• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.159-166
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• 2010

In this paper, to obtain the Minimum Spanning Tree (MST) from the graph with several nodes having the same weight, I applied both Bor$\dot{u}$vka and Kruskal MST algorithms. The result came out to such a way that Kruskal MST algorithm succeeded to obtain MST, but not did the Prim MST algorithm. It is also found that an algorithm that chooses Inter-MSF MWE in the $2^{nd}$ stage of Bor$\dot{u}$vka is quite complicating. The $1^{st}$ stage of Bor$\dot{u}$vka has an advantage of obtaining Minimum Spanning Forest (MSF) with the least number of the edges, and on the other hand, Kruskal MST algorithm has an advantage of always obtaining MST though it deals with all the edges. Therefore, this paper suggests an Hybrid MST algorithm which consists of the merits of both Bor$\dot{u}$vka's $1^{st}$ stage and Kruskal MST algorithm. When applied additionally to 6 graphs, Hybrid MST algorithm has a same effect as that of Kruskal MST algorithm. Also, comparing the algorithm performance speed and capacity, Hybrid MST algorithm has shown the greatest performance Therefore, the suggested algorithm can be used as the generalized MST algorithm.

• Journal of Biosystems Engineering
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• v.31 no.1 s.114
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• pp.52-58
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• 2006

Various robots were developed for harvesting fruits and vegetables. However, each robot was designed for a specific task such as harvesting apples or vegetables. This has been a big hurdle in application of robots to agriculture. A new type of hybrid manipulator with both parallel and serial joints was developed and designed to apply to various kinds of field operations. The hybrid manipulator had 2 extra degree of freedom in serial joints which made it flexible in switching one to the other type of hybrid manipulator, for example, PUMA to SCARA. And it was designed to harvest heavy fruits such as musky melons or water melons even behind leaves or branches of tree. This hybrid manipulator showed less than $\pm1mm$ position error. It was concluded that the hybrid manipulator was an effective and feasible tool to perform various works and to increase working performance.

• Journal of Digital Convergence
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• v.6 no.4
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• pp.177-183
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• 2008

This paper aims to offer a solution based on intelligent document classification to create a user-centric information retrieval system allowing user-centric linguistic expression. So, structures expressing user intention and fine document classifying process using EBL, similarity, knowledge base, user intention, are proposed. To overcome the problem requiring huge and exact semantic information, a hybrid process is designed integrating keyword, thesaurus, probability and user intention information. User intention tree hierarchy is build and a method of extracting group intention between key words and user intentions is proposed. These structures and processes are implemented in HDCI(Hybrid Document Classification with Intention) system. HDCI consists of analyzing user intention and classifying web documents stages. Classifying stage is composed of knowledge base process, similarity process and hybrid coordinating process. With the help of user intention related structures and hybrid coordinating process, HDCI can efficiently categorize web documents in according to user's complex linguistic expression with small priori information.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.27-43
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• 2005

This paper presents a new hybrid data mining technique using error pattern modeling to improve classification accuracy when the data type of a target variable is binary. The proposed method increases prediction accuracy by combining two different supervised learning methods. That is, the algorithm extracts a subset of training cases that are predicted inconsistently by both methods, and models error patterns from the cases. Based on the error pattern model, the Predictions of two different methods are merged to generate final prediction. The proposed method has been tested using practical 10 data sets. The analysis results show that the performance of proposed method is superior to the existing methods such as artificial neural networks and decision tree induction.

• ETRI Journal
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• v.36 no.6
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• pp.1016-1022
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• 2014

This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees and artificial neural networks is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.659-668
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• 2008

Recently, the component model based on the Exogenous Connector has been proposed in which controls are separated from computation by managing the beginning and result of method calls in the connector. Although it could be loosely coupled between components, it has a problem that is a potential preponderance of element objects of the system by increasing the number of connectors and connection levels. In this paper we propose the Tree Component Model with the Hybrid Message Passing that combines direct and indirect message passing. In our model, components are wrapped by interfaces and controls are separated from computation by only using their interface references. There is a unique feature that the composition structure of components becomes the tree always. As a result of demonstration and comparison, it is found that the Tree Component Model is applicable practically and decreases objects to mediate message passing and build the system.

• Korean Journal of Plant Resources
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• v.20 no.5
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• pp.442-445
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• 2007

Seedlings height of hybrids varied depending on mating combinations. Among the progenies from the mating combination, P. thunbergii(CN4)$\times$P. densiflora(KW29) showed the best plant growth. The mean height of this combination was 521 cm at the age of 8 years(yrs), which was 9% higher than rest of the crosses. Seedlings height of progenies using P. thunbergii(JN37) as mother tree showed 28%, 33%, and 29% higher than those of open-pollinated progenies of the mother tree at the ages of 4yrs, 6yrs, and 8yrs, respectively. On the other hand, using P. densiflora (KB5) as father tree showed 45%, 48%, and 32% higher than those of open-pollinated progenies of the father tree. This result may be caused by hybrid vigor.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.140-140
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• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• Journal of Korean Society of Forest Science
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• v.77 no.4
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• pp.382-388
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• 1988

Improvement of productivity by forest tree breeding work in Korea was estimated for a few important tree species. Progenies of 17 plus trees of red pine (Pines densiflora) outgrew by 57 percentage compared with progenies of unselected trees at age 15. If best three families are selected among the 17, more than double in volume grow-th is expected. The hybrid Pinus rigida ${\times}$ P. taeda showed more than double volume growth compare to P. rigida at a southern plantation at age 15. However, the superiority of the hybrid decreased at northern plantations, mainly because of low coldhardiness of the hybrid. At a northern plantation, the hybrid grew less than the P. rigida on upper hill, while the hybrid grew much better than the P. rigida on flat area. Another hybrid Populus alba ${\times}$ P. glandulosa grew faster than both parents by two to two and half times according to planting sites at age 10. Introduction of Pinus rigida also showed increased volume growth. Volume increase by selection of best five provenances among 45 at age 12 was estimated as 53 percent compare to progenies of plus trees in Korea, Additional 19 percent of volume increase was expected by selection of the best families within the best provenances. Annual production of chestnuts reached about 70,000 M/T by planting resistant clones to chestnut gall wasp (Dryocosmus kuriphilus), which killed almost all susceptible trees. Although polyploid trees and mutants have been produced by colchicine treatments in over 10 tree species, none of them is economically important Remarkable improvement of productivity is expected by biotechnology in future through selection, hybridization, introduction of foreign genes at cell, cell organelle and gene level, and gene transformation. At present, mass propagation of superior planting materials by tissue culture will increase the productivity.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.263-272
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• 2007

This paper proposes a skeleton-based hierarchical shape description scheme, called a skeleton tree, for accurate shape-based image retrieval. A skeleton tree represents an object shape as a hierarchical tree where high-level nodes describe parts of coarse trunk regions and low-level nodes describe fine details of boundary regions. Each node refines the shape of its parent node. Most of the noise disturbances are limited to bottom level nodes and the boundary noise is reduced by decreasing weights on the bottom levels. The similarity of two skeleton trees is computed by considering the best match of a skeleton tree to a sub-tree of another skeleton tree. The proposed method uses a hybrid similarity measure by employing both Fourier descriptors and moment invariants in computing the similarity of two skeleton trees. Several experimental results are presented demonstrating the validity of the skeleton tree scheme for the shape description and indexing.