motor imagery movement datasets with both cued and uncued are tested to verify its feasibility.

• Communications of the Korean Mathematical Society
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• v.21 no.2
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• pp.363-374
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• 2006

A new bivariate beta distribution based on the Appell function of the third kind is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure as well as the Fisher information matrix.

• Journal of Home Health Care Nursing
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• v.23 no.1
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• pp.45-52
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• 2016

Purpose: This study aimed to investigate the effects of providing prostatic hypertrophy patients with information about an upcoming prostate biopsy procedure on their anxiety, depression, and sleep quality. Methods: Sixty-two participants were divided equally into an experimental and control group. Experiments were conducted from July 31, 2015, to March 30, 2016. After providing information, we evaluated anxiety, depression, and sleep quality using structured questionnaires. Data were analyzed using chi-square tests, Fisher's exact tests, t-tests, and ANCOVA using SPSS. Results: The experimental group demonstrated significantly lower levels of anxiety and depression than the control group. The experimental group also demonstrated significantly higher sleep quality. Conclusion: Information on an upcoming prostate biopsy improved psychological outcomes in patients with prostatic hypertrophy. This education should be incorporated into nursing practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.629-638
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• 2020

This study was designed to investigate the health information usage of immigrants. A questionnaire survey was conducted on 171 immigrants. Data was analyzed for descriptive statistics, chi-square test, and Fisher's exact test. The frequency of migrants' use of health information is low, and the number of respondents who use health information less than once a month is highest. There were statistically significant differences in the frequency of use of health information according to age, occupation, and those who contracted diseases. The main source of health information was the Internet, and there were differences in the sources of health information according to age and whether the Internet was used. Most of the respondents used health information for themselves, and there was a difference in the targets of using health information according having a cohabitee and the perceived health status. It was found that the majority of immigrants do not actively use health information. However, when the age increased or the immigrant was unhealthy, the use of health information increased to solve health problems. Therefore, it is important to provide health information in a variety of ways according to the characteristics of immigrants.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.708-714
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• 2000

In this paper, an one-dimensional VLSI array for high speed processing of fractal image compression algorithm based the quad-tree partitioning method is proposed. First of all, the single assignment code algorithm is derived from the sequential Fisher's algorithm, and then the data dependence graph(DG) is obtained. The two-dimension array is designed by projecting this DG along the optimal direction and the one-dimensional VLSI array is designed by transforming the obtained two-dimensional array. The number of Input/Output pins in the designed one-dimensional array can be reduced and the architecture of process elements(PEs) can he simplified by sharing the input pins of range and domain blocks and internal arithmetic units of PEs. Also, the utilization of PEs can be increased by reusing PEs for operations to the each block-size. For fractal image compression of 512X512gray-scale image, the proposed array can be processed fastly about 67 times more than sequential algorithm. The operations of the proposed one-dimensional VLSI array are verified by the computer simulation.

• The Journal of the Convergence on Culture Technology
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• v.4 no.2
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• pp.171-178
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• 2018

The study was done to analyze the effects of aroma inhalation method on preoperative anxiety of upper and lower surgical patients. The research design was a nonequivalent control group non-synchronized design. The subjects were a total 60 patients of each group 30 patients that were operated on under general anesthesia for upper and lower limbs surgery. The tool of the Amsterdam preoperative anxiety information scale(APAIS), systolic and diastolic blood pressure, and pulse rate levels was measured the day before surgery. The data were analyzed by the $x^2$ test Fisher's exact test, paird t-test, and the independent t-test using SPSS 20.0. Study result indicated that Lavender aroma therapy had the effect on reduction of anxiety before surgery and reduction of blood pressure, and pulse rate levels. Therefore, the study result could be used as a scientifical data that can be applied to the nursing interventions that use the aroma inhalation method and contributing to development of the holistic nursing care.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.77-86
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• 2005

In this paper, we designed a learning algorithm of LVQ that extracts classification errors and learns ones and improves classification performance. The proposed LVQ learning algorithm is the learning Networks which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVQ. To extract pattern vectors which cause classification errors, we proposed the error-cause condition, which uses that condition and constructed the pattern vector space which consists of the input pattern vectors that cause the classification errors and learned these pattern vectors , and improved performance of the pattern classification. To prove the performance of the proposed learning algorithm, the simulation is performed by using training vectors and test vectors that are Fisher' Iris data and EMG data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.53-62
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• 2010

This paper introduces a classification algorithm which can be applied to a learning problem with incomplete data sets, missing variable values or a class value. This algorithm uses a data expansion method which utilizes weighted values and probability techniques. It operates by extending a classifier which are considered to be in the optimal projection plane based on Fisher's formula. To do this, some equations are derived from the procedure to be applied to the data expansion. To evaluate the performance of the proposed algorithm, results of different measurements are iteratively compared by choosing one variable in the data set and then modifying the rate of missing and non-missing values in this selected variable. And objective evaluation of data sets can be achieved by comparing, the result of a data set with non-missing variable with that of C4.5 which is a known knowledge acquisition tool in machine learning.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.33-39
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• 2004

In this paper. we design the learning algorithm of LVQ which is used Forward Counter Propagation Networks to improve classification performance of LVQ networks. The weights of Forward Counter Propagation Networks which is between input layer and cluster layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm. Finally. pattern vectors is classified into subclasses by neurons which is being in the cluster layer, and the weights of Forward Counter Propagation Networks which is between cluster layer and output layer is learned to classify the classified subclass, which is enclosed a class. Also. kr the number of classes is determined, the number of neurons which is being in the input layer, cluster layer and output layer can be determined. To prove the performance of the proposed learning algorithm. the simulation is performed by using training vectors and test vectors that ate Fisher's Iris data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.