• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• Research in Mathematical Education
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• v.2 no.1
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• pp.163-181
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• 1998

The paper deals with some aspects of early childhood geometry in the Czech Republic. Children's first geometrical experiences come from real life. In our opinion, there exist four types of geometrical experience which can be called the partition of space, the filling of space motion in space and the dimension of space. We distinguish three levels of the mathematical learning process: a spontaneous level, an operational level and a theoretical level.

• Research in Mathematical Education
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• v.1 no.2
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• pp.163-181
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• 1997

The paper deals with some aspects of early childhood geometry in the Czech Republic. Children's first geometrical experiences come from real life. In our opinion, there exist four types of geometrical experience which can be called the partition of space, the filling of space motion in space and the dimension of space. We distinguish three levels of the mathematical learning process: a spontaneous level, an operational level and a theoretical level.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.109-112
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• 2007

온라인 음악 시장이 점차 커지고 있다. 이에 따라 사용자를 위한 다양한 서비스가 요구되고 있다. 하지만 현재 적용되는 서비스는 통계적인 수치에 기반하는 순위권 나열 혹은 테마나 장르별 음악 소개에 그치고 있다. 따라서 본 논문에서는 사용자의 성향에 가까운 음악을 분석하고 이를 추천하는 방법을 제시한다. 음악 추천 시스템을 위해 우선 사용자의 성향을 분석하기 위하여 사용자가 청취했던 음악의 음파를 분석하여 특성을 추출하여 벡터로 나타낸다. 하지만 추출된 성향과 다른 음악의 성향을 비교해야 하는데 음악의 양이 방대하기 때문에 시간이 오래 걸릴 수 있다. 따라서 이 문제를 해결하기 위해 공간 분할을 통해 검색의 범위를 축소시키고, 음악을 빠르게 추천한다. 실험 결과, 사람의 주관적인 해석이 아닌 음파의 해석을 통해 보다 객관적이고 자동화된 추천 방법을 구현할 수 있었다. 그리고 같은 성질의 음악이 추천되어짐을 확인할 수 있었다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.66-69
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• 2003

This paper considers a reinforcement learning(RL) which deals with real environments. Most reinforcement learning studies have been made by simulations because real-environment learning requires large computational cost and much time. Furthermore, it is more difficult to acquire many rewards efficiently in real environments than in virtual ones. The most important requirement to make real-environment learning successful is the appropriate construction of the state space. In this paper, to begin with, I show the basic overview of the reinforcement learning under real environments. Next, 1 introduce a state-space construction method under real environmental which is State Partition Method. Finally I apply this method to a robot navigation problem and compare it with conventional methods.

• Journal of Mechanical Science and Technology
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• v.16 no.5
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• pp.676-682
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• 2002

The laminar convective heat transfer in ventilated space with various horizontal partitions was studied numerically and experimentally For the numerical study, the governing equations were solved by using a finite volume method for various numbers Re, Gr, Pr and partition numbers. The experimental study was conducted by using a holographic interferometer. The isotherms and velocity vectors have been presented for various parameters. As the number and length of partition increased, convective heat transfer decreased. Based on the numerical data, correlation equations were obtained for the mean Nusselt number in term of Gr/Re$^2$. In the region of Gr/Re$^2$$\leq$ 1, the mean Nusselt number was small, but in the region of Gr/Re$^2$> 1, the mean Nusselt number was constant.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.497-508
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• 2005

This paper aims at studying on K-means Clustering focusing on initialization which affect the clustering results in K-means cluster analysis. The four different methods(the MA method, the KA method, the Max-Min method and the Space Partition method) were compared and the clustering result shows that there were some differences among these methods, especially that the MA method sometimes leads to incorrect clustering due to the inappropriate initialization depending on the types of data and the Max-Min method is shown to be more effective than other methods especially when the data size is large.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1495-1507
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• 2022

The improvement of thermal-hydraulic analysis techniques is essential to ensure the safety and reliability of nuclear power plants. The one-dimensional two-fluid model has been adopted in state-of-the-art thermal-hydraulic system codes. Current constitutive equations used in the system codes reach a mature level. Some exceptions are the partition method of wall friction in the momentum equation of the two-fluid model and the interfacial drag force model for a horizontal two-phase flow. This study is focused on deriving the partition method of wall friction in the momentum equation of the two-fluid model and modeling the interfacial drag force model for a horizontal bubbly flow. The one-dimensional momentum equation in the two-fluid model is derived from the local momentum equation. The derived one-dimensional momentum equation demonstrates that total wall friction should be apportioned to gas and liquid phases based on the phasic volume fraction, which is the same as that used in the SPACE code. The constitutive equations for the interfacial drag force are also identified. Based on the assessments, the Rassame-Hibiki correlation, Hibiki-Ishii correlation, Ishii-Zuber correlation, and Rassame-Hibiki correlation are recommended for computing the distribution parameter, interfacial area concentration, drag coefficient, and relative velocity covariance of a horizontal bubbly flow, respectively.

• Korean Institute of Interior Design Journal
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• v.17 no.5
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• pp.133-140
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• 2008

This study is purposed to understand the usage of the color and the material pattern in detail and to apply for interior architecture. Many documents have prescribed the color and the pattern at random. While the usage of the color and the materials was ignored rather than architectural form, the importance of the color and the materials stands out in modern interior space. The villa, the weekend home of the Savoye family, was built between 1928 and 1931. Particularly, the villa Savoye was focused for this study. Le Corbusier viewed case pieces for storage and wall partition for division as architecture, and he units furniture and architecture by developing partition that could be painted either the wall color to become part of the wall or in contrasting colors to stand out as wall partition. He loved white and lie believed in using it for interiors, but noted that it should also be balanced with a wall related polychromy. Color became an integral part of white structure of the villa savoye that was raised on stilt with an exterior wall at the base painted green as a visual connection with the lawn. Color was used architecturally in the interior as well, with white walls interrupted by planes of pink, blue and red ocher and it gives the space an unexpected playfulness with tile color of the finishing materials. the various usage of the color and material patterns constitute an element of great architectural richness. They have a unique principle based on emotional order and make the man move to another space and experience the spacial connection.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.456-462
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• 2008

The classification is that a new data is classified into one of given classes and is one of the most generally used data mining techniques. Memory-Based Reasoning (MBR) is a reasoning method for classification problem. MBR simply keeps many patterns which are represented by original vector form of features in memory without rules for reasoning, and uses a distance function to classify a test pattern. If training patterns grows in MBR, as well as size of memory great the calculation amount for reasoning much have. NGE, FPA, and RPA methods are well-known MBR algorithms, which are proven to show satisfactory performance, but those have serious problems for memory usage and lengthy computation. In this paper, we propose DPA (Dynamic Partition Averaging) algorithm. it chooses partition points by calculating GINI-Index in the entire pattern space, and partitions the entire pattern space dynamically. If classes that are included to a partition are unique, it generates a representative pattern from partition, unless partitions relevant partitions repeatedly by same method. The proposed method has been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory and FPA, and RPA.