• Journal of Science Education
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• v.38 no.1
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• pp.205-229
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• 2014

The purposes of this study were to explore what components of science communication and its level are contained in text panels of exhibitions in natural history museums and to propose its development direction of exhibition education in Korea. First, to find out the component and level of science communication contained in exhibition panels, the researcher team developed the analyzing tool which was called SEPAT (Science Exhibition Panel Analyzing Tool), then employed them to profile the component and level of science communication. Second, the researchers introduced the exemplary designed media of exhibitions to demonstrate how much science communication could be enhanced. The results were made as follows. First, the components of science communication was considerably weighted toward to 'concept' one. There were also a few 'awareness' and 'engagement', both of which were under 5% in each zone of exhibition and there was not 'NOSI' or 'opinion' embedded in the analyzed exhibitions. Second, the various type of designing exhibitions were found to promote or enhance the restrictedly represented components of science communication. It is suggestable for exhibitions to be designed through various type of 'media' to enhance science communication. Visitors are required to experience rich science communication to meet their educational needs, and exhibition developers in natural history museums and other museums are recommended to be professional in containing all components of science communication through various type of designing exhibitions.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• Microbiology and Biotechnology Letters
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• v.33 no.3
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• pp.222-225
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• 2005

Stimulatory effects of near infra-red (NIR) rays radiation have been studied within the limits of photosynthesis, phototaxis, and photodermatology. While most of these studies have been done by direct NIR radiation, we investigated the effects of the NIR rays-treated materials on microbial growth. NIR in wavelength of 1,400${\~}$1,700 nm was applied for different kind of materials. Under fast growing conditions in rich media, materials treated with the NIR rays or not did not show any differences in growth of microorganisms. However, under slow growing conditions in minimal media, data showed that NIR rays-treated cloths and hygienic bands affect negatively on the growth of bacteria (Salmonella enteritidis) and fungi (Candida albicans). In addition, it was estimated that the effect of NIR rays on bacterial growth is kept going on S. enteritidis.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.45-46
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• 2007

In order to go digital broadcasting in Korea, it is conducted various policies in the country which be expanded network, be increased digital broadcasting hours. And broadcasting stations in the country close down analog broadcasting until 2012. Moreover IPTV is a method of delivering broadcast television and on-demand, rich media content that uses an IP(Internet protocol network) as the medium. And an IP is regarded as a very favorable approach for the future "Medium for Digital TV". However It is not easy to replace the entire digital infrastructure. And there are some problems in the digital infrastructure for Digital TV(i.e. channel zapping delay). Moreover user require service. IPMG is to solve these problems. IPMG is digital converter that allows receive and transmit signal by using many kinds of medium for Digital TV. Moreover IPMG provides users a Network PVR service. In this paper we developing, manufacturing IPMG and analyze its performance.

• Smart Media Journal
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• v.6 no.3
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• pp.75-82
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• 2017

Recently, the marine monitoring technology is actively being studied since the sea is a rich repository of natural resources that is taken notice in the world. In particular, the marine environment data should be collected continuously in order to understand and analyze the marine environment, however the study of automatic monitoring of marine environment in Korea is not enough. In this paper, we proposed the marine environment monitoring system based on open source. The proposed system can be designed as a scale out system using Hadoop based time series database which it can easily process the increasing collection data by a scale out computer resources. It can also be used to analyze marine data by visualizing collected data.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.718-732
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• 2020

Conducting sentiment analysis and opinion mining are challenging tasks in natural language processing. Many of the sentiment analysis and opinion mining applications focus on product reviews, social media reviews, forums and microblogs whose reviews are topic-similar and opinion-rich. In this paper, we try to analyze the sentiments of sentences from online webcast reviews that scroll across the screen, which we call live barrages. Contrary to social media comments or product reviews, the topics in live barrages are more fragmented, and there are plenty of invalid comments that we must remove in the preprocessing phase. To extract evaluative sentiment sentences, we proposed a novel approach that clusters the barrages from the same commenter to solve the problem of scattering the information for each barrage. The method developed in this paper contains two subtasks: in the data preprocessing phase, we cluster the sentences from the same commenter and remove unavailable sentences; and we use a semi-supervised machine learning approach, the naïve Bayes algorithm, to analyze the sentiment of the barrage. According to our experimental results, this method shows that it performs well in analyzing the sentiment of online webcast barrages.

• Advances in Energy Research
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• v.4 no.3
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• pp.213-221
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• 2016

The main purpose of this work is to test the validation of use of a four step reaction mechanism to simulate the laminar speed of hydrogen enriched methane flame. The laminar velocities of hydrogen-methane-air mixtures are very important in designing and predicting the progress of combustion and performance of combustion systems where hydrogen is used as fuel. In this work, laminar flame velocities of different composition of hydrogen-methane-air mixtures (from 0% to 40% hydrogen) have been calculated for variable equivalence ratios (from 0.5 to 1.5) using the flame propagation module (FSC) of the chemical kinetics software Chemkin 4.02. Our results were tested against an extended database of laminar flame speed measurements from the literature and good agreements were obtained especially for fuel lean and stoichiometric mixtures for the whole range of hydrogen blends. However, in the case of fuel rich mixtures, a slight overprediction (about 10%) is observed. Note that this overprediction decreases significantly with increasing hydrogen content. This research demonstrates that reduced chemical kinetics mechanisms can well reproduce the laminar burning velocity of methane-hydrogen-air mixtures at lean and stoichiometric mixture flame for hydrogen content in the fuel up to 40%. The use of such reduced mechanisms in complex combustion device can reduce the available computational resources and cost because the number of species is reduced.

• Cross-Cultural Studies
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• v.31
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• pp.415-438
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• 2013

This paper explores how to teach Chinese, using multi-media resources such as Chinese dramas and focusing on one of Jin Yong's dramas, The Return of the Condor Heroes. The purpose of this study is to develop teaching methodologies for university students learning Chinese through drama to integrate language skills: enhancing communicative competence and understanding Chinese cultures. First, the overview of previous studies provides several cases of foreign language education using drama. Teaching Chinese through drama can be an integrative education because students can develop their communicative competence as well as understand the cultures of the target language. In other words, the contexts of drama may offer rich sources of the history of China, Han Chinese ethnocentrism, and knowledge of Chinese literature as well as geography. Second, this study applies the principles of Tomlinson (2010) for materials development in language teaching into the case of Chinese drama. It concentrates on Jin Yong's The Return of the Condor Heroes that the author has used in the Chinese language courses for three years. It examines the characteristics of the drama for developing effective ways of teaching and learning Chinese language and culture. Furthermore, it discusses the impact of using drama on changes in students' pervasive perceptions about unnecessity of Chinese classical literature. Third, this paper presents some sample lessons which may help teachers to develop understanding of how to organize lessons through drama. Finally, it illustrates university students' opinions about using drama to learn Chinese.

• Smart Media Journal
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• v.10 no.1
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• pp.79-87
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• 2021

In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.412-434
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• 2023

This study discusses the high-order diffusion method in the wavelet domain. It aims to improve the edge protection capability of the high-order diffusion method using wavelet coefficients that can reflect image information. During the first step of the proposed diffusion method, the wavelet packet decomposition is a more refined decomposition method that can extract the texture and structure information of the image at different resolution levels. The high-frequency wavelet coefficients are then used to construct the edge detection function. Subsequently, because accurate wavelet coefficients can more accurately reflect the edges and details of the image information, by introducing the idea of state weight, a scheme for recovering wavelet coefficients is proposed. Finally, the edge detection function is constructed by the module of the wavelet coefficients to guide high-order diffusion, the denoised image is obtained. The experimental results showed that the method presented in this study improves the denoising ability of the high-order diffusion model, and the edge protection index (SSIM) outperforms the main methods, including the block matching and 3D collaborative filtering (BM3D) and the deep learning-based image processing methods. For images with rich textural details, the present method improves the clarity of the obtained images and the completeness of the edges, demonstrating its advantages in denoising and edge protection.