• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1037-1040
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• 1988

In this study, we performed the recognition test on Korean vowel using peripheral auditory model. In addition, for the purpose of objective comparision, the recognition test is performed by extracting LPC cepstrum coefficients from the same data. And the same speech data are mixed with the Guaussian white noise quantitatively, then we repeated the same test, too. So we verified that this auditory model has a adaptability on noise.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.37-37
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• 2006

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.515-520
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• 2002

In general, we use the hierarchical Poisson-gamma model for the Poisson data in generalized linear model. Time effect will be emphasized for the analysis of the observed data to be collected annually for the time period. An extended model with time effect for estimating the effect is proposed. In particularly, we discuss the Quasi likelihood function which is used to numerical approximation for the likelihood function of the parameter.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1560-1563
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of support vector machine neural networks model (SVM-NNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of SVM-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1346-1349
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• 2010

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.423-430
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• 2000

Future microcellular systems will require distributed network control. A packet-switched network is suitable for this requirement. The packet reservation multiple access(PRMA) is a Reservation-ALOHA like protocol for wireless terminals to transmit packet speech to a base station. It allows spatially distributed users in cellular systems to transmit packeted voice and data to a common base station using a shared channel. In the existing PRMA, the problem is that the voice packets may collide with the data packets due to simultaneous channel access. the problem may be a major performance degradation factor to a voice and data mixed system. We propose a new PRMA method that integrates voice and data traffic efficiently by resolving the collision problem between data and voice packets. The proposed PRMA method gives a performance improvement than the existing PRAMA method in terms of voice packet dropping probability and data delay characteristic. From analytic results, we can confirm that the proposed PRMA method show a performance improvement than the existing PRMA protocol.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.335-348
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• 2005

The rapid development of microarray technologies enabled the monitoring of expression levels of thousands of genes simultaneously. Recently, the time course gene expression data are often measured to study dynamic biological systems and gene regulatory networks. For the data, biologists are attempting to group genes based on the temporal pattern of their expression levels. We apply the consensus clustering algorithm to a time course gene expression data in order to infer statistically meaningful information from the measurements. We evaluate each of consensus clustering and existing clustering methods with various validation measures. In this paper, we consider hierarchical clustering and Diana of existing methods, and consensus clustering with hierarchical clustering, Diana and mixed hierachical and Diana methods and evaluate their performances on a real micro array data set and two simulated data sets.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.303-310
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• 2013

Forty two female students whose fat mass ratio was over 30% were participated in the experiment of fat mass loss of two treatments for 8 weeks. They kept diary for foods they ate every day, took a picture of the foods, transmitted the picture to the experimenter by the camera phone. Among those, 28 students took the picture by regular camera phone (Treatment A), and the other students used smart phone (Treatment B). Fat mass weight and its related variables had been measured repeatedly four times at an interval of two weeks during 8 weeks. It was shown from mixed model analysis of repeated measurements data that AR(1) covariance matrix was selected as the optimal covariance matrix pattern. The correlation between two successive times is highly correlated as 0.838. Based upon the AR(1) covariance matrix structure, the students using smart phones were somewhat more effective in losing fat mass weight than the students using regular camera phones. The time effect was highly significant, but the treatment-time interaction effect was insignificant. The baseline effect and total cholesterol were found to be significant, but the calories with taking foods were somewhat significant, but the waist to hip ratio was found to be insignificant.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.287-297
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• 2016

This research paper is of a 'mixed method' research design: the quantitative analysis covering general data and the current condition of male nurses, the qualitative analysis being used on interview transcript data. The research subjects are 19 male nurses who work at a hospital and 29 female nurses who are doing Masters degrees in "J" province of the Republic of Korea. The data collection period was March 25 to April 1, 2015. The quantitative data was analyzed with SPSS WIN 19.0 software while the qualitative data was analyzed according to the 'contents analysis' method. The results show that the satisfaction of male participants in their profession is higher than average. The item 'growth as a professional' was rated highest as a satisfying aspect of working as a nurse. A difference was observed in the points of view of male and female participants, however, both male and female nurses have a positive view of male nurses which over comes traditional stereotypes. These results will be used to establish a positive image of nurses across genders.