• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.121-128
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• 2016

Social Media transformed the mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, in regards to disaster management, the necessity for public participation policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for purposes of implementing social media disaster management. Social Big Board collects a daily average of 36 million tweets in Korean in real time and automatically filters disaster safety related tweets. The filtered tweets are then automatically categorized into 71 disaster safety types. This real time tweet monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relations to disaster management. It is a first step towards disaster management that communicates with the people that allows us to hear the voice of the people concerning disaster issues and also understand their emotions at the same time. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is key algorithms, will be described. Disaster issues are divided into two categories: potential issues, which refers to abnormal signs prior to disaster events, and occurrence issues, which is a notification of disaster events. The detection models of these two categories are defined and the performance of the models are compared and evaluated.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.709-713
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• 2009

Recently, a lot of research that applies data acquired from devices such as cameras and RFIDs to context aware services is being performed in the field on Life-Log and the sensor network. A variety of analytical techniques has been proposed to recognize various information from the raw data because video and audio data include a larger volume of information than other sensor data. However, manually watching a huge amount of media data again has been necessary to create supervised data for the update of a class or the addition of a new class because these techniques generally use supervised learning. Therefore, the problem was that applications were able to use only recognition function based on fixed supervised data in most cases. Then, we proposed a method of acquiring supervised data from a video sharing site where users give comments on any video scene because those sites are remarkably popular and, therefore, many comments are generated. In the first step of this method, words with a high utility value are extracted by filtering the comment about the video. Second, the set of feature data in the time series is calculated by applying functions, which extract various feature data, to media data. Finally, our learning system calculates the correlation coefficient by using the above-mentioned two kinds of data, and the correlation coefficient is stored in the DB of the system. Various other applications contain a recognition function that is used to generate collective intelligence based on Web comments, by applying this correlation coefficient to new media data. In addition, flexible recognition that adjusts to a new object becomes possible by regularly acquiring and learning both media data and comments from a video sharing site while reducing work by manual operation. As a result, recognition of not only the name of the seen object but also indirect information, e.g. the impression or the action toward the object, was enabled.

• Textile Coloration and Finishing
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• v.22 no.3
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• pp.282-291
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• 2010

Digital textile printing(DTP) is becoming more important because the production trend of textile printing goods is adapting to small-lot multiple items. Recently enhanced use of DTP is closely connected with production of high value-added products in fashion industry, which is also appropriate for quick response system(QRS). Quality of DTP depends on pre-treatment, after-treatment, ink, media, printer, etc. One of these parameters, Selection of good media is very important to obtain high quality of DTP products. Especially, the effects of media on printing quality of DTP according to yarn twist and structure of knitting fabric were examined in this study. Two types of yarn twist of 830 t.p.m and 1630 t.p.m for cotton knit were used and five types of media structures were knitted with single circular knitting machine. First, MIU, MMD, SMD's values are closely related with surface roughness of sample as well as printing quality. The hard twist samples were higher values than normal twist samples in the same media structure. In case of SMD, the values increased from plain to corduroy types. Second, aspect of line sharpness, line area, and line width values of hard twist samples decreased from plain to corduroy than those of normal twist samples. Third, line deviation values of hard twist samples, blurriness of line, also decreased than those of normal twist samples.

• STI Policy Review
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• v.8 no.1
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• pp.41-61
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• 2017

The literature in research policy extensively addresses the interaction between public R&D and the society. Scholars have paid particular attention to the way science and technology are diffused into the society and industry with the aim of substantiating their potential value. In practice, having recognized the importance of the said interaction, R&D entities and governmental organizations promote scientific and technological innovations that result from their R&D activities. Yet, the nature of news media exposure as their primary channel to promote R&D outcomes has been remarkably understudied. Using the results of R&D projects supported by the National Research Foundation of Korea (NRF), this study examines R&D entities' strategic use of the news media to publicize their outcomes. The empirical results suggest that the scale of an R&D project positively affects the counts of media exposure of its R&D outcomes, whereas the level of technology readiness and the technology life-cycle do not have significant influence. In addition, the results suggest that, compared to senior researchers, young researchers are more likely to publicize their R&D outcomes and that R&D outcomes from highly ranked universities are more likely to be publicized than those from lower-ranking universities despite our control for R&D outcomes. The aforementioned results suggest that in promoting the diffusion of science and technology, especially to the public, policymakers should be concerned about incentives for those who provide techno-scientific information, such as researchers. The social need for the diffusion of techno-scientific information into the public (e.g., technology transfer and diffusion) is an insignificant factor in determining the media exposure of such information, whereas personal benefits and sensitive issues related to a researcher's own R&D activities (e.g., justification for R&D activities) drive researchers to publicize their R&D outcomes. This paper suggests that policymakers, especially those concerned with better diffusion of scientific and technological innovations need to design a proper incentive system to maximize the societal benefits of media exposure.

• Korean Chemical Engineering Research
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• v.57 no.6
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• pp.804-811
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• 2019

This study was performed the real motion and DEM simulation of ball motion using three different types of grinding media with different size and materials in media formation for optimization of process conditions in a traditional ball mill (media ball mill). In the simulation, the rotational speed of the mill, the material of the medium, the velocity of the medium, and the coefficient of friction between the media and the wall of pot were fixed into the actual experimental conditions. The motion of various kinds of grinding media was quantitatively measured by setting the grinding zone defined in the present study on the photographs taken and the snapshot images analyzed in the simulation. In addition, we observed the quantitatively measured value and the changed morphology of the sample and examined the correlation. Therefore, it is suggested to optimize the grinding media which has the greatest influence on the grinding zone under specific experimental conditions.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.127-136
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• 2018

With the increased value in digital contents, the influence of social media has increased exponentially over the past years. Focused around those in their teens and twenties, social media has spread its influence to people regardless of one's age or gender. This increased attention is reflected by the public's interest in pets, especially those dealt with in the personal media sector. This paper will focus on the two most popular Korean cat youtube channels called "CreamHeroes" and "SuriNoel." By analyzing the top thirty most viewed videos on each channel, real time streaming, goods based on the cats starring on the channel, and comments left by the channels' subscribers, it can be concluded that people watching videos categorized as "Viewnimal" derive surrogate pleasure from their viewings. The following creates the potential for increased conversation regarding the subject of shelter animals and animal abuse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.9-14
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• 2024

Hue, value, and chroma are the fundamental colour components used in colour property research to identify colour in the digital media environment. In the Munsell colour system, which is based on the characteristics of visual perception, the basic properties are classified into hue, value, and chroma. The methods for recording these three properties can be divided into the colour appearance system and the colour mixing system: in the former, they are documented based on a colour chart that focuses on visual perception, and in the latter, accurate numerical records are kept without concern for discolouration. Colour terminology is crucial for conveying and expressing colours, and colours can be classified and defined according to the combination of hue, value, and chroma. With the development of various media, it has become possible to represent a range of colours previously unachievable, necessitating basic research into the characteristics of colour perception by further subdividing digital-oriented colour studies. In this study, we conducted psychophysical experiments to identify and analyse the categories of value and chroma needed to recognise each colour among the ten representative colours of the Munsell colour system, based on visual perception on a display. This study analyses the results of these experiments, defines their significance as foundational research data on colour perception characteristics, and suggests directions for future research.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.74-76
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• 2010

Digital images or videos are used in modern digital devices. The resolution of HDTV in digital broadcasting system is higher than that of previous analog systems. Also, mobile phone with 3G can provide images as well as video streaming services in realtime. In these circumstances, the visual quality of images has become an important factor. We can make image clear by transient improvement process that reduces transient in edges. In this paper, we present an transient improvement algorithm. The proposed algorithm improves edges by making smooth edge to steep edge. Before performing transient improvement algorithm, edge detection algorithm should be operated. Laplacian operator is used in edge detection, and the absolute value of it is used to calculate gain value. Then, local maximum and minimum values are computed to discriminate current pixel value to raise up or pull down. Compensating value that gain value multiplies with the difference between maximum (or minimum) value and current pixel value adds (or subtracts) to current pixel value. That is, improved signal is generated by making the narrow transient of edge. The advantage of proposed algorithm is that it doesn't produce shooting problem like overshoot or undershoot.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.115-135
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• 2012

Currently, smart signage as a new kind of advertisement media has been widely used and has had a significant effect on consumers. In this study, we examine the impact on the attitude towards smart signage advertisement based on the Ducoffe's Web advertisement model. In particular, we investigate how the advertising factors (interaction, informativeness, irritation, and entertainment) as well as the contextual factors (localization, immediacy, and personalization) have effects on the value and attitude towards smart signage advertisement. Furthermore, we examine the moderating effect of individual defensive propensity on the relationship between affecting factors and the advertising value. By analyzing 192 samples from undergraduates, we found that four out of seven factors have significant effects on the value towards smart signage. More specifically, for advertising factors, informativeness and irritation have positive effects on the advertising value. For contextual factors, on the other hand, localization and entertainment have positive effects on the value towards smart signage. Besides, we discovered that the defensive propensity moderate the relationship between localization and the advertising value.