• International Journal of Contents
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• v.7 no.4
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• pp.108-115
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• 2011

The current study aims to analyze the acceptance of International Standard Terminology (IST) related to herbs and formulas used in Korea. It also intends to examine limitations of each term source by linking texts for herbal medicine research and formula research used in schools of oriental medicine with medicinal substance-formula classification names within the IST framework. This study examined 64 medicinal classification names of IST, including synonyms, 41 formula classification names, 65 classification names of "Herbal Medicine Study," 89 medicinal classification names of "Shin's Clinical Herbal Medicine Study," and lastly 83 formula classification names of "Formula Study." Data on their chief virtue, efficacy and characteristics as medicinal substances were extracted from their definitions, and such data were used to perform Chinese character-English mapping using the IST. The outcomes of the mapping were then analyzed in terms of both lexical matching and semantic matching. In terms of classification names for medicinal substances, "Herbal Medicine Study" had 60.0% lexical matching, whereas "Shin's Clinical Herbal Medicine Study" had 48.3% lexical matching. When semantic matching was also applied, "Herbal Medicine Study" showed a value of 87.7% and "Shin's Clinical Herbal Medicine Study" 74.2%. In terms of formula classification names, lexical matching was 28.9% of 83 subjects, and when semantic matching was also considered, the value was 30.1%. When the conceptual elements of this study were applied, some IST terms that are classified with other codes were found to be conceptually consistent, and some terms were not accepted due to different depths in the classification systems of each source.

• KIEAE Journal
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• v.9 no.4
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• pp.3-10
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• 2009

It is not an overstatement to say the factory are the number one cause in creating environmental load. However, only a few studies have been done upto this date on environmentally friendly factory. Thus, This study is to present the characteristics of environmentally friendly factory. A survey of current literatures and cases show the characteristics of environmentally friendly factories and buildings and environment assessment method and plan. To better measure the environmentally friendly qualities as written in literature across the globe, classification system was constructed. The classification system was made and important factors were found based on the precedent paper on environmentally friendly building plan and environment assessment method at building and cases and abroad in the literature review. The classification used 4 different sectors : Land & Transportation, Architectural Planning Technique, Environment & Equipment, Energy & Material. Within these 4 sectors 33 discrete factors are applied to the factory according to literature and case review and specialist advice.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.155-164
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• 2018

The temperature is a sense that can be felt by touch and sight. However, the concept of the temperature sensation is rarely used together with the concept of visual sensation and tactile sensation. In this study, the sensation of the temperature sensed through tactile and visual sense was investigated by the visual temperature depending on color and material characteristics. The textile was selected as a sample that could include color and material characteristics. The textile sample was composed of each 15-16 kinds of Yellow, Red, Blue, and Green of total 90 samples. The analytical method was to analyze first, the warm-cool of the colors of Yellow, Red, Blue, Green, and then to the visual temperature according to visual classification and tactile classification. And we investigated the correlation of the visual temperature depending on weight, thickness, and unevenness. As a result, the number of textiles felt by Cool and Warm differed according to the warm-cool of the colors feeling in the same textile. However, the visual temperature was different to each classification of textile. In particular, it was noticeable in thin, see-through and matte textiles. In relation to weight, thickness, unevenness and the visual temperature, the textile classification related to the weight is a classification of a hard, matte textile, and the textile classification related to the thickness is a thin, see-through textile.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.143-150
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• 2012

In Korea more than 38,000 types of hazardous material(HAZMAT) are distributed, accordingly the accidents during transportation are also increasing. The agencies related to HAZMAT such as Environment Ministry, National Emergency Management Agency and National Police Agency have their own regulations. However, the classification criteria of HAZMAT are different to each other, which causes many problems in response to transportation accidents. In this study the classification standard of HAZMAT and the classification code using CAS number are suggested to manage HAZMAT efficiently. Through efficient management and standard classification of HAZMAT, the rapid and systematic response to transportation accidents related to HAZMAT is expected to be possible.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• The Journal of Bigdata
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• v.4 no.2
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• pp.61-71
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• 2019

Chemical Mechanical Planarization (CMP) process that planarizes semiconductor wafer's surface by polishing is difficult to manage reliably since it is under various chemicals and physical machinery. In CMP process, Material Removal Rate (MRR) is often used for a quality indicator, and it is important to predict MRR in managing CMP process stably. In this study, we introduce prediction models using machine learning techniques of analyzing time-series sensor data collected in CMP process, and the classification models that are used to interpret process quality conditions. In addition, we find meaningful variables affecting process quality and explain process variables' conditions to keep process quality high by analyzing classification result.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.704-707
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• 1999

Partial discharge(PD) in air insulated electric power systems is responsible for considerable power lossesfrom high voltage transmission lines. PD in air often leads to deterioration of insulation by the combined action of the discharge ions bombarding the surface and the action of chemical compounds that are formed by the discharge and may give rise to interference in ommunication systems. PD can indicate incipient failure. Thus understanding and classification of PD in air is very important to discern source of PD. In this paper, we investigated PD in air by using statical method. We classified air discharge with corona, surface discharge and cavity discharge by source of discharge. we used the mean pulse-height phase distribution $H_{qmean}(\psi)$, the max pulse-height phase distribution $H_{qmax}(\psi)$ , the pulse count phase distribution $H_n(\psi)$ and the max pulse height vs. repetition rate $H_{q}(n)$ for analysis PD pattern. We used statistical operators, such as skewness(S+. S-1, kurtosis(K+, K-), mean phase(AP+. AP-), cross-correlation factor(CC) and asymmetry from the distribution.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.1
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• pp.65-73
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• 2007

Pattern classification of single and multiple discharge sources was applied using a wavelet image signal method in which a feature extraction was applied using a hidden sub-image. A feature extracting method that used vertical and horizontal images using an MSD method was applied to an averaging process for the scale of pulses for the phase. A feature extracting process for the preprocessing of the input of a neural network was performed using an inverse transformation of the horizontal, vertical, and diagonal sub-images. A back propagation algorithm in a neural network was used to classify defective signals. An algorithm for wavelet image processing was developed. In addition, the defective signal was classified using the extracted value that was quantified for the input of a neural network.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.121-139
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• 2003

Currently, it is not popular to use the STEP based product information in the construction drawing files, in spite of the importance and possibility of using various product data in drawing files on the CALS/EC environment. This paper aims to demonstrate a construction drawing information management system based on ISO 10303/STEP. To achieve this aim, the authors have analyzed the current construction drawing information classification hierarchy widely used for domestic and international, and examined the material data connection mechanism within CAD drawing data, and finally investigated the management systems for construction documentations and drawings in a public companies. Therefore, the expected benefit of the proposed system is that STEP drawing information management will be done standardization and the information of STEP construction drawing can be managed, shared and supported design business through materials data connection.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.8
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• pp.898-903
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• 2004

In this paper, neural networks is studied to apply as a PD source classification in XLPE power cable specimen. For treeing discharge sources in the specimen, three defected models are made. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.