• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.11-21
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• 2014

The purpose of this study was to furnish basic information for forest community ecology and to accumulate vegetational datum related to hierarchy of forest community for the efficient management of forest vegetation in Mt. Mani. Samples were collected and analyzed by 32 releves from August to October in 2010 using phytosociological analysis methodology of Z-M school and importance value analysis. The results were summarized that the forest vegetation was classified into 5 units in total. Importance value at vegetation unit 1 indicated Pinus densiflora 54.31 (18.10%), Quercus mongolica 39.21 (13.07%), Carpinus coreana 37.29 (12.43%), at vegetation unit 2 Quercus mongolica 89.43 (22.23%), Rhododendron mucronulatum 57.75 (14.43%), Carpinus coreana 47.19(11.80%), at vegetation unit 3 Styrax japonica 53.97 (13.50%), Acer mono 33.60 (8.40%), Carpinus coreana 26.48 (6.62%), Quercus serrata 22.51 (5.64%), at vegetation unit 4 Carpinus coreana 47.70 (11.92%), Quercus acutissima 38.40 (9.60%) and at vegetation unit 5 Evodia daniellii 80.59 (20.14%), Robinia pseudoacacia 35.00 (8.74%), Pueraria thunbergiana 28.63 (7.15%), Quercus dentata 28.20 (7.05%) in the order, respectively.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.1
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• pp.1-22
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• 2023

This study proposes an integrated use of region and industry as a way to classify firms' innovation activities by type. Existing studies have used the method of determining innovative activities according to the components of the technological regimes and aggregating them by industry classification, but this method cannot fully reflect the heterogeneity within industries in an increasingly sophisticated innovation environment. Therefore, this study divides firms by region and industry and conducts a cluster analysis on the proportion of innovative activities by the components of the technological regimes to derive a total of four innovation types. Using the 2016 Korean Innovation Survey to classify innovation types in the manufacturing industry, we found that innovation activities are concentrated in Seoul, Busan, Incheon, and Chungnam/ Sejong/ Daejeon area, with different deviations by region and industry. The results of the aggregation of industrial innovation activities, weighted by corporate activity by region, show that the level of innovation activity in some manufacturing industries, such as petrochemicals, manufacturing of medical, precision and optical instruments, watches and clocks, is high, but the level of innovation in other sectors within the manufacturing industry is generally low.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5097-5104
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• 2013

To derive implication for marketing strategy for Korean cosmetic products in China, an analysis was conducted on the difference in quality perception and purchase behavior between two groups of Chinese women classified by their awareness of Korean Wave. Analytical methods including k-means clustering method, independent samples t-test, factor analysis were applied on the survey results of Chinese women residing in Guangzhou city. The positive impact of Korean Wave on quality perception and brand image is much stronger for higher awareness group, compared against for lower awareness group, that leads to higher product satisfaction and willingness to recommend purchases. Thus, marketing strategies need to be adjusted based on the difference in customers awareness of Korean Wave. However, the low price is the primary inducement for purchases for both groups, increased efforts to enhance brand image and product quality as premium products is strongly required, together with the utilization of Koran Wave.

• The Journal of Korean Medicine
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• v.17 no.2 s.32
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• pp.337-393
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• 1996

The purpose of this study is to evaluate and standardize the four scales of Questionnaire for the Sasang Constitution Classification 　II (QSCCII). QSCCII is newly prepared by statistical item analysis and is designed to examine its diagnostic discriminability. QSCCII is administered to 1366 random informants. From the survey, we could get the data for the standardization. The criteria of standardization are based on the data from 265 informants who are examined by professionals. Collectted data are analyzed by internal consistency, variation analysis(ANOVA), Duncan test and discrimination analysis of SPSS PC+ V4.0 program. The results are as follows reliability of four scales for QSCCII is relatively valid. The internal consistency of Tae-yang(太陽) (太陽) scale is Cronbach's a=0.5708. That of So-yang(少陽) scale is a=0.5708. That of Tae-eum(太陰) scale is a =0.5922. That of So-eum(少陰) scale is a=0.6319. 2. There is a significant difference between each group through variation analysis of four scales. 3. The process of standardization is based on the average value and standard deviation with respect to age and sex difference of each criteria 4. This study suggests a source of standardization of Sasang Constitution Classification by providing norms in which the differences of age, sex, and number of items are taken into deep consideration. QSCC Ⅱ, therefore, can be applied to every age(the 10's to the 60's) and sex groups. 5. The recalculation of the raw-score to standard value (T-score) shows that the diagnostic discriminability (Hit-ratio: 70.08%) of QSCC Ⅱ brings about 37% improvement than proportional chance criteria (33.33%). Especially, Hit-ratios of Tae-eum In(74.5%) and So-eum In(70.8%) are higher than that of So-yang In(60.0%). 6. QSCC has discriminability only to male informants. Compared with QSCC, however, QSCC II has relatively efficient discriminability both to male and female informants. 7. These results would be a demonstration of the fact that the QSCC II could be used as a tool for sasang constitution classification.

• Journal of Sasang Constitutional Medicine
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• v.8 no.1
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• pp.187-246
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• 1996

The purpose of this study is to evaluate and standardize the four scales of Questionnaire for the Sasang Constitution ClassificationII (QSCCII). QSCCII is newly prepared by statistical item analysis and is designed to examine its diagnostic discriminability. QSCCII is administered to 1366 random informants. From the survey, we could get the data for the standardization. The criteria of standardization are based on the data from 265 informants who are examined by professionals. Collected data are analyzed by internal consistency, variation analysis(ANOVA), Duncan test and discrimination analysis of SPSS PC+ V4.0 program. The results are as follows 1) The reliability of four scales for QSCCII is relatively valid. The internal consistency of Tae-yang(太陽) scale is Cronbach's ${\alpha}=0.5708$. That of So-yang(少陽) scale is ${\alpha}=0.5708$. That of Tae-eum(太陰) scale is ${\alpha}=0.5922$. That of So-eum(少陰) scale is ${\alpha}=0.6319$. 2) There is a significant difference between each group through variation analysis of four scales. 3) The process of standardization is based on the average value and standard deviation with respect to age and sex difference of each criteria. 4) This study suggests a source of standardization of Sasang Constitution Classification by providing norms in which the differences of age, sex, and number of items are taken into deep consideration. QSCCII, therefore, can be applied to every age(the 10's to the 60's) and sex groups. 5) The recalculation of the raw-score to standard value (T-score) shows that the diagnostic discriminability (Hit-ratio : 70.08%) of QSCCII brings about 37% improvement than proportional chance criteria(33.33%). Especially, Hit-ratios of Tae-eum In(74.5%) and So-eum In(70.8%) are higher than that of So-yang In(60.0%). 6) QSCC has discriminability only to male informants. Compared with QSCC, however, QSCCII has relatively efficient discriminability both to male and female informants. 7) These results would be a demonstration of the fact that the QSCCII could be used as a tool for sasang constitution classification.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Journal of Korean Society of Forest Science
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• v.106 no.3
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• pp.275-287
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• 2017

The purpose of this study was to analyze forest vegetation type classification and relationships between the type and environment factor in Mt. Dutasan. Data were collected by total of forty six plots using Z-M phytosociological method from June to October, 2016, and analyzed by vegetation classification, canopy layer structure and relationships between vegetation unit and environment factor using coincidence methods. As a result of vegetation type classification, Quercus mongolica community group was classified at a top level of vegetation hierarchy that was classified into Rhododendron schlippenbachii community and Betula costata community. R. schlippenbachii community was divided into Lychnis cognata group and R. schlippenbachii typical group. L. cognata group was subdivided into Veratrum oxysepalum subgroup and L. cognata typical subgroup. B. costata community was divided into Fraxinus mandshurica group and Betula schmidtii group. F. mandshurica group was subdivided into Weigela subsessilis subgroup and Cimicifuga heracleifolia subgroup. Therefore the forest vegetation was composed of six vegetation units with two kinds of bisected species groups and fourteen species groups. As the result of an analysis of canopy layer structure, there were two kinds of structures with monotonous structures V. oxysepalum subgroup (vegetation units 1), L. cognata typical subgroup (vegetation units 2), W. subsessilis subgroup (vegetation units 4) and complicated structures R. schlippenbachii typical group (vegetation units 3), C. heracleifolia subgroup (vegetation units 5), Betula schmidtii group (vegetation units 6). The vertical layer structure of vegetation unit 5 was the most developed and vegetation unit 6 had the lowest coverage of herb layer. According to the correlation between vegetation unit and environmental factor, R. schlippenbachii community (vegetation units 1~3) and B. costata community (vegetation units 4~6) were classified based on 1,100 m of altitude, middle slope, twenty of slope degree, twenty percents of bare rock and thirty centimeters of DBH in tree layer. R. schlippenbachii community (vegetation units 1~3) showed positive correlation with altitude, topography and B. costata community (vegetation units 4~6) showed negative correlation tendency with them.