• Korean Journal of Environment and Ecology
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• v.19 no.1
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• pp.9-18
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• 2005

We analyzed community forming patterns and forest vegetation of goldenrain tree communities in Anmyeondo, Daegu Naegokdong, Pohang Youkangri, Yanghakri, Balsanri, Daedongbaeri, Mophori and Seochonri. The vegetation data for analysis collected from 68 quadrats of 8 sites Using the Braun-Blanquet method, from April 2002 to September 2003. A total of 201 species were found and the area was covered with $30\~100\%$ of tree layer, $0\~90\%$ of shrub layer and $20\~100\%$ of herb layer. Oplismenus undulatifolius, Pueraria thunbergiana, Quercus dentata, Clematis apiifolia, Ligustrum obtusifolium, Rosa multiflora, Artemisia princeps var. orientalis, Humulus japonicus and Robinia pseudo -acacia were the species in high frequency. To analyze the community classification and ordination, we used the technique of TWINSPAN and DECORANA. The surveyed areas with 68 quadrats were divided into 3 groups by TWINSPAN and divided into 3 communities with axis 1 date volume by DECORANA.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.

• Journal of Technology Innovation
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• v.28 no.1
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• pp.31-52
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• 2020

This study was started to verify the preliminary(Ex-ante) discrimination power of the firm's high-activity using the 'Forward-looking' oriented technology appraisal model used in technology financing. The analytical firms are classified into the industry (manufacturing / non-manufacturing) and the age of company (initial / non-initial). High-activity SMEs are defined as those that achieve at least twice the average asset turnover ratio of the cluster. As a result of the discriminant model by applying C5.0 method, which is one of decision tree models, classification accuracy is more than 99% in all industries and the age of company, and it is confirmed that the discriminant power of the model is stable. As a result, the management expertise, capital involvement and funding capacity items were identified as a critical variable for the high-activity SMEs. In addition, the technology management capability and technology life cycle were also confirmed to be the items to determine high-activity SMEs in the manufacturing industry. Through this, it was possible to confirm some possibility of prior discrimination and policy utilization of high-activity SMEs by using technology appraisal items.

• Journal of Korean Society of Forest Science
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• v.25 no.1
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• pp.13-47
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• 1975

Among the many species of bamboo, it is well known that the dwarf-type is widely distributed in the tropical regions, and the slender type in temperated zone. In the temperated zone the trees have extensively differentiated into one hundred species in 50 genera. In many oriental countries, the bamboo wood is being used as a material for construction and for the manufacture of technical instruments. The bamboo shoot is also regarded as a good and delicious edible resource. Moreover, recent medical investigation verifies that the sap of certain species of the bamboo is an antibiotic effect against cancer. Fortunately, it is very easy to propagate the bamboo trees by using cutting from southeastern Asian countries. This important resource can further be used as a significant source of pulp, which is becoming increasingly important. The classification system of this significant resource has not been completely established to date, even though its importance has been emphasized. Initiated by Canlevon Linne in the 18th century, a classification method concerning the morphological characteristics of flowers was the first step in developing a classification. But it was not an easy task to accomplish, because this type of classification system is based on the sexual organs in bamboo trees. Because the bamboo has a long life cycle of 60-120 years and classification according to this method was very difficult as the materials for the classification are not abundant and some species have changed, even though many references related to the morphological classification of bamboo trees are available nowadays. So, the certification of bamboo trees according to the morphological classification system is not reasonable for us. Consequently, the classification system of bamboo trees on the basis of endomorphological characteristics was initiated by Chinese-born Liese. And classification method based on the morphological characteristics of the vascular bundle was developed by Grosser. These classification methods are fundamentally related to Holltum's classification method, which stressed the morphology of the ovary. The author investigated to re-establish a new classification method based on the vascular sheath. Twenty-six species in 11 genera which originated from Formosa where used in the study. The results obtained from the investigation were somewhat coordinated with those of Crosser. Many difficulties were found in distinguishing the species of Bambusa and Dendrocalamus. These two species were critically differentiated under the new classification system, which is based on the existence of a separated vascular bundle sheath in the bamboo. According to these results, it is recommended that Babusa divided into two groups by placing it into either subspecies or the lower categories. This recommendation is supported by the observation that the evolutional pattern of the bamboo thunk which is from outward to inward. It is also supported by the viewpoint that the fundamental hypothesis in evolution is from simple to complex. There remained many problems to be solved through more critical examination by comparing the results to those of the classification based on the sexual organs method. The author observed the figure of the cross-sectional area of vascular trunk of bamboo tree and compared the results with those of Grosser and Liese, i.e. A, $B_1$, $B_2$, C, and D groups in classification. Group A and $B_2$ were in accordance with the results of those scholars, while group D showed many differences, Grosser and Liese divided bamboo into "g" type and "h" type according to the vascular bundle type; and they included Dendrocalamus and Bambusa in Group D without considering the type of vascular bundle sheath. However, the results obtained by the author showed that Dendrocalamus and Bambusa are differentiated from each other. By considering another group, "i" identified according to the existence of separated vascular bundle sheath. Bambusa showed to have a separated vascular bundle sheath while Dendrocalamus does not have a separated vascular bundle sheath. Moreover, Bambusa showed peculiar characteristics in the figure of vascular development, i.e., one with an inward vascular bundle sheath and the other with a bivascular bundle sheath (inward and outward). In conclusion, the bamboo species used in this experiment were classified in group D, without any separated vascular bundle sheath, and in group E, with a vascular bundle sheath. Group E was divided into two groups, i.e., and group $E_1$, with bivascular sheath, and group $E_2$, with only an inward vascular sheath. Therefore, the Bambusa in group D as described by Grosser and Liese was included in group E. Dendrocalamus seemed to be the middle group between group $E_l$ and group $E_2$ under this classification system which is summarized as follows: Phyllostachys-type: Group A - Phyllostachys, Chymonobambus, Arundinaria, Pseudosasa, Pleioblastus, Yashania Pome-type: Group $B_2$ - Schizostachyum, Melocanna Hemp-type: Group D - Dendrocalamu Bambu-type: Group $E_1$ - Bambusa ghi.

• Atmosphere
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• v.17 no.2
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• pp.159-169
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• 2007

A comparison of the three land cover data sets (United States Geological Survey: USGS, International Geosphere Biosphere Programme: IGBP, and University of Maryland: UMd), derived from 1992-1993 Advanced Very High Resolution Radiometer(AVHRR) data sets, was performed over the Asian continent. Preprocesses such as the unification of map projection and land cover definition, were applied for the comparison of the three different land cover data sets. Overall, the agreement among the three land cover data sets was relatively high for the land covers which have a distinct phenology, such as urban, open shrubland, mixed forest, and bare ground (>45%). The ratios of triple agreement (TA), couple agreement (CA) and total disagreement (TD) among the three land cover data sets are 30.99%, 57.89% and 8.91%, respectively. The agreement ratio between USGS and IGBP is much greater (about 80%) than that (about 32%) between USGS and UMd (or IGBP and UMd). The main reasons for the relatively low agreement among the three land cover data sets are differences in 1) the number of land cover categories, 2) the basic input data sets used for the classification, 3) classification (or clustering) methodologies, and 4) level of preprocessing. The number of categories for the USGS, IGBP and UMd are 24, 17 and 14, respectively. USGS and IGBP used only the 12 monthly normalized difference vegetation index (NDVI), whereas UMd used the 12 monthly NDVI and other 29 auxiliary data derived from AVHRR 5 channels. USGS and IGBP used unsupervised clustering method, whereas UMd used the supervised technique, decision tree using the ground truth data derived from the high resolution Landsat data. The insufficient preprocessing in USGS and IGBP compared to the UMd resulted in the spatial discontinuity and misclassification.

• Journal of The Korean Association For Science Education
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• v.40 no.3
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• pp.321-336
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• 2020

We explore automated scoring models of scientific argumentation. We consider how a new analytical approach using a machine learning technique may enhance the understanding of spoken argumentation in the classroom. We sampled 2,605 utterances that occurred during a high school student's science class on molecular structure and classified the utterances into five argumentative elements. Next, we performed Text Preprocessing for the classified utterances. As machine learning techniques, we applied support vector machines, decision tree, random forest, and artificial neural network. For enhancing the identification of rebuttal elements, we used a heuristic feature-engineering method that applies experts' classification of morphemes of scientific argumentation.

• Korean Journal of Environmental Biology
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• v.21 no.3
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• pp.262-270
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• 2003

This study was carried out to analyze forest vegetation of Jinaksan in Geumsan, Chungnam Province. Employing the releve method of Braun-Blanquet, 26 plots were sampled in forest of Jinaksan. The communities were classified into Quercus mongolica, Quercus variabilis, Quercus aliena, and Pinus densiflora communities. Coverage rate was 79.4% in tree layer,27.6% in subtree layer,37.0% in shrub layer, 31.1% in herb layer, respectively. The importance values were 45.51 in Q. mongolica,44.17 in P. densiflora,26.56 in Q. variabilis,26.78 in Q. serrata,20.81 in Q. aliena, and 15.58 in Prunus serrulata var. spontanea, respectively. Most of the DBH in the Q. mongolica, Q. variabilis, Q. aliena, and p. densiflora was between 5 cm and 15 cm. Therefore, Q. mongolica, Q. variabilis, and Q. aliena will be dominant species in the study area for several decades.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.67-74
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• 2006

Contort-aware computing technology is one of the key technology of ubiquitous computing in the mobile device environment. Context recognition computing enables computer applications that automatically respond to user's everyday activity to be realized. In this paper, We use accelerometer could sense activity states of the object and apply to mobile devices. This method for estimating human motion states utilizes various statistics of accelerometer data, such as mean, standard variation, and skewness, as features for classification, and is expected to be more effective than other existing methods that rely on only a few simple statistics. Classification algorithm uses simple decision tree instead of existing neural network by considering mobile devices with limited resources. A series of experiments for testing the effectiveness of the our context detection system for mobile applications and ubiquitous computing has been performed, and its result is presented.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.395-432
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• 2021

Groundwater recharge rates vary widely by location and with time. They are difficult to measure directly and are thus often estimated using simulations. This study employed frequency and regression analysis and a classification and regression tree (CART) algorithm in a machine learning method to estimate groundwater recharge. CART algorithms are considered for the distribution of precipitation by subbasin (PCP), geomorphological data, indices of the relationship between vegetation and landuse, and soil type. The considered geomorphological data were digital elevaion model (DEM), surface slope (SLOP), surface aspect (ASPT), and indices were the perpendicular vegetation index (PVI), normalized difference vegetation index (NDVI), normalized difference tillage index (NDTI), normalized difference residue index (NDRI). The spatio-temperal distribution of groundwater recharge in the SWAT-MOD-FLOW program, was classified as group 4, run in R, sampled for random and a model trained its groundwater recharge was predicted by CART condidering modified PVI, NDVI, NDTI, NDRI, PCP, and geomorphological data. To assess inter-rater reliability for group 4 groundwater recharge, the Kappa coefficient and overall accuracy and confusion matrix using K-fold cross-validation were calculated. The model obtained a Kappa coefficient of 0.3-0.6 and an overall accuracy of 0.5-0.7, indicating that the proposed model for estimating groundwater recharge with respect to soil type and vegetation cover is quite reliable.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.892-905
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• 2022

This study attempted to derive high-risk groups of adolescent status delinquency(ASD) and to identify related factors. This study was conducted with 1,979 adolescents enrolled in the first year of high school, data from the 7th year of the 4th grade panel of the Korean Children and Youth Panel Survey. Classification and regression tree analysis method was used. The ASD group was 264, which was 13.3% of the total. The high-risk group for ASD is that is male who has a low perception of positive parenting style. Positive parenting style was found to be the most important influencing factor in ASD, followed by gender, emotional problems, relationship with teacher, and achievement value. In order to prevent ASD, it is necessary to develop a parenting education program and an intervention program specialized for male adolescents. In addition, interventions that comprehensively deal with emotional problems such as depression and social withdrawal are required, going beyond the previous interventions that focused on aggression. In particular, it has been found that relationship with teachers is the most important influencing factor in the school environment. Through education on the causes and consequences of ASD and training on counseling techniques, the promotion of relationships with teachers will act as a protective factor to prevent ASD.