• Journal of Digital Contents Society
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• v.12 no.3
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• pp.383-390
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• 2011

The purpose of this study was to examine major motivations for using SNSs and the effect of them on SNS participation. In order to address the research questions, 253 undergraduate and graduate students participated. Results of the study were summarized as follows. First, Cyworld was mainly used followed by Facebook and Twitter. Most of the respondents had access to SNSs via smart devices. The average frequency of SNS use was 1-3 times a day and they used them less than 30 minutes a time. The reasons why they started to use SNSs were mainly to follow current trends, maintain friendship, and accept acquaintances recommendations. Second, the result of component analysis derived four primarily underlying dimensions related to SNS use; self-satisfaction, social interaction, recreation, and information seeking. Third, both self-satisfaction and social interaction motivation had significant correlation with SNS participation. The results of multiple regression analysis showed that self motivation was more influential on active participation than social interaction and information seeking motivation.

• Convergence Security Journal
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• v.15 no.5
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• pp.87-95
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• 2015

Recently, The cloud computing technology is emerging as an important issue in the world, and In technology and services, has attracted much attention. Cloud services have evolved from simple forms to complex forms(using multiple mobile devices and communication services(Kakao talk, Facebook, etc.). In particular, as the cloud is especially facilitated the collection of user information, it can now be analyzed with the user's taste and preference. And many of the benefits of the cloud became increasingly closely with our lives. However, the positive aspects of cloud computing unlike the includes several vulnerabilities. For this reason, the Hacking techniques according to the evolution of a variety of attacks and damages is expected. Therefore, this paper will be analyzed through case studies of attack and vulnerability to the privacy threats factors of the cloud computing services. and In the future, this is expected to be utilized as a basis for the Privacy security and Response.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• Convergence Security Journal
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• v.22 no.5
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• pp.11-20
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• 2022

As the Internet and web technology develop around mobile devices, image data contains various types of sensitive information such as people, text, and space. In addition to these characteristics, as the use of SNS increases, the amount of damage caused by exposure and abuse of personal information online is increasing. However, research on de-identification technology based on multi-type object detection for personal information protection is insufficient. Therefore, this paper proposes an artificial intelligence model that detects and de-identifies multiple types of objects using existing single-type object detection models in parallel. Through cutmix, an image in which person and text objects exist together are created and composed of training data, and detection and de-identification of objects with different characteristics of person and text was performed. The proposed model achieves a precision of 0.724 and mAP@.5 of 0.745 when two objects are present at the same time. In addition, after de-identification, mAP@.5 was 0.224 for all objects, showing a decrease of 0.4 or more.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.39-46
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• 2012

Electrical impedance tomography(EIT) can produce functional images with conductivity distributions associated with physiological events such as cardiac and respiratory cycles. EIT has been proposed as a clinical imaging tool for the detection of stroke and breast cancer, pulmonary function monitoring, cardiac imaging and other clinical applications. However EIT still suffers from technical challenges such as the electrode interface, hardware limitations, lack of animal or human trials, and interpretation of conductivity variations in reconstructed images. We improved the KHU Mark2 EIT system by introducing an EIT electrode interface consisting of nano-web fabric electrodes and by adding a synchronized biosignal measurement system for gated conductivity imaging. ECG and respiration signals are collected to analyze the relationship between the changes in conductivity images and cardiac activity or respiration. The biosignal measurement system provides a trigger to the EIT system to commence imaging and the EIT system produces an output trigger. This EIT acquisition time trigger signal will also allow us to operate the EIT system synchronously with other clinical devices. This type of biosignal gated conductivity imaging enables capture of fast cardiac events and may also improve images and the signal-to-noise ratio (SNR) by using signal averaging methods at the same point in cardiac or respiration cycles. As an example we monitored the beat by beat cardiac-related change of conductivity in the EIT images obtained at a common state over multiple respiration cycles. We showed that the gated conductivity imaging method reveals cardiac perfusion changes in the heart region of the EIT images on a canine animal model. These changes appear to have the expected timing relationship to the ECG and ventilator settings that were used to control respiration. As EIT is radiation free and displays high timing resolution its ability to reveal perfusion changes may be of use in intensive care units for continuous monitoring of cardiopulmonary function.

• Journal of Acupuncture Research
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• v.33 no.4
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• pp.65-72
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• 2016

Objectives : While neck pain is highly prevalent in Korea, studies examining its Korean medical treatment are currently lacking. The aim of this study was to assess current Korean medical treatment practice patterns for neck pain. Methods : A preliminary questionnaire was developed to investigate current practice patterns of neck pain and cervical intervertebral disc displacement (IDD) treatment, and underwent further revision through external review. The final questionnaire was distributed as a web-based survey to 18,289 potential respondents by email. Results : The response rate was 3.34 %. Most participants replied that they received multiple Korean medicine interventions for neck pain treatment consisting of such methods as acupuncture, wet cupping, interferential current therapy and electroacupuncture. A total of 378 respondents acknowledged that diagnostic testing was needed for neck pain treatment. The most commonly used Korean Standard Classification of Diseases (KCD) principal diagnosis code for neck pain was M542, and for cervical IDD was M501. Conclusion : This survey study helps determine current practice patterns of neck pain, and recognizes the need for use of diagnostic devices in neck pain treatment. These results are further anticipated to provide basic data for clinical practice guidelines (CPGs) and future studies using Korean National Health Insurance and Health Insurance Review & Assessment Service data.

• Journal of Korean Medicine Rehabilitation
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• v.28 no.1
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• pp.73-84
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• 2018

Objectives While Temporomandibular disorders (TMD) is highly prevalent in Korea, studies examining its Korean medical treatment are currently lacking. The aim of this study was to assess current Korean medical treatment practice patterns for TMD. Methods A preliminary questionnaire was developed to investigate current practice patterns of TMD treatment and underwent further revision through external review. The final questionnaire was distributed as a web-based survey to 18,289 potential respondents by email. Results The response rate was 2.23%. Most participants replied that they received multiple Korean medicine interventions for TMD treatment consisting of such methods as acupuncture, chuna manipulation, electroacupuncture. The percentage of treatment services among uncovered services, which need to be covered by national health insurance was high in the order of pharmacopuncture, chuna manipulation, and herbal medicine. The most commonly used diagnostic examination tools for TMD was Physical examination and next was Imaging diagnosis. The frequency of TMD treatment was the highest at 2~3 times per week (76%) and the period was from 4 to 12 weeks (63%). Conclusions This survey study helps determine current practice patterns of TMD, and recognizes the need for use of diagnostic devices in TMD treatment. These results are further anticipated to provide basic data for clinical practice guide lines (CPGs).

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.53-60
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• 2008

Streaming media has contributed to a significant amount of today's Internet Traffic. Like traditional web objects, rich media objects can benefit from proxy caching, but caching streaming media is more of challenging than caching simple web objects, because the streaming media have features such as huge size and high bandwidth. And to support various bandwidth requirements for the heterogeneous ubiquitous devices, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we define the 9-events of transcoding proxy using 4-atomic events. According to these events, the transcoding proxy can define the next actions. Then, we also propose the segment-based caching policy for the transcoding proxy system. The performance results show that the proposing policy have a low delayed start time, high byte-hit ratio and less transcoding data.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.528-545
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• 2007

Recently ontology has been an attractive technology along with the business strategy of providing a plenty of more intelligent services. The essential problem in application domains using ontology is that all members, agents, and application programs in the domains must share the same ontology concepts. However, a variety of mobile devices, sensing devices, and network components manufactured by various companies, a variety of common carriers, and a variety of contents providers make multiple heterogeneous ontologies more likely to coexist. We can see many past researches fallen into resolving this semantic interoperability. Such methods can be broadly classified into by-mapping, by-merging, and by-translation. In this research, we focus on by-translation among them which uses a translation rule directly made between two heterogeneous ontology data like OntoMorph. However, the manual composition of the direct translation rule is not convenient by itself and if there are N ontologies, the direct method has the rule composition complexity of $O(N^2)$ in the worst case. Therefore, in this paper we introduce the cascade composition of translation rules based on web openness in order to improve the complexity. The research result made us recognize some important factors in an ontology translation system, that is speediness of translation, and conveniency of translation rule composition, and some experiments and comparing analysis with existing methods showed that our cascade method has more conveniency with insuring the speediness and the correctness.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.179-192
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• 2014

Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.