• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Progress in Medical Physics
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• v.19 no.4
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• pp.269-275
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• 2008

Although MR imaging is generally applicable to depict knee joint deterioration it, is sometimes occurred to mis-read and mis-diagnose the common knee joint diseases. In this study, we employed magnetization transfer ratio (MTR) method to improve the diagnosis of the various knee joint diseases. Spin-echo (SE) T2-weighted images (TR/TE 3,400-3,500/90-100 ms) were obtained in seven cases of knee joint deterioration, FSE T2-weighted images (TR/TE 4,500-5,000/100-108 ms) were obtained in seven cases of knee joint deterioration, gradient-echo (GRE) T2-weighted images (TR/TE 9/4.56/$50^{\circ}$ flip angle, NEX 1) were obtained in 3 cases of knee joint deterioration, In six cases of knee joint deterioration, fat suppression was performed using a T2-weighted short T1/tau inverse recovery (STIR) sequence (TR/TE =2,894-3,215 ms/70 ms, NEX 3, ETL 9). Calculation of MTR for individual pixels was performed on registration of unsaturated and saturated images. After processing to make MTR images, the images were displayed in gray color. For improving diagnosis, three-dimensional isotropic volume images, the MR tristimulus color mapping and the MTR map was employed. MTR images showed diagnostic images quality to assess the patients' pathologies. The intensity difference between MTR images and conventional MRI was seen on the color bar. The profile graph on MTR imaging effect showed a quantitative measure of the relative decrease in signal intensity due to the MT pulse. To diagnose the pathologies of the knee joint, the profile graph data was shown on the image as a small cross. The present study indicated that MTR images in the knee joint were feasible. Investigation of physical change on MTR imaging enables to provide us more insight in the physical and technical basis of MTR imaging. MTR images could be useful for rapid assessment of diseases that we examine unambiguous contrast in MT images of knee disorder patients.

• (The)Study of the Eastern Classic
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• no.70
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• pp.303-345
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• 2018

In this article, how the Bangmok(榜目) documents, which are essentially lists of successful passers for the civil competitive examination system of the $Chos{\breve{o}}n$ dynasty, when rendered into digitalized formats, could serve as source of information, which would not only lets us know the $Chos{\breve{o}}n$ individuals' social backgrounds and bloodlines but also enables us to understand the intricate nature that the Yangban network had, will be discussed. In digitalized humanity studies, the Bangmok materials, literally a list of leading elites of the $Chos{\breve{o}}n$ period, constitute a very interesting and important source of information. Based upon these materials, we can see how the society -as well as the Yangban community- was like. Currently, all data inside these Bangmok lists are rendered in XML(eXtensible Makrup Language) format and are being served through DBMS(Database Management System), so anyone who would want to examine the statistics could freely do so. Also, by connecting the data in these Bangmok materials with data from genealogy records, we could identify an individual's marital relationship, home town, and political affiliation, and therefore create a complex narrative that would be effective in describing that individual's life in particular. This is a graphic database, which shows-when Bangmok data is punched in-successful passers as individual nodes, and displays blood and marital relations in a very visible way. Clicking upon the nodes would provide you with access to all kinds of relationships formed among more than 90 thousand successful passers, and even the overall marital network, once the genealogical data is input. In Korea, since 2005 and through now, the task of digitalizing data from the Civil exam Bangmok(Mun-gwa Bangmok), Military exam Bangmok (Mu-gwa Bangmok), the "Sa-ma" Bangmok and "Jab-gwa" Bangmok materials, has been completed. They can be accessed through a website(http://people.aks.ac.kr/index.aks) which has information on numerous famous past Korean individuals. With this kind of source of information, we are now able to extract professional Jung-in figures from these lists. However, meaningful and practical studies using this data are yet to be announced. This article would like to remind everyone that this information should be used as a window through which we could see not only the lives of individuals, but also the society.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.

• Journal of Society of Occupational Therapy for the Aged and Dementia
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• v.12 no.2
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• pp.87-95
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• 2018

Objective : Vibration stimulators are easier to obtain in clinical settings than other treatment tools, and it is advantageous that the arm activation training can be performed passively. Despite the following advantages, recent studies on vibration sense have not been activated yet. The purpose of this study was to investigate the effect of vibration sensation on the hands of the affected upper limb on unilateral reduction of stroke patients. Method : Patients with unilateral neglect due to stroke were enrolled in this study for about 3 weeks from October 19, 2018 to November 7, The research design used ABA design among the single-subject experimental research design, and a total of 18 circuits (4 baseline, 6 intervention, 3 baseline regression) were performed once a day on weekdays Respectively. MMES-K was used to select the subjects. Line bisection test (LBT), Albert's test and Star Cancellation Test (SCT) were used as unilateral neglect test. For the analysis, the baseline and intervention period measurements were visually analyzed using graphs and mean values were used. Result : All three evaluations showed that the number of errors missed during the training period was lower than the baseline period, and this decrease remained after training. The error was reduced by an average of $2{\pm}1.2$ omissions and an average omissions of $0.6{\pm}0.5$ omitting an average of $4.5{\pm}1$ omissions in the line break test. As a result of the Albert test, the average error decreased by $22.5{\pm}1.9$ omissions and $8{\pm}7.3$ omissions and $0.3{\pm}0.5$ omissions, respectively. In the star clearance test, the average error decreased from $26{\pm}4.6$ to $21.8{\pm}1.7$ and $20{\pm}0$, respectively. Conclusion : In this study, vibrotactile stimulation therapy showed a continuous effect on improving unilateral neglect. Based on these findings, further research should be conducted in order to improve objectivity in future studies. Further research on various arbitration methods that maximize the effect of intervention will be needed.