• The Korean Journal of Pain
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• v.33 no.3
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• pp.234-244
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• 2020

Background: Chronic pain affects approximately 22% of the world's population. Opioids can be useful in chronic pain management. However, some patients have negative perception of opioids. The purpose of this research was to evaluate patients' perception about opioids and investigate problems associated with prescribing and taking opioids in South Korea. Methods: Patients who visited a pain clinic in 14 university hospitals of South Korea from September through October 2018 were asked to complete anonymous questionnaires about taking opioids. Results: Of the 368 patients that were surveyed (female 53.3%, male 46.7%), 56.8% were prescribed opioids. In the opioid group, 92.8% patients had heard of opioids from their doctor and 72.6% of them had a positive perception about opioids. The side effects associated with opioid use were constipation (35.4%), dizziness (24.6%), nausea and vomiting (17.4%), dysuria (6.2%), and addiction (2.0%). In the no opioid group, the primary sources of information about opioids were doctors (49.2%), mass media (30.8%), and the internet (16.2%). The main reasons why 39.0% patients did not take opioids were fear of addiction (57.7%) and side effects (38.5%). There were 71.5% and 60.9% patients in the opioid and no opioid group, respectively, who wished to take opioids when their numeric rating scale pain score was ≥ 7. Conclusions: Perception of opioids among patients who take them was either neutral or positive. However, 39.0% patients who have not been prescribed opioids did not want an opioid prescription, citing fear of addiction and side effects as the primary reasons.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.37-47
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• 2011

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.336-344
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• 2021

The purpose of this study was to identify the self-awareness of smartphone dependence among undergraduate students and their response to the same. The data was drawn from a survey on smartphone overdependence conducted by the Ministry of Science and information and communications technology (ICT) and the National Information Society Agency in 2017. The responses of 1,735 undergraduate students were analyzed by frequency, percentage, mean, standard deviation, minimum-maximum value, ��2-test, independent t-test, Pearson's correlation coefficient, and stepwise multiple regression analysis. The results indicated that 22.3% of participants were at risk of smartphone dependence, and 63.6% of them were unaware of their dependence on smartphones. The perception of smartphone dependence was significantly associated with a higher risk of smartphone dependence (��=.35, p=.000) and the increasing use of applications such as games (��=.19, p=.000), television/video (��=.11, p=.000), and learning (��=.11, p=.000). Of the participants with dependence awareness, only a few knew about the existence of centers to prevent smartphone and internet dependence. Moreover, they rarely utilized these centers. However, the participants felt the need for more counseling agencies (26.8%), programs for dealing with oneself (23.2%), information about smartphone dependence (14.9%), and help to overcome dependence (10.9%). These findings show the need to establish public services so that students can easily access correct information on smartphone dependence and address this problem.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.2
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• pp.89-102
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• 2018

With the development of mobile technology, asset management on the Internet have also developed a lot. Drawing on Technology Acceptance Model, this study examines YUEBAO deployment to model consumers' purchase intention to use financial products offered online. In this study, we hypothesized that the characteristics of online asset management product will affect the purchase intention through perceived usefulness and conduct empirical analysis on Chinese consumers. In the study model, the independent variables were considered to include individual involvement, experience, product protection, corporate credibility, convenience, mobility, and familiarity. In addition, the parameters constitute the usefulness, and the dependent variable is the purchase. The results are as follows. First, YUEBAO's complementarity, corporate credibility, convenience, and familiarity have a significant influence on YUEBAO's usefulness. Second, The YUEBAO's usefulness has a noticeable effect on the purchase intention. To perceive the high usefulness, the practicality strategy of enhancing the protection property, corporate reliability, convenience and familiarity of the online asset management product is needed. The study of consumer purchase behavior and consumer purchase intention of online wealth management products is very valuable for academic and practical work.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.129-136
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• 2008

Along with the development in cutting-edge digital technology, the street space is also being changed. Mobile telecommunication units and internet give a big change in a human being's lifestyle. And the ubiquitous computing is proceeding with expanding its application range from the indoor space to the street space. As the street furniture is the convenient facility that allows a human being's life in street space to be abundant, it is getting advanced. First of all, in terms of such phenomenon, this study analyzed the cases of a research on application of street space and the actual condition of a change in the number of individuals for the street furniture, through a literature research of ubiquitous. Also, it researched into the realities of using the street furniture of the walking-desired streets at Daehac-ro and Hongdae district, where are two representative places related to digital generation. The next was carried out FGI (Focus Group Interview) with users of the street space in front of Hongik University and managers of the street furniture, and was researched into the use & management behavior, and recognition level on the street furniture. Thus, the key elements were extracted such as interchange of information for cultural activities, automation for interaction variability in function. Finally the core elements for future vision of street furniture in this digital era were extracted in 3I, namely, Information, Intellectualization, and Integration. This is considered to be applied to the establishment of direction in the process of high-tech digitalization in street furniture related to information hereafter.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.59-76
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• 2014

The revolution of smart media such as smart phone, smart TV and tablets has brought easiness for people to get contents and related information anywhere and anytime. The characteristics of the smart media have changed user behavior for watching the contents from passive attitude into active one. Video is a kind of multimedia resources and widely used to provide information effectively. People not only watch video contents, but also search for related information to specific objects appeared in the contents. However, people have to use extra views or devices to find the information because the existing video contents provide no information through the contents. Therefore, the interaction between user and media is becoming a major concern. The demand for direct interaction and instant information is much increasing. Digital media environment is no longer expected to serve as a one-way information service, which requires user to search manually on the internet finding information they need. To solve the current inconvenience, an interactive service is needed to provide the information exchange function between people and video contents, or between people themselves. Recently, many researchers have recognized the importance of the requirements for interactive services, but only few services provide interactive video within restricted functionality. Only cooking domain is chosen for an interactive cooking video query service in this research. Cooking is receiving lots of people attention continuously. By using smart media devices, user can easily watch a cooking video. One-way information nature of cooking video does not allow to interactively getting more information about the certain contents, although due to the characteristics of videos, cooking videos provide various information such as cooking scenes and explanation for each recipe step. Cooking video indeed attracts academic researches to study and solve several problems related to cooking. However, just few studies focused on interactive services in cooking video and they still not sufficient to provide the interaction with users. In this paper, an interactive cooking video query service system with linked data to provide the interaction functionalities to users. A linked recipe schema is used to handle the linked data. The linked data approach is applied to construct queries in systematic manner when user interacts with cooking videos. We add some classes, data properties, and relations to the linked recipe schema because the current version of the schema is not enough to serve user interaction. A web crawler extracts recipe information from allrecipes.com. All extracted recipe information is transformed into ontology instances by using developed instance generator. To provide a query function, hundreds of questions in cooking video web sites such as BBC food, Foodista, Fine cooking are investigated and analyzed. After the analysis of the investigated questions, we summary the questions into four categories by question generalization. For the question generalization, the questions are clustered in eleven questions. The proposed system provides an environment associating UI (User Interface) and UX (User Experience) that allow user to watch cooking videos while obtaining the necessary additional information using extra information layer. User can use the proposed interactive cooking video system at both PC and mobile environments because responsive web design is applied for the proposed system. In addition, the proposed system enables the interaction between user and video in various smart media devices by employing linked data to provide information matching with the current context. Two methods are used to evaluate the proposed system. First, through a questionnaire-based method, computer system usability is measured by comparing the proposed system with the existing web site. Second, the answer accuracy for user interaction is measured to inspect to-be-offered information. The experimental results show that the proposed system receives a favorable evaluation and provides accurate answers for user interaction.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.101-123
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• 2012

Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.