• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.903-913
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• 2015

The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.

• 한국벤처창업학회:학술대회논문집
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• 2008.04a
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• pp.179-208
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research.Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.1-28
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and Empirical Research on the R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research. Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.605-613
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• 2015

This paper addresses the problem to make sparse the projection matrix in pattern recognition method. Recently, the size of computer program is often restricted in embedded systems. It is very often that developed programs include some constant data. For example, many pattern recognition programs use the projection matrix for dimension reduction. To improve the recognition performance, very high dimensional feature vectors are often extracted. In this case, the projection matrix can be very big. Recently, RSR(roated sparse regression) method[1] was proposed. This method has been proved one of the best algorithm that obtains the sparse matrix. We propose three methods to improve the RSR; outlier removal, sampling and elastic net RSR(E-RSR) in which the penalty term in RSR optimization function is replaced by that of the elastic net regression. The experimental results show that the proposed methods are very effective and improve the sparsity rate dramatically without sacrificing the recognition rate compared to the original RSR method.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.468-481
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• 2018

This study aims to empirically investigate how users' online engagement behaviors predict their uses of paid contents. To this end, the data from the 2016 Korean Media Panel Survey, which has been conducted annually by the Korea Information Society Development Institute(KISDI), were analyzed. Major findings(N=8.313) were as follows. First, the active type of online engagement(e.g., posting, commenting), which contributes to direct creation of online contents, was the most powerful predictor to explain the DV. On the other hand, relatively passive actions of user engagement(e.g., sharing, endorsing, voting) turned out to have no significant effects on the uses of paid contents, just as personality traits and online privacy concerns did. Based on these results, it is recommended that online contents or platform service providers should try to establish clearly-targeted marketing strategies, after thoroughly collecting and analyzing the data of users' various online behaviors.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.85-93
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• 2018

The Latent Growth Modeling(LGM) is known as the arising analysis method of longitudinal data and it could be classified into unconditional model and conditional model. Unconditional model requires estimated value of intercept and slope to complete a model of fitness. However, the existing LGM is in absence of a structured methodology to estimate slope when longitudinal data is neither simple linear function nor the pre-defined function. This study used Sequential Pattern of Association Rule Mining to calculate slope of unconditional model. The applied dataset is 'the Youth Panel 2001-2006' from Korea Employment Information Service. The proposed methodology was able to identify increasing fitness of the model comparing to the existing simple linear function and visualizing process of slope estimation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.11-19
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• 2021

In this paper, we propose a prototype platform combined with the power management system using, as an auxiliary power storage device, a supercapacitor that can be fast charged and discharged with high power efficiency as well as semi-permanent charge and discharge cycle life. For the proposed platform, we designed a technique which is capable of detecting the state of power cutoff or resumption of power supplied from the solar panel in accordance with physical environment changes through an interrupt attached to the micro-controller was developed. To prevent data loss in a computing environment in which continuous power supply is not guaranteed, we implemented a low-level system software in the micro-controller to transfer program context and data in volatile memory to nonvolatile memory when power supply is cut off. Experimental results shows that supercapacitors effectively supply temporary power as auxiliary power storage devices. Various benchmarks also confirm that power state detection and transfer of program context and data from volatile memory to nonvolatile memory have low overhead.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.119-126
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• 2021

Recently OTT video service has grown rapidly and has a negative impact on the growth of pay-TV subscribers. Consequently the substitution of OTT services for pay-TV services will begin. This study explores OTT usage patterns, dividing into three sectors (OTT service use, OTT usage volume, and paid-OTT service use), by considering users' demographice factors, smart device ownership, pay-TV subscription, and bundle service use, by employing the Mediapanel dataset. The results showed that age, income, smartTV usage, market size, cable/satellite subscribers, TV VOD expenses, movie VOD expenses, and mobile bundle use are associated with OTT service use. The results also showed that age, household sizes, tablePC usgage, cable/satellite subscribers, TV VOD expenses, other VOD expenses, and unlimited data plans are associated with OTT usage volume. Lastly the results showed that age, gender, income, tabletPC usage, cable subscribers, other VOD expenses, mobile bundle usage, and unlimited data plans are associated with paid-OTT service use.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.203-210
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• 2022

In this study, we tried to examine the longitudinal mediating effects of school violence damage experience and aggression in the relationship between child maltreatment experiences and school bullying experiences. For the analysis data for this purpose, the 3rd, 5th, 6th, and 7th data of the Korean Children and Youth panel data of the Korea Youth Policy Research Institute were used. A total of 1,813 data were analyzed using the statistical program SPSS 26.0 and Amos 26.0 version as a multivariate latent growth model. As a result of the analysis, it was possible to confirm the mediating effects of school violence victimization experiences and aggression. These results suggest that multilateral efforts are needed to lower the level of maltreatment, school violence victimization, and aggression that affect the school bullying experiences. Based on the results of this analysis, this study specifically suggested practical measures to prevent adolescents' maltreatment experiences from being reproduced as school bullying experiences.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.279-291
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• 2018

This study is designed to demonstrate risk factors of unmet medical care for people with cerebrovascular disease. To do this, statistical analysis was performed by using hierarchical logistic regression analysis with SPSS/WIN24.0 program using Korean Medical Panel data in 2014. In the final model of the hierarchical logistic regression analysis, which is based on Anderson's Model, adjusted for the factors of the predisposing and enabling factors, the explanatory variables affecting the unmet medical development are gender, economic activity, income level, the experience of lying in a sickbed, restriction on activity, subjective health condition, and the number of chronic diseases. Based on the results of this study, the practical and policy implications for the effective management and treatment of cerebrovascular disease should be included in the countermeasures for cerebrovascular disease, a strategy to reduce the unmet medical incidence of cerebrovascular disease, in order to meet the medical needs, the necessity of comprehensive measures considering various dimensions of variables and the influential variables of unmet medical emergence have been suggested for the necessity of making a detailed service manual that can improve accessibility to medical services.