• Journal of the Korean Society of Earth Science Education
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• v.1 no.1
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• pp.41-51
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• 2008

For teaching-learning to geological region of earth science part in science education, middle school, the practical uses of natural science museum are very effective. So, the appropriate uses of the natural science museum are necessary for the teaching and learning of Science Education. This study aims to consider the presentation characteristics of the natural science museum and to examine how is effective it to geological region in middle school science curricula on those uses. From the results, the natural science museum is low in multi-sided and open-endedness presentation characteristics but high in ones of accessible characteristic. And its presentations are good in multimodal characteristics using supported materials but relatively low in relevant and multimedia ones. In the museum, diorama and self-performing presentation types are not but internet ones are most. The presentations of the natural science museum are mainly assigned to knowledge region linked to basic science concepts but relatively insufficient in STS aspects, on the basis of connection the presentations with middle school science curricula. It is respected that these insufficiencies might be diminished by variable arrangements of and explanations to the presentations for understanding improvements. And, applies to the presentations in STS may be encountered, if multi-sided observations to them is available.

• Journal of Science of Art and Design
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• v.9
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• pp.117-136
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• 2006

The purpose of the present study is to explore the possibility of computer graphics as a new expression tool for high-grade elementary students' poster making by suggesting specific teaching-learning methods focused on expression using computer graphics to make posters in Unit 9 'Designing Notices' for 6th-grade elementary students. Through this study, we confirmed various possibilities of computer graphics as a new medium for art education and particularly its possibility for children's creative expression activities in expressing images hard to express with paper and brush and applying desired colors to the picture. The use of computer graphics as a new paradigm of art education in the 21st century is expected to contribute to the improvement of diversified visual literacy. Thus, art class in school education needs to take an active attitude in intrdoducing various multimedia.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.205-217
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• 2018

Deep learning using convolutional neural networks (CNNs) is being studied in various fields of image recognition and these studies show excellent performance. In this paper, we compare the performance of CNN architectures, KCR-AlexNet and KCR-GoogLeNet. The experimental data used in this paper is obtained from PHD08, a large-scale Korean character database. It has 2,187 samples of each Korean character with 2,350 Korean character classes for a total of 5,139,450 data samples. In the training results, KCR-AlexNet showed an accuracy of over 98% for the top-1 test and KCR-GoogLeNet showed an accuracy of over 99% for the top-1 test after the final training iteration. We made an additional Korean character dataset with fonts that were not in PHD08 to compare the classification success rate with commercial optical character recognition (OCR) programs and ensure the objectivity of the experiment. While the commercial OCR programs showed 66.95% to 83.16% classification success rates, KCR-AlexNet and KCR-GoogLeNet showed average classification success rates of 90.12% and 89.14%, respectively, which are higher than the commercial OCR programs' rates. Considering the time factor, KCR-AlexNet was faster than KCR-GoogLeNet when they were trained using PHD08; otherwise, KCR-GoogLeNet had a faster classification speed.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.115-123
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• 2015

The infrared light is known to be less dependent on background light compared to the visible light, and thus many applications such as remote sensing and image surveillance use the infrared image. Similar to color images, infrared images can also be degraded by hazy weather condition, and consequently the performance of the infrared image-based applications can decrease. Nevertheless, infrared image dehazing has not received significant interest. In this paper, we analyze the characteristic of infrared images, especially near-infrared (NIR) images, and present an NIR dehazing algorithm using the analyzed characteristics. In particular, a machine learning framework is adopted to obtain an accurate transmission map and several post-processing methods are used for further refinement. Experimental results show that the proposed NIR dehazing algorithm outperforms the conventional color image dehazing method for NIR image dehazing.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.21-28
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• 2015

Feature normalization as a pre-processing step has been widely used to reduce the effect of different scale in each feature dimension and error rate in classification. Most of the existing normalization methods, however, do not use the class labels of data points and, as a result, do not guarantee the optimality of normalization in classification aspect. A supervised rank normalization method, combination of rank normalization and supervised learning technique, was proposed and demonstrated better result than others. In this paper, another technique, training sample selection, is introduced in supervised feature normalization to reduce classification error more. Training sample selection is a common technique for increasing classification accuracy by removing noisy samples and can be applied in supervised normalization method. Two sample selection measures based on the classes of neighboring samples and the distance to neighboring samples were proposed and both of them showed better results than previous supervised rank normalization method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.71-79
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• 2017

In this paper, we implemented the exchange rate forecasting neural network using heterogeneous computing. Exchange rate forecasting requires a large amount of data. We used a neural network that could leverage this data accordingly. Neural networks are largely divided into two processes: learning and verification. Learning took advantage of the CPU. For verification, RTL written in Verilog HDL was run on FPGA. The structure of the neural network has four input neurons, four hidden neurons, and one output neuron. The input neurons used the US $ 1, Japanese 100 Yen, EU 1 Euro, and UK £ 1. The input neurons predicted a Canadian dollar value of $ 1. The order of predicting the exchange rate is input, normalization, fixed-point conversion, neural network forward, floating-point conversion, denormalization, and outputting. As a result of forecasting the exchange rate in November 2016, there was an error amount between 0.9 won and 9.13 won. If we increase the number of neurons by adding data other than the exchange rate, it is expected that more precise exchange rate prediction will be possible.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.2
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• pp.157-165
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• 2015

The purpose of this study is to analyse literacy of children from multicultural backgrounds, and identify cognitive-linguistic predictors that can affect their literacy. First, the higher-grade students showed better cognitive-linguistic variables in reading and writing performance. Second, it has been noted that the predictor variable of reading in children from multicultural backgrounds was homeostasis in visual form, which is a sub-variable of visual perception. This implies that detained characteristics play an important role in reading prerequisite. Therefore it can be said that it is more important to recognise features and clues about the details than reading familiar words. Furthermore, learning consonants and vowels should come first rather than studying letters at the first stages of learning Korean.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.5
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• pp.173-185
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• 2016

As a dual-degree program/exchange student program becomes widespread, the faculty and students consisting of a course are being globalized. Recently, there has been an online or blended learning-based course, which is evolved from a conventional offline course. However, the course has no consideration of a dual-degree program or exchange student program because it is limited to a domestic university. To create and manage a global course, there have several of difficulties in the aspects of cost or effectiveness. As a solution to tackle them, it is necessary to do research on providing blended global courses with a fusion approach of online and offline. In this paper, we studied and presented a model of blended global courses. To create and maintain overseas scholar-oriented courses, we devised eight types of blended global courses depedning on their opening time and the cooperative relation between online and offline and made their comparative analysis. The blended global course proposed in this paper can be applied to cultivating global human resources in universities.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.11
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• pp.519-528
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• 2016

Most cultural contents currently we face are not suitable for associating with state of arts and high technology as simply providing one-sided learning. Pictures and movies of cultural contents also sees to utilize for efficacy of cultural education. There are still some limitations to draw interest from users when providing one-sided learning for cultural study, which aims to only deliver knowledge itself. In this paper, we propose interactive HMD VR cultural contents that can support more experience to get rid of aforementioned limitations. To this end, we first select quite interesting and wellknown cultural contents from world wide to draw more attention and effect. To increase immersion, presence and interactivity we have used HMD VR and Leapmotion, which intentionally draws more attention to increase interest. The cultural contents also facilitate augmented information as well as puzzle gaming components. To verify, we have carried out a user study as well.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.155-160
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• 2023

This paper presents a method for predicting blood pressure using the photoplethysmography signals. First, after measuring the optical blood flow signal, artifacts are removed through a preprocessing process, and a signal for learning is obtained. In addition, weight and height, which affect blood pressure, are measured as additional information. Next, a system is built to estimate systolic and diastolic blood pressure by learning the photoplethysmography signals, height, and weight as input variables through an artificial intelligence algorithm. The constructed system predicts the systolic and diastolic blood pressures using the inputs. The proposed method can continuously predict blood pressure in real time by receiving photoplethysmography signals that reflect the state of the heart and blood vessels, and the height and weight of the subject in an unconstrained method. In order to confirm the usefulness of the artificial intelligence-based blood pressure prediction system presented in this study, the usefulness of the results is verified by comparing the measured blood pressure with the predicted blood pressure.