• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.7-14
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• 2017

Theoretically, it is known that common beliefs and/or common knowledge cannot be attained in asynchronously distributed multiagent environments, however, it show that some propositions with deadlines can be attained as common beliefs among a set of fully trusted agents even when they communicate to each other asynchronously. Generally, in the multiagent environment, the attainment of common beliefs is approached as a problem of communication, and for the common beliefs paradox that the common beliefs is not attained on a system without communication time restriction is applied to loose coarser granularity and it prove that forming common beliefs is possible by relaxing necessary requirements through the KakaoTalk chatting model. I also experimented with the reasoning function that confirms the common beliefs by inquiring about the common belief generated by implementing the inference function in each agent of the KakaoTalk chatting model. Through utilizing metalogic programming, a formalization of the presentation and reasoning of common beliefs has been achieved, and the group chatting model of KakaoTalk was adopted in experiments to show that common beliefs can be formed among distributed agents using asynchronous communication.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.143-150
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• 2022

Audio-based SNS also needs a visual guide to reach the contents desired by the users. Therefore, this study investigates visual interface design elements that influence the experience of using audio contents in audio-based SNS. Prior researches have identified that the generally acknowledged interface design elements are important for the usability of audio contents. Through the analysis of the currently launched audio-based SNS, the influence of general interface elements were again confirmed, and via the analysis of other audio content services, a new interface evaluation element was explored. Accordingly, with five general interface evaluation elements-layout, color, icon, typography, graphic image, multimedia elements are newly defined and proposed as crucial factors in evaluating the UI of audio-based SNS.

• Korean Medical Education Review
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• v.24 no.3
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• pp.231-239
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• 2022

This study aimed to examine the influence of the coronavirus disease 2019 (COVID-19) pandemic on areas of Korean medical students' lives, assess concerns, and investigate the strategies they used to cope with stress due to the pandemic. An online survey with a total of 53 items on the impact of COVID-19, concerns, and coping strategies was sent to medical students, and responses were collected from April 27, 2021 to May 30, 2021. In total, 1,329 students were included in the study. Analysis was performed using the chi-square test, independent-sample t-test, and one-way analysis of variance, and the post-hoc Scheffé test or Games-Howell test was performed for multiple comparisons. The main negative impacts of the pandemic were on hobbies/leisure activities and mental health, and medical students expressed the highest levels of concern regarding restriction of movement, returning to everyday life, and risk of infection for family and friends. Female students more strongly agreed that COVID-19 had increased their depressed mood and anxiety (p<0.001 and p=0.003, respectively). Furthermore, the negative impacts of the pandemic on different areas of life significantly affected current levels of depressed mood and anxiety. To cope with pandemic-related stress, students used several strategies such as talking with family or friends (91.5%), sleeping (83.1%), exercising (72.8%), using social networking services (60.8%), drinking alcohol (37.8%), and practicing meditation/mindfulness (24.4%); the effectiveness of these strategies ranged from 3.45 to 4.19 on a 5-point Likert-type scale (1-5). The study findings suggest that COVID-19 has influenced the mental health of medical students and raised concerns in many areas of their lives. Students used various strategies to cope with the pandemic-related stress; since the effectiveness of frequently used approaches varied, it is essential to guide medical students to develop effective coping strategies.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.43-59
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• 2019

Today, with the spread of smartphones and the development of social networking services, structured and unstructured big data have stored exponentially. If we analyze them well, we will get useful information to be able to predict data for the future. Large amounts of data need to be collected first in order to analyze big data. The web is repository where these data are most stored. However, because the data size is large, there are also many data that have information that is not needed as much as there are data that have useful information. This has made it important to collect data efficiently, where data with unnecessary information is filtered and only collected data with useful information. Web crawlers cannot download all pages due to some constraints such as network bandwidth, operational time, and data storage. This is why we should avoid visiting many pages that are not relevant to what we want and download only important pages as soon as possible. This paper seeks to help resolve the above issues. First, We introduce basic web-crawling algorithms. For each algorithm, the time-complexity and pros and cons are described, and compared and analyzed. Next, we introduce the state-of-the-art web crawling algorithms that have improved the shortcomings of the basic web crawling algorithms. In addition, recent research trends show that the web crawling algorithms with special purposes such as collecting sentiment words are actively studied. We will one of the introduce Sentiment-aware web crawling techniques that is a proactive web crawling technique as a study of web crawling algorithms with special purpose. The result showed that the larger the data are, the higher the performance is and the more space is saved.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.57-69
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• 2020

As more people share their opinions in online communities, such as Internet portals and social networking services, more opinions are manipulated for the benefit of particular individuals and groups. In particular, when manipulations occur for political purposes, they influence election results as well as government policies and the quality of life. This type of manipulation has targeted the general public, and their analysis and detection has also focused on such manipulation. However, to more efficiently spread propaganda, recent manipulations have targeted common interest groups(e.g., a group of those interested in real estate) and propagated information whose content and style are customized to those groups. This work characterizes such manipulations on common interest groups and proposes method to detect manipulations. To this end, we collected and analyzed opinions posted on 10 common interest groups before and after an election. As a result, we found that manipulations on common interest groups indeed occurred and were gradually increasing toward the election date. We also proposed a detection system that examines individual opinions, their authors, and their collaborators. Using the collected opinions, we demonstrated that the proposed system can accurately classify more than 90% of manipulated opinions and that many of these opinions were posted by multiple collaborators. We believe that regular audits of opinions using the proposed system can quickly isolate manipulations and decrease their impact. Moreover, the proposed features can be used to identify manipulations in domains other than politics.

• Health Policy and Management
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• v.34 no.1
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• pp.1-3
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• 2024

Currently, the issue of poor accessibility to essential medical services has been brought to light as a social discontent. In order to strengthen the essential medical service system, the government has announced the "the policy package related to essential medical service" as a comprehensive solution and has vowed to invest more than 10 trillion won by 2028. As it contains crucial elements for changing the framework of the healthcare system, I would like to present several points to consider in policy implementation. Given that this package contains important elements for changing the framework of the healthcare system, there are a few issues to consider in policy implementation. First, a mechanism to prevent politicization should be established when designing the physician training system. Second, changing from a hospital centered on residents to one centered on specialists means that the society bears the cost of training residents, while paying a high price for specialist services. The willingness of society to pay for the costs incurred by such a change should be carefully considered, and an appropriate budget must be prepared. Third, as the operation of shared human resources and inter-organizational networking, among other detailed policy measures, are still at a level of conceptual discussion, various issues should be solidly reviewed and considered for in the mid to long term to suit the conditions of the domestic healthcare system.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.113-118
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• 2024

Recently, advancements in artificial intelligence and computer graphics technology have led to the emergence of various virtual humans across multiple media such as movies, advertisements, broadcasts, games, and social networking services (SNS). In particular, in the advertising marketing sector centered around virtual influencers, virtual humans have already proven to be an important promotional tool for businesses in terms of time and cost efficiency. In Korea, the virtual influencer market is in its nascent stage, and both large corporations and startups are preparing to launch new services related to virtual influencers without clear boundaries. However, due to the lack of public disclosure of the development process, they face the situation of having to incur significant expenses. To address these requirements and challenges faced by businesses, this paper implements a photogrammetry-based facial capture system for creating realistic virtual humans and explores the use of these models and their application cases. The paper also examines an optimal workflow in terms of cost and quality through MetaHuman modeling based on Unreal Engine, which simplifies the complex CG work steps from facial capture to the actual animation process. Additionally, the paper introduces cases where virtual humans have been utilized in SNS marketing, such as on Instagram, and demonstrates the performance of the proposed workflow by comparing it with traditional CG work through an Unreal Engine-based workflow.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.95-106
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• 2016

The purpose of this study was to examine how college students use Facebook and the ways in which they feel of commitment while using Facebook. The Big Five Personality Model has been considerably used in the psychology fields, and the researchers have started to explore the role of characteristic factors in influencing an individual's use of social media, such as Facebook which has become one of the most popular social networking site in the world. Therefore, the current study aims to specify the links between The Big Five Personality Model and usage patterns as well as commitment of Facebook. Two hundreds thirty five college students participated in a survey and the results are as follows: First, participants who were high in extraversion and agreeableness were more likely to do information sharing activities such as sharing posts to their friends, writing comments on the other's posts. In addition, participants who were high in openness to experience, conscientiousness, and neuroticism were more likely to do information producing activities including offering events, group, or public pages to meet people both on and offline. Second, in terms of the relationship between personality traits and commitment to the Facebook, the study found that extraversion and neuroticism were related to users' commitment to Facebook. These findings are consistent with the existing literature regarding extraversion and neuroticism were representative personality factors when it comes to commitment of media. Specifically, the study found that those who were high in neuroticism were more likely to produce information such as posting photos repeatedly or tagging their friends on posts, and also more likely to feel commitment on Facebook. These findings confirm that personality is a highly relevant factor in determining individual's behavior and the degree of commitment on Facebook. Based on these findings implications and limitations of the study are discussed.

• Journal of the HCI Society of Korea
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• v.5 no.1
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• pp.37-43
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• 2010

Twitter has been continuously growing since October, 2006. Especially, not only the users and the number of messages have been increasing but also a new concept in social networking called 'micro blogging' has diffused. Within Korea, service such as 'me2day' has already been introduced and the improvement of internet accessibility within mobile devices is expected to expand the 'micro blogs'. In this point, this research is executed to study the new medium, 'micro blog'. To do so, we collected and analyzed Twitter logs of Korean users. Especially, we were curious about the extreme heavy users using Twitter, despite of the linguistic and cultural barrier of the foreign service. Who they are, why and how they use the 'micro blog'. First, we reviewed the general aspect of followers and messages by collecting a certain number of random samples. Using the Lorenz curve we found out that there was the imbalance within the users and based on this phenomenon we deducted an extreme heavy user group. In order to perform further analysis, log analysis was performed on the extreme heavy users. As the result, the users used multiple mobile and desktop 'Twitter' clients. The usage pattern was similar to that of internet usage time but was used during their "micro" time. The users using 'Twitter' not only to spread messages about important information, special events and emotions, but also as a habitual 'chatting tool' to express ordinary personal chats similar to SMS and IM services. In this research, it is proved that 68% of the total messages were ordinary personal chats. Also, with 24% of the total messages were retweets, we were able to find out that virtually connected 'people' and 'relationships' acted as the dominant trigger of their articulation.