• Journal of Digital Convergence
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• v.13 no.1
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• pp.243-248
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• 2015

Recognition model is not defined when you configure a model, Been added to the model after model building awareness, Model a model of the clustering due to lack of recognition models are generated by modeling is causes the degradation of the recognition rate. In order to improve decision tree state tying modeling using parameter estimation of Bayesian method. The parameter estimation method is proposed Bayesian method to navigate through the model from the results of the decision tree based on the tying state according to the maximum probability method to determine the recognition model. According to our experiments on the simulation data generated by adding noise to clean speech, the proposed clustering method error rate reduction of 1.29% compared with baseline model, which is slightly better performance than the existing approach.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.321-327
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• 2004

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

• Journal of the Korean Institute of Gas
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• v.2 no.3
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• pp.12-17
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• 1998

Fault tree construction for hazard assessment requires so much time and labor, so it is very difficult to be applied to the large scale chemical plant. For the synthesis of fault tree in chemical processes, this study represents the cause-effect relations between process variables by using the Signed Directed Graph(SDG), and has synthesized Fault Tree(FT) by searching the causes of fault events using the general operator and loop operators defined corresponding to path characteristics on the SDG.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.22-24
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• 2002

본 논문에서는 백트랙킹 알고리즘을 이용한 하드웨어/소프트웨어 분할 방법을 제안한다. 최적의 해를 찾을 때에 효율적인 가지치기 함수를 정의하여 불필요한 탐색 단계를 제거하므로써 계산 시간이 단축될 수 있도록 하였다. 또한 제약조건에 따라 트리의 검색 순서에 변화를 주어 효율적인 검색이 되도록 하였다. 제안된 알고리즘의 성능평가를 위해 시뮬레이티드 어닐링 방법의 결과와 비교 분석하였다.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.250-257
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• 2003

As the memory access time becomes slower relative to the fast processor speed, most systems use cache memory to reduce the gap. The cache performance has an increasingly large impact on the performance of algorithms. Blocking is the well known method to utilize cache and has shown good results in multiplying matrices and search trees like d-heap. But if we use blocking in the data structures which require rotation during insertion or deletion, the execution time increases as the data movements between blocks are necessary. In this paper, we have proposed the extended pairing heap algorithms using block node and shown by experiments that our structure is superior Also in case of using block node, we use less memory space as the number of pointers decreases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2169-2177
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• 2015

This paper proposes a new pattern matching module to overcome the increased runtime of previous algorithm using RAM, which was designed to overcome cost limitation of hash-based algorithm using CAM (Content Addressable Memory). By adopting Merge FSM algorithm to reduce the number of state, the proposed module contains state block and entry block to use in RAM. In the proposed module, one input string is compared with multiple entry strings simultaneously using entry block. The effectiveness of the proposed pattern matching unit is verified by executing Snort 2.9 rule set. Experimental results show that the number of memory reads has decreased by 15.8%, throughput has increased by 47.1%, while memory usage has increased by 2.6%, when compared to previous methods.

• Journal of KIISE:Databases
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• v.29 no.3
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• pp.193-206
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• 2002

In this paper, we design and implement an efficient bulk-loading algorithm for CIR-Tree. Bulk-loading techniques increase node utilization, improve query performance and reduce index construction time. The CIR-tree has variable size of internal node entries since it only maintains minimal dimensions to decriminate child nodes. This property increases fan-out of internal nodes and improves search performance. Even though several bulk-loading algorithms for multi/high-dimensional index structures have been proposed, we cannot apple them to CIR-tree because of the variable size of internal node entries. In this paper, we propose an efficient bulk- loading algorithm for CIR-tree that improves the existing bulk-loading algorithm and accomodates the property of CIR-tree. We also implement it on a storage system MiDAS-III and show superiority of our algorithm through various experiments.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.1-10
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• 2008

In order to high-performance data Processing, effective resource selection is needed since grid resources are composed of heterogeneous networks and OS systems in the grid environment. In this paper. we classify grid resources with data properties and user requirements for resource selection using a decision tree method. Our resource selection method can provide suitable resource selection methodology using classification with a decision tree to grid users. This paper evaluates our grid system performance with throughput. utilization, job loss, and average of turn-around time and shows experiment results of our resource selection model in comparison with those of existing resource selection models such as Condor-G and Nimrod-G. These experiment results showed that our resource selection model provides a vision of efficient grid resource selection methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1133-1137
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• 2008

Sphere decoding is considered as one of the most promising methods for multiple-input multiple-output (MIMO) detection. This paper proposes a novel 2-level-search sphere decoding algorithm. In the proposed algorithm, symbol detection is concurrently performed on two levels of the tree search, which helps avoid discarding good candidates at early stages. Simulation results demonstrate the good performance of the proposed algorithm in terms of bit-error-rate (BER).

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.381-384
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• 2006

센서 네트워크 환경에서 스트림 데이터를 모니터링 하기 위해서는 스트림 데이터에 대한 연속적인 질의들을 효과적으로 처리하는 것이 필요하다. 이러한 연속적인 질의를 빠르게 검색하고 처리하기 위하여 낮은 저장 비용과 빠른 탐색 성능을 가진 질의 색인 기법이 많이 활용되고 있다. 기존 연구들은 사전에 삽입될 Interval 을 알고 트리를 구성하므로 동적인 삽입, 삭제가 불가능하거나 삽입된 Interval 수와 Interval 의 범위에 따라 높은 저장 비용이나 상대적으로 느린 탐색 속도를 보인다. 따라서 이 논문에서는 연속적인 질의 처리를 효율적으로 하기 위하여 Hashed Multiple Lists 를 제안한다. 제안된 기법은 빠른 선형 탐색 성능과 낮은 저장 비용을 요구하며 삽입, 삭제가 용이하고 다양한 범위를 표현할 수 있는 장점이 있다. 제안된 색인 기법은 센서 네트워크를 응용한 시스템과 상황 인식 시스템 등에서 연속적인 질의를 처리하는데 활용할 수 있다.