• Journal of Engineering Education Research
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• v.15 no.4
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• pp.41-47
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• 2012

Data mining and knowledge discovery techniques have shown to be effective in finding hidden underlying rules inside large database in an automated fashion. On the other hand, analyzing, assessing, and applying students' survey data are very important in science and engineering education because of various reasons such as quality improvement, engineering design process, innovative education, etc. Among those surveys, analyzing the students' views on science-technology-society can be helpful to engineering education. Because, although most researches on the philosophy of science have shown that science is one of the most difficult concepts to define precisely, it is still important to have an eye on science, pseudo-science, and scientific misconducts. In this paper, we report the experimental results of applying decision tree induction algorithms for analyzing the questionnaire results of high school students' views on science-technology-society (HS-VOSTS). Empirical results on various settings of decision tree induction on HS-VOSTS results from one South Korean university students indicate that decision tree induction algorithms can be successfully and effectively applied to automated knowledge discovery from students' survey data.

• The Journal of Natural Sciences
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• v.18 no.1
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• pp.91-97
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• 2007

The Korean name "Bizooki" tree was named by the shape of winter bud which is like a slim bow. There are four scientific names in the tree which are Cleyera japonica Thunberg, Cleyera ochnacea DC, Sakakia ochnacea Nakai, and Ternstroemia gymnanthera. And the English name are Japanese Ternstroemia and Japanese Cleyera. "Bizooki" tree has planted at Buddhist temples in Japan for the ritual. The best result of stem cutting in "Bizooki" tree, 100 percent of rooting, could be accomplished in July when cuttings were done on the mixture-soil containing the same rates by volume of vermiculite, peatmoss and perlite with cuts processed with IBA 1,000 mg/l under the circumstances that 70% of shade, plastic mulching, and mist were conditioned.

• Textile Coloration and Finishing
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• v.21 no.2
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• pp.29-39
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• 2009

The color mixture, obtained from Indigo and Japanese pagoda tree, was applied to cellulose fibers such as cotton, linen and rayon to diversify color gamut of natural dyes. The color mixture was tried with two different methods. The first process was that cellulose fibers were dyed with $5{\sim}25%$ owf Japanese pagoda tree solution, and then dyed 1 to 4 times with Indigo. The second process was dyeing 1 to 7 times with Indigo, followed by dyeing with $5{\sim}25%$ owf Japanese pagoda tree solution. K/S value of the dyed fibers with one colorant and color mixture increased in the order of linen, cotton, rayon. It was also found that the first process could give higher K/S values than the second process.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.49-58
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• 2011

Fault Tree Analysis(FTA) builds fault trees to perform safety analysis of systems. However, building fault trees depends on domain knowledge and expertize on target systems and consumes lots of time and efforts. In this paper, we propose a technique that builds fault trees systematically based on state-transition models which are software design artifacts. For the end, this paper identifies conditions that should be satisfied to guarantee safety of state-transition models and develop templates for fault tree construction. This paper also describes the results of appling the proposed method to railway crossing control system.

• Journal of the Korea Computer Industry Society
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• v.10 no.3
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• pp.79-86
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• 2009

This paper proposes a mechanism for prompt and efficient construction of sensor network connecting sensor nodes and base stations using limited length edges minimum spanning tree. This mechanism can rapidly build a connecting tree which may be used in routing of sensor network. In an experiment for 2000 input terminal nodes, this mechanism can curtail 94.7% construction time comparing with the method by naive minimum spanning tree without tree length overheads. This shows the proposed mechanism can apply well to the application of swift construction of a sensor network.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• Journal of Environmental Science International
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• v.32 no.1
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• pp.11-24
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• 2023

This study aimed to provide preliminary data for the improvement of the tree doctor qualification test (first written test), which was newly created by enforcing the Forest Protection Act on June 28, 2018., The high demand for system improvement accelerated this study. The results were analyzeds through literature and questionnaire surveys. Writing test questions and the license of the tree doctor qualification exam are currently managed by the Korea Forestry Research Institute, and it is deemed that the test should be entrusted to Human Resources Development Service of Korea for fair and transparent management. Additionally, the plan for the improvement of the subject-wise scope of examination questions writing, difficulty of test questions, and acceptance rate of the first test should be prepared after public hearings or seminars related to the examination questions.

• Korean Management Science Review
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• v.11 no.3
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• pp.55-65
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• 1994

Given the flow matrix, plant size and department sizes, the algorithms in this paper provide the layout with rectilinear distance. To construct automated facility design, cut tree approach is employed. A branch and bound computer code developed by Tillinghast is modifided to find the feasible fits of departments without shape distortion in the plant rectangle.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.250-254
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• 2010

As the number of input and fuzzy set of a fuzzy system increase, the size of the rule base increases exponentially and becomes unmanageable (curse of dimensionality). In this paper, tree architectures of fuzzy controller (TAFC) is proposed to overcome the curse of dimensionality problem occurring in the design of fuzzy controller. TAFC is constructed with the aid of AND and OR fuzzy neurons. TAFC can guarantee reduced size of rule base with reasonable performance. For the development of TAFC, genetic algorithm constructs the binary tree structure by optimally selecting the nodes and leaves, and then random signal-based learning further refines the binary connections (two-step optimization). An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.208-212
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• 1998

This paper suggests the method to recognize the various defect patterns of cold mill strip using binary decision tree constructed by genetic algorithm automatically. In case of classifying the complex the complex patterns with high similarity like the defect patterns of cold mill strip, the selection of the optimal feature set and the structure of recognizer is important for high recognition rate. In this paper genetic algorithm is used to select a subset of the suitable features at each node in binary decision tree. The feature subset of maximum fitness is chosen and the patterns are classified into two classes by linear decision function. After this process is repeated at each node until all the patterns are classified respectively into individual classes. In this way , binary decision tree classifier is constructed automatically. After construction binary decision tree, the final recognizer is accomplished by the learning process of neural network using a set of standard p tterns at each node. In this paper, binary decision tree classifier is applied to recognition of the defect patterns of cold mill strip and the experimental results are given to show the usefulness of the proposed scheme.