• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.211-216
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• 2008

이 논문은 철근 가공 산업 현장에서 스프레드쉬트에 의해 수작업으로 행하던 절단 작업의 계획 수립을 자동화된 시스템에 의해 최적의 절단 계획을 생성하도록 하는 소프트웨어의 개발을 다룬다. 이를 위하여, 먼저 시스템의 데이터 표현과 최적 문제 풀이를 위한 자동 계획 알고리듬의 설계가 요구된다. 이것은 다중 규격의 1차원 자재 절단 문제를 푸는 것으로, 동적계획법에 근거하여 자재 절단 문제를 재구성하고, 유한 범위의 조합 열에서도 근사 최적의 해를 찾을 수 있는 탐색 기법을 사용한 자재 절단 계획 알고리듬을 사용하였다. 그리고, 자동화된 철근 가공 산업용 소프트웨어는 작업 환경에 맞게 사용이 편리한 그래픽 화면과 사용자 인터페이스가 요구되는데, 공개 소프트웨어를 활용한 GUI 라이브러리 툴킷인 GTK+를 활용하여 이를 구현하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1463-1468
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• 2003

This paper presented the real-time self-tuning learning control based on evolutionary computation, which proves its superiority in finding of the optimal solution at the off-line learning method. The individuals of the populations are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations is proposed. It is possible to control the control object slightly varied as time changes. As the state value of the control object is generated, evolutionary strategy is applied each sampling time because the learning process of an estimation, selection, mutation is done in real-time. These algorithms can be applied; the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.421-430
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• 2000

This paper presents a new approach which uses $A^*$ search and genetic algorithms for solving large scale multi-objective shortest path problem. The focus of this paper is motivated by the problem of finding Pareto optimal paths for an advanced traveler information system(ATIS) in the context of intelligent transportation system(ITS) application. The individual description, the decoding rule, the selection strategy and the operations of crossover and mutation are proposed for this problem. The keynote points of the algorithm are how to represent individuals and how to calculate the fitness of each individual. The high performance of the proposed algorithm is demonstrated by computer simulations.

• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.347-355
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• 1997

In this study, the applicability of genetic algorithms into the parameter estimation of storage function method for flood routing model is investigated. Genetic algorithm is mathematically established theory based on the process of Darwinian natural selection and survival of fittest. It can be represented as a kind of search algorithms for optima point in solution space and make a reach on optimal solutions through performance improvement of assumed model by applying the natural selection of life as mechanical learning province. Flood events recorded in the Daechung dam are selected and used for the parameter estimation and verification of the proposed parameter estimation method by the split sample method. The results are analyzed that the performance of the model are improved including peak discharge and time to peak and shown that the parameter Rsa, and f1 are most sensitive to storage function model. Based on the analysis for estimated parameters and the comparison with the results from experimental equations, the applicability of genetic algorithm is verified and the improvements of those equations will be used for the augmentation of flood control efficiency.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.49-55
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• 2007

To improved the multi-resolution fast hierarchical motion estimation by using de-interlacing algorithm that is effective in term of both performance and VLSI implementation, is proposed so as to cover large search area field-based as well as frame based image processing in SoC design. In this paper, we have simulated a various picture mode M=2 or M=3. As a results, the proposed algorithm achieved the motion estimation performance PSNR compare with the full search block matching algorithm, the average performance degradation reached to -0.7dB, which did not affect on the subjective quality of reconstructed images at all. And acquiring the more desirable to adopt design SoC for the fast hierarchical motion estimation, we exploit foreground and background search algorithm (FBSA) base on the dual arithmetic processor element(DAPE). It is possible to estimate the large search area motion displacement using a half of number PE in general operation methods. And the proposed architecture of MHME improve the VLSI design hardware through the proposed FBSA structure with DAPE to remove the local memory. The proposed FBSA which use bit array processing in search area can improve structure as like multiple processor array unit(MPAU).

• The Journal of the Acoustical Society of Korea
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• v.24 no.8
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• pp.498-504
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• 2005

We introduce a Korean speech recognition platform (ECHOS) developed for education and research Purposes. ECHOS lowers the entry barrier to speech recognition research and can be used as a reference engine by providing elementary speech recognition modules. It has an easy simple object-oriented architecture, implemented in the C++ language with the standard template library. The input of the ECHOS is digital speech data sampled at 8 or 16 kHz. Its output is the 1-best recognition result. N-best recognition results, and a word graph. The recognition engine is composed of MFCC/PLP feature extraction, HMM-based acoustic modeling, n-gram language modeling, finite state network (FSN)- and lexical tree-based search algorithms. It can handle various tasks from isolated word recognition to large vocabulary continuous speech recognition. We compare the performance of ECHOS and hidden Markov model toolkit (HTK) for validation. In an FSN-based task. ECHOS shows similar word accuracy while the recognition time is doubled because of object-oriented implementation. For a 8000-word continuous speech recognition task, using the lexical tree search algorithm different from the algorithm used in HTK, it increases the word error rate by $40\%$ relatively but reduces the recognition time to half.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.48-57
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• 1997

This paper presents the automatic construction and parameter optimization technique for fuzzy logic controllers using genetic algorithm. In general. the design of fuzzy logic controllers has difficulties in the acq~lisition of expert's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controllers c:an be degraded in the case of plant parameter variations or unpredictable incident which a designer may have ignored, and the parameters of fuzzy logic controllers obtained by expert's control action may not be optirnal. Some of these problems can be resolved by the use of genetic algorithm. The proposed method can tune the parameters of fuzzy logic controllers including scaling factors and determine: the appropriate number of fuzzy rulcs systematically. Finally, we provides the second order dead time plant to evaluate the feasibility and generality of the proposed method. Comparison shows that the proposed method can produce fuzzy logic controllers with higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controllers.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.63-69
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• 2001

A corpus-based lip sync algorithm for synthesizing natural face animation is proposed in this paper. To get the lip parameters, some marks were attached some marks to the speaker's face, and the marks' positions were extracted with some Image processing methods. Also, the spoken utterances were labeled with HTK and prosodic information (duration, pitch and intensity) were analyzed. An audio-visual corpus was constructed by combining the speech and image information. The basic unit used in our approach is syllable unit. Based on this Audio-visual corpus, lip information represented by mark's positions was synthesized. That is. the best syllable units are selected from the audio-visual corpus and each visual information of selected syllable units are concatenated. There are two processes to obtain the best units. One is to select the N-best candidates for each syllable. The other is to select the best smooth unit sequences, which is done by Viterbi decoding algorithm. For these process, the two distance proposed between syllable units. They are a phonetic environment distance measure and a prosody distance measure. Computer simulation results showed that our proposed algorithm had good performances. Especially, it was shown that pitch and intensity information is also important as like duration information in lip sync.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1013-1016
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• 1998

A method for generation of design verification tests from behavior-level VHDL program is presented. Behavioral VHDL programs contain multiple communicating processes, signal assignment statements. So for large, complex system, it is difficult problem to test or simulation. In this paper, we proposed a new hardware design verification method. For this method generates control flow graph(CFG.) and process modeling graph(PMG) in the given under the testing VHDL program. And this method proved very effective that all the assumed design errors could be detected.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.173-179
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• 2000

Genetic algorithm(GA) is applied for detecting multiple outliers. GA is a heuristic optimization tool solving for near optimal solution. We compare the performance of GA and the other diagnostic measures commonly used for detecting outliers in regression model. The results show that GA seems to have better performance than the others for the detection of multiple outliers.