• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.45-61
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• 2017

The objective of this study is to understand the application of relative location system and minute classification system in the DDC and to identify the effect of the relative location system and minute classification system during the late of 19th century. In order to achieve the objective, four main investigation areas were chosen: relative location system, minute classification system, and DDC influence to other libraries and classification systems. First, DDC applied a relative location system revolutionarily instead of a fixed location system for arranging books on the shelves, so it opened the period of modern library classification systems. Second, it used a minute classification system, and could classify books which had minute subjects. Third, it applied form to a criterion for dividing divisions and sections, so it helped for classifying books. Fourth, it used a numerical decimal system as a classification system, then people could use it economically and practically. Last, DDC influenced modern classification system such as the Expansive Classification and the Subject Classification etc. DDC is a suitable library classification system for the needs of the times, and it is a practical classification system for each library.

• Fashion & Textile Research Journal
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• v.6 no.3
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• pp.285-296
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• 2004

Fashion business must reflect the seasonable fashion trend because fashion has change always, and therefore fashion business has a big risk at the attribute. Careful consideration should be given to the selection of a particular color code to meet the purpose of marketing research in various color products. It must be designed to grasp systematically and comprehensively the current trend of colors. The most suitable color code for meeting this proposition would be one based on the designation by color ranges. The ISCC-NBS method of designating colors, published in 1955, was established by dividing the color solid into 267 color name blocks. The detailed classification like the ISCC-NBS system is very appropriate to serve the purpose of giving all color names according to color ranges. But it is somewhat too complicated to answer the purpose of surveying the trend of colors and of comparing and evaluating the ups and downs in the popularity of the range of each individual color. I have worked out the most convenient method of designating colors in accordance with the type of investigation needed. It is the classification which involves four classification system in itself, fundamental, gross, medium, and minute. The fundamental classification system classifies hues and neutrals into 16ranges. The gross classification system divides the above 16 ranges into 30. The medium classification divides the above 30 ranges into 103 in terms of tones. The minute classification divides the above 103 ranges into 207 in terms of specipic hues.

• Journal of Korean Biological Nursing Science
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• v.16 no.4
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• pp.342-348
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• 2014

Purpose: The purpose of this study was to examine the effects of pressure ulcer classification system education on hospital nurses' knowledge and visual discrimination ability of pressure ulcer classification system and incontinence-associated dermatitis. Methods: One group pre- and post-test was used. A convenience sample of 96 nurses participating in pressure ulcer classification system education, were enrolled in single institute. The education program was composed of a 50-minute lecture on pressure ulcer classification system and case-studies. The pressure ulcer classification system and incontinence-associated dermatitis knowledge test and visual discrimination tool, consisting of 21 photographs including clinical information were used. Paired t-test was performed using SPSS/WIN 18.0. Results: The overall mean difference of pressure ulcer classification system knowledge (t=4.67, p<.001) and visual discrimination ability (t=10.58, p<.001) were statistically and significantly increased after pressure ulcer classification system education. Conclusion: Overall understanding of pressure ulcer classification system and incontinence-associated dermatitis after pressure ulcer classification system education was increased, but tended to have lack of visual discrimination ability regarding stage III, suspected deep tissue injury. Differentiated continuing education based on clinical practice is needed to improve knowledge and visual discrimination ability for pressure ulcer classification system, and comparison experiment research is required to evaluate its effects.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.33-38
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• 2020

Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.396-408
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• 1996

The purposes of this study were to standardise the forest working system to design the intensity of working system in felling operation of the thinning forest in our country as well as to contrive the improvement of working method and the increase of productivity. For the purpose of investigating these, element working was classified by felling operation in softwood thinning forest, and a pulse rate were measured and analyzed. The results were as follow : 1. From the analysis of the pulse frequence measurment, the average pulse showed 108 pulse per minute for worker A in the total of pure working time, 130 pulse per minutes for worker B, 119 pulse per minute for worker C and 125 pulse per minute for worker D, respectively. 2. From the results of the pulse frequence analysis according to element working classification, the highest pulse frequence represented 115 pulse per minute for worker A in the circumference, 131 pulse per minute for worker B in the movement, 122 pulse per minute for worker C in the limbing operation and 128 pulse per minute for work D in hang-up. 3. If the original pulse frequence was 100% for workers, the working intensity showed as follow : worker A was 160%(original pulse frequence was 61=100%) for the total of the working intensity and 188% for the circumference among element working. Worker B was 220%(original pulse frequence was 57=100%) for the total of the working intensity and 229 for movement among element working. Worker C was 159%(original pulse frequence was 73=100%) for the total of the working intensity and 168% for limbing operation among the element working. Worker D was 156%(original pulse frequence was 70=100%) for the total of working intensity and 182% for hang-up among element working. 4. At the limit point of Labor performance rating, showing the total of working intensity, overtime pulse rate per minute was 30 for worker A, 207 for worker B, 14 for worker C and 67 for worker D. Worker B was highest in working intensity, and got physically a big load.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.6
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• pp.319-331
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• 2016

This study explores the signal characteristics for different averaging intervals and defines representative verticies for each observatory by criterion of percent rate and variance. The shorter averaging interval shows the higher frequency variation, though the lower percent rate. In the tidal currents, we could hardly find the differences between 60-minute and 20-minute averaging. The newly defined criterion improves reliability of HF-radar data compared with the present reference which deselects the half by percent rate.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.1910-1915
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• 2008

The load analysis for the distribution system and facilities has relied on measurement equipment. Moreover, load monitoring incurs huge costs in terms of installation and maintenance. This paper presents a new model to analyze wherein facilities load under a feeder every 15 minutes using meter reading data that can be obtained from a power consumer every 15 minute or a month even without setting up any measuring equipment. After the data warehouse is constructed by interfacing the legacy system required for the load calculation, the relationship between the distribution system and the power consumer is established. Once the load pattern is forecasted by applying clustering and classification algorithm of temporal data mining techniques for the power customer who is not involved in Automatic Meter Reading(AMR), a single-line diagram per feeder is created, and power flow calculation is executed. The calculation result is analyzed using various temporal and spatial analysis methods such as Internet Geographic Information System(GIS), single-line diagram, and Online Analytical Processing (OLAP).