• Journal of Korean Academy of Fundamentals of Nursing
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• v.9 no.1
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• pp.56-65
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• 2002

The purpose of this study was to investigate the level of alienation, depression, suicidal ideation and delinquency in high school students and to explore the relationships between the variables. The respondents, 226 students attending a high school located in Chonnam province made up the convenience sample. Data were collected using a structured questionnaire which included the alienation scale, suicidal ideation scale, BDI, and delinquency scale. Data collection was done between June 20 and July 6, 2001. Data were analyzed with the SAS program and included descriptive statistics, t-test, ANOVA and Pearson's correlation coefficients. There were no significant association between alienation and general characteristics of the students. The scores for depression were significantly higher in female students, in students who had recently dropped in their school ranking compared to students who had improved. The scores of suicidal ideation were significantly higher in male students. Also, the scores of delinquency were significantly higher in male students, and students in the high economic class and those with low school rankings. There were significant positive correlations between alienation and other ; alienation and depression (r= .432, p= .000), alienation and suicidal ideation (r= 267. p= 000), and alienation and delinquency (r= 150, p= .024). Findings from this study suggest that subsequent practical study in consideration of Korean sociocultural background is needed to identify the cause of alienation and develop supportive strategies to maintain mental health in high school students. Also, study on alienation of students should be based on family, community and popular culture in combination with improvements in school environment.

• Restorative Dentistry and Endodontics
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• v.38 no.1
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• pp.31-35
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• 2013

Objectives: This study compared the cyclic fatigue resistance of nickel-titanium (NiTi) files obtained in a conventional test using a simulated canal with a newly developed method that allows the application of constant fatigue load conditions. Materials and Methods: ProFile and K3 files of #25/.06, #30/.06, and #40/.04 were selected. Two types of testing devices were built to test their fatigue performance. The first (conventional) device prescribed curvature inside a simulated canal (C-test), the second new device exerted a constant load (L-test) whilst allowing any resulting curvature. Ten new instruments of each size and brand were tested with each device. The files were rotated until fracture and the number of cycles to failure (NCF) was determined. The NCF were subjected to one-way ANOVA and Duncan's post-hoc test for each method. Spearman's rank correlation coefficient was computed to examine any association between methods. Results: Spearman's rank correlation coefficient (${\rho}$ = -0.905) showed a significant negative correlation between methods. Groups with significant difference after the L-test divided into 4 clusters, whilst the C-test gave just 2 clusters. From the L-test, considering the negative correlation of NCF, K3 gave a significantly lower fatigue resistance than ProFile as in the C-test. K3 #30/.06 showed a lower fatigue resistance than K3 #25/.06, which was not found by the C-test. Variation in fatigue test methodology resulted in different cyclic fatigue resistance rankings for various NiTi files. Conclusions: The new methodology standardized the load during fatigue testing, allowing determination fatigue behavior under constant load conditions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.184-192
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• 2019

Focusing on the emerging influencer market of SNS (Social Network Service), This study attempts to clarify the priority of Influencer characteristics when the customer decided to purchase products through the promotion of influencers. Since the influencer marketing differs from the Online information source marketing, this study has an academic implication in that integrated the influence of the characteristics of the Online information sources and the characteristics of SNS contents. For this purpose, through the literature research on Information sources and Influencers, the characteristics of influencers were reconstructed and priorities were derived using the AHP (Analytic Hierarchy Process) technique. The upper layer of the AHP structure was set to expertise, trustworthiness, social attractiveness, and content attractiveness, and the lower layer structured the model with 13 subfactors. The results are summarized as follows. First, in the result of combining the importance of the $1^{st}$ and $2^{nd}$ classes, the detailed factors of expertise and trustworthiness, ranked from the top to six, are largely influenced in purchasing decisions in influencer marketing. Second, content attractiveness is the third rank in the $1^{st}$ layer. Influencer marketing shows that content is more important than social attractiveness. Besides, the $7^{th}$ to $9^{th}$ positions of the overall rankings accounted for visual information, storytelling, and external attractiveness, which are the details of content attractiveness, and it is confirmed that it is more effective for influencer marketing to emphasize content attractiveness than social attractiveness. Although the influencer marketing differs from the existing information marketing, this study has an academic implication in that integrated the influence of the characteristics of the source and the characteristics of the contents.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.21-28
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• 2022

The increase in the number of large cities and the size of their population sharpens attention to the new role of cities as entities to ensure a high-quality, safe and modern life of citizens, which has become significantly more active in recent years. The rapid spread of smart cities in the modern world has actualized the issue of analyzing their success and assessing the role of various factors in this. Every success of a smart city is always the result of a unique combination of the most modern technologies, environmental and social initiatives, skillful and consistent management, as well as available human potential. The purpose of the article is to analyze the success factors of smart cities based on the generalization of the results of the most famous ratings. In order to identify the impact of various factors, primarily intellectual, on the success and leadership positions of smart cities, the following ratings were consistently analyzed: Smart City Index (SCI), City in Motion Index (CIMI), Global Power City Index (GPCI), Global Cities Index (GCI), Global Cities Outlook (GCO). They have a different list of indicators and main pillars (dimensions), but all ratings take into account aspects such as: governance, ICT, mobility, functionality, human capital, etc. The highest correlation coefficient, that is, the strongest linear relationship of the CIMI index was found with such factors as: Human capital, Economy, Governance and Technologies. Summarizing the results of the TOP 20 smart cities according to different ratings allowed us to confirm that the list of leaders is very similar in all ratings. Among those cities that are in the TOP-20 in all five indexes are: London, Sydney and Singapore. There are four indices: New York, Paris, Tokyo, Copenhagen, Berlin, Amsterdam, Melbourne. Achieving leadership positions in smart city rankings is always the result of a combination and synergy of certain factors, and first of all, it is the quality of human capital. The intensity and success of the use of information and communication technologies in locality management processes, city planning and improvement of the city's living conditions depend on it.

• Journal of Korean Society of Forest Science
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• v.94 no.3 s.160
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• pp.183-190
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• 2005

This study was carried out to find out the possibility for developing methodologies on the index for forest sustainability and to assess sustainability indices of metropolitan and provincial districts based on conditions of their forest health and management programmes in Korea. To find out some indicators to be utilized in developing the forest sustainability indices, total 84 possible indicators were selected and combined from 69 major programmes contained in the 4th Forest Development Plan and the Forest Vision for 21st Century and other 15 indicators selected separately from other forest policies. Those candidate indicators were reviewed throughly under evaluation processes and 33 indicators were finally chosen in developing the forest sustainability indices. Those indicators were classified into 3 categories, namely indicators for pressure, state, and response. Forest health could be represented by pressure and state indicators, while forest management programmes could be assessed by response indicators. Scores of importance for each indicator were assigned through Delphi survey and analyzed to project the extra weight value by summing rankings given to each index an applied to the standardized value of each index. Forest sustainability indices of metropolitan and provincial districts were analyzed and compared, based on relevant data of the year 2002. This study was kind a preliminary one in forest sustainability index and the names of metropolitan and provincial districts were not identified in this study. The indices could be very valuable in assessing quantitatively the level of forest health and intensity of forest management programmes in each districts and comparisons could be made among them, if all self-governing districts agree unanimously on the indices of forest sustainability and relevant indicators chosen in the study.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.353-376
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• 2023

The global pandemic and the development of virtual and augmented reality technologies have led a metaverse boom that enables a lot of interactions in virtual worlds, and is being utilized in various fields such as business, government, and education etc. Despite the growing interest in the metaverse, its scope and definition are still unclear and the concept is still evolving, making it challenging to establish its governance. Governmental entities are also investing intensively in public metaverses to make public value and promote social welfare, but they are underutilized due to lack of systematic governance. Therefore, in this study, we propose a public metaverse governance framework and identify the relative importance of the factors. Furthermore, since a public metaverse should be accessible to anyone who wants to use, we explore the factors of shadow work and examine the ways to minimize it. Based on the socio-technical system theory, we derived public metaverse governance factors from previous literature and topic modeling and then generate a framework with 23 factors through expert interviews. We then tested relative priority of the factors using the analytic hierarchical process (AHP) from the experts. As a result, the top five overall rankings are: 'roles and responsibilities', 'standardization/modularization', 'collaboration and communication', 'law and policies', and 'availability/accessibility'. The academic implications of this study are that it provides a comprehensive framework for public metaverse governance, and then the practical implications include suggesting prioritized considerations for metaverse operations in the public sector.

• Asia Marketing Journal
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• v.16 no.4
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• pp.75-87
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• 2015

As more companies become interested in global markets, it has become crucial for firms to create globalized brands whose positioning, advertising strategy, personality, looks, and feel are consistent across nations. The purpose of this study is to investigate the global branding strategy of the Hyundai Motor Company (hereafter HMC) in order to show how the company processes its branding strategy. HMC, one of the leading global companies in the automobile industry, set up its brand identity as "Modern premium", in alignment with their new slogan "New Thinking New Possibilities", in 2011. The aim of the "Modern premium" concept was to provide consumers with new experiences and values beyond their expectations. HMC wanted their consumers to think of their cars as not only a medium of transportation but as a life space, where they can share experiences alongside HMC. In an effort to conduct consumer research in 5 different nations, HMC selected "brilliant" as a key communication concept. The word "brilliant" expresses the functional, experiential, and emotional dimensions of HMC. HMC furthermore chose "live brilliant" as a key campaign message in order to reinforce their communication concept. After this decision, the "live brilliant" campaign was exhibited through major broadcast channels around the world. The campaign was the company's first worldwide brand campaign, where a single message was applied to all major markets, with the goal of building up a consistent image as a global brand. This global branding strategy is worth examining due to its significant contribution to growth generation in the global market. Overall, the 'live brilliant' global brand campaign not only improved HMC's reputation image-wise, with the 'Modern Premium' conceptualization of the brand as 'simple', 'creative' and 'caring', but also improved the consumer's familiarity, preference and purchase intention of HMC. In fact, the "live brilliant" campaign was a successful campaign which increased HMC's brand value. Notably, HMC's brand value increased continuously and reached 9 billion US dollars in 2013, leading it to reach 43rd place in the Global Brand Rankings according to the brand consulting group Interbrand. Its brand value largely surpassed that of Nissan (65th) and Chevrolet (89th) in 2013. While it is true that the global branding strategy of HMC involved higher risks, it was highly successful according to cross-nation consumer research. Therefore, this paper concludes that the global branding strategy of HMC made a positive impact on its performance. We further suggest HMC to combine its successful marketing with social media such as Facebook, Twitter, and Instagram and embrace digital media by extending its brand communication horizon to the mobile internet

• Journal of Animal Science and Technology
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• v.53 no.4
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• pp.325-332
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• 2011

This research was conducted to analyze the effects of raising farm on the heritability and breeding values of Hanwoo cows for their carcass traits, including cold carcass weight (CWT), back-fat thickness (BFT), eye-muscle area (EMA) and marbling score (MAR). The carcass data and pedigree data were collected from steers raised on Hanwoo farms in Pyeongchang-gun, Gangwon-do, South Korea. Three analytical models were applied for the estimation of heritabilities and breeding values. The first model (model 1) included slaughter house-year-month combination as fixed effects and age at slaughter was fitted as linear and quadratic covariates. The second model (model 2) was similar to model 1, but raising farm was additionally included as random effect. The third model (model 3) was similar to model 1 but farm effects were additionally included as fixed effect. The comparisons between the model 1 and the models including farm effect (model 2 and model 3) revealed that heritability estimates from model 2 or model 3 were smaller to those from model 1 for all carcass traits. Especially, obvious decrease of heritability was observed in CWT where heritability was 0.23 from model 1, 0.15 from model 2 and 0.18 from model 3. The maximum log likelihood of the model 2 and 3 were higher than those of model 1 for all traits. In model 2 that raising farm was included as a random effect, the ratio of farm variance to the total phenotypic variance were ranged from 4% (EMA) to 18% (CWT). Top 10% and bottom 10% of female cows were selected based on the breeding values from model 1, and the Spearman's rank correlation coefficients among models were estimated for each trait within selected group. The correlation coefficients were ranged from 0.57 to 0.95 in top 10% group and from 0.68 to 0.95 in bottom 10% group. These results show that the discrepancies in the rankings of breeding values can be based on the models applied. In conclusion, the results obtained in this study suggest that the herd effect or farm effect should be included in the analytical model when breeding values are estimated with the purpose of improvement of carcass traits of Hanwoo breeding cows.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.