• Korean Journal of Computational Design and Engineering
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• v.8 no.2
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• pp.75-83
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• 2003

In this paper, OSP(Octal Space Partitioning) tree is proposed for the real time culling of infinite sets of geometries in interactive Virtual Environment applications. And MSVBSP(Modified Shadow Volume BSP) tree is suggested for the occlusion culling. Experimental results show that the OSP and MSVBSP tree are efficiently implemented in real time rendering of interactive geometries.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.787-790
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• 2017

Data quality is the main issue in the classification problems; generally, the presence of noisy instances in the training dataset will not lead to robust classification performance. Such instances may cause the generated decision tree to suffer from over-fitting and its accuracy may decrease. Decision trees are useful, efficient, and commonly used for solving various real world classification problems in data mining. In this paper, we introduce a preprocessing technique to improve the classification accuracy rates of the C4.5 decision tree algorithm. In the proposed preprocessing method, we applied the naive Bayes classifier to remove the noisy instances from the training dataset. We applied our proposed method to a real e-commerce sales dataset to test the performance of the proposed algorithm against the existing C4.5 decision tree classifier. As the experimental results, the proposed method improved the classification accuracy by 8.5% and 14.32% using training dataset and 10-fold crossvalidation, respectively.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.11a
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• pp.334-335
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• 2006

Solid insulation exposed to voltage is degraded by electrical tree process. And the degradation of the insulation is accelerated by voltage application. For this experimental, specimen of electrical tree model is made by XLPE (cross-linked polyethylene). And the size of the specimen is 7*5*7 $mm^3$. Distance of needle and plane is 2 mm. Voltages applied for acceleration test are 12 kV to 15 kV. And distribution characteristic of degraded stage is studied too. As a PD detecting and data process, discharge data acquire from PD detecting system (Biddle instrument). The system presents statistical distribution as phase resolved. Moreover the processing time of electrical tree is recorded to know the speed of degradation according to voltage.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.172-175
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• 1992

This paper proposes the methods to construct the tree-structured database and analyze the distribution system network. In order to cope with an extensive amount of data and the frequent breaker switching operations in distribution systems, the database for system configuration is constructed using binary trees. Once the tree-structured database has been built, the system tracing of distribution network can be rapidly performed. This remarkably enhances the efficiency of data search and easily adapts to system changes due to switching operations. The computation method of fast power flow using tree search strategies is presented. The methods in the paper may be available in the field of distribution system operation.

• Spatial Information Research
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• v.15 no.2
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• pp.181-187
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• 2007

To make digital terrain data, automatic correlation matching by stereo airborne/satellite images has been researched. The result of automatic correlation matching has a limit on extracting exact ground height because of angle of sensor, tree of height. Therefore, the amount of editing works depend on the distribution of spatial feature in images as well as image quality. This paper shows that the automatic correlation matching result was affected by density and height of tree.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.91-99
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• 2006

The incremental parsing technique plays an important role in language-based environment which allows the incremental construction of a program. It improves the performance of a system by reanalyzing only the changed part of a program. The conventional incremental parsing uses the stack data structure in order to store the parsing information. In this paper, we suggest a threaded tree construction algorithm which parse by adding the threaded node address instead of using a stack data structure. We also suggest an incremental threaded tree construction which has incremental parsing process of five steps using the constructed threaded tree.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.543-559
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• 2017

Tree-based regression and classification ensembles form a standard part of the data-science toolkit. Many commonly used methods take an algorithmic view, proposing greedy methods for constructing decision trees; examples include the classification and regression trees algorithm, boosted decision trees, and random forests. Recent history has seen a surge of interest in Bayesian techniques for constructing decision tree ensembles, with these methods frequently outperforming their algorithmic counterparts. The goal of this article is to survey the landscape surrounding Bayesian decision tree methods, and to discuss recent modeling and computational developments. We provide connections between Bayesian tree-based methods and existing machine learning techniques, and outline several recent theoretical developments establishing frequentist consistency and rates of convergence for the posterior distribution. The methodology we present is applicable for a wide variety of statistical tasks including regression, classification, modeling of count data, and many others. We illustrate the methodology on both simulated and real datasets.

• Spatial Information Research
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• v.19 no.2
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• pp.71-76
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• 2011

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

• Journal of Korean Society for Quality Management
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• v.48 no.2
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• pp.297-307
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• 2020

Purpose: The purpose of this study is to analyze the factors that affect ammunition performance by applying data mining techniques to the Ammunition Stockpile Reliability Program (ASRP) data of the 155mm propelling charge. Methods: The ASRP data from 1999 to 2017 have been utilized. Logistic regression and decision tree analysis were used to investigate the factors that affect performance of ammunition. The performance evaluation of each model was conducted through comparison with an artificial neural networks(ANN) model. Results: The results of this study are as follows; logistic regression and the decision tree analysis showed that major defect rate of visual inspection is the most significant factor. Also, muzzle velocity by base charge and muzzle velocity by increment charge are also among the significant factors affecting the performance of 155mm propelling charge. To validate the logistic regression and decision tree models, their classification accuracies have been compared with the results of an ANN model. The results indicate that the logistic regression and decision tree models show sufficient performance which conforms the validity of the models. Conclusion: The main contribution of this paper is that, to our best knowledge, it is the first attempt at identifying the significant factors of ASPR data by using data mining techniques. The approaches suggested in the paper could also be extended to other types ammunition data.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.257-271
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• 2006

Recently, flash memories are one of best media to support portable computer's storages in mobile computing environment. The features of non-volatility, low power consumption, and fast access time for read operations are sufficient grounds to support flash memory as major database storage components of portable computers. However, we need to improve traditional Indexing scheme such as B-Tree due to the relatively slow characteristics of flash operation as compared to RAM memory. In order to achieve this goal, we devise a new indexing scheme called F-Tree. F-Tree improves tree operation performance by compressing pointers and keys in tree nodes and rewriting the nodes without a slow erase operation in node insert/delete processes. Based on the results of the performance evaluation, we conclude that F-Tree indexing scheme outperforms the traditional indexing scheme.