• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.61-72
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• 2018

Different types of traditional Korean clothes (Hanbok) are appearing in the market with the increasing interest of culture consumers. In order to turn traditional Korean clothes into everyday clothes that adequately reflect various demands of culture consumers, it is important to satisfy both functional and emotional aspects of clothing. However, there is lack of existing studies on emotions of culture consumers while wearing traditional Korean clothes. In this study, 28 emotional words regarding traditional Korean clothes were extracted by applying the Delphi method and conformity rating survey to 182 emotional words reported in existing studies and references from areas such as psychology, linguistics, and sensibility engineering. The 28 selected emotional words can be used to express emotions felt by culture consumers about traditional Korean clothes. Also, words were grouped based on the correlation according to factor analysis. Based on common characteristics, the emotional words were classified into 6 categories of 'pleasure,' 'aesthetic sense,' 'harmony,' 'novelty,' 'likability,' and 'stability.' These 6 emotional categories were concluded to represent emotions of consumers about traditional Korean clothes. The 28 emotional words and 6 representative emotions noted in this study can be used as basic data for measuring emotions of culture consumers of traditional Korean clothes. A future study task is to design a detailed assessment scale to measure emotions of culture consumers about traditional Korean clothes using representative emotions.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.595-625
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• 2012

Recently environment-friendly pellet boilers have interests as emissions of greenhouse gases are regulated internationally and energy security becomes more important to oil addicted countries including Republic of Korea. But the Korean market for pellet boilers is on the initial stage due to the high production costs relative to other conventional boilers. Hence the Korean government has supported financially and promoted the pellet boiler business. In this sense, it would contribute market stratergy and effective promotion policy for both of the government and private companies if we can forecast market shares of pellet boilers appropriately. For this purpose, this study surveyed potential consumers' preferences on pellet boilers among various alternatives using a choice experiment reflecting intangible costs. As the market share of new technology increases, intangible costs decline. According to different intangible cost scenarios, we experimented people's preferences on oil, gas, electric, and pellet boilers. A multinomial logit model was employed to estimate coefficient parameters of common attributes for various alternative boilers. Based on the estimates, we forecasted market shares of individual boilers. We found that as intangible costs decline, the market share of pellet boiler increase substantically while market shares of electric and gas boilers decrease dramatically. The market share of oil boiler did not change significantly. Meanwhile, as people are more rich, more educated, and exposed to advertisement on pellet boilers, the likelihood of choosing the pellet boiler increases.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.9-17
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• 2020

In this paper, we proposed an SNS review analysis method based on deep learning for user tendency. The existing SNS review analysis method has a problem that does not reflect a variety of opinions on various interests because most are processed based on the highest weight. To solve this problem, the proposed method is to extract the user's personal tendency from the SNS review for food. It performs classification using the YOLOv3 model, and after performing a sentiment analysis through the BiLSTM model, it extracts various personal tendencies through a set algorithm. Experiments showed that the performance of Top-1 accuracy 88.61% and Top-5 90.13% for the YOLOv3 model, and 90.99% accuracy for the BiLSTM model. Also, it was shown that diversity of the individual tendencies in the SNS review classification through the heat map. In the future, it is expected to extract personal tendencies from various fields and be used for customized service or marketing.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.49-58
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• 2005

There has been an increase in the interest of applications that use a combination of both pervasive computing technology and context-aware technology. This application based on the development environment along with the support of developing context-aware applications is now being researched thoroughly and by many. The service management system provides services that are needed for context-aware applications. This system is an integral part of the developmental environment of context-aware applications. But there is a restrictive matching based on ontology that uses simple syntactic matching or a plain type of service used in previous researches. And there is also no consideration for context-aware information. Also, if the user is unable to find a service that is satisfactory, or is a service which a user does not desire, they may use a service which is composed of other existing services. This paper proposes a service management system based on context-aware information. The proposed system enables the accurate finding of services by considering semantic matching methods based on ontology and context-aware information. If the user does not find a service that is helpful in the service registry, it can provide the service list to enable other existing service compositions, by providing the functionality of these service compositions. As a result, the experiment of the system proposed has shown that the system properly supported the service discovery based on context-aware information and service composition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.49-58
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• 2011

Typically, vision-based AR systems operate on the basis of prior knowledge of the environment such as a square marker. The traditional marker-based AR system has a limitation that the marker has to be located in the sensing range. Therefore, there have been considerable research efforts for the techniques known as real-time camera tracking, in which the system attempts to add unknown 3D features to its feature map, and these then provide registration even when the reference map is out of the sensing range. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a real-time camera tracking is achieved on the basis of a plane tracking algorithm. Also we suggest a method for re-detecting features to maintain registration of virtual objects. The proposed method can cope with the problem that the features cannot be tracked, when they go out of the sensing range. The main advantage of the proposed system are not only low computational cost but also convenient. It can be applicable to an augmented reality system for mobile computing environment.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.19-29
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• 2011

A Blog provides commentary, news, or content on a particular subject. The important part of many blogs is interactive format. Sometimes, there is a heated debate on a topic and any article becomes a political or sociological issue. In this paper, we proposed a method to predict the popularity of an article in advance. First, we used hit count as a factor to predict the popularity of an article. We defined the saturation point and derived a model to predict the hit count of the saturation point by a correlation coefficient of the early hit count and hit count of the saturation point. Finally, we predicted the virtual temperature of an article using 4 types(explosive, hot, warm, cold). We can predict the virtual temperature of Internet discussion articles using the hit count of the saturation point with more than 70% accuracy, exploiting only the first 30 minutes' hit count. In the hot, warm, and cold categories, we can predict more than 86% accuracy from 30 minutes' hit count and more than 90% accuracy from 70 minutes' hit count.

• The KIPS Transactions:PartD
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• v.14D no.4 s.114
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• pp.381-388
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• 2007

Consumers changed to the subject to produce a digital contents as data transmission technique is advanced and a digital machine is diffused variously. Users are interested greatly in a user creative movie (UCM) production among various online contents. The UCM production method which uses the music and picture is the method that users make the UCM more easily. However, the UCM production service has the problem that any association does not exist in the music and picture and that the picture changes according to fixed time interval without the relation at a music rhythm. To solve this problem, we propose the UCM production method which uses a music analysis and picture analysis in the paper. A music analysis finds a picture change time according to the rhythm and a picture analysis finds the association of the picture. A music analysis finds strong parts of the sound which uses Root-Mean-Square (RMS). And a picture analysis classifies the picture as a scenery picture and people picture which uses structure simplicity of the picture(SSP) and face region detection. A picture analysis got correct result of 86.4% in the experiment and we can finds the association at each picture and arranges the sequence which the picture appears. Therefore, if we use a music and picture analysis at the UCM production, users may make natural and efficient movie.

• Information Systems Review
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• v.13 no.1
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• pp.33-59
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• 2011

Although online social network services widely used in human networking and recruiting industries, it is showing off its limitations in followings-it's hard to reach the status of seamless connection between offline and online; the incompletion and low credibility of the information came from non-face-to-face profile exchange; and the restraint of user autonomy due to centralized control. This paper defines the ubiquitous social network management which enables the seamless real-time face-to-face social interactions of the users based on WPAN (Wireless Personal Area Network) who share the same interest in real word and deduces a ubiquitous social network management framework based on it. As an instance of ubiquitous social network management, u-Recruiting service model will be designed and analyzed. The Analysis using the business model will be followed by the possible scenario of service model. The role, value proposition and potential benefits of the each participants in this service model and will be given as well. In order to evaluate relative advantages of the model suggested by this study, 6 cases will be compared.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.74-84
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• 2016

Open Source Software (OSS) is a new paradigm for software development. The system is based on the notion of giving software (including sources) away for free, and making money on services, customizing and maintenance. For these reasons, many software companies have considered adopting and using OSS in Software R&D. A variety of factors may influence the use of decision making of OSS. The objective of this study was to explore the significant factors affecting the use decision of OSS and the job performance of OSS usage in software R&D. A research model was suggested based on the TOE Framework and Information Systems Success Model. These findings show that technical benefits of OSS have significant effects on OSS use. The technical benefits of OSS, and organization context, in turn, have significant effects on the use of OSS. On the other hand, the technical risks of OSS and the environment context have no effects on OSS use. In addition, OSS use and user satisfaction have significant effects on the individual job performance. This research contributes towards advancing the theoretical understanding of the OSS Benefits and Performance in Software Development.