• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.98-103
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• 2000

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

• Journal of Forest and Environmental Science
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• v.28 no.2
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• pp.63-67
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• 2012

Crown ratio is the ratio of live crown length to tree height. It is often used as an important predictor variable for tree growth equation. It indicates tree vigor and is a useful parameter in forest health assessment. The objective of the study was to develop crown ratio prediction models for Tectona grandis. Based on the data set from the temporary sample plots, several non linear equations including logistics, Chapman Richard and exponential functions were tested. These functions were evaluated in terms of coefficient of determination ($R^2$) and standard error of the estimate (SEE). The significance of the estimated parameters was also verified. Plot of residuals against estimated crown ratios were observed. Although the logistic model had the highest $R^2$ and the least SEE, Chapman-Richard and Exponential functions were observed to be more consistent in their predictive ability; and were therefore recommended for predicting crown ratio in the stand.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.10
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• pp.591-597
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• 2003

In this paper, a best-basis selection algorithm that improves the performance of the coding gains and the computational complexity is proposed. The proposed algorithm limits the computational complexity according to the resolved threshold value and decomposes the parent subbands by using the top-down tree search and the relative energy between the parent subbands and the child subbands. For the experiments of the proposed algorithm, the bit-rates, the peak signal-to-noise ratio (PSNR), and the reconstructed images are presented by using the Quad-tree coder. The result of the proposed algorithm is compared to that of DWT algorithm using the Quad-tree coder for a set of standard test images. In addition, the result of the proposed algorithm is compared to that of JPEG-2000 algorithm and that of S+P algorithm.

• Korean Management Science Review
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• v.26 no.1
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• pp.65-76
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• 2009

The undirected Steiner tree problem in graphs is known to be NP-hard. The objective of this problem is to find a shortest tree containing a subset of nodes, called terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step. graph reduction rules eliminate useless nodes and edges which do not contribute to make an optimal solution. In the second step, a max-min ant colony optimization combined with Prim's algorithm is developed to solve the reduced problem. The proposed algorithm is tested in the sets of standard test problems. The results show that the algorithm efficiently presents very correct solutions to the benchmark problems.

• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6B
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• pp.727-735
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• 2001

본 논문은 8-VSB Advanced Digital TV용으로 사용할 수 있도록 ATSC(Advanced Television Standard Committee)의 규약을 만족시키도록 구현한 Reed Solomon 디코더에 대하여 기술한다. 구현된 RS Decoder는 공유된 Tree 구조의 Arithmetic 블록을 사용하여 종래의 기술보다 더 효율적인 연산기 구조를 제안하였으며 빠른 에러 탐지와 정정 시간으로 인한 FIFO의 사용갯수와 Latency Time을 크게 감소시킨 개선된 구조를 제안한다. 일반적으로 2N+A만큼의 Latency Time과 FIFO 개수를 N+A 만큼으로 감소시켰다. 이 RS 디코더는 Verilog HDL로 설계되었고 Synopsys Design Compiler에 의해 합성되었다.

• Korean Journal of Heritage: History & Science
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• v.42 no.1
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• pp.144-157
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• 2009

Nondestructive methods to check the vitality of trees and to find out internal decay of old-giant trees include the use of electrical resistance, ultrasound transmission time, microdrilling, and infrared thermography etc. Among these, ultrasound transmission offers some advantages compared to others such as it is an entirely nondestructive detection method and it can be applied to very big trees. However, the ultrasound equipment is comparatively expensive and not broadly spread yet. On the other hand, Shigometer is versatile to be applied to check vitality of the tree and find out internal decay. Electrical conductivity of plant tissues is a very useful characteristics to determine the vitality and internal decay of trees. Electrical resistance of cambial area tells about the vitality of a tree and electrical resistance of heartwood reveals discoloration or decay of it. For determination of the vitality of the tree, the standard equation for calibration of measured electrical resistances should be developed by measuring and analyzing electrical resistance from at least 30-40 trees of the same species with that tree. All the factors, especially tree species, diameter of the stem, and temperature, which can altered the electrical resistance of trees, should be taken into consideration in the development of the equation. If the standard equation is developed for old-giant trees that we should conserve, it will be very useful. In addition, periodical and continued measuring of a certain tree will help to determine the condition of the tree by comparing the measurement with accumulated data of the tree. Measuring electrical resistance of wood might not require the standard equation. But it also needs to check electrical resistance of sound wood of the same tree species. If the stems that should be examined is thicker than 40cm, it is better to use the ultrasound measurement combined to Shigometer.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.156-165
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• 2023

IEEE 802.15.4e-TSCH is recognized as a wireless industrial sensor network standard used in IoT systems. To ensure both power savings and reliable communications, the TSCH standard uses techniques including channel hopping and bandwidth reserve. In TSCH mode, scheduling is crucial because it allows sensor nodes to select when data should be delivered or received. Because a wide range of applications may necessitate energy economy and transmission dependability, we present a distributed approach that uses a cluster tree topology to forecast scheduling requirements for the following slotframe, concentrating on the Poisson model. The proposed Optimized Minimal Scheduling Function (OMSF) is interested in the details of the scheduling time intervals, something that was not supported by the Minimal Scheduling Function (MSF) proposed by the 6TSCH group. Our contribution helps to deduce the number of cells needed in the following slotframe by reducing the number of negotiation operations between the pairs of nodes in each cluster to settle on a schedule. As a result, the cluster tree network's error rate, traffic load, latency, and queue size have all decreased.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.351-359
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• 2016

This study was conducted to analyze the effect of climate change on the tree-ring growth of Pinus koraiensis in Korea. Annual tree-ring growth data of P. koraiensis collected by the $5^{th}$ National Forest Inventory were first organized to analyze yearly growth patterns of the species. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, five clusters were identified. Yearly growing degree days and standard precipitation index based on daily mean temperature and precipitation data from 1951 to 2010 were calculated by cluster. Using the information, yearly temperature effect index(TEI) and precipitation effect index(PEI) by cluster were estimated to analyze the effect of climatic conditions on the growth of the species. Tree-ring growth estimation equations by cluster were developed by using the product of yearly TEI and PEI as independent variable. The tree-ring growth estimation equations were applied to the climate change scenarios of RCP 4.5 and RCP 8.5 for predicting the changes in tree-ring growth by cluster of P. koraiensis from 2011 to 2100. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of P. koraiensis and for predicting changes in tree-ring growth patterns caused by climate change.