• East Asian mathematical journal
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• v.37 no.4
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• pp.523-541
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• 2021

Education for the future society should emphasize the experience of sharing, coexisting, and solving problems in cooperation with each other in the community. Accordingly, in addition to the problem-solving capability, which is the ultimate goal of mathematics education, it is necessary to strengthen the capability to solve unstructured problems through collaboration. This study attempted to suggest that solving complex problems through collaboration is used in school classes or gifted education by introducing polymath that solves problems using collective intelligence. Accordingly, a target problem was set and an example of polymath in which community members exert each other's intelligence to solve the problem. In addition, by investigating the perceptions of students who have experienced polymath, positive aspects and improvements of polymath were suggested. Through this, this study can contribute to revitalization of mathematics teaching and learning methods using collective intelligence.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.246-250
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• 2006

As a result of the rapid development in the digital content industry, designers have to visualize colors across a range of digital media in a relevant and sophisticated manner. The purpose of this study is to develop a new digital color design education curriculum for enhancing learners' capability of digital color management. This study presents an original university-level color design curriculum for digital color learning that includes traditional color learning. In order to develop interactive pedagogy that provides diverse color experiences to students, this study suggestes a blended learning method that combines face-to-face instruction and web-based instruction. Through two case studies at universities, this paper illustrate the effectiveness of the proposed digital color design curriculum.

• Journal of IKEEE
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• v.23 no.4
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• pp.1400-1407
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• 2019

In this paper, we propose a support vector machine (SVM) based gas classifier that can support real-time self-learning. The modified sequential minimal optimization (MSMO) algorithm is employed to train the proposed SVM. By using a shared structure for learning and classification, the proposed SVM reduced the hardware area by 35% compared to the existing architecture. Our system was implemented with 3,337 CLB (configurable logic block) LUTs (look-up table) with Xilinx Zynq UltraScale+ FPGA (field programmable gate array) and verified that it can operate at the clock frequency of 108MHz.

• Journal of the Korean Society of Earth Science Education
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• v.6 no.2
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• pp.112-123
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• 2013

Under this research, the survey is made on the definitive influence of the first-year education process of the science focus school for each of humanities, science and science core courses and the level of satisfaction of the non-curriculum experiment activity program for each course to find out the effectiveness of the first-year education process of the science focus school. For this purpose, this research has set three research issues. First, By clarifying the research result through the first-year education curriculum for science core school, noticeable change was observed for science focus school students through the change of attitude related to science for each desired course of students. Second, in the self-directed learning characteristics change, there was meaningful change for each desired field of students. Students hoping for humanities curriculum had great help in improvement of creative thinking for openness, creativeness and the like, but the influence was slightly insufficient in the moderation and control capability on themselves in learning attitude. Third, By analyzing the research result comprehensively, the first-year education curriculum for science core school provides high level of tailored science learning for the science focus school students and the level of satisfaction for students was significantly high.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.147-165
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• 2021

In this work, we empirically evaluated the efficiency of the recent EfficientNetB0 model to identify and diagnose malaria parasite infections in blood smears. The dataset used was collected and classified by relevant experts from the Lister Hill National Centre for Biomedical Communications (LHNCBC). We prepared our samples with minimal image transformations as opposed to others, as we focused more on the feature extraction capability of the EfficientNetB0 baseline model. We applied transfer learning to increase the initial feature sets and reduced the training time to train our model. We then fine-tuned it to work with our proposed layers and re-trained the entire model to learn from our prepared dataset. The highest overall accuracy attained from our evaluated results was 94.70% from fifty epochs and followed by 94.68% within just ten. Additional visualization and analysis using the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm visualized how effectively our fine-tuned EfficientNetB0 detected infections better than other recent state-of-the-art DCNN models. This study, therefore, concludes that when fine-tuned, the recent EfficientNetB0 will generate highly accurate deep learning solutions for the identification of malaria parasites in blood smears without the need for stringent pre-processing, optimization, or data augmentation of images.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.181-195
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• 2023

To predict the rheological behaviours along with the compressive strength of self-compacting concrete that incorporates environmentally friendly ingredients as cement substitutes, a comparative evaluation of machine learning methods is conducted. To model four parameters, slump flow diameter, L-box ratio, V-funnel time, as well as compressive strength at 28 days-a complete mix design dataset from available pieces of literature is gathered and used to construct the suggested machine learning standards, SVM, MARS, and Mp5-MT. Six input variables-the amount of binder, the percentage of SCMs, the proportion of water to the binder, the amount of fine and coarse aggregates, and the amount of superplasticizer are grouped in a particular pattern. For optimizing the hyper-parameters of the MARS model with the lowest possible prediction error, a gravitational search algorithm (GSA) is required. In terms of the correlation coefficient for modelling slump flow diameter, L-box ratio, V-funnel duration, and compressive strength, the prediction results showed that MARS combined with GSA could improve the accuracy of the solo MARS model with 1.35%, 11.1%, 2.3%, as well as 1.07%. By contrast, Mp5-MT often demonstrates greater identification capability and more accurate prediction in comparison to MARS-GSA, and it may be regarded as an efficient approach to forecasting the rheological behaviors and compressive strength of SCC in infrastructure practice.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.167-177
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• 2024

With advancements in satellite technology, interest in target detection and identification is increasing quantitatively and qualitatively. Synthetic Aperture Radar(SAR) images, which can be acquired regardless of weather conditions, have been applied to various areas combined with machine learning based detection algorithms. However, conventional studies primarily focused on the detection of stationary targets. In this study, we proposed a method to identify moving targets using an algorithm that integrates sub-aperture SAR images and cosine similarity calculations. Utilizing a transformer-based deep learning target detection model, we extracted the bounding box of each target, designated the area as a region of interest (ROI), estimated the similarity between sub-aperture SAR images, and determined movement based on a predefined similarity threshold. Through the proposed algorithm, the quantitative evaluation of target identification capability enhanced its accuracy compared to when training with the targets with two different classes. It signified the effectiveness of our approach in maintaining accuracy while reliably discerning whether a target is in motion.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.2
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• pp.5-23
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• 2015

The aim of this study is to analyze the effects of the creative writing program that is one of the practical strategy of information literacy on self-directed learning abilities of elementary school students. According to the results, this program raise the average score of 33.69 points from 130.14 to 163.83 significantly in their self-directed learning abilities. Among the specific abilities of them, this program affects learning planning and evaluation capability meaningfully. But the long term continuous of learning executive is not changed significantly by this program. As the results of after interview with the students who take part in this program, the most of them respond that they could reduce their fear of writing and apply the reading and writing strategies to other subjects. So, if we teach this program with subjects consistently and use the learning strategies of information literacy, we could improve the long term continuous of learning executive.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.3
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• pp.1-22
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• 2009

A firm's competitive capabilities become greater when the firm has a specific knowledge. There are many studies have been examined how to accumulate the firm specific knowledge and to get the competitive capability on the various perspectives. This study suggest that the conceptual framework on the absorptive capability through reviews on the knowledge management theory. And it also suggests that the proposition about the technological capability building process through the in depth case study on a small and medium sized company in a LCD industry. This study found the following major characteristics about the absorptive capability building and knowledge creating process. First, it is required to building an absorptive capability rapidly that the harmony of local capabilities, integrative capabilities, and intensity of effort. And the most important factor is the intensity of effort in a small and medium sized firm with a weak knowledge base. Second, it is required to develop an innovative new product that the utilization of expeditious learning mechanism based on the exploration and exploitation process. Finally, complementary assets are needed to proactive exploration and exploitation. Based on the findings, the theoretical and managerial implications are derives and the further research directions are proposed.

• 한국벤처창업학회:학술대회논문집
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• 2009.08a
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• pp.67-88
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• 2009

A firm's competitive capabilities become greater when the firm has a specific knowledge. There are many studies have been examined how to accumulate the firm specific knowledge and to get the competitive capability on the various perspectives. This study suggest that the conceptual framework on the absorptive capability through reviews on the knowledge management theory. And it also suggests that the proposition about the technological capability building process through the in depth case study on a small and medium sized company in a LCD industry. This study found the following major characteristics about the absorptive capability building and knowledge creating process. First, it is required to building an absorptive capability rapidly that the harmony of local capabilities, integrative capabilities, and intensity of effort. And the most important factor is the intensity of effort in a small and medium sized firm with a weak knowledge base. Second, it is required to develop an innovative new product that the utilization of expeditious learning mechanism based on the exploration and exploitation process. Finally, complementary assets are needed to proactive exploration and exploitation. Based on the findings, the theoretical and managerial implications are derives and the further research directions are proposed.