• Journal of Plant Biology
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• v.27 no.2
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• pp.61-72
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• 1984

The concept of natural grouping of plant designated as the "Amentiferous" is no longer given serious credence, and many of the families included in this grouping have been dispersed in diverse order. Because a review of taxonomic treatments of amentiferous taxa reveals diverse classifications, it has become necessary to investigate new characteristics and attempt to determine the significance of these characteristics in terms of amentiferous taxonomy. Protein analyses by isoelectrofocusing(IEF) and rocket immunoelectrophoresis(RIE) have proved to be useful in the delicitation of Quercus taxa using pollen extracts from selected taxa. When Quercus pollen extracts were separated by electrophoresis based on their isoelectric points in a stable pH gradient and substrates for estrase activity were stained, ten bands were revealed between pH 5-14. Within Lepidobalanus grouping, a great diversity in the pollen protein zymograms was observed with some segregation corresponding to the designated taxonomic sections. Two taxa of Cyclobalanopsis produced a zymogram that is somewhat similar to taxa included within the section Prinus of Lepidobalanus, and less similar to taxa within the section Cerris of the same subgenus. Three tested taxa of the Cerris are in the similar zymogram each other, being segregable from the taxa of Prinus. Quantitative and qualitative analyses for serological relationships within and among th Quercus were also employed. To calculate the degree of protein similarity, total rocket heights obtained from RIE provided an index of serological correspondence(SC). It is reconfirmed that the Quercus is distantly separated from the Fagus according to SC. Comparative data from rocket number and SC in the tested taxa of Quercus also indicate that Lepidobalanus is separable from Cyclobalanopsis. Within the Lepidobalanus Q. acutissima and Q. acutissima x variabilis are almost homogeneors and distinguishable from the other tested taxa of same subgenus. Although the number of taxa tested has been limited, the overall serological evidence best reflects the classification proposed by Redher(1940) and Melchior (1964), having the genus Quercus subdivided into three subgunera: Erythrobalanus, Lepidobalanus, and Cyclobalanopsis.alanopsis.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.725-736
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• 2003

To provide the information needed to make a decision, it is important to know the relationship or pattern between variables in database. Grouping objects which have similar characteristics of pattern is called as cluster analysis, one of data mining techniques. In this study, it is compared with several partitioning clustering algorithms, based on the statistical distance or total variance in each cluster.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.145-156
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• 1998

In a classical clustering problem, grouping is done on the basis of similarities or distances (dissimilarities) among the elements. Therefore, the objective is to minimize the variance within each group while maximizing the between-group variance among all groups. In this paper, however, a new class of clustering problem is introduced. We call this a laydown grouping problem (LGP). In LGP, the objective is to minimize both the within-group and between-group variances. Furthermore, the problem is expanded to a multi-dimensional case where the two-way minimization process must be considered for each dimension simultaneously for all measurement characteristics. At first, the problem is assessed by analyzing its variance structures and their complexities by conjecturing that LGP is NP-complete. Then, the simulated annealing (SA) algorithm is applied and the results are compared against that from others.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Korean Institute of Interior Design Journal
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• v.14 no.3 s.50
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• pp.208-215
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• 2005

The purpose of this study is to analyze the relationship between the personality type and the residential evaluation & remodeling preference. The subjects of this investigation were collected through questionnaire from two hundred and twelve adult residents who live in Seoul, Korea. The collected cases are analyzed by using statistics software spss-win. The personality is classified eight types; E(extraversion), I(introversion), S(sensing), N(intuition), T(thinking), F(feeling), J(judging) and P(perceiving) in MBTI (Myers Briggs Type Indicator). By using the rotated component matrix of varimax method, the satisfaction of the actual residential conditions is classified into seven grouping factors. The preference of interior image is classified into thirteen factors. The important living patterns - activity, interest, and opinion - are classified into ten factors. And the important needs of residential remodeling are classified into twelve factors. By using the one way anova method, between these forty two grouping factors and personality type MBTI, there are analyzed several significances that will be useful in residential design and remodeling design & planning

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.90-99
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• 1992

In this paper, we propose a neural network model for speech recognition. The model consists of feature extraction parts and recognition parts. The interconnection model based on ${\Delta}^2$G operator was used for frequency analysis. Two features, global feature and local feature, were extracted from this model. Recognition parts consist of global grouping stage and local grouping stage. When the input pattern was coded by slope method, the recognition rate of speakers, A and B, was 100%. When the test was performed with the data of 9 speakers, the recognition rate of 91.4% was obtained.

• Journal of the Daesoon Academy of Sciences
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• v.20
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• pp.25-66
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• 2009

This paper checked the trend of exiting researches on Jeungsan's thought and investigated the academic problems of Daesun's thought as an basic work to form the deep academic discussions on Daesun's thought. Grouping into the scriptures of Jeungsangyo, its theses and papers, I synthesized the present state of researches. In the case of papers, I divided into three periods, before 1990, 1990s' and after 2000. Grouping into three fields, the periods, the researchers and the themes, I investigated the characteristics of the researches of Jeungsan's thought through the main scriptures, theses and papers, and reports of actual state. In conclusion, I brought up the ten problems about academic questions of Daesun's thought.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1969-1976
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then, a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs in other groups. The neural network model with back propagation algorithm is used, and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines for the design of environmentally conscious products in conceptual design phase.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.380-390
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• 2015

In this study, the major 38 tributaries in Nakdong River were monitored for flow rate and water quality in order to understand the characteristics of the watershed and to find improvement plan. The flow rate and water quality for each target tributary were evaluated based on the monitoring data in 2013~2014 using a statistical package SPSS-22.0. In addition, the tributary grouping method was conducted using a $BOD_5$ concentration/flowrate and TP concentration/flowrate monitoring data. The average values of $BOD_5$, $COD_{Mn}$, TP and TOC concentrations in Gumicheon, Gyeonghocheon, Jincheoncheon, Gisegokcheon, Yonghacheon and Yonghocheon located at Nakdong Waegwan and Nakdong Goryung watershed were high and in the grade of III or IV (5~8 mg/L). The Pearson correlation coefficients of TOC with $BOD_5$, $COD_{Mn}$, and TP were greater (r=0.8, p<0.01) than those of the other water quality parameters (12 species). The tributaries with high values of water quality parameters ($BOD_5$ > 3.0 mg/L, TP > 0.1 mg/L) and flowrate (Q > $0.1m^3/sec$) were selected for improving water quality according to the stream grouping method. Five tributaries (Gumicheon, Gisegokcheon, Yonghacheon, Yeongsancheon, Mijeoncheon and Yonghocheon) were classified as Group I, which require polices and plans for water quality improvement.