• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.73-75
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• 1987

The paper proposes a class of discrete-time adaptive controller which may be applicable without sufficient a priori information. Against choices of the Information, GPC algorithm may seem to be more robust than any other methods reported, but it is the method based on Indirect approach. It is, therefore, reasonable to propose an algorithm via the zero-gain prediction, in which the control parameters are directly estimated and calculated.

• East Asian mathematical journal
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• v.26 no.5
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• pp.615-626
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• 2010

In this paper, we analyze discontinuous Galerkin methods with penalty terms, namly symmetric interior penalty Galerkin methods, to solve nonlinear parabolic equations. We construct finite element spaces on which we develop fully discrete approximations using extrapolated Crank-Nicolson method. We adopt an appropriate elliptic-type projection, which leads to optimal ${\ell}^{\infty}$ ($L^2$) error estimates of discontinuous Galerkin approximations in both spatial direction and temporal direction.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.3-24
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• 2001

In cases where strong a priori knowledge about the object being analyzed is available, it can be embedded into the formulation of the snake model. When prior knowledge of shape is available for a specific application, information concerning the shape of the desired objects can be incorporated into the formulation of the snake model as an active contour model. In this paper we show Five points algorithm can be applied to design invariant energy.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.365-374
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• 2020

In this paper, we analyzed how 5-year-old children perceive a robot's ability to attribute mental states to oneself and to others, which shall hereafter be referred to as a robot's theory of mind (RToM). A total of 34 5-year-old children were given two typical false-belief tasks, an 'unexpected-contents task' and a 'change-of-location task', in order to evaluate whether a child's perceived RToM was connected to their own ToM. In addition, we investigated whether a child's perception of RToM was influenced by either a priori experience with robots or that child's gender. The results are as follows. Firstly, the 5- year-old preschool children universally recognized robots as beings that have a human-like mind both in 1st order and 2nd order perspectives, which indicates that children perceive robots as beings distinct from mechanical toys. Secondly, a priori child-robot interaction experience was found to have a positive influence on a child's perceived RToM. Thirdly, the gender of children did not significantly affect their perceived RToM. This study serves to add to the macroscopic results of prior research, which indicate that children perceive robots as intermediate beings between living and inanimate objects: significantly, it analyzes the children's perception of robots through the lens of theory of mind, which is one of the key elements of cognitive development. This research lays the foundations for designing effective child-robot interactions, in situations in which robots serve as peers or assistants for educational purposes.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.44-49
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• 2007

It is difficult to obtain high-resolution images by 3D gravity inversion, because the problem is extremely underdetermined - there are too many model parameters. In order to reduce the number of model parameters we propose a 3D gravity inversion scheme utilising Euler deconvolution as a priori information. The essential point of this scheme is the reduction of the nonuniqueness of solutions by restricting the inversion space with the help of Euler deconvolution. We carry out a systematic exploration of the growing body process, but only in the restricted space within a certain radius of the Euler solutions. We have tested our method with synthetic gravity data, and also applied it to a real dataset, to delineate underground cavities in a limestone area. We found that we obtained a more reasonable subsurface density image by means of this combination between the Euler solution and the inversion process.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.632-641
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• 2000

Conventional character extraction methods extract character regions using methods such as color reduction, region split and merge and texture analysis from the whole image. Because these methods use many heuristic variables and thresholding values derived from a priori knowledge, it is difficult to generalize them algorithmically. In this paper, we propose a method that can extract character regions using a topographical feature extraction method and a point-line-region extension method. The proposed method can also solve the problems of conventional methods by reducing heuristic variables and generalizing thresholding values. We see that character regions can be extracted by generalized variables and thresolding values without using a priori knowledge of character region. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is over 98%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.1-11
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• 2006

This paper presents a digital auto-focusing method using a priori estimated point-spread-functions (PSF) database. The proposed algorithm efficiently removes out-of-focus blur in a degraded input image by selecting the optimal PSF from the database. The database consists of optical characteristics of image formation system. The PSF selection Process is performed based on a novel focusing measure. The proposed method includes a spatially adaptive filter for removing both noise and ringing artifacts. Experimental results show that the proposed method efficiently removes out-of-focus blur using significantly reduced computational load compared with the existing method.

• Environmental Engineering Research
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• v.11 no.4
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• pp.217-231
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• 2006

The gas-phase formation of polychlorinated naphthalenes (PCNs) and dibenzofurans (PCDFs) was experimentally investigated by slow combustion of the three chlorophenols (CPs): 2-chlorophenol (2-CP), 3-chlorophenol (3-CP) and 4-chlorophenol (4-CP), in a laminar flow reactor over the range of 550 to $750^{\circ}C$ under oxidative condition. Contrary to the a priori hypothesis, different distributions of PCN isomers were produced from each CP. To explain the distributions of polychlorinated dibenzofuran (PCDF) and PCN congeners, a pathway is proposed that builds on published mechanisms of PCDF formation from chlorinated phenols and naphthalene formation from dihydrofulvalene. This pathway involves phenoxy radical coupling at unsubstituted ortho-carbon sites followed by CO elimination to produce dichloro-9, 10-dihydrofulvalene intermediates. Naphthalene products are formed by loss of H and/or Cl atoms and rearrangement. The degree of chlorination of naphthalene and dibenzofuran products decreased as temperature increased, and, on average, the naphthalene congeners were less chlorinated than the dibenzofuran congeners. PCDF isomers were found to be weakly dependent to temperature, suggesting that phenoxy radical coupling is a low activation energy process. Different PCN isomers, on the other hand, are formed by alternative fusion routes from the same phenoxy radical coupling intermediate. PCN isomer distributions were found to be more temperature sensitive, with selectivity to particular isomers decreasing with increasing temperature.

• School Mathematics
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• v.18 no.3
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• pp.733-747
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• 2016

To describe mathematics learning relying on a priori assumptions about the learners has a risk of assuming the learners as well-prepared subjects. In this study we investigate the epistemological perspective of Gilles Deleuze which is expected to give overcome this risk. Then we analyze the constructivist's epistemology and prior discussions about learning mathematics in the preceding studies accordingly. As a result, a priori assumption on which students are regarded as well-prepared for learning mathematics is reconsidered and we propose a new model of thought to highlight the involuntary aspect of the occurrence of thinking facilitated by the encounter with mathematical signs. This perspective gives a new vision on involuntary aspects of mathematics learning and the learner's confusion or difficulty at the starting point of learning.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.41-50
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• 2024

An increasing pattern of extreme rainfall recently affected the rural infrastructures with catastrophic damage, especially the overtopping of a fill dam embankment in the Republic of Korea. The overtopping was caused by the sudden increase in reservoir water level over the dam crest level, and it was not easy work to predict a priori because of its non-linear behavior. Fuzzy time series (FTS) is a fuzzy-logic inference procedure and is suited to apply to non-linear prediction methods such as machine learning. This study used the Wangshin reservoir and Goesan-dam cases, which experienced overtopping in 2023 and 2022, respectively. Wangshin Reservoir was a typical agricultural fill dam and needed to stack more available data, with only the daily storage rate (water level) of 7 years, starting on 2 May 2016. Therefore, we used Goesan-dam data to select appropriate variables and compare the analysis result, which was stacked with about 17 years of records. The analyses adapted LSTM to compare with FTS. As a result, the reservoir water level was applied to predict the overtopping water level, and it was shown that the FTS method could predict the actual water levels effectively according to the result of comparison with LSTM. Then, the FTS method was expected to predict reservoir water level a priori to make appropriate countermeasures on overtopping events as one of the alternatives.