• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.737-741
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• 1993

In this paper, we design the fuzzy logic controller(FLC) for a nonlinear multivariable steam generating unit. Based on the knowledges of operator, the self-organizing controller(SOC) - a kind of FLC - is developed and tested. Both FLC and SOC based on linguistic rules have the advantages of not needing of some exact mathematical model for plant to be controlled. Beside, the SOC modifies the existing control rules by monitoring the control performance. The computer simulations have been carried out for the 200MW steam generating unit to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• Analytical Science and Technology
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• v.8 no.4
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• pp.707-714
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• 1995

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonstrates its excellent utility for the complex depth profile system. It includes the stable restoration of the depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.857-860
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• 1993

In this paper, we apply the self generating neuro fuzzy model (SGNFM) to the dimension analysis of the chaotic time series. Firstly, we formulate a nonlinear time series identification problem with nonlinear autoregressive (NARMAX) model. Secondly, we propose an identification algorithm using SGNFM. We apply this method to the estimation of embedding dimension for chaotic time series, since the embedding dimension plays an essential role for the identification and the prediction of chaotic time series. In this estimation method, identification problems with gradually increasing embedding dimension are solved, and the identified result is used for computing correlation coefficients between the predicted time series and the observed one. We apply this method to the dimension estimation of a chaotic pulsation in a finger's capillary vessels.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.567-570
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• 2001

현재의 출입국 관리자는 여권을 제시하면 여권을 육안으로 검색하고 수작업으로 정보를 입력하여 여권 데이터베이스와 대비하는 것이다. 본 논문에서는 이러한 문제점을 해결하기 위하여 자동으로 여권을 인식할 수 있는 방법을 제안한다. 여권에는 사용자에 대한 많은 정보들이 있는데 여권 영상에서 코드 정보 영역을 히스토그램 방식과 소벨 연산자를 이용하여 코드 영역 및 개별 코드 문자를 추출하고 새로운 자가 생성 지도학습 알고리즘(Self-Generating Supervised Learning Algorithm)을 제안하여 여권 인식에 적응하였다. 10개의 여권 영상을 실험한 결과 모든 코드의 문자 영역이 추출되었고 인식되었다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.2
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• pp.25-32
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• 2006

In this paper, we propose a fast correlation attack on the shrinking and self-shrinking generator. This attack is an improved algorithm or the fast correlation attack by Zhang et al. at CT-RSA 2005. For the shrinking generator, we recover the initial state of generating LFSR whose length is 61 with $2^{15.43}$ keystream bits, the computational complexity of $2^{56.3314}$ and success probability 99.9%. We also recover the initial state of generating LFSR whose length is $2^{40}$ of the self-shrinking generator with $2^{45.89}$ keystream bits, the computational complexity of $2^{112.424}$ and success probability 99.9%.

• Journal of The Korean Association For Science Education
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• v.30 no.5
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• pp.668-680
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• 2010

In this study, we investigated the characteristics, the mapping understanding, the mapping errors, and the perceptions of student-generated analogies on the separation of mixtures using the sizes of particles by elementary school students' approaches to learning. Fourth graders (N=92) were selected and administered with the tests on the approaches to learning, self-generating analogies, and perception of self-generating analogies. The results revealed that the meaningful learners made more analogies, especially structural/functional, enriched, and higher systematic ones than the rote learners. However, there were little difference in students' approaches to learning in the subcategories of representation (verbal, pictorial, and verbal/pictorial), artificiality (artificial and everyday), and abstraction (abstract and concrete). The meaningful learners had deeper understanding of the analogy and fewer mapping errors than the rote learners. In addition, the numbers of the shared attributes included in student-generated analogies and the scores of the mapping understanding of the meaningful learners were significantly higher than those of the rote learners. Many students, regardless of students' approaches to learning, had positive perceptions of the self-generating analogies in various cognitive and motivational aspects. However, they also point out the various difficulties in the self-generating analogies as their disadvantages. Educational implications of these findings are discussed.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.1
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• pp.37-42
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• 2003

In this paper a self-organizing fuzzy system with rule pruning is proposed. A conventional self-organizing fuzzy system having only rule generation has a drawback in generating many slightly different rules from the existing rules which results in increased computation time and slowly learning. The proposed self-organizing fuzzy system generates fuzzy rules based on input-output data and prunes redundant rules which are caused by parameter training. The proposed system has a simple structure but performs almost equivalent function to the conventional self-organizing fuzzy system. Also, this system has better learning speed than the conventional system. Simulation results on several numerical examples demonstrate the performance of the proposed system.

• Bulletin of the Korean Mathematical Society
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• v.51 no.6
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• pp.1841-1850
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• 2014

It is known that the ranks of the semigroups $\mathcal{SOP}_n$, $\mathcal{SPOP}_n$ and $\mathcal{SSPOP}_n$ (the semigroups of orientation preserving singular self-maps, partial and strictly partial transformations on $X_n={1,2,{\ldots},n}$, respectively) are n, 2n and n + 1, respectively. The idempotent rank, defined as the smallest number of idempotent generating set, of $\mathcal{SOP}_n$ and $\mathcal{SSPOP}_n$ are the same value as the rank, respectively. Idempotent can be seen as a special case (with m = 1) of m-potent. In this paper, we investigate the m-potent ranks, defined as the smallest number of m-potent generating set, of the semigroups $\mathcal{SOP}_n$, $\mathcal{SPOP}_n$ and $\mathcal{SSPOP}_n$. Firstly, we characterize the structure of the minimal generating sets of $\mathcal{SOP}_n$. As applications, we obtain that the number of distinct minimal generating sets is $(n-1)^nn!$. Secondly, we show that, for $1{\leq}m{\leq}n-1$, the m-potent ranks of the semigroups $\mathcal{SOP}_n$ and $\mathcal{SPOP}_n$ are also n and 2n, respectively. Finally, we find that the 2-potent rank of $\mathcal{SSPOP}_n$ is n + 1.

• Clinical and Experimental Pediatrics
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• v.50 no.12
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• pp.1165-1172
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• 2007

Self/non-self discrimination and unresponsiveness to self is the fundamental properties of the immune system. Self-tolerance is a state in which the individual is incapable of developing an immune response to an individual's own antigens and it underlies the ability to remain tolerant of individual's own tissue components. Several mechanisms have been postulated to explain the tolerant state. They can be broadly classified into two groups: central tolerance and peripheral tolerance. Several mechanisms exist, some of which are shared between T cells and B cells. In central tolerance, the recognition of self-antigen by lymphocytes in bone marrow or thymus during development is required, resulting in receptor editing (revision), clonal deletion, anergy or generation of regulatory T cells. Not all self-reactive B or T cells are centrally purged from the repertoire. Additional mechanisms of peripheral tolerance are required, such as anergy, suppression, deletion or clonal ignorance. Tolerance is antigen specific. Generating and maintaining the self-tolerance for T cells and B cells are complex. Failure of self-tolerance results in immune responses against self-antigens. Such reactions are called autoimmunity and may give rise to autoimmune diseases. Development of autoimmune disease is affected by properties of the genes of the individual and the environment, both infectious and non-infectious. The host's genes affect its susceptibility to autoimmunity and the environmental factors promote the activation of self-reactive lymphocytes, developing the autoimmunity. The changes in participating antigens (epitope spreading), cells, cytokines or other inflammatory mediators contribute to the progress from initial activation to a chronic state of autoimmune diseases.

• Journal of the Korean Vacuum Society
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• v.5 no.2
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• pp.99-106
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• 1996

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonhstrates its excellent utility for the complex depth profile system . It includes the stable restoration of depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.