• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.894-906
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• 2006

There are many difficulties to develop a mobile contents due to many constraints on mobile environments. It is difficult to make a good mobile contents with only visual reduction of existing contents on wire Internet. Therefore, it is essential to devise the data representation and to develop the authoring tool to meet the needs of the mobile contents market. We suggest the compact mobile contents to learn Chinese characters and developed its authoring tool. The animation which our system produces is realistic as if someone writes letters with pen or brush. Moreover, our authoring tool makes a user generate a Chinese character animation easily and rapidly although she or he has not many knowledge in computer graphics, mobile programming or Chinese characters. The method to generate the stroke animation is following: We take basic character shape information represented with several contours from TTF(TrueType Font) and get the information for the stroke segmentation and stroke ordering from simple user input. And then, we decompose whole character shape into some strokes by using polygonal approximation technique. Next, the stroke animation for each stroke is automatically generated by the scan line algorithm ordered by the stroke direction. Finally, the ordered scan lines are compressed into some integers by reducing coordinate redundancy As a result, the stroke animation of our system is even smaller than GIF animation. Our method can be extended to rendering and animation of Hangul or general 2D shape based on vector graphics. We have the plan to find the method to automate the stroke segmentation and ordering without user input.

• Journal of the Korean association of regional geographers
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• v.9 no.4
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• pp.505-518
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• 2003

The purpose of this paper is to review Post-Fordist urban economic theories that have tackled the recent changes of urban economies in large cities in the world since 1980s, so that we can conceptualise the changes of urban economies in Korean cities. In the perspective of the Post-Fordist urban economic theories, the recent changes of urban economies in the world are deeply related to the transformation of capitalist world economic system from Fordism to Post-Fordism. To see these changes which can be called as the new urbanization process in the economic aspect, we will focus especially such theories as new industrial space (district) theory based on the flexible specialization paradigm, informational city theory based on the information and communication mode paradigm, and cluster and regional innovation theory based on the institution and network paradigm. Also we will consider the social polarization process and dual city phenomena that have been observed for the most part of big cities in the world.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• Journal of The Korean Association For Science Education
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• v.28 no.6
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• pp.685-695
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• 2008

An analysis on the Inquiry unit of Science 10 textbooks was conducted in terms of nature of science (NOS). The subject of the analysis was instructional objectives, activities and sentences in the unit of ten Science 10 textbooks. Contents of the instructional objectives could be grouped into nature of science, nature of scientists, scientific methods, and Science-Technology-Society. The concrete nature of scientific knowledge (SK) and constructing scientific theory or model, however, were not found in the objectives. The total number of activities in the Inquiry unit was 38. Seventeen out of them were presented without any supplemental or introductory materials, and 21 activities were provided with information followed by questions, discussions or investigations. For the most activities, any clear statements about NOS elements and desired/informed views of NOS were not made. The sentences of the Inquiry units were mixed up with constructivist and inductive views on NOS. The definition of science tended to be described based on the inductive view. And the generation of SK tended to be described as discovering regularities in natural phenomena rather than constructing theories. For science teachers who want to teach NOS effectively, stating clear learning objectives and elements of NOS and presenting reading materials with relevant views on nature of science were necessary.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.485-490
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• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• Journal of KIISE:Software and Applications
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• v.32 no.1
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• pp.1-9
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• 2005

In this paper we propose a modified fuzzy min-max neural network model for pattern classification and discuss the usefulness of the model. We define a new hypercube membership function which has a weight factor to each of the feature within a hyperbox. The weight factor makes it possible to consider the degree of relevance of each feature to a class during the classification process. Based on the proposed model, a knowledge extraction method is presented. In this method, a list of relevant features for a given class is extracted from the trained network using the hyperbox membership functions and connection weights. Ft)r this purpose we define a Relevance Factor that represents a degree of relevance of a feature to the given class and a similarity measure between fuzzy membership functions of the hyperboxes. Experimental results for the proposed methods and discussions are presented for the evaluation of the effectiveness and feasibility of the proposed methods.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.19-28
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• 2021

Recently, in the field of education, various attempts have been made to apply virtual reality technology to an educational field and use it as an educational medium. Accordingly, in the science subject area, it is necessary to simulate science experiments that can make various and active experiments out of various limitations such as space and situation by using virtual reality environment construction technology. In this study, after selecting a physics course from a science subject, an experimental simulation using a parabolic motion formula, one of physical phenomena, is implemented in a virtual space, and then used in actual physics education based on the learning standards of the STEAM theory. Prove this is possible. Through this, it was confirmed that a specific educational model using virtual reality space can be designed, and it shows that education can be conducted with more effective educational methods in various subjects of education through the combination of traditional educational model and modern technology. Regarding the results of the research, it suggests the possibility of future research plans and practical use in the educational field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.627-632
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• 2021

ITL (information-theoretic learning) has been applied successfully to adaptive signal processing and machine learning applications, but there are difficulties in deciding the kernel size, which has a great impact on the system performance. The correntropy algorithm, one of the ITL methods, has superior properties of impulsive-noise robustness and channel-distortion compensation. On the other hand, it is also sensitive to the kernel sizes that can lead to system instability. In this paper, considering the sensitivity of the kernel size cubed in the denominator of the cost function slope, a new adaptive kernel estimation method using the rate of change in error power in respect to the kernel size variation is proposed for the correntropy algorithm. In a distortion-compensation experiment for impulsive-noise and multipath-distorted channel, the performance of the proposed kernel-adjusted correntropy algorithm was examined. The proposed method shows a two times faster convergence speed than the conventional algorithm with a fixed kernel size. In addition, the proposed algorithm converged appropriately for kernel sizes ranging from 2.0 to 6.0. Hence, the proposed method has a wide acceptable margin of initial kernel sizes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.378-384
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• 2023

In this study, we aim to derive the descriptor vector conditions that can simultaneously achieve the efficiency and accuracy of artificial Neural Network Potentials (NNP). The material system selected is silicon, a highly applicable material in various industries. Atomic structure-dependent energy data for training artificial neural networks were generated through density functional theory calculations. Behler-Parrinello type atomic-centered symmetric functions were employed as descriptors, and various length vector NNPs were generated. These NNPs were applied to reproduce the structure and mechanical properties of silicon materials in molecular dynamics simulations. In our findings, the minimum vector length for achieving both learning and computational efficiency while maintaining property reproducibility is approximately 50. It was also observed that, for the same conditions, incorporating more angle-dependent symmetric functions into the descriptor vector, could enhance the accuracy of NNP. Our results can provide guidelines for optimizing the conditions of descriptor vectors to achieve both efficiency and accuracy of NNP, simultaneously.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.2 no.2
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• pp.46-58
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• 2003

The main purpose of developing HSE-based products is to make a human being feel the greatest comfort under the circumstances which vary according to the change of environmental element values. In order to attain a successful achievement, some evaluation and analysis on human sensibility should be proceeded ahead of developing them. In this paper, neural network theories are applied to analyse the structures of comfort sensibility and feeling which are hard to be expressed in mathematical form. In order to verify the performance of the HSE controller, a substitute for a real chamber for simulation is also developed in this study.