• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.6
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• pp.1109-1123
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• 2017

This study analyzed a somatotype of teenager's that was suitable to improve the reality of a virtual model size. We analyzed 843 teenagers 12-18 years old from the 6th Size Korea data. First, factor analysis was done for abstracting new criteria and dividing the somatotype; subsequently, we selected the waist height proportion to stature (body proportion) and drop (torso shape). Next, the cluster analysis was done with these criteria; subsequently, 5 body proportion types and 7 torso shapes were distinguished. A virtual model size for 4 somatotype with more than 50 persons was also designed by a regression analysis that constituted sizes for each factor. The designed model size was compared with body size as well as with Clo's virtual model size. The research model showed a high similarity in sizes with body as well as improved reality over the Clo model that presented size problems such as low waist height, bigger bust, and smaller thigh circumference than the real body.

• Korean Journal of Environment and Ecology
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• v.31 no.1
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• pp.93-103
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• 2017

The purpose of this study is to assess the recovery rate of vegetation structure after restoration works at the damaged Nogodan area in Jirisan National Park. Fourteen monitoring plots were set up at restoring work area and twelve control plots were set up at natural forest near monitoring plots. Flora, Relative Importance Percentage and Similarity Index were analyzed. Mean Similarity Index between monitering plot and control plot near helliport area showed thirty five point two percent and height of shrub layer recovered up to twenty percent, approxomately durindg twenty three years after experimental restoration works. Mean Similarity Index between monitering plot and control plot around Nogodan peak area showed seventeen point six percent but height of shrub layer recovered up to twenty percent, approxomately during ninteen years after restoration works. Mean similarity index between monitering plot and control plot on transfered millitary area showed thirty four point three percent but coverage of shrub layer showed twenty percent,approxomately during seven years after restoration works. Long term monitering shall be necessary for developing assessment criteria of ecologial restoration and ecological restoration technology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.385-385
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• 2020

본 연구에서는 가뭄과 연관되는 다양한 관련 요인을 포함한 가뭄취약성 평가방안을 수립하고 이를 적용하는 것을 목표로 하였다. 평가기법은 평가인자와 가중치 선정, 평가자료 데이터베이스 구축, 평가자료와 가중치를 조합한 평가의 세 단계로 구성되었으며 평가인자 및 가중치 선정에는 Delphi 조사기법을 적용하고 평가기법으로는 최근 널리 적용되고 있는 MCDM (Multi-Criteria Decision Making) 방법인 TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) 기법을 활용하였다. 평가인자는 기상분야(Meteorological factors), 농업분야(Agricultural factors), 사회경제분야(Socioeconomic factors), 환경분야(Natural System)로 구성하였으며 선정된 인자에 대한 데이터베이스를 구성하기 위하여 기상청, 농어촌공사, 수자원공사 등의 관계기관이 관리하는 자료를 수집하였다. 수립한 가뭄취약성 평가방안을 2016년 3월부터 2019년 9월까지 우리나라 시군구 행정구역 단위, 총 167개 지역이며 순위법, 비율법, fuzzy 등 가중치 선정방법에 따라 결과에 약간의 차이가 나타난다. 가뭄예보결과와 취약성 평가결과를 비교해 보면 충청남도 홍성군이 동기간 동안 가뭄예경보 발령 횟수가 가장 많았으며, 충청남도 보령시와 서산시도 매우 높은 빈도로 확인되었다. 평가 결과, 충청북도, 경상남도, 전라남도에 가뭄 취약지역이 다수 도출 되어 이들 지역에 대한 가뭄 대응 방안 수립이 필요한 것으로 분석되었다.

• Korean Institute of Interior Design Journal
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• v.19 no.4
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• pp.3-10
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• 2010

The purpose of this study is to select and analyze words that represent various emotional states towards a spatial environment. Selecting appropriate words for the sensibility evaluation of a spatial environment is a process of constructing sensibility indicators, so that an accurate selection of sensibility words is very important. To collect basic words for this study, words for expressing sensation, emotional states, and sensibility regarding a spatial environment have been collected first via free association and a literature review of previous studies. In the second stage, the selected words are refined. Fifteen evaluators have participated in the first process of refining words, 140 college students participated in the second process, and than the final list of 277 refined words has been selected. During the third stage, 15 specialists were asked to evaluate the appropriateness of sensibility evaluation words, for that 7 point-scale has been applied. Then, 99 words with an average point of 4.55 or more and a standard deviation of 1.55 or lower were selected. After investigating the similarity in the meanings of the selected words, 55 pairs of contrasting words have been selected as a final list of sensibility evaluation words. During this last stage, 307 college students majoring in related fields were asked to evaluate the appropriateness of sensibility evaluation words for a spatial environment, and 7 point-scale was obtained. A factor analysis, cluster analysis, and multidimensional analysis have been conducted on the data obtained from these survey. According to the results of the factor analysis, the eight important factors are obtained from the sensibility evaluation criteria of a spatial environment(form, texture, function, value, comfort, aesthetics, atmosphere, and affinity). The factors obtained from this study can be used in the beginning stage of evaluating the sensibility factors of a spatial environment. In addition, the results of this study can be used as basic data when constructing a list of evaluation indicators to select various complex sensibility words for a space; or as general indicators when evaluating various spatial design factors.

• Fire Science and Engineering
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• v.28 no.3
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• pp.62-71
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• 2014

The importance of the firefighting education & Training is being magnified in order to enhance and strengthen a firefighters' ability and to reduce the firefighters' fatality and casualty. Therefore, It is needed to expand the facilities. In this study, with a comparative analysis of the global firefighting education & training facilities for fire suppression, we try to present the necessity and the basic contents of the establishing the installation criteria for the domestic firefighting education & training facilities. It has to contain specific purpose of the training and minimum standards for the structures with a guarantee of an international level. Naturally, the top priority is a safety of trainees and trainers. And, it should pay attention to a higher effectivity of the training course with a active reflection of the standard operation procedures' scenarios. Simultaneously, by securing a similarity and a compatibility to the other standards, it must maintain the balance of a whole standard.

• International Journal of Highway Engineering
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• v.17 no.4
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• pp.135-141
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• 2015

PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.253-258
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.340-342
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• 2004

In this paper, we introduce a new category of fuzzy inference systems baled on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of information with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.343-345
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• 2004

We propose a new category of fuzzy set-based fuzzy inference systems based on data granulation related to fuzzy space division for each variables. Data granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of data with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. Numerical example is included to evaluate the performance of the proposed model.