• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.1-8
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• 2017

In this paper, we introduce a technique to retarget human motion data to the humanoid body in a constrained environment. We assume that the given motion data includes detailed interactions such as holding the object by hand or avoiding obstacles. In addition, we assume that the humanoid joint structure is different from the human joint structure, and the shape of the surrounding environment is different from that at the time of the original motion. Under such a condition, it is also difficult to preserve the context of the interaction shown in the original motion data, if the retargeting technique that considers only the change of the body shape. Our approach is to separate the problem into two smaller problems and solve them independently. One is to retarget motion data to a new skeleton, and the other is to preserve the context of interactions. We first retarget the given human motion data to the target humanoid body ignoring the interaction with the environment. Then, we precisely deform the shape of the environmental model to match with the humanoid motion so that the original interaction is reproduced. Finally, we set spatial constraints between the humanoid body and the environmental model, and restore the environmental model to the original shape. To demonstrate the usefulness of our method, we conducted an experiment by using the Boston Dynamic's Atlas robot. We expected that out method can help the humanoid motion tracking problem in the future.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.401-408
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• 2013

In this paper, we propose a method that automatically detects organs having similar appearances in medical images by learning both context and appearance features. Since only the appearance feature is used to learn the classifier in most existing detection methods, detection errors occur when the medical images include multiple organs having similar appearances. In the proposed method, based on the probabilities acquired by the appearance-based classifier, new classifier containing the context feature is created by iteratively learning the characteristics of probability distribution around the interest voxel. Furthermore, both the efficiency and the accuracy are improved through 'region based voting scheme' in test stage. To evaluate the performance of the proposed method, we detect femur and tibia which have similar appearance from SKI10 knee joint dataset. The proposed method outperformed the detection method only using appearance feature in aspect of overall detection performance.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.187-195
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• 2012

Smart phone allows advertisers to estimate customers behavior by selecting user context awareness information and gives users instant feed back about their behavior. Electronic equipments such as smart phone enable advertisers to advertise interesting product for each customers at the point of purchase. In this paper, we deal with the trends of Smart phone and internet based TV in the spotlight as the upcoming advertising media and propose the effective way of advertising, Smart Advertising model, which can give users advertising contents of their interesting product by collecting user context information from a variety of devices including N-screen in smart space. This model will induce modern people who live in flood of advertisements to buy products by providing interesting advertising contents.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.149-156
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• 2022

In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID⁺ that includes both the news content information and its social context information. The CoAID⁺ dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID⁺ dataset in various perspectives, we present some interesting features capable of differentiating real and fake news.

• ETRI Journal
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• v.37 no.2
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• pp.417-427
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• 2015

With recent advances in media technology, the creation of a relatively new service, N-screen, has been realized. N-screen provides seamless connections among various media and enables users to enjoy entertainment content at any time and any location. With such recent advances comes opportunity; therefore, for those N-screen service providers who have established an early edge in the ICT industry, it is imperative that they maintain this and stay ahead of the ensuing competition. In this context, the objective of this study is two-fold; first, we aim to find factors influencing the behavior of existing and potential N-screen service users, and then second, to examine the differences in how these factors operate within the two user types. The results of this study show that the perceived value and subjective norm are important influencers in both user types. However, price fairness and innovativeness are only influential on the attitude and intention of potential users, while some aspects of media usage have only significant influences on the behavior and loyalty of existing users. Based on these results, we provide some implications for both researchers and practitioners who wish to better understand the nature of N-screen users.

• Korean Institute of Interior Design Journal
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• v.24 no.4
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• pp.61-69
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• 2015

The purpose of study is not only analyzes the space images expressed with mass-produced furniture of the time and economy throughout the cover pages of IKEA published catalogs since 1951 to 2015 but also is set to deduct the characteristics of spatial expression regarding the usage of digital media applied catalogs which is to be published along with the 2015 catalog. Thus, throughout research of basic literature such as domestic and foreign academic material, books, and websites, the theoretical consideration of the meaning of IKEA's pursuit of selling manufactured furnitures is foregone. Based on the above, Analyze and organize periodically applied interior space in accordance with context characteristic by understanding the attribute of catalogue from expansion of media space applied new digital media. The importance of research on IKEA is not only the quality of products designed by them, but emotional aspect that deeply penetrate customer's actual daily life. Implication of digital media message to advertisement is a important role in society that shares digitalized information. IKEA's innovative attempt of connection to new world using traditional method of marketing expression and smart device may help people better understand space.

• The Journal of Information Systems
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• v.24 no.1
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• pp.147-168
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• 2015

Why people reduce or stop using social network services(SNS), which are regarded as a mean of relationship and communication, unlike the early trend? To explain the phenomenon, this study tries to predict psychological decision making process of users from perspectives of cognitive dissonance theory. From this perspective, this study attempted an integrative approach that reflected 'User's literacy' indicating the ability of individuals to use SNS, and 'negative mass media influence' such as media reports on side effects or the bad experiences of acquaintances, along with the 3 factors used in the SNS Prior research. This study conducted an empirical analysis by surveying 256 facebook users, and the major findings are as follows:- First, Social-overload, complexity, uncertainty and negative media influence are significantly affect dissonance on the use of SNS. Second, Dissonance on the use of SNS significantly affects the behavior that possibly reduces and limits the use of SNS. In other words, the users who have experienced psychological dissonance respond passively by avoiding the use of SNS to resolve the dissonance. Third, the moderating effect of User's literacy wasn't a significant. This study presents a clue to understand psychological decision making process of use of SNS and a guideline for establishing practical strategies. In addition, it is important to note that this study contributes to expansion of theoretical discussion about usage.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.445-454
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• 2021

Leader and leadership are one of the important aspects in the life of a country. This study aims to predict the intention of young voters to vote for state leader elections by expanding the theory of planned behavior to the Indonesian context. Apart from the importance of the presidential election, research rarely uses the theory of planned behavior, and to the best of researchers' knowledge, there are no studies that have applied the theory of planned behavior to predict the intention to vote for the president. Therefore, this study is an attempt to fill that gap. Two hundred questionnaires were distributed using non-probability purposive sampling. Data analysis was carried out using the structural equation modeling (SEM) approach. The results showed that attitude and behavior control were positively related to voters' intention to elect presidential candidates. Furthermore, information from social media also has a positive relationship with the attitude of choosing presidential candidates. However, the results also show that subjective norms do not have a significant relationship with voters' intention. This study contributes knowledge to researchers, practitioners, and policymakers about the factors that influence youth intention to vote in Indonesia, namely, attitudes, perceived behavior control, and information from social media.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.759-766
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• 2021

In this digital age, all organizational environments force businesses to adopt Information and Communication Technologies (ICT) since these technologies have immense impact on such businesses' competitiveness and productivity. Nonetheless, the productivity and the competitiveness enjoyed by such firms vary depending on the size or the organizations, context of the country; developing or developed, and what kinds of technologies are adopted. This investigation focused on small- and medium-sized enterprises (SMEs) of Eastern province of Sri Lanka where such studies are scanty. The adoption of social media (SM) by SMEs is inclined to change how organizations operate, this calls for an investigation of the elements that impact SMEs to adopt SM and such investigation. Technology-Organization-Environment (TOE) framework was based to understand the factors. Research approach was quantitative approach using questionnaire survey. Data were collected using online form to see 285 valid responses. Structural Equation Modelling was deployed to evaluate the proposed model. Results revealed that Relative Advantage, Compatibility, Complexity, Observability, Competitive Intensity, Bandwagon Pressure, and Competitive Pressure were influencing, while Trialability, Top Management Support, CEO's Innovativeness did not show statistically significant influence on SMEs' social media adoption.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.467-476
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• 2021

Purpose: The purpose of this study is to understand the social perceptions of nurses in the context of the COVID-19 outbreak through analysis of media articles. Methods: Among the media articles reported from January 1st to September 30th, 2020, those containing the keywords '[corona or Wuhan pneumonia or covid] and [nurse or nursing]' are extracted. After the selection process, the text mining and topic modeling are performed on 454 media articles using textom version 4.5. Results: Frequency Top 30 keywords include 'Nurse', 'Corona', 'Isolation', 'Support', 'Shortage', 'Protective Clothing', and so on. Keywords that ranked high in Term Frequency-Inverse Document Frequency (TF-IDF) values are 'Daegu', 'President', 'Gwangju', 'manpower', and so on. As a result of the topic analysis, 10 topics are derived, such as 'Local infection', 'Dispatch of personnel', 'Message for thanks', and 'Delivery of one's heart'. Conclusion: Nurses are both the contributors and victims of COVID-19 prevention. The government and the nurses' community should make efforts to improve poor working conditions and manpower shortages.