• Archives of design research
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• v.18 no.2 s.60
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• pp.5-14
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• 2005

Graphic Design is being developed as a unique genre and widely applied to movie, TV broadcasting, music video, computer an, web design, animation, and game. Some university added motion graphics in their curriculum recently. However Motion Graphic has not been defined clearly and pedagogy of motion graphics was not studied enough. Motion Graphic is not merely moving picture. Its typical purpose and concept are evolving because of the diversified application. Meta-synthesis between media and hybrid development based on diverse approach and composite presentational methods are also changing Motion Graphic. Various technology such as photograph, analytical engine, hypermedia, multimedia, digital composite picture, network and interface should be studied to understand Motion Graphic. This study reviews the historic background of Motion Graphic mainly related to its advent. A fundamental definition of Motion Graphic including the space and time is suggested and the international trend is introduced. Future Motion Graphic and possible development was also predicted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1485-1491
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• 2019

As the type and size of vital signs become extensive at the moment lately, a research is actively progressing to define vital signs as big data and analyze it. We generally use a similar method of processing big data on social network as a way to treat vital signs as big data. Vital Sign Big Data should be extracted as feature data, stored separately, and analyzed with various analytical instruments. In other words, it should ensure interoperability and compatability of data, and the index expression in analytical tools should be concise. For this end, I defined the vital sign as the standard meta-model base of HL7 in this dissertation, and I propose a model for analyzing vital signs using OCL, the OMG's standard mathematical specification language. In addition, the proposed model can be confirmed the applicability by figuring out the consumption of calories using ECG data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.165-174
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• 2019

They are frequently used today in public places such as street, subway, school or library. Since users can sometimes print documents that contain confidential data using Printer Kiosks, the devices should store and manage the documents securely. In this paper, we identify potential security threats in Printer Kiosks and suggest practical attack scenarios that can take place. To show the feasibility of suggested attack, we analyzed network traffic that were generated by the real Printer Kiosk device. As a result of our analysis, we have found that attackers can access other users' scanned files and access other users' documents from Printer Kiosk's home page. We confirmed that using our attack, we could retrieve other users' personal data.

• KNOM Review
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• v.21 no.2
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• pp.10-17
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• 2018

With the popularization of smart devices and the development of wireless Internet, the consumption method of music contents is changing to streaming rather than downloading. In this paper, we analyze the meta data of the music source exposed on the network traffic for the 19 music streaming services in Korea and abroad. We propose a preventive measure. As a result of analysis, we found that all of the 19 services were exposed to the metadata of the music. We propose a music and metadata protection method such as certificate fixing method to prevent exposure of such music and metadata.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.95-114
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• 2020

This paper, a meta-analysis of the effect of the start-up support policy on the start-up performance was conducted to examine the effect of the start-up support policy on the start-up performance of beneficiary companies and to provide theoretical and practical implications to support organizations and practitioners. To this end, 35 papers containing the correlation coefficient, which is a positive statistical value, were selected from the previous studies in academic journals and dissertations published in Korea from 2007 to 2020. In the preceding study of the start-up support policy, the independent variables include funding, education support, facility/equipment support, network support, mentoring support, consulting support, marketing support, management support, technical support, manpower support, and finance as a dependent variable. The effect size of the impact on aptitude and non-financial performance was reviewed. The pattern of the effect size was presented as a forest plot for easy visual understanding, and outliers were verified through sensitivity analysis for small-study-effect data with publication convenience. As a result of analyzing the effect size of the government-supported policy, it was verified that the effect size was generally medium or higher, affecting the entrepreneurial performance. Among the independent variables, the factor that has the greatest effect on startup performance is manpower support, followed by technical support, marketing support, management support, facility/equipment support, education support, mentoring support, funding, network support, and consulting support. It was analyzed that the effect size was large in order. As the 「Small and Medium Business Startup Support Act」 was recently reorganized from the manufacturing industry to digital transformation and smartization on October 8, 2020, the start-up support policy should consider the start-up stage and verify the priorities to organize the budget.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.599-610
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• 2016

This paper reports the results of a systematic review (SR) and meta-analysis research to compare the effect of Kangaroo care, targeting mothers and premature infants. A randomized clinical trial study was performed until February 2015. The domestic literature contained the non-randomized clinical trial research without restriction according to the level of the study design. A search of the Ovid-Medline, CINAHL, PubMed and KoreaMed, the National Library of KOREA, the National Assembly Library, NDSL, KISS and RISS. Through the KMbase we searched and combined the main term ((kangaroo OR KC OR skin-to-skin) AND (care OR contact)) AND (infant OR preterm OR Low Birth Weight OR LBW), ((kangaroo OR kangaroo OR kangaroo) AND (care OR nursing care OR management OR skin contact)) was made; these were all combined with a keywords search through the selection process. They were excluded in the final 25 studies (n=3051). A methodology checklist for randomized controlled trials (RCTs) designed by SIGN (Scottish Intercollegiate Guidelines Network) was utilized to assess the risk of bias. The overall risk of bias was regarded as low. In 16 studies that were evaluated as a grade of "++", 9 studies were evaluated as a grade of "+". As a result of meta-analysis, kangaroo care regarding the effects of premature mortality, severe infection/sepsis had an insignificant effect. Hyperthermia incidence, growth and development (height and weight), mother-infant attachment, hypothermia incidence, length of hospital days, breast feeding rate, sleeping, anxiety, confidence, and gratification of mothering role were considered significant. In satisfaction of the role performance, depression and stress presented contradictory research results for individual studies showing overall significant difference. This study has some limitations due to the few RCTs comparing kangaroo care in the country. Therefore, further RCTs comparing kangaroo care should be conducted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6099-6111
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• 2015

This study was a systematic review and meta-analysis comparing the effects of aquatic exercise and land-based exercise in the treatment of knee osteoarthritis. 7 studies (n=449) met selection and exclusion criteria out of 287 potential studies obtained from the literature search via Ovid-Medline, Cochrane Library CENTRAL, CINAHL, RISS and KISS. The overall risk of bias of selected studies using SIGN (Scottish Intercollegiate Guidelines Network) checklist for randomized controlled trials (RCT) was regarded as low. As a result of meta analysis, Standardized Mean Difference (SMD) for pain was -0.26(95% CI -0.49, -0.03, p=0.03, $I^2=14%$), which implies that aquatic exercise groups had significant less pain than land-based exercise groups. On the other hand, there was no significant difference between aquatic exercise groups and land based exercise groups for flexion Range of Motion (ROM) (-0.12, 95% CI -0.51, 0.27, p=0.53, $I^2=0%$), extension ROM (-0.04, 95% CI -0.55, 0.48, p=0.89, $I^2=43%$), physical function (-0.12, 95% CI -0.44, 0.19, p=0.44, $I^2=0%$), Quality of Life (QOL) (-0.15, 95% CI -0.54, 0.24, p=0.46, $I^2=0%$). This study has some limitations due to few RCTs comparing aquatic exercise groups and land-based exercise groups in the treatment of knee osteoarthritis. Therefore, further RCTs should be conducted along with long-term outcomes.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.77-100
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• 2018

The objectives of this study is to present a discovering process of interdisciplinary convergence technology using text mining of big data. For the convergence research of biotechnology(BT) and information communications technology (ICT), the following processes were performed. (1) Collecting sufficient meta data of research articles based on BT terminology list. (2) Generating intellectual structure of emerging technologies by using a Pathfinder network scaling algorithm. (3) Analyzing contents with topic modeling. Next three steps were also used to derive items of BT-ICT convergence technology. (4) Expanding BT terminology list into superior concepts of technology to obtain ICT-related information from BT. (5) Automatically collecting meta data of research articles of two fields by using OpenAPI service. (6) Analyzing contents of BT-ICT topic models. Our study proclaims the following findings. Firstly, terminology list can be an important knowledge base for discovering convergence technologies. Secondly, the analysis of a large quantity of literature requires text mining that facilitates the analysis by reducing the dimension of the data. The methodology we suggest here to process and analyze data is efficient to discover technologies with high possibility of interdisciplinary convergence.