• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.53-60
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• 2004

This paper is the study for the automatic pulse-power diagnostic system to discriminate the four constitutions with the piezo-sensor module and digital signal processing hardware attached on the patient arm-neck and the statistical decision software instead of the fingers and intelligence of a traditional korean doctor. This system can be used as a important medical equipment because this automatically diagnostic system has shown the excellent performance of the 65∼76% correctness against the 50∼66% correctness which the general korean doctors with knowledge and experiences have shown. Additionally, this paper has discussed the excellent characteristics of the automatic discrimination algorithm of the four constitutions.

• International Journal of Costume and Fashion
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• v.8 no.1
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• pp.53-64
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• 2008

This study defined luxury hanbok, categorized its consumers according to their lifestyles, and examined the differences between the lifestyle groups in preferred images of luxury hanbok and consumer habits. The subjects of the study were 216 luxury hanbok consumers resident in Seoul. The various types of statistical analyses used in this study were frequency, factor analysis, Cronbach's a, cluster analysis, ANOVA, Duncan-test and $X^2$-test. The results of this study were as follows: 1. The lifestyle of luxury hanbok consumers was classified broadly into 4 groups as: brand oriented, economic/appearance oriented, family oriented/socially oriented, self-driven/economic oriented. 2. The preferred images included these five factors: splendor, elegance, uniqueness, simplicity and tradition. The elegant image was aspired to by the brand oriented group. Meanwhile, the traditional image is sought after by both the brand oriented group and the economic/appearance oriented group. 3. The lifestyle groups differed significantly in the selection criterion such as material, brand and rarity. The brand oriented group placed greater importance on material, brand and rarity than other groups. 4. In addition, each group differed in their frequency of purchase, price range, and demographic characteristics.

• The Journal of Korean Medicine
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• v.30 no.6
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• pp.103-111
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• 2009

Objectives: To investigate the possibility of GamiSamgieum (SGMX) as a combination therapy with statins on hyperlipidemia using an animal model. Methods: Forty eight ICR mice (male) were divided into six groups of eight mice each: naive, induced, Lipitor 5 mg/kg, Lipitor 5 mg/kg plus SGMX 100 mg/kg, Lipitor 10 mg/kg, and Lipitor 10 mg/kg plus SGMX mg/kg treatment group. Hyperlipidemia was induced by feeding a purified high fat diet for all groups (except naive) along with treatment of drugs for 6 weeks, and then biological parameters were examined on the last experiential day. Results: Lipitor treatment lowered total cholesterol and increased HDL-cholesterol compared to the induced group with no statistical significance. However, co-treatment of SGMX with Lipitor revealed synergic effects on total cholesterol and HDL-cholesterol significantly (P < 0.05) in both. SGMX co-treatment also significantly protected liver tissues from the oxidative stress in liver tissues (P < 0.05) and augmented inhibitory effect of Lipitor against fat accumulation in the body. Conclusion: These results indicate the possibility of that SGMX can be used for patients having hyperlipidemia as a combination therapy with statin drugs.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.34-43
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• 2006

This paper shows modeling methods for VBR video trace. It is well known that VBR video trace is characterized as longterm correlated and highly intermittent burst data. To analyze this, we attempt to model it using neural network with auxiliary linear structures derived from residual threshold. For testing purpose, we generate VBR video trace from chaotic nonlinear function combined with the geometric random noise. The modeling result of the generated data shows that the attempted method represents more accurately than the traditional neural network. However, we also found that combining hRU to the attempted modeling method can yield a closer agreement to statistical features of the generated data than the attempted modeling method alone.

• Korean Management Science Review
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• v.19 no.1
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• pp.75-88
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• 2002

In recent years, it Is necessary to develop an alternative measure, the time efficiency of management activities, as a more measurable and operational tool Instead of traditional accounting measures such as inventories turnover. Therefore the concept of throughput time has got much attention as useful tool for controlling time based management. The purpose of this paper is to investigate the usefulness and adaptability of throughput time. The sample consists of 212 non-banking firms listed on the Korean Stock Exchange. The test Period were 10 years(1989-1998). The regression analysis for this study was performed using the cross-sectional data for the sample, and it was also performed for each Industry. The results show that net Income to tonal assets and labor productivity (value added Per employee) variables in the model was signiflcantly associated with throughput time. On the other hand, the relationship between throughput time and logistics cost to sales do largely not have statistical significance. Especially, it is found that the relationship do not have significance or negative response in food & beverage industry and wholesale & retail industry. In summary, the results show that the measure of throughput time can be an effective managerial Indicator for time based competition and management.

• Proceedings of the Microbiological Society of Korea Conference
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• 2002.10a
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• pp.22-26
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• 2002

There are a number of ways in which environmental microbiology and microbial ecology will benefit from DNA micro array technology. These include community genome arrays, SSU rDNA arrays, environmental functional gene arrays, population biology arrays, and there are clearly more different applications of microarray technology that can be applied to relevant problems in environmental microbiology. Two types of the applications, bacterial identification chip and functional gene detection chip, will be presented. For the bacterial identification chip, a new approach employing random genome fragments that eliminates the disadvantages of traditional DNA-DNA hybridization is proposed to identify and type bacteria based on genomic DNA-DNA similarity. Bacterial genomes are fragmented randomly, and representative fragments are spotted on a glass slide and then hybridized to test genomes. Resulting hybridization profiles are used in statistical procedures to identify test strains. Second, the direct binding version of microarray with a different array design and hybridization scheme is proposed to quantify target genes in environmental samples. Reference DNA was employed to normalize variations in spot size and hybridization. The approach for designing quantitative microarrays and the inferred equation from this study provide a simple and convenient way to estimate the target gene concentration from the hybridization signal ratio.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.256-261
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• 2014

The problem of top-${\kappa}$ set similarity joins finds the top-${\kappa}$ pairs of records ranked by their similarities between two sets of input records. We propose an efficient algorithm to return top-${\kappa}$ similarity join pairs using a sampling technique. From a sample of the input records, we construct a histogram of set similarity joins, and then compute an estimated similarity threshold in the histogram for top-${\kappa}$ join pairs within the error bound of 95% confidence level based on statistical inference. Finally, the estimated threshold is applied to the traditional similarity join algorithm which uses the min-heap structure to get top-${\kappa}$ similarity joins. The experimental results show the good performance of the proposed algorithm on large real datasets.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.14 no.1
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• pp.1-8
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• 2008

New concepts and solutions for the Flexible Food Packaging Design have been demanded to meet the various customer's needs and to compete with other worldwide products. Future-oriented designs beyond the basic functions of preserving and protecting contents can only meet the demands on product's reliability and consumer's satisfaction, specially considering environmental issues. This study is to describe the spiritual values of Korean Flexible Food Packaging Design on the basis of comprehensive understanding and to identify the process of changes and developments. The thesis also forecasts the future of Flexible Food Packaging. Little progress in the Flexible Food Packaging has been made because of the slow response, only to meet the increasing demand without any statistical or theoretical study. On the contrary, Korean Flexible Food Packaging Design has been developed by imitating foreigners' and made mistake of not creating original design reflecting a native traditional culture. This study researches the roles of food-classified flexible packaging to predict the near future trend of packaging industry classifying those into functional, visual, environmental and industrial aspects.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.137-146
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• 2005

Neural network is one of the most notable technique. It usually provides more powerful forecasting models than the traditional time series techniques. Employing the Ensemble technique in forecasting model, one should provide a initial distribution. Usually the uniform distribution is assumed so that the initialization is noninformative. However, it would be expected a sequential informative initialization based on data rather than the uniform initialization gives further reduction in forecasting error. In this note, a modified Ensemble algorithm using sequential initial probability is developed. The sequential distribution is designed to have much weight on the recent data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.286-289
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• 2007

This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.