• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.287-294
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• 2007

Many classification algorithms for real world data suffer from a data class imbalance problem. To solve this problem, various methods have been proposed such as altering the training balance and designing better sampling strategies. The previous methods are not satisfy in the distribution of the input data and the constraint. In this paper, we propose a focused sampling method which is more superior than previous methods. To solve the problem, we must select some useful data set from all training sets. To get useful data set, the proposed method devide the region according to scores which are computed based on the distribution of SOM over the input data. The scores are sorted in ascending order. They represent the distribution or the input data, which may in turn represent the characteristics or the whole data. A new training dataset is obtained by eliminating unuseful data which are located in the region between an upper bound and a lower bound. The proposed method gives a better or at least similar performance compare to classification accuracy of previous approaches. Besides, it also gives several benefits : ratio reduction of class imbalance; size reduction of training sets; prevention of over-fitting. The proposed method has been tested with kNN classifier. An experimental result in ecoli data set shows that this method achieves the precision up to 2.27 times than the other methods.

• Cartoon and Animation Studies
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• s.49
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• pp.425-464
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• 2017

The Knowledge of the Channel (e) is often used as educational materials; it delivers very short but compelling message of strong or interesting timeliness. However, as the media environment changes, expectations and demands for The Knowledge The Knowledge of the Channel (e) is used in school education and what should be improved upon to increase utilization of educational resources. We surveyed 361 elementary, middle and high school teachers and analyzed the frequency of using, approach and learning activities of The Knowledge of the Channel (e) in school education. We also analyzed difficulties in using it in the school and what improvements should be made. Result show that the frequency of using The Knowledge of the Channel (e) in school is highest in elementary schools, followed by middle school, and then high school. Teachers strongly consider curricular relevance when selecting broadcasting contents for education, and among programs of EBS(Educational Broadcasting System), most frequently use The Knowledge of the Channel (e). The The Knowledge of the Channel (e) is mainly used as an incentive for increasing motivation. When examined by elementary school curriculum, this material is highly utilized in subjects with content such as society, morality, and science, or with approaches that require various perspectives. However, it is difficult for teachers to find materials directly related to their classes, and since other media content similar to The Knowledge of the Channel (e) is abundant, the utilization of The Knowledge of the Channel (e) is decreasing. To improve this, The Knowledge of the Channel (e) needs to improve its platform and transformed the type of The Knowledge of the Channel (e) content being provided on social media.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.85-92
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• 2019

A 3D virtual character playing a role in a digital story-telling has a unique style in its appearance and motion. Because the style reflects the unique personality of the character, it is very important to preserve the style and keep its consistency. However, when the character's motion is directly controlled by a user's motion who is wearing motion sensors, the unique style can be discarded. We present a novel character motion control method that uses only a small amount of animation data created only for the character to preserve the style of the character motion. Instead of machine learning approaches requiring a large amount of training data, we suggest a search-based method, which directly searches the most similar character pose from the animation data to the current user's pose. To show the usability of our method, we conducted our experiments with a character model and its animation data created by an expert designer for a virtual reality game. To prove that our method preserves well the original motion style of the character, we compared our result with the result obtained by using general human motion capture data. In addition, to show the scalability of our method, we presented experimental results with different numbers of motion sensors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.841-849
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• 2023

Construction projects have risks due to various factors such as construction delays and construction accidents. Based on these construction risks, the method of calculating the construction period of the construction project is mainly made by subjective judgment that relies on supervisor experience. In addition, unreasonable shortening construction to meet construction project schedules delayed by construction delays and construction disasters causes negative consequences such as poor construction, and economic losses are caused by the absence of infrastructure due to delayed schedules. Data-based scientific approaches and statistical analysis are needed to solve the risks of such construction projects. Data collected in actual construction projects is stored in unstructured text, so to apply data-based risks, data pre-processing involves a lot of manpower and cost, so basic data through a data classification model using text mining is required. Therefore, in this study, a document-based data generation classification model for risk management was developed through a data classification model based on SVM (Support Vector Machine) by collecting construction project documents and utilizing text mining. Through quantitative analysis through future research results, it is expected that risk management will be possible by being used as efficient and objective basic data for construction project process management.

• Journal of The Korean Association For Science Education
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• v.20 no.1
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• pp.20-28
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• 2000

We examined how science teachers in academic high schools perceived the 6th science curriculum and how they practiced under the curriculum. A nationwide survey was administered to obtain the responses from 402 teachers of 135 high schools. Most thought that the main themes of curriculum revision were well-embedded in the 'objectives', and that the 'content and content structure' were proper. However, they thought that the 'objectives' were not stated explicitly enough to develop teaching materials and to improve actual teaching and evaluation, and that some statements in the sections of 'method' and 'evaluation' were not proper if considered actual teachers' ability to teach inquiry and educational facilities. Many teachers also felt that the information about the curriculum was not sufficiently included at in-service teacher training programs, and that students' knowledge, attitude, and problem solving ability were not enhanced. Only few teachers were found to apply the STS approaches, reconstruct lessons, vary the structure of learning group, and develop evaluation tools with their colleagues. The lack of the practices was explained by entrance-examination-centered instruction and assessment, poor educational facilities, and lack of innovative teaching materials.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.85-94
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• 2010

This paper introduces a novel way to leverage convolution parse tree kernel to extract the interaction information between two proteins in a sentence without multiple features, clues and complicated kernels. Our approach needs only the parse tree alone of a candidate sentence including pairs of protein names which is potential to have interaction information. The main contribution of this paper is two folds. First, we show that for the PPI, it is imperative to execute parse tree pruning removing unnecessary context information in deciding whether the current sentence imposes interaction information between proteins by comparing with the latest existing approaches' performance. Secondly, this paper presents that tree kernel decay factor can play an pivotal role in improving the extraction performance with the identical learning conditions. Consequently, we could witness that it is not always the case that multiple kernels with multiple parsers perform better than each kernels alone for PPI extraction, which has been argued in the previous research by presenting our out-performed experimental results compared to the two existing methods by 19.8% and 14% respectively.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.99-112
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• 2020

This study empirically analyzed the relationship with major influencing factors in enhancing innovation capability of start-ups and their influence on innovation performance. If the existing innovation competency studies were analyzed from a general corporate perspective, In this study, it was analyzed from the perspective of start-up companies with less than 7 years of founding. As a result of a survey on startups, learning competency among the sub-variables of innovation competency, R&D competency and marketing competency are significant positive (+) consistent with both organizational competence related to organizational culture and organizational goals, technology commercialization competency, and close product competency. Has been shown to affect. The technical competence part does not have a significant effect on the product competency. However, it could not be interpreted that the importance of these competencies was low. This is because although technical competence did not directly affect product competency, it was analyzed as a meaningful result in relation to R&D competency. In addition, the characteristics of the company were classified into technology orientation and market orientation, and the relationship between each sub-variable was analyzed. The technical competence of a technology-oriented company did not have a significant effect on the product competency, but it was found that it had an effective effect on the R&D capacity. It is also consistent with the research findings that the initial survival rate is low as the characteristics of start-ups are often based on technology and ideas. Based on these results, There is a difference in major innovation capabilities according to the growth stage of a company. From a practical point of view, I would like to present approaches and implications for strengthening the competence of start-ups.

• Journal of Elementary Mathematics Education in Korea
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• v.18 no.1
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• pp.1-17
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• 2014

Instructions for the commutative property of multiplication at elementary schools tend to be based on checking the equality between the quantities of 'a times b 'and b' times a, ' for example, $3{\times}4=12$ and $4{\times}3=12$. This article critically examined the approaches to teach the commutative property of multiplication from Kant's perspective of mathematical knowledge. According to Kant, mathematical knowledge is a priori. Yet, the numeric exploration by checking the equality between the amounts of 'a groups of b' and 'b groups of a' does not reflect the nature of apriority of mathematical knowledge. I suggest we teach the commutative property of multiplication in a way that it helps reveal the operational schema that is necessarily and generally involved in the transformation from the structure of 'a times b' to the structure of 'b times a.' Distributive reasoning is the mental operation that enables children to perform the structural transformation for the commutative property of multiplication by distributing a unit of one quantity across the other quantity. For example, 3 times 4 is transformed into 4 times 3 by distributing each unit of the quantity 3, which results in $3{\times}4=(1+1+1){\times}4=(1{\times}4)+(1{\times}4)+(1{\times}4)+(1{\times}4)=4+4+4=4{\times}3$. It is argued that the distributive reasoning is also critical in learning the subsequent mathematics concepts, such as (a whole number)${\times}10$ or 100 and fraction concept and fraction multiplication.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.53-61
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• 2022

Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.