• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.149-154
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• 2024

This paper proposes an algorithm that remedy Floyd's the tortoise and the hare algorithm (THA) shortcomings which is specialized in singly linked list (SLL), so this algorithm fails to detect the cycle in undirected graph, digraph, and tree with multiple inputs or outputs. The proposed algorithm simply pruning the source and sink with only one edge using cycle detection of single edge node pruning. As a result of the experimental of various list, undirected graph, digraph, and tree, the proposed algorithm can be successively detect the cycle all of them. Thus, the proposed algorithm has the simplest and fastest advantage in the field of cycle detection.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.11-14
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• 1990

The detection of pulmonary blood vessels is very difficult owing to their complex tree structures and different widths. In this paper, We propose a new detection algorithm. The motivation of this algorithm is that Han is the best detector. So, this algorithm is developed to imitate the human searching process. To realize it, the algorithm consist of two components. One is Pyramid Images whose one pixel is median value of four pixels of the previous low level. Searching gradually from high level to low level, We concentrate on global and main information of structure at the first. Then based on it, We search the detailed data in low level. The other is fuzzy logic which makes it easy to convert searching process expressed as human language into numeric multi_value. This algorithm showes speedy and robust results. But the more study on both human searching process and the detection of small part is needed.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.147-160
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• 2008

BPMS(business process management system) facilitates defining new processes or updating existing processes. However, processing of exceptional or nonroutine task requires the intervention of domain experts or introduction of the situation specific resolution process. This paper assumes sufficient amount of business process exception handling cases are stored in the process repository. Since the retrieval of the best exception handling process requires a good understanding about the exceptional situation, context awareness is an important issue. To facilitate the understanding of exceptional situation and to enable the efficient selection of the best exception handling process, we adopted the 'situation variable' and 'decision variable' construct. A case example for exception handling in the e-commerce delivery process is provided to illustrate how the proposed construct works. Application of the C5.0 algorithm guarantees the construction of an optimum search tree. It also implies that an efficient search path has been identified for the context aware selection of the best exception handling process.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.30-39
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• 2003

In this paper, we carried out the performance evaluation of HM-Net(Hidden Markov Network) speech recognition system for Korean speech databases. We adopted to construct acoustic models using the HM-Nets modified by HMMs(Hidden Markov Models), which are widely used as the statistical modeling methods. HM-Nets are carried out the state splitting for contextual and temporal domain by PDT-SSS(Phonetic Decision Tree-based Successive State Splitting) algorithm, which is modified the original SSS algorithm. Especially it adopted the phonetic decision tree to effectively express the context information not appear in training speech data on contextual domain state splitting. In case of temporal domain state splitting, to effectively represent information of each phoneme maintenance in the state splitting is carried out, and then the optimal model network of triphone types are constructed by in the parameter. Speech recognition was performed using the one-pass Viterbi beam search algorithm with phone-pair/word-pair grammar for phoneme/word recognition, respectively and using the multi-pass search algorithm with n-gram language models for sentence recognition. The tree-structured lexicon was used in order to decrease the number of nodes by sharing the same prefixes among words. In this paper, the performance evaluation of HM-Net speech recognition system is carried out for various recognition conditions. Through the experiments, we verified that it has very superior recognition performance compared with the previous introduced recognition system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.302-308
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• 1988

The paper describes a very simple algorithm for reducing the encoding complexity of vector quantization(VQ), exploiting the feature of a vector currently being encoded. A proposed VQ of 16(=4x4) vector dimension shows a slight performance degradation of about 0.1-1.9dB, however, with only 16-32 among 256 codeword searches, i.e., with just 1/16-1/8 search complexity compared to a full-search VQ. And the proposed VQ scheme is also compared to outperform tree-search VQ with regard to their SNR performance and memory requirement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4587-4605
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• 2019

High Efficiency Video Coding (HEVC) suffers from high computational complexity due to its quad-tree structure in motion estimation (ME). This paper exposes an adaptive search range decision algorithm for accelerating HEVC integer-pel ME on GPU which estimates the optimal search range (SR) using a MAP (Maximum A Posteriori) estimator. There are three main contributions; First, we define the motion feature as the standard deviation of motion vector difference values in a CTU. Second, a MAP estimator is proposed, which theoretically estimates the motion feature of the current CTU using the motion feature of a temporally adjacent CTU and its SR without any data dependency. Thus, the SR for the current CTU is parallelly determined. Finally, the values of the prior distribution and the likelihood for each discretized motion feature are computed in advance and stored at a look-up table to further save the computational complexity. Experimental results show in conventional HEVC test sequences that the proposed algorithm can achieves high average time reductions without any subjective quality loss as well as with little BD-bitrate increase.

• Journal of the Korea Society of Computer and Information
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• v.19 no.7
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• pp.103-111
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• 2014

This paper proposes a modified algorithm that improves on Dijkstra's algorithm by applying it to purely two-way traffic paths, given that a road where bi-directional traffic is made possible shall be considered as an undirected graph. Dijkstra's algorithm is the most generally utilized form of shortest-path search mechanism in GPS navigation system. However, it requires a large amount of memory for execution for it selects the shortest path by calculating distance between the starting node and every other node in a given directed graph. Dijkstra's algorithm, therefore, may occasionally fail to provide real-time information on the shortest path. To rectify the aforementioned shortcomings of Dijkstra's algorithm, the proposed algorithm creates conditions favorable to the undirected graph. It firstly selects the shortest path from all path vertices except for the starting and destination vertices. It later chooses all vertex-outgoing edges that coincide with the shortest path setting edges so as to simultaneously explore various vertices. When tested on 9 different undirected graphs, the proposed algorithm has not only successfully found the shortest path in all, but did so by reducing the time by 60% and requiring less memory.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.496-503
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• 2010

Speech recognition system is developed of standalone, In case of a mobile terminal using that low recognition rate represent because of limitation of memory size and audio compression. This study suggest vocabulary recognition highest performance improvement system for separate acoustic search and lexical search. Acoustic search is carry out in mobile terminal, lexical search is carry out in server processing system. feature vector of speech signal extract using GMM a phoneme execution, recognition a phoneme list transmission server using Lexical Tree Search algorithm lexical search recognition execution. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.71%, represent recognition speed of 1.58 second.

• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.221-228
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• 2010

Since string operations were applied to computational biology, security and search for Internet, various data structures and algorithms for computing efficient string operations have been studied. The all-pairs suffix-prefix matching is to find the longest suffix and prefix among given strings. The matching algorithm is importantly used for fast approximation algorithm to find the shortest superstring, as well as for bio-informatics and data compressions. In this paper, we propose an algorithm to find all-pairs suffix-prefix matching using the suffix array, which takes O($k{\cdot}m$)�� time complexity. The suffix array algorithm is proven to be better than the suffix tree algorithm by showing it takes less time and memory through experiments.