Lee, Sukjoon;Lee, Sang Wook;Hong, Bo Yeong;Eom, Hongmin;Shin, Hyu-Seok;Kim, Kyung-Min
Spatial Information Research
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v.22
no.3
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pp.89-99
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2014
The aim of this study is to represent the residential population distribution in Seoul, Korea more precisely through the dasymetric mapping method. Dasymetric mapping can be defined as a mapping method to calculate details from truncated spatial distribution of main statistical data by using ancillary data which is spatial data related to the main data. In this research, there are two types of data used for dasymetric mapping: the population data (2010) based on a output area survey in Seoul as the main data and the building footprint data including register information as ancillary spatial data. Using the binary method, it extracts residential buildings as actual areas where residents do live in. After that, the regression method is used for calculating the weights on population density by considering the building types and their gross floor areas. Finally, it can be reproduced three-dimensional density of residential population and drew a detailed dasymetric map. As a result, this allows to extract a more realistic calculating model of population distribution and draw a more accurate map of population distribution in Seoul. Therefore, this study has an important meaning as a source which can be applied in various researches concerning regional population in the future.
The purpose of this study is to suggest the improvement plan for an effective benefit sharing support policy through empirical analysis on the benefit sharing operation of government as well as the benefit sharing support policy of government affecting firm performance. Therefore, this study analyzed current problems on benefit sharing operation of government as well as performed a survey for 225 participating and cooperation firms regarding firm performance. This study found some improvements such as insufficient diverse incentive measures leading to the difficulty of participating firm's increase and spread, insufficient substantial benefit sharing such a cash allocation between consignment firms, the increase of biz management system model failing to induce innovation of new technology or product, and difficult spread into 2nd, 3rd cooperative firms besides 1st ones, meanwhile, verifying the positive influence of government benefit sharing support policy on both participating and cooperation firms, especially on the performance of cooperation firms. As a further study, it is necessary to increase the objectiveness and accuracy of a research through verification of the interrelationships between firm statue and performance on the basis of more objective and quantitative data such a sales increase or R&D capability of cooperation firms.
Self-employed women are highly vulnerable to social risks like unemployment and poverty as job instability has increased in recent decades. Despite this, the Korean public policy focus has been on employees, not the self-employed. This may be closely linked to the legacy of the East Asian welfare model policy logic. Therefore, this study explores social risk levels by gender and employment status and examines the relation between social risks of self-employed women and the East Asian welfare model policy logic, through comparing-means analysis and ordered logit regression analysis using the 9th wave data of the Korea Welfare Panel Study Korea. The study yields evidence of divisions in social risk levels according to gender and employment status: that is, a gender difference, and a substantial gap between self-employed workers and regular employees. Furthermore, the findings of the study indicate that self-employed women — especially in small businesses — are more vulnerable to social risks than are self-employed men. This strongly supports the conclusion that the higher social risks of self-employed women in Korea are closely linked to the legacy of East Asian welfare model policy logic, which focuses on social protection for core workers and largely neglects women.
In this paper, an exploratory analysis study was conducted on establishing a strategy to utilize living labs to enhance the innovation of the energy sector. Through the previous research literature, it was possible to confirm the concept, essential components, innovation characteristics of living labs, and types of innovation issues in the energy sector as the theoretical background. Based on this, the case studies of energy living lab (8 overseas, 1 domestic) were analyzed focusing on the possibility of utilizing living lab as an approach to innovation issues in the energy sector, establishing a customized strategy for essential components of living lab and enhancing innovation. It was confirmed that the establishment of a customized strategy for the essential components of the living lab could be a driving force in enhancing innovation, and the Living Lab is effectively used as an approach method for innovation issues(demand management, supply technology, enhance R&D acceptance and promote commercialization, technology policies) in the energy sector. As a result of the case studies, the driving force of each living lab was derived from the viewpoint of contributing to innovation, and strategies for using the living labs for each energy innovation problem were established. This study is an exploratory and descriptive analytical study of the utilization strategy and value of the living lab model as an approach to innovation issues in the energy field, which can provide a living lab strategy framework that has not been tried in the past and enables living lab activation and network formation. It can also be considered to have academic, practical, and policy implications in that it can also contribute.
This study employs text mining techniques to compare user responses across various Over-The-Top (OTT) service platforms. The primary objective of the research is to understand user satisfaction with OTT service platforms and contribute to the formulation of more effective review strategies. The key questions addressed in this study involve identifying prominent topics and keywords in user reviews of different OTT services and comprehending platform-specific user reactions. TF-IDF is utilized to extract significant words from positive and negative reviews, while BERTopic, an advanced topic modeling technique, is employed for a more nuanced and comprehensive analysis of intricate user reviews. The results from TF-IDF analysis reveal that positive app reviews exhibit a high frequency of content-related words, whereas negative reviews display a high frequency of words associated with potential issues during app usage. Through the utilization of BERTopic, we were able to extract keywords related to content diversity, app performance components, payment, and compatibility, by associating them with content attributes. This enabled us to verify that the distinguishing attributes of the platforms vary among themselves. The findings of this study offer significant insights into user behavior and preferences, which OTT service providers can leverage to improve user experience and satisfaction. We also anticipate that researchers exploring deep learning models will find our study results valuable for conducting analyses on user review text data.
The K-POP market has become influential not only in culture but also in society as a whole, including diplomacy and environmental movements. As a result, various papers have been conducted based on machine learning to identify the success factors of idols by utilizing traditional data such as music and recordings. However, there is a limitation that previous studies have not reflected the influence of new media platforms such as Instagram releases, YouTube shorts, TikTok, Twitter, etc. on the popularity of idols. Therefore, it is difficult to clarify the causal relationship of recent idol success factors because the existing studies do not consider the daily changing media trends. To solve these problems, this paper proposes a data collection system and analysis methodology for idol-related data. By developing a container-based real-time data collection automation system that reflects the specificity of idol data, we secure the stability and scalability of idol data collection and compare and analyze the clusters of successful idols through a K-Means clustering-based outlier detection model. As a result, we were able to identify commonalities among successful idols such as gender, time of success after album release, and association with new media. Through this, it is expected that we can finally plan optimal comeback promotions for each idol, album type, and comeback period to improve the chances of idol success.
KIPS Transactions on Computer and Communication Systems
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v.10
no.10
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pp.261-268
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2021
Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.
Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.
This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the academic and economic level and oral parafunctional habits, emphasizing the need for the education of oral parafunctional habits, providing the basic data in order to accomplish correctly until the oral health of the oral maxillofacial region. From May 2013 till July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of 1, 2 grade of two high school located in Chungnam, Korea. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) the stress by class showed that grade 2 was higher than grade 1 in all areas. The stress of the school life (2.21) (p<0.01), interpersonal relationship (p<0.01), and own problem (p<0.05) showed the significant difference; 3) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral parafunctional habits all showed the significant difference (p<0.001). The correlation between the stress and the oral parafunctional habits showed a weak negative correlation as -0.30, and the stress of the school life, own problem, environment problem, and interpersonal relationship showed very strong correlations more than 0.7; 4) Fit measures test result of stress, academic level, and family economic level model all showed more than 0.9 in good of fit index, adjusted goodness of fit index, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral parafunctional habits.
Kang, Young-Soon;Han, Min Ho;Lee, Moon Hee;Hong, Su Hyun;Park, Heungsik;Jung, Jae-Chul;Lee, Jeongrai;Lee, Eun-Woo;Kang, Kyung Hwa;Kim, Cheol Min;Kim, Byung-Woo;Choi, Yung Hyun
Journal of Life Science
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v.23
no.11
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pp.1397-1403
/
2013
Fructus Sophorae, the dried ripe fruit of Styphnolobium japonicum (L.), is an herbal ingredient used in traditional Oriental medicine. This study was carried out to investigate the effects of Fructus Sophorae extracts (FSE) on immune modulation in a murine RAW 264.7 macrophage model. As immune response parameters, the production of prostaglandin $E_2$ ($PGE_2$) and tumor necrotic $factor-{\alpha}$ ($TNF-{\alpha}$) were evaluated. Our data revealed that FSE increased the macrophage activation and the production of $PGE_2$ and $TNF-{\alpha}$, which was consistently correlated with upregulation of cyclooxygenase-2 (COX-2) and $TNF-{\alpha}$ expression at both transcriptional and translational levels. On comparative cytokine protein array, FSE significantly increased several cytokines, which was associated with phosphorylation of mitogen- activated protein kinases (MAPKs), including extracellular signal-regulated kinase (ERK), p38 MAPK and c-Jun N-terminal kinase (JNK), and Akt in RAW 264.7 cells. However, each inhibitor of these molecules attenuated the FSE-induced $PGE_2$ production. These results indicate that FSE activated macrophages through the activation of MAPKs and phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathways in RAW 264.7 macrophages. These findings suggest that FSE may provide a promising source of an immunoenhancing agent.
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