• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.685-691
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• 2008

The selection of classification boundaries in fuzzy rule- based classification systems is an important and difficult problem. So various methods based on learning processes such as neural network, genetic algorithm, and so on have been proposed for it. In a previous study, we pointed out the limitation of the methods and discussed a method for fuzzy partitioning in the overlapped region on feature space in order to overcome the time-consuming when the additional parameters for tuning fuzzy membership functions are necessary. In this paper, we propose a method to determine three types of classification boundaries(i.e., non-overlapping, overlapping, and a boundary point) on the basis of statistical information of the given dataset without learning by extending the method described in the study. Finally, we show the effectiveness of the proposed method through experimental results applied to pattern classification problems using the modified IRIS and standard IRIS datasets.

• The KIPS Transactions:PartC
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• v.15C no.6
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• pp.493-506
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• 2008

In this paper we suggest dynamic access control model based on context satisfied with requirement of u-healthcare environment through researching the role based access control model. For the dynamic security domain management, we used a distributed object group framework and context information for dynamic access control used the constructed database. We defined decision rule by knowledge reduction in decision making table, and applied this rule in our model as a rough set theory. We showed the executed results of context based dynamic security service through u-healthcare application which is based on distributed object group framework. As a result, our dynamic access control model provides an appropriate security service according to security domain, more flexible access control in u-healthcare environment.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.45 no.2
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• pp.106-113
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• 2009

For the safety and cost reduction in the navigation, the automatic and intelligent system has been developed for the vessel, and the most important factor in the system is to decide the collision risk exactly. In this paper, we propose an advanced collision risk decision system for collision avoidance of the system. The conventional researches using DCPA and TCPA for calculating the collision risk have a problem to produce a same collision risk regardless of bearings for the ships, if they are located in the same distance from own ship. To solve this problem, in addition to DCPA and TCPA, we introduce the factor of VCD(variation of compass degree) and constant, CR which derived from COLREG'72(International Regulation for Preventing Collision at Sea, 1972) for evaluating the collision risk including even the burden of own ship navigator due to the encountering angle of each vessels. We decided the collision risk legally by the rule considering the relative situation of vessels. And therefore, the proposed system has two advantages, of which one is to produce more detail collision risk and another is to reflect the real underway situation in conformity with the rule.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.877-884
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• 2011

The decision tree is a representative algorithm of data mining and used in many domains such as retail target marketing, fraud detection, data reduction, variable screening, category merging, etc. This method is most useful in classification problems, and to make predictions for a target group after dividing it into several small groups. When we create a model of decision tree with a large number of input variables, we suffer difficulties in exploration and analysis of the model because of complex trees. And we can often find some association exist between input variables by external variables despite of no intrinsic association. In this paper, we study on the removal method of unnecessary input variables using multiple external association rules. And then we apply the removal method to actual data for its efficiencies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.87-93
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• 2014

For n/m=qm+r, there is no simple divisibility rule for simple m=7 such that is the n multiply by m? This problem can be more complex for two or more digits of m. The Dunkels method has been known for generalized divisibility test method, but this method can not compute very large digits number that can not processed by computer. This paper suggests simple and exact divisibility method for m completely irrelevant n and m of digits. The proposed method sets $r_1=n_1n_2{\cdots}n_l(mod m)$ for $n=n_1n_2n_3{\cdots}n_k$, $m=m_1m_2{\cdots}m_l$. Then this method computes $r_i=r_{i-1}{\times}10+n_i(mod m)$, $i=2,3,{\cdots}k-l+1$ and reduces the digits of n one-by-one. The proposed method can be get the quotient and remainder with easy, fast and correct for various n,m experimental data.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.113-122
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• 2015

This study aims to evaluate future stream flow by the operation of agricultural reservoir group at the upper stream of the Miho River. Four agricultural reservoirs with storage capacities greater than one million cubic meters within the watershed were selected, and the RCP 8.5 climate change scenario was applied to simulate reservoir water storage and stream flow assuming that there are no changes in greenhouse gas reduction. Reservoir operation scenarios were classified into four types depending on the supply of instream flow, and the water supply reliability of each reservoir in terms of water supply under different reservoir operation scenarios was analyzed. In addition, flow duration at the watershed outlet was evaluated. The results showed that the overall run-off ratio of the upper stream watershed of the Miho River will decrease in the future. The future water supply reliability of the reservoirs decreased even when they did not supply instream flow during their operation. It would also be difficult to supply instream flow during non-irrigation periods or throughout the year (January-December); however, operating the reservoir based on the operating rule curve should improve the water supply reliability. In particular, when instream flow was not supplied, high flow increased, and when it was supplied, abundant flow, ordinary flow, and low flow increased. Drought flow increased when instream flow was supplied throughout the year. Therefore, the operation of the agricultural reservoirs in accordance with the operating rule curve is expected to increase stream flow by controlling the water supply to cope with climate change.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.203-210
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• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.460-465
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• 2007

In this paper, we propose a novel pattern classification method based on statistical properties of the given data and fuzzy-rough set to minimize the coupling problem of the rules. In the proposed method, statistical properties is used by a selection criteria for deciding a partition number of antecedent fuzzy sets, and for minimizing an coupling problem of the generated rules. Moreover, rough set is used as a tool to remove unnecessary attributes between generated rules from the numerical data. In order to verify the validity of the proposed method, we compared the classification results (i.e, classification precision) of the proposed with the conventional pattern classification methods on the Fisher's IRIS data. From experiment results, we can conclude that the proposed method shows relatively better performance than those of the classification methods based on the conventional approaches.

• Steel and Composite Structures
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• v.37 no.6
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• pp.711-731
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• 2020

This paper deals with free vibration of FG sandwich annular sector plates on Pasternak elastic foundation with different boundary conditions, based on the three-dimensional theory of elasticity. The plates with simply supported radial edges and arbitrary boundary conditions on their circular edges are considered. The influence of carbon nanotubes (CNTs) waviness, aspect ratio, internal pores and graphene platelets (GPLs) on the vibrational behavior of functionally graded nanocomposite sandwich plates is investigated in this research work. The distributions of CNTs are considered functionally graded (FG) or uniform along the thickness of upper and bottom layers of the sandwich sectorial plates and their mechanical properties are estimated by an extended rule of mixture. In this study, the classical theory concerning the mechanical efficiency of a matrix embedding finite length fibers has been modified by introducing the tube-to-tube random contact, which explicitly accounts for the progressive reduction of the tubes' effective aspect ratio as the filler content increases. The core of structure is porous and the internal pores and graphene platelets (GPLs) are distributed in the matrix of core either uniformly or non-uniformly according to three different patterns. The elastic properties of the nanocomposite are obtained by employing Halpin-Tsai micromechanics model. A semi-analytic approach composed of 2D-Generalized Differential Quadrature Method (2D-GDQM) and series solution is adopted to solve the equations of motion. The fast rate of convergence and accuracy of the method are investigated through the different solved examples. Some new results for the natural frequencies of the plate are prepared, which include the effects of elastic coefficients of foundation, boundary conditions, material and geometrical parameters. The new results can be used as benchmark solutions for future researches.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.103-108
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• 2022

In this paper, we propose a new image analysis method based on regression manifold 3-D PCA. The proposed method is a new image analysis method consisting of a regression analysis algorithm with a structure designed based on an autoencoder capable of nonlinear expansion of manifold 3-D PCA and PCA for efficient dimension reduction when entering large-capacity image data. With the configuration of an autoencoder, a regression manifold 3-DPCA, which derives the best hyperplane through three-dimensional rotation of image pixel values, and a Bayesian rule structure similar to a deep learning structure, are applied. Experiments are performed to verify performance. The image is improved by utilizing the fine dust image, and accuracy performance evaluation is performed through the classification model. As a result, it can be confirmed that it is effective for deep learning performance.