• Journal of Digital Contents Society
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• v.17 no.6
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• pp.613-621
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• 2016

This paper has the first aim to analyze Elsa's magic power of why and how she, as a heroine in the animation of Frozen, is in the emotion of fear and anger. This paper will explain why these two emotions are twisted compound to identify Elsa's iced emotion in the ice kingdom. And secondly, this paper attempts to connect Elsa's fear emotion in her real life is the other flip with that of anger throughout the characters' network in Frozen, which symbolically reflect the feminine pattern of real society that Walt Disney prospects for the dream society. Through the cognitive process for Elsa's ice kingdom between emotion status and social network, we can assume the pattern of social network with emotional chart and the archetype of human emotion through the cognitive-emotional storytelling on the emotion of Elsa in Frozen.

• Journal of Educational Research in Mathematics
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• v.13 no.2
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• pp.159-178
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• 2003

This study analyzes on the reasoning in the process of justification and mathematical problem solving in our primary mathematics textbooks. In our analyses, we found that the inductive reasoning based on the paradima-tic example whose justification is founnded en a local deductive reasoning is the most important characteristics in our textbooks. We also found that some propositions on the properties of various quadrangles impose a deductive reasoning on primary students, which is very difficult to them. The inductive reasoning based on enumeration is used in a few cases, and analogies based on the similarity between the mathematical structures and the concrete materials are frequntly found. The exposition based en a paradigmatic example, which is the most important characteristics, have a problematic aspect that the level of reasoning is relatively low In Miyazaki's or Semadeni's respects. And some propositions on quadrangles is very difficult in Piagetian respects. As a result of our study, we propose that the level of reasoning in primary mathematics is leveled up by degrees, and the increasing levels are following: empirical justification on a paradigmatic example, construction of conjecture based on the example, examination on the various examples of the conjecture's validity, construction of schema on the generality, basic experiences for the relation of implication.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.129-137
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• 2020

Recently, software size and program code complexity have increased due to application to various fields of software. Accordingly, the existence of program bugs inevitably occurs, and the cost of software maintenance is increasing. In open source projects, developers spend a lot of debugging time when solving a bug report assigned. To solve this problem, in this paper, we apply SeqGAN algorithm to software bug repair. In detail, the SeqGAN model is trained based on the source code. Open similar source codes during the learning process are also used. To evaluate the suitability for the generated candidate patch, a fitness function is applied, and if all test cases are passed, software bug correction is considered successful. To evaluate the efficiency of the proposed model, it was compared with the baseline, and the proposed model showed better repair.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.917-924
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• 2008

Motion estimation and compensation in the spatial domain check the searching area of specified size in the previous frame and search block to minimize the difference with current block. When we check the searching area, it consumes the most encoding times due to increasing the complexity. We can solve this fault by means of motion estimation using shifting matrix in the transform domain instead of the spatial domain. We derive so the existed shifting matrix to a new recursion equation that we decrease more computations. We modify simply vertical shifting matrix and horizontal shifting matrix in the transform domain for motion estimation of half-pixel accuracy. So, we solve increasing computation due to bilinear interpolation in the spatial domain. Simulation results prove that motion estimation by the proposed algorithm in DCT-based transform domain provides higher PSNR using fewer bits than results in the spatial domain.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.11-22
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• 2004

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem(CSP) in which variables and constraints are distributed among multiple automated agents. ACSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CAPs. In recent years, many new backtracking algorithms for solving distributed CSPs have been proposed. But most of all, they have common drawbacks that the algorithm assumes the priority of agents is static. In this thesis, we establish a basic algorithm for solving distributed CSPs called dynamic priority search algorithm that is more efficient than common backtracking algorithms in which the priority order is static. In this algorithm, agents act asynchronously and concurrently based on their local knowledge without any global control, and have a flexible organization, in which the hierarchical order is changed dynamically, while the completeness of the algorithm is guaranteed. And we showed that the dynamic priority search algorithm can solve various problems, such as the distributed 200-queens problem, the distributed graph-coloring problem that common backtracking algorithm fails to solve within a reasonable amount of time. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-making. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.261-269
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• 2003

Steel bridges, which have been damaged by load and corrosion, need repair or strengthening. In general, before the repair welding procedure, cutting procedure carry out. Therefore, the investigating of the behavior of stress generated by cutting is so important for safety of structure. Residual stress produced by gas cutting was analyzed using 2D and 3D thermal elasto plastic FEM. According to the results, the magnitude of temperature was analyzed by 2D FEM is smaller than that was analyzed using the 3D FEM program at the start and end edge of flange. And the magnitude and distribution of residual stress of perpendicular to the cutting line was analyzed by the 2D FEM program was similar to that was analyzed by the 3D FEM program. Therefore, it is possible to predict of cutting stress by 2D and 3D FEM.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.48-57
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• 2010

Previous post sender recognition study was focused on recognizing the address of receiver. Relatively, there was lack of study to recognize the information of sender's address. Post sender recognition study is necessary for the service and application using sender information such as returning. This paper did the experiment and suggested how to recognize post sender using SIFT. Although SIFT shows great recognition rate, SIFT had problems with time and mis-recognition. One is increased time to match keypoints in proportion as the number of registered model. The other is mis-recognition of many similar keypoints even though they are all different models due to the nature of post sender. To solve the problem, this paper suggested SIFT adding distance function and did the experiment to compare time and function. In addition, it is suggested how to register and classify models automatically without the manual process of registering models.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.492-507
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• 2008

Many classical network analysis methods approach networks in aspatial perspectives. Measuring network reliability and finding critical nodes in particular, the analyses consider only network connection topology ignoring spatial components in the network such as node attributes and edge distances. Using local network autocorrelation measure, this study handles the problem. By quantifying similarity or clustering of individual objects' attributes in space, local autocorrelation measures can indicate significance of individual nodes in a network. As an application, this study analyzed internet backbone networks in the United States using both classical disjoint product method and Getis-Ord local G statistics. In the process, two variables (population size and reliability) were applied as node attributes. The results showed that local network autocorrelation measures could provide local clusters of critical nodes enabling more empirical and realistic analysis particularly when research interests were local network ranges or impacts.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.19-27
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• 2023

In the process of collecting social reviews, a number of noise reviews irrelevant to a given search keyword can be included in the search results. To filter out such reviews, machine learning can be used. However, if the number of reviews is insufficient for a target place to be analyzed, filtering accuracy can be degraded due to the lack of training data. To resolve this issue, we propose a supervised learning method to improve accuracy of the noise review filtering for the places with insufficient reviews. In the proposed method, training is not performed by an individual place, but by a group including several places with similar characteristics. The classifier obtained through the training can be used for the noise review filtering of an arbitrary place belonging to the group, so the problem of insufficient training data can be resolved. To verify the proposed method, a noise review filtering model was implemented using LSTM and BERT, and filtering accuracy was checked through experiments using real data collected online. The experimental results show that the accuracy of the proposed method was 92.4% on the average, and it provided 87.5% accuracy when targeting places with less than 100 reviews.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.260-267
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• 2009

It is very difficult to form a desired complex sound field at a designated region precisely as an application of acoustic arrays, which is one of important objects of array systems. To solve the problem, a filter design method was suggested, which employed the concept of an inverse method using the acoustical holography based on the boundary element method. In the acoustical holography used for the source identification, the measured field data are employed to reconstruct the vibro-acoustic parameters on the source surface. In the analogous problem of source array design, the desired field data at some specific points in the sound field was set as constraints and the volume velocity at the surface points of the source plane became the source signal to satisfy the desired sound field. In the filter design, the constraints for the desired sound field are set, first. The array source and given space are modelled by the boundary elements. Then, the desired source parameters are inversely calculated in a way similar to the holographic source identification method. As a test example, a target field comprised of a quiet region and a plane wave propagation region was simultaneously realized by using the array with 16 loudspeakers.