• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.3
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• pp.19-31
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• 2017

Plants are the basis for sustainable green growth, and the value of existence and importance of trees including landscape Plants can't be emphasized enough. Therefore, they are precious living things thriving in all sorts of public services, and continuous civil complaints for justifiable compensation of landscape Plants are filed. First, the standard formula of planting intervals according to production target specifications is calculated using root-collar caliper and diameter at breast height, and apply (1) standard medium sized trees which have not yet reached commercialization [deciduous tree production goal (R(B) less than 6cm]= (target standard)= [target standard $R(cm){\times}15{\times}0.7$]. (2) In case of commercialization(R6~R10)= [target standard $R(cm){\times}15{\pm}5%$], (3) In case of more than R12= [target standard $R(cm){\times}15{\times}130%$] shall be applied. In case of using diameter at breast height (4) In case of commercialization(B6~B10)= [target standard $B(cm){\times}20{\times}15{\pm}5%$], (5) In case of more than B12= [target standard $B(cm){\times}20{\times}130%$] shall be applied. Second, appraisal methods based on tree classification of compensation for loss are classified according to planted locations. (1) landscape trees within a house=[price of arrival at the site+planting cost], (2) landscape trees in places such as arboretum=[management technology of tress + relocation expenses considering scarcity of the trees (3) landscape trees in a place of loads= [landscape tree production cost + work out added price. In case of producted landscape threes (4) landscape trees ready to be commercialized as sales loss.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.1-6
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• 2007

In order to operate a secure network, it is very important for the network to raise positive detection as well as lower negative detection for reducing the damage from network intrusion. By using SVM on the intrusion detection field, we expect to improve real-time detection of intrusion data. However, due to classification based on calculating values after having expressed input data in vector space by SVM, continuous data type can not be used as any input data. Therefore, we present the hybrid model between SVM and decision tree method to make up for the weak point. Accordingly, we see that intrusion detection rate, F-P error rate, F-N error rate are improved as 5.6%, 0.16%, 0.82%, respectively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.1
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• pp.55-63
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• 2006

This study was carried out to analyze community character and classify forest community with phytosociological method and quadrat method to forest of Mt. Busosan in Buyeo-Gun.1. Communities by phytosociological method were classified into Pinus densiflora community and Quercus sp. community. With the classification of TWINSPAN, the community was categorized into Pinus densiflora - Quercus variabilis community and Pinus densiflora - Styrax japonica community.2. The importance value of Pinus densiflora, Quercus acutissima, Prunus sargentii, Styrax japonica, Quercus serrata, Quercus variabilis, Pinus rigida, Quercus aliena in tree layer were 83.20, 41.87, 30.93, 24.85, 23.27, 20.97, 20.28, and 9.46, respectively. The relative coverage of Stephanandra incisa, Quercus serrata, Styrax japonica, Parthenocissua tricuspidata, Rhododendron mucronulatum, Lindera obtusiloba, Prunus sargentii, Quercus variabilis, Indigofera kirilowii, Quercus acutissima, Lespedeza maximowiczii, and Acer pseudosibolianum in shrub layer were 9.62%, 9.55%, 9.18%, 7.85%, 6.18%, 5.25%, 4.82%, 4.15%, 3.98%, 3.98%, 3.55%, and 2.98%, respectively.3. According to size distribution map of diameter breast height of dominant species, the dominant species of Mt. Busosan was Pinus densiflora, and Quercus sp. such as Quercus acutissima, Quercus variabilis, and Quercus serrata may compete with the Pinus densiflora in the future.4. According to the ordination analysis of Mt. Busosan forest, Pinus densiflora - Styrax japonica community was found in moist site and Pinus densiflora - Quercus variabilis community was found in dry site.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.165-172
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• 2015

The inactive student rate is becoming a major problem in most open universities worldwide. In Indonesia, roughly 36% of students were found to be inactive, in 2005. Data mining had been successfully employed to solve problems in many domains, such as for educational purposes. We are proposing a method for preventing inactive students by mining knowledge from student record systems with several state of the art ensemble methods, such as Bagging, AdaBoost, Random Subspace, Random Forest, and Rotation Forest. The most influential attributes, as well as demographic attributes (marital status and employment), were successfully obtained which were affecting student of being inactive. The complexity and accuracy of classification techniques were also compared and the experimental results show that Rotation Forest, with decision tree as the base-classifier, denotes the best performance compared to other classifiers.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.59-65
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• 2002

Recently, lots of researchers work focused on the intrusion detection system. Pattern matching technique is commonly used to detect the intrusion in the system, However, the method requires a lot of time to match between systems rule and inputted packet data. This paper proposes a new intrusion detection system based on the pattern matching technique. Proposed system reduces the required time for pattern matching by using classified system rule. The classified rule is implemented with a general tree for efficient pattern matching. Thereby, proposed system could perform network intrusion detection efficiently.

• Journal of Applied Reliability
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• v.17 no.1
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• pp.28-37
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• 2017

Purpose: This paper proposes a procedure that may infer and identify interaction failures in a module. Methods: In design FMEA, we defined an interaction model between components and proposed a method for selecting a single component by using the standard specification classification table and four methods for choosing the related components. We also introduced the function tree for function and requirement characteristic analysis and proposed utilization of standard stress lists and 1st and 2nd stress analysis tables to determine the effect the stress analysis has on interactions. Finally, the interaction mechanism diagram was proposed and used to infer the failure mechanism. Process FMEA also established procedures in a similar way. Results: We established a procedure for predicting the failure mode due to interaction between components based on Company A's multi-step FMEA procedure. Conclusion: By applying the proposed interaction FMEA procedure to the development model, we were able to confirm the effect of the new derivation on the failure mode of interaction, which was not predicted by the existing FMEA.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.358-365
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• 2016

We propose a novel application of random forest, a machine learning-based general classification algorithm, to analyze the influence of design attributes on the silicon-to-SPICE (S2S) gap. To improve modeling accuracy, we introduce magnification of learning data as well as randomization for the counting of design attributes to be used for each tree in the forest. From the automatically generated decision trees, we can extract the so-called importance and impact indices, which identify the most significant design attributes determining the S2S gap. We apply the proposed method to actual silicon data, and observe that the identified design attributes show a clear trend in the S2S gap. We finally unveil 10nm key fin-shaped field effect transistor (FinFET) structures that result in a large S2S gap using the measurement data from 10nm test vehicles specialized for model-hardware correlation.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.59-65
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• 2002

Recently, lots of researchers work focused on the intrusion detection system. Pattern matching technique is commonly used to detect the intrusion in the system, However, the method requires a lot of time to match between systems rule and inputted packet data. This paper proposes a new intrusion detection system based on the pattern matching technique. Proposed system reduces the required time for pattern matching by using classified system rule. The classified rule is implemented with a general tree for efficient pattern matching. Thereby, proposed system could perform network intrusion detection efficiently.

• The Mathematical Education
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• v.42 no.2
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• pp.111-119
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• 2003

This research discussed a general concept on the qualitative research methods in mathematics education. It provided a classification of research methods in mathematics education. It also described research trends in mathematics education. It addressed how research design facilitates formulating a research problem, selecting a research design, choosing who and what to study, deciding how to approach Participants, selecting means to collect data choosing how to analyzing data, and interpreting data and applying the analysis. This study addressed the issues involved in choosing relevant populations and in selecting and sampling qualitative data. It described how populations are conceptualized and distinguished between probability sampling and criterion based selection. It discussed not only data arrangement such as, cross-sectional and categorical indexing, non-cross- sectional data organization, but also diagram flow chart matrix, cognitive map, family tree to facilitate analyzing data.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.159-165
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• 2000

A new state evaluation approach for structural safety is presented in this study. To reduce the subjectivity of the view and judgement of each expert founded on a limited body of knowledge in cognitive and inferential process of safety assessment, we introduced inductive learning method in AI. Inductive learning derives generalization from experiences. Decision tree induction algorithm analyzes the domain knowledge, produce rules via decision trees and then allow us to determine the classification of an object from case examples. The training set of state evaluation is constructed according to the selected attributes from working reports of RC bridge girders.