• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1075-1081
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• 2013

Twitter, Facebook, and KakaoStory are the major SNS in Korea. Social knowledge production is being produced by those services from numerous collaboration and co-participation in those SNS. Wikipedia or Naver JishikIN service was regarded as the representative product of collective knowledge production during the wired internet era. However now at the wireless internet era centered with smart phones, various forms of collective knowledge production would be achieved by connecting to SNS in real-time. In this thesis, the survey data of collective knowledge production for users of three SNS have been compared and analyzed. The difference of the collective knowledge production mechanism among Twitter, Facebook and KakaoStory has been studied and compared through three variables: the motivation of collective knowledge production, the preference of collective knowledge production model, and collective knowledge production cultural perception. As a result of the analysis of the discriminant factors for three SNS user groups, it turns out that the diversity-toward usage motivation, personal contribution motivation, and collective knowledge production tendency perception are the most influential variables. This thesis is of significance in that it unites the value of social science such as social capital and collective knowledge production from the viewpoint of computer science and opens the new chapter of collective knowledge production with the real-time SNS of wireless internet from the wired internet.

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.596-610
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• 2007

In order to reduce the complexity of SVC encoding, we introduce a fast mode decision method in the enhancement layers of spatial scalability by selectively performing the inter-layer residual prediction of SVC. The Inter-layer residual prediction coding in Scalable Video Coding has a large advantage of enhancing the coding efficiency since it utilizes the correlation between two residuals from a lower spatial layer and its next higher spatial layer. However, this entails the dramatical increase in the complexity of SVC encoders. The proposed method is to analyze the characteristics of integer transform coefficients for the subtracted signal for two residuals from lower and upper spatial layers. Then it selectively performs the inter-layer residual prediction coding and rate-distortion optimizations in the upper spatial enhancement layer if the SAD values of residuals exceed adaptive threshold values. Therefore, by classifying the residuals according to the properties of integer-transform coefficients only with SAD of residuals between two layers, the SVC encoder can perform the inter-layer residual coding selectively, thus significantly reducing the total required encoding time. The proposed method results in reduction of the total encoding time with 51.5% in average while maintaining the RD performance with negligible amounts of quality degradation.

• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.627-653
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• 2006

The purpose of this study lies in understanding how the spectrum assigned for each mobile operator affects the consumers of mobile service. For this purpose, we have observed the change of path coefficient in the structural equation, using control variables. However, the structure of the mobile service market in Korea has become fixed. Considering this tendency and the conclusion of this study, the 'lock-in effect' occurs seriously in the mobile service market in Korea. It can be explained by the fact that CS(Customer Satisfaction) of the cellular subscribers little affects customer loyalty but the market dominance of the cellular service in the actual market has continued for a long time. In this study, we figured out a strong prejudice about call quality, which is caused by spectrum difference among competitors. Cellular subscribers tends to believe that call quality of their cellular service is better than that of PCS. In addition, we found that PCS operators can catch customer's retention by investment into network in order to increase call quality.

• Korean Security Journal
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• no.57
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• pp.205-230
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• 2018

The purpose of this study is to examine the structural model between servant - transformational leadership, organizational citizenship behavior and organizational performance of private security organizations. The security guards working in private security companies in Seoul and Gyeonggi - do were selected as population, random sampling method. The survey was conducted from September 1, 2016 to November 30. Accoridng to the purpose of the study, this study conducted factor analysis(EFA/CFA), reliability analysis, convergence and discriminant validity analysis, and covariance structure analysis using SPSSWIN 21.0 and AMOS 21.0. The conclusions of this study are as follows. First, servant leadership has a positive (+) effect (${\beta}=.406$) on organizational citizenship behavior statistically at .001 level. Second, transformational leadership has a positive (+) effect (${\beta}=.373$) on organizational citizenship behavior statistically at .001 level. Third, organizational citizenship behavior has a positive (+) effect (${\beta}=.615$) on organizational performance statistically at .01 level. Fourth, servant leadership does not affect the organizational performance statistically (${\beta}=.211$). Fifth, transformational leadership does not affect the organizational performance statistically (${\beta}=.058$). Sixth, organizational citizenship behavior has statistically positive (+) mediation effect (${\beta}=.249$) in the relationship between servant leadership and organizational performance. Seventh, organizational citizenship behavior has statistically positive (+) mediating effects (${\beta}=.230$) on the relationship between transformational leadership and organizational performance. Innovation and Improvement of National Emergency Management System in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.493-502
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• 2019

Recently, the installation of renewable energy including PV systems in distribution systems has increased energetically to cope with climate change and energy shortages according to the government's policy of renewable energy 3020. On the other hand, the electrical performance and lifespan of PV modules installed outdoors can be decreased considerably due to a range of deterioration phenomena depending on the ambient environmental factors. To overcome these problems, replacement of degraded PV modules with new ones is increased before the lifespan guaranteed by the makers of PV modules. Therefore, this paper proposes a disposal diagnosis algorithm to evaluate the time interval of the optimal replacement for PV modules according to performance degradation rate of PV modules. In addition, this study modeled an economic evaluation, which is composed of the cost and benefit of PV systems. From the simulation results based on the proposed modeling and algorithm to consider the performance degradation rate specifically, the replacement approach was found to have the best B/C ratio in 10th year with a 3[%] degradation rate and the disposal diagnosis algorithm of PV modules are useful and practical tools for economic evaluations of the replacement of PV modules.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.207-224
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• 2018

In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.140-155
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• 2020

This study was conducted to identify the location characteristics of infected farms in the areas where livestock diseases were clustered(southern Gyeonggi-do and Chungcheong-do), analyze the probability of disease occurrence in poultry farms, find out the areas corresponding to the conditions, and use them as the basis for prevention of livestock diseases, selection of discriminatory prevention zones, and establishment of prevention strategies and as the basic data for complementary measures. The increase of one poultry farm within a radius of 3-kilometers increases the risk of HPAI infection by 10.9% compared to the previous situation. The increase of 1m in distance from major roads with two lanes or more reduces the probability of HPAI infection by 0.001% compared to the previous situation. If the distance of the poultry farm located with 15 kilometers from a major migratory bird habitat increases by 15 to 30 kilometers, the chance of infection with HPAI is reduced by 46.0%. And if the distance of the same poultry farm increase by more than 30 kilometers, the chances of HPAI infection are reduced by 88.5%. Based on the results of logistic regression, the predicted probability was generated and the actual area of the location condition with 'more than 15 poultry farms within 3km a radius of, within 1km distance from major roads, and within 30km distance from major migratory birds habitat was determined and the infection rate was measured. It is expected that the results of this study will be used as basic data for preparing the data and supplementary measures when the quarantine authorities establish discriminatory quarantine areas and prevention strategies, such as preventive measures for the target areas and farms, or control of vehicles, by identifying the areas where livestock diseases are likely to occur in the region.

• Journal of Korean Elementary Science Education
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• v.40 no.4
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• pp.520-544
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• 2021

This study aims to develop a scientific creativity test for exploring the relationship between elementary students' creative process and product. For this, the researcher reviewed the literatures of scientific creativity and developed the items based on the constructs of creative process and product. After a review conducted by nine science education specialists, a pilot test, and additional revision and supplementation of observation test, the test, consisting of two sets-"animals" and "plants"-was finally conducted on 105 fifth-grade students. The test results were analyzed by using statistical analysis software. WinSteps, SPSS, and AMOS. The main findings from this study are as follows. First, when it comes to scientific creativity, creative process consists of science knowledge, inquiry skills, and creative thinking skills (divergent, convergent, and associative thinking skills). Creative product in science is a new and scientifically useful idea realized in a certain form. Second, observation, which was selected as a representative inquiry skill in this research, should not be related to creative thinking skills. Third, among the rest of the items, usefulness had the lowest averages, as it was, perhaps, difficult to satisfy the teachers' criteria for the scientific validity and usefulness. Fourth, the Spearman correlation coefficients between the items of "animals" and "plants" to find out the parallel-form reliability were significant, except for the item of originality. Fifth, the test was satisfactory with regard to the three aspects of construct validity-convergent, discriminant, and nomological. This study concludes by discussing the usefulness of this test, which has the possibility of exploring the relationship between creative process and product and of playing a role as an authentic evaluation tool in school.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.519-531
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• 2023

With the aim of preventing safety accidents at construction sites, the company aims to create safe behaviors intended through variables called smart safety and health activities to help reduce industrial accidents. Purpose: It analyzes how smart safety and health activities affect accidents caused by unsafe behavior and changes in worker behavior, which is the root cause, and verifies the hypothesis that it helps prevent safety accidents and protect workers' lives. Method: Smart safety and health activities were selected as independent variables (X), and intended safety and anxiety, which are workers' behavioral intentions, were set as dependent variables (Y), attitude and subjective norms, and planned behavioral control as parameters (M). Exploratory factor analysis, discriminant validity analysis, and intensive validity analysis of safety and health activities were used to analyze the scale's reliability and validity. To verify the hypothesis of behavior change, the study was verified through Bayesian model analysis and MC simulation's probability density distribution. Result: It was found that workers who experienced smart safety and health activities at construction sites had the highest analysis of reducing unstable behavior and performing intended safety behavior. The research hypothesis that this will affect changes in worker behavior has been proven, the correlation between variables has been verified in the structural equation and path analysis of the research analysis, and it has been confirmed that smart safety and health activities can control and reduce worker instability. Conclusion: Smart safety and health activities are a very important item to prevent accidents and change workers' behavior at construction sites.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.