• Journal of Biosystems Engineering
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• v.25 no.5
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• pp.399-408
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• 2000

This study is final focused on developing fruit harvesting robot can distinguish fruit type and status accurately. Multi-joint robot is able to discriminate tree shape and select mature fruit by image processing. The multi-joint robot consists of (a) rotating base, (b)turning first joint-arm, (c)rotating and turning second joint-arm, (d)rotating and turning third joint-arm, (e)rotating and turning last joint and (f)picker hand. The operational ranges of the robot are: horizontal 860~2,220mm, vertical 1,440~2,260mm, 270 degrees’rotation angle, 90 or 270 degrees’turning angle. The robot weighs 330kg. The multi-joint robot was designed in high accuracy and efficiency by getting as close as the movements of human arms and waist.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.539-551
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• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.225-253
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• 2015

The standard is a nation's one of the most important industrial issues that improve the social and economic efficiency and also the basis of the industrial development and trade liberalization. This research analyzes the enactment and the utilization of Korean industrial standards(KS) of various industries. This paper examines Korean industries' KS utilization status based on the KS possession, enactments and inquiry records. First, we implement multidimensional scaling method to visualize and group the KS possession records and the nation's institutional issues. We develop several hypothesis to find the decision factors of how each group's KS possession status impacts on the standard enactment activities of similar industry sectors, and analyzes the data by implementing regression analysis. The results show that the capital intensity, R&D activities and sales revenues affect standardization activities. It suggests that the government should encourage companies with high capital intensity, sales revenues to lead the industry's standard activities, and link the policies with the industry's standard and patent related activities from R&D. Second, we analyze the impacts of each KS data's inquiry records, the year of enactments, the form and the industrial segment on the utilization status by implementing statistical analysis and decision tree method. The results show that the enactment year has significant impact on the KS utilization status and some KSs of specific form and industrial segment have high utilization records despite of short enactment history. Our study suggests that government should make policies to utilize the low-utilized KSs and also consider the utilization of standards during the enactment processes.

• The KIPS Transactions:PartC
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• v.10C no.3
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• pp.345-354
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• 2003

IP Multicast is required of more little network resources than one in unicast. Furthermore, reliable multicast has been researched for supporting reliability at IP Multicast mechanism. Although these studies are carried out, they only have focused on general data. In other words, in case that realtime packet, they can not support reliability since they do not consider realtime properties such as dependency of interframe and playback in time. Besides, we also request to support scalability because we are based on Mobile IP network together with internet. Thus, we need a mechanism to guarantee reliability and scalability of realtime stream data. In this paper, we propose PER (Preceding Error Recovery) that reflect characteristics of the realtime data, especially for H.323. PER provides scalable reliability because it is based on tree-based multicast basically and helps to support scalable relibility as reducing control packet and recovers stream buffer space from underflow status as soon as possible. PER shows much better scalable and reliable than existing works.

• Journal of Microbiology
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• v.40 no.4
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• pp.335-339
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• 2002

Partial sequences of 16S rRNA gene of five chroococcalian blue-green algal strains, Aphanothece nidulans KCTC AG10041, Aphanothece naegelii KCTC AG10042, Microcystis aeruginosa KCTC AG10159, Microcystis ichthyoblabe KCTC AG10160, and Microcystis viridis KCTC AG10198, which were isolated from water from the Geumgang River, were determined and were inferred their phylogenetic and taxonomic positions among taxa of order Chroococcales. Most taxa of Chroococcales whose partial 16S rRNA gene sequences were aligned in this study, are clustered with other related taxa. Aphanothece nidulans KCTC AG10041 and Aphanothece naegelii KCTC AG10042 made a cluster with other European species of these genera, which supported 100% of the bootstrap trees with a very high sequence similarity (97.4-99.4%) in this study. Three strains, Microcystis aeruginosa KCTC AG10159, M. ichthyoblabe KCTC AG10160, and M. viridis KCTC AG10198, formed a cluster with other Microcystis spp. supported 100 % of the bootstrap trees with a similarity of 97.0-99.9% except for two strains. However, this phylogentic tree made no resolution among the species of Microcystis spp. The topology of the tree reconfirmed the taxonomic status of three species of Microcystis, identified in this study based on the morphology, as three colonial types of Microcystis aeruginosa com. nov. Otsuka et al. (1999c). The genera of chroococcalian cyanophytes are heterogeneously clustered in these sequence analyses. We suggest that more molecular studies on the genera of Chroococcales with reference strains, widely collected from restricted geographic or environmental ranges, get accurate taxonomic or phylogenetic determinations.

• Korean Journal of Environment and Ecology
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• v.23 no.2
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• pp.151-160
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• 2009

To investigate the vegetation structure of the section from Naesosa to Naebyonsan district, thirty plots which Size is $100m^2$ were set up in the Byeonsan Peninsula National Park. According to the classification(TWINSPAN) and ordination(DCA) analysis which were used for community division, the plots are appeared in uncontiguity with each ones. At the end of classification analysis, the community was divided into the four groups of Pinus densiflora(I), Pinus densiflora-Quercus serrata(II), Zelkova serrata-Rhamnella frangulioides(III) and Aphanaghe aspera-Rhamnella frangulioides community(IV). Through the results, Pinus densiflora community coast-sided will be going with status quo, but Pinus densiflora-Quercus serrata community inland-sided will progress toward Q. serrata dominated community. It was turned out that the forest of the Byeonsan Peninsula National Park is about over 40-year-old through tree ring analysis.

• Journal of Ecology and Environment
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• v.44 no.2
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• pp.90-97
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• 2020

Background: Natural forests are generally considered to be less prone to biological invasions than other modified ecosystems, particularly when canopy cover is high. Few decades of management of degraded forests by local communities in Nepal has increased canopy cover and altered disturbance regimes. These changes might have reduced the abundance of invasive alien plant species (IAPS) in forests. To understand the status of IAPS in such forests, we studied two community managed Shorea robusta forests (Sundari and Dhusheri) of Nawalpur district in central Nepal. In these two forests, vegetation sampling was done using circular plots 10 m radius at forest edge, gaps, and within canopy. Variation of IAPS richness and cover across these microhabitats were compared, and their variation with tree canopy cover and basal area analyzed. Result: Altogether 14 IAPS were recorded in the study forests; among them Chromolaena odorata, Ageratum houstonianum, and Lantana camara had the highest frequency. Mikania micrantha was at the early stage of colonization in Sundari Community Forest (CF) but absent in Dhuseri CF. Both IAPS cover and richness was higher at forest edge and gap than in canopy plots and both these attributes declined with increasing canopy cover and tree basal area. Conclusion: The results indicate that increase in canopy cover and closure of forest gaps through participatory management of degraded forests can prevent plant invasions and suppress the growth of previously established IAPS in Shorea robusta forests of Nepal. This is the unacknowledged benefit of participatory forest management in Nepal.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.2
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• pp.1-9
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• 2009

Due to the increase of carbon dioxide in the atmosphere and global warming, the importance of forest ecosystems, as a place of carbon accumulation and emission, has received a great amount of recognition lately. This study was performed to help understand and provide the current status of carbon cycle in the pinus densiflora stand, Korea. The samples were collected from average 35-years-old Pinus densifiora rands in Gongju, Youngdong, Chungsan, Muju, Mupung, and Jangsu regions. Total thirty aboveground sample trees were cut, and ten roots were sampled, and soil samples were collected. Average carbon concentrations in foliage, branch, stem bark, stem wood, and root were 55.7%, 56.0%, 56.0%, 57.3%, and 56.5%, respectively. Carbon content was estimated by the model $Wt=aD^b$ where Wt is oven-dry weight in kg and D is DBH in cm. Total carbon content (aboveground and root) was 42.39tonC/ha in the Pinus densiflora stand. The proportion of each tree component to total carbon content was high in order of stemwood, root, branch, stem bark, and foliage. Total net primary production (aboveground and root) was estimated at 6.51tonC/ha/yr in Pinus densiflora stand. The proportion of each tree component to total net primary carbon content was high in order of sternwood, root, branch, foliage and stembark. Soil carbon contents in the study sites was 43.51tonC/ha at 0-50cm soil depth.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.89-101
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• 2008

The most used tool for quality control is control chart in manufacturing industry. But it has limitations at current situation where most of manufacturing facilities are automated and several manufacturing processes have interdependent relationship such as CCM assembly line. To Solve problems, we propose quality management system based on data mining that are consisted of monitoring system where it monitors flows of processes at single window and feature extraction system where it predicts the yield of final product and identifies which processes have impact on the quality of final product. The quality management system uses decision tree, neural network, self-organizing map for data mining. We hope that the proposed system can help manufacturing process to produce stable quality of products and provides engineers useful information such as the predicted yield for current status, identification of causal processes for lots of abnormality.