• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.225-232
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• 2011

Restricted Hypercube-Like (RHL) graphs are a graph class that widely includes useful interconnection networks such as crossed cube, Mobius cube, Mcube, twisted cube, locally twisted cube, multiply twisted cube, and generalized twisted cube. In this paper, we show that for an m-dimensional RHL graph G, $m{\geq}4$, with an arbitrary faulty edge set $F{\subset}E(G)$, ${\mid}F{\mid}{\leq}m-2$, graph $G{\setminus}F$ has a hamiltonian path between any distinct two nodes s and t if dist(s, V(F))${\neq}1$ or dist(t, V(F))${\neq}1$. Graph $G{\setminus}F$ is the graph G whose faulty edges are removed. Set V(F) is the end vertex set of the edges in F and dist(v, V(F)) is the minimum distance between vertex v and the vertices in V(F).

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.175-187
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• 2006

The data cube is an aggregation operator that computes group-bys for all possible combination of dimension attributes. %on the number of the dimension attributes is n, a data cube computes $2^n$ group-bys. Each group-by in a data cube is called a cuboid. Data cubes are often precomputed and stored as materialized views in data warehouses. These data cubes need to be updated when source relation change. The incremental maintenance of a data cube is to compute and propagate only its changes. To compute the change of a data cube of $2^n$ cuboids, previous works compute a delta cube that has the same number of cuboids as the original data cube. Thus, as the number of dimension attributes increases, the cost of computing a delta cube increases significantly. Each cuboid in a delta cube is called a delta cuboid. In this paper. we propose an incremental cube maintenance method that can maintain a data cube by using only $_nC_{{\lceil}n/2{\rceil}}$ delta cuboids. As a result, the cost of computing a delta cube is substantially reduced. Through various experiments, we show the performance advantages of our method over previous methods.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.553-560
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• 2003

A range-sum query is very popular and becomes important in finding trends and in discovering relationships between attributes in diverse database applications. It sums over the selected cells of an OLAP data cube where target cells are decided by specified query ranges. The direct method to access the data cube itself forces too many cells to be accessed, therefore it incurs severe overheads. The prefix-sum cube was proposed for the efficient processing of range-sum queries in OLAP environments. However, the prefix-sum cube has been criticized due to its space requirement. In this paper, we propose a lossless compression method called the overlapped-subcube that is developed for the purpose of compressing prefix-sum cubes. A distinguished feature of the overlapped-subcube is that searches can be done without decompressing. The overlapped-subcube reduces the space requirement for storing prefix-sum cubes, and improves the query performance.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.9-16
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• 2008

This paper presents a new Boolean extraction technique for logic synthesis. This method extracts two-cube Boolean subexpression pairs from each logic expression. It begins by creating two-cube array, which is extended and compressed with complements of two-cube Boolean subexpressions. Next, the compressed two-cube array is analyzed to extract common subexpressions for several logic expressions. The method is greedy and extracts the best common subexpression. Experimental results show the improvements in the literal counts over well-known logic synthesis tools for some benchmark circuits.

• Communications of Mathematical Education
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• v.13 no.2
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• pp.765-773
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• 2002

정육면체 27개를 면끼리 붙여서 7개의 조각을 만들어, 이것을 조합하여 3${\times}$3${\times}$3 정육면체가 되도록 하는 퍼즐로 소마큐브(Soma Cube)가 많이 알려져 있다. 이런 입체퍼즐은 공간지각력과 문제해결능력을신장시켜서 창의력을 키우는 데 매우 효과적이므로, 교육적 소재로서 수업에 활용하면 좋다. 이 웍샵에서는 소마큐브와 같은 원리를 갖지만 조각의 모양이 전혀 다른 조이큐브(Joy Cube)와 펀큐브(Fun Cube, Diabolic Cube)를 직접 만들어서, 이를 수업에 활용하는 방법을 소개하려고 한다. 조이큐브는 초등학교 고학년, 펀큐브는 전학년에서 활용이 가능하다.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.596-605
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• 2001

In this paper we propose a method, called the range-based cube partitioning (RCP)method for reducing I/O cost of cube computation in OLAP The method improves I/O performance of cube partitioning process by overlapping some computation between partitioning stages. For overlapping the computation, the method partitions the cube based on the ranges of attribute values, not the points of attribute value, Through analysis any experiments, we show the performance of the proposed method with comparison of the previous cube partitioning method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.11
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• pp.975-988
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• 2017

Since 2000, about 750 cubesats have been launched as of August 2017 and development and the launch of cubesat increased exponentially. Since standard of cubesat has been proposed in 1999, cubesats have grown considerably beyond the scope of education and technology verification to commercial use in the area of space exploration and earth observation, and the variety of cubesat mission and type has increased recently. In Korea, some universities and individuals have independently developed cubesats since 2000, and cubesat contests which were organized by KARI and sponsored by Ministry of Science and ICT from 2012 highly contributed to cubesat development in Korea. In addition, domestic institutes such as KARI, KASI started to develop cubesats for space science and exploration mission. Nineteen cubesats have been progressed or completed in development until now. In this paper, we present the technical trend and describe all cubesats in Korea.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.353-362
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• 2006

A data warehouse is a data repository that enables users to store large volume of data and to analyze it effectively. In this research, we investigate an algorithm to establish a multidimensional data cube which is a powerful analysis tool for the contents of data warehouses and databases. There exists an inevitable retrieval overhead in a multidimensional data cube due to the sparsity of the cube. In this paper, we propose a dense sub-cube extraction algorithm that identifies dense regions from a large sparse data cube and constructs the sub-cubes based on the dense regions found. It reduces the retrieval overhead remarkably by retrieving those small dense sub-cubes instead of scanning a large sparse cube. The algorithm utilizes the bitmap and histogram based techniques to extract dense sub-cubes from the data cube, and its effectiveness is demonstrated via an experiment.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.214-215
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• 2012

본원적 큐브란 사용자의 얼굴을 다각면에서 추출하여 주성분분석(PCA: Principal component analysis)을 통해 다차원 정보를 통합하여 큐브형태로 표현된 것을 의미한다. 두 눈의 연결점과 입의 연결점을 이은 후 그 둘의 법선벡터를 얼굴의 방향으로 표현하는 것으로써 평면 사진에 얼굴방향을 부여한다. 그럴 경우 동일인물의 다양한 사진들을 모았을 경우 각 사진들이 얼굴방향을 달리하는 사진큐브로 표현될 수 있다. 이로써 기존에는 얼굴방향이 다른 동일인물의 사진을 정확하게 구분해 낼 수 없던 한계를 뛰어넘을 수 있다. 또한 큐브는 방향이 조금씩 다른 모든 사진을 저장할 필요가 없으므로 저장공간이 크게 절감되는 장점이 있다. 또한 단체 사진에서 개인의 이미지를 추출한 뒤 본 연구의 큐브와 매칭시켜 인물을 탐색하거나 소유한 이미지를 공유하는 기법을 포함한다. 결과적으로 큐브를 활용하여 효과적으로 인물탐색이 가능 해지는 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.25-26
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• 2010

대용량 데이터의 효율적 분석을 위해 데이터 뷰브가 연구되었으며, 데이터 큐브 계산의 고비용 문제점을 해결하기 위하여 큐브의 일부 영역만을 계산하는 빙산 큐브가 등장하였다. 빙산 큐브는 저장 공간의 감소, 집중적인 분석 등의 장점이 있으나, 여전히 많은 계산과 저장 공간을 필요로 하는 단점이 있다. 본 논문에서는 이러한 문제점을 해결하는 실용적인 방법으로 대용량 문제를 분산하여 처리하는 분산 병렬 컴퓨팅 기술인 맵리듀스(MapReduce) 프레임워크를 사용하여 분산 병렬 빙산 큐브인 MR-Naive와 MR-BUC 알고리즘을 제안한다. 실험을 통해 맵리듀스 프레임워크를 통한 빙사 큐브 계산이 효율적으로 분산 병렬 처리 됨을 확인하였다.