• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1395-1409
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• 2006

A spatial data warehouse has spatial data cube composed of multi-dimensional data for efficient OLAP(On-Line Analytical Processing) operations. A spatial data cube supporting concept hierarchies holds huge amount of data so that many researches have studied a incremental update method for minimum modification of a spatial data cube. The Cube, however, compressed by eliminating prefix and suffix redundancy has coalescing paths that cause update inconsistencies for some updates can affect the aggregate value of coalesced cell that has no relationship with the update. In this paper, we propose incremental batch update method of a spatial data cube. The proposed method uses duplicated nodes and extended node structure to avoid update inconsistencies. If any collision is detected during update procedure, the shared node is duplicated and the duplicate is updated. As a result, compressed spatial data cube that includes concept hierarchies can be updated incrementally with no inconsistency. In performance evaluation, we show the proposed method is more efficient than other naive update methods.

• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.73-79
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• 2014

During developing cubesat flight software, Communication test between cubesat and ground station is needed. For this, we have constructed indoor ground station without outdoor antenna for decreasing total cost and time. In this time, if output power of ground station is high, it will affect for cubesat transceiver to be fail. For solving this problem, ground station must be designed for output power of it to be lower than input power of cubesat satellite, and it must be verified. In this paper, first, we describe cubesat indoor ground station using UHF and VHF. Second, we describe output power decreasing test for indoor operation of ground station by attaching attenuators in the end of the output connector.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.242-250
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• 1996

Communications on hypercube nodes are done by explicit message routing. So efficient message routing is very important for the performance of hypercube multicomputers. However, hypercube nodes can be faulty due to hardware and/o r software problems, which is called an injured hypercube. A reliable hypercube system should tolerate the problems. One of the methods to enhance reliability on injured hypercube is to use fault-tolerant message routing algorithms. In this paper, we propose a message routing algorithm with possible shortest distance using disjoint paths. To analyze the performance, the algorithm is simulated and evaluated.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.4
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• pp.431-439
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• 2000

In this paper, we propose a system-level diagnosis algorithm for hypercube muti-processors using adaptive cube partition method. Feng[1] proposed a diagnosis algorithm for hypercube multiprocessors which gives a better performance compared to previous researches[2, 3]. But cube partitions in Feng's algorithm are performed without syndrome analysis. Therfore unnecessery overhead is made during cube partitions. In this paper, we propose an adaptive cube partition method which gives better partition through syndrome analysis and reduces diagnosis cost. We give a simulation result for comparisons. We have found that our algorithm shows better performance compared to Feng's method.

• Journal of Space Technology and Applications
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• v.3 no.4
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• pp.342-354
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• 2023

The paradox of cubesat development process in the New Space paradigm is related to a complicated and time-consuming system engineering procedure. Due to their low cost and quick production time, cubesats are a highly accessible space asset in the startup-driven "New Space" industry. In reality, however, the development process experienced by the student teams selected through the national cubesat competition is quite different from what we expect. This is because cubesats are designed and implemented using a lengthy and tedious procedure defined by the systems engineering perspective. The purpose of this work is to explain to developers who are unfamiliar with systems engineering the role and function of systems engineering in each step of the cubesat development process.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.199-201
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• 2003

온라인 분석처리 시스템의 핵심 기술인 큐브를 효과적으로 산출하기 위한 많은 연구들이 이루어 졌다. 이러한 연구는 크게 온라인 분석처리 시스템의 결과 데이터를 저장하는 방식에 의해 MOLAP과 ROLAP으로 구분하여 이루어 졌다. 최근에 온라인 분석처리 시스템에서 큐브 산출에 대한 연구로 다중키 엑세스를 효율적으로 처리하는 다차원 파일 구조를 사용하여 집계 연산의 효율을 높이는 연구가 이루어졌다. 본 논문은 이러한 연구들을 바탕으로 다차원 파일 구조를 사용하여 효과적으로 큐브를 산출하고 결과 값을 미리 저장하는 일반적인 방법을 제안한다.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.475-486
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• 2009

Data cube plays an important role in multi-dimensional, multi-level data analysis. Meeting on-line analysis requirements of data stream, several cube structures have been proposed for OLAP on data stream, such as stream cube, flowcube, S-cube. Since it is costly to construct data cube and execute ad-hoc OLAP queries, more research works should be done considering efficient data structure, query method and algorithms. Stream cube uses H-cubing to compute selected cuboids and store the computed cells in an H-tree, which form the cuboids along popular-path. However, the H-tree layoutis disorderly and H-cubing method relies too much on popular path.In this paper, first, we propose $H^*$-tree, an improved data structure, which makes the retrieval operation in tree structure more efficient. Second, we propose an improved cubing method, $H^*$-cubing, with respect to computing the cuboids that cannot be retrieved along popular-path when an ad-hoc OLAP query is executed. $H^*$-tree construction and $H^*$-cubing algorithms are given. Performance study turns out that during the construction step, $H^*$-tree outperforms H-tree with a more desirable trade-off between time and memory usage, and $H^*$-cubing is better adapted to ad-hoc OLAP querieswith respect to the factors such as time and memory space.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.225-236
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• 2003

MOLAP systems store data in a multidimensional away called a 'cube' and access them using way indexes. When a cube is placed into disk, it can be Partitioned into a set of chunks of the same side length. Such a cube storage scheme is called the chunk-based MOLAP cube storage scheme. It gives data clustering effect so that all the dimensions are guaranteed to get a fair chance in terms of the query processing speed. In order to achieve high space utilization, sparse chunks are further compressed. Due to data compression, the relative position of chunks cannot be obtained in constant time without using indexes. In this paper, we propose a bitmap index for chunk-based MOLAP cubes. The index can be constructed along with the corresponding cube generation. The relative position of chunks is retained in the index so that chunk retrieval can be done in constant time. We placed in an index block as many chunks as possible so that the number of index searches is minimized for OLAP operations such as range queries. We showed the proposed index is efficient by comparing it with multidimensional indexes such as UB-tree and grid file in terms of time and space.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.335-343
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• 2009

The crossed cube has received great attention because it has equal or superior properties compared to the hypercube that is widely known as a versatile parallel processing system. It has been known that disjoint two copies of a mesh of size $4{\times}2^m$ or disjoint four copies of a mesh of size $8{\times}2^m$ can be embedded into a crossed cube with dilation 1 and expansion 1 [Dong, Yang, Zhao, and Tang, 2008]. However, it is not known that disjoint multiple copies of a mesh with more than eight rows and columns can be embedded into a crossed cube with dilation 1 and expansion 1. In this paper, we show that disjoint $2^{n-1}$ copies of a mesh of size $2^n{\times}2^m$ can be embedded into a crossed cube with dilation 1 and expansion 1 where $n{\geq}1$ and $m{\geq}3$. Our result is optimal in terms of dilation and expansion that are important measures of graph embedding. In addition, our result is practically usable in allocating multiple jobs of mesh structure on a parallel computer of crossed cube structure.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.455-464
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• 2012

Due to the recent data explosion, methods which can meet the requirement of large data analysis has been studying. This paper proposes MRIterativeBUC algorithm which enables efficient computation of large data cube by distributed parallel processing with MapReduce framework. MRIterativeBUC algorithm is developed for efficient iterative operation of the BUC method with MapReduce, and overcomes the limitations about the storage size and processing ability caused by large data cube computation. It employs the idea from the iceberg cube which computes only the interesting aspect of analysts and the distributed parallel process of cube computation by partitioning and sorting. Thus, it reduces data emission so that it can reduce network overload, processing amount on each node, and eventually the cube computation cost. The bottom-up cube computation and iterative algorithm using MapReduce, proposed in this paper, can be expanded in various way, and will make full use of many applications.