• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.39-51
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• 2016

In accordance to rapid aging of population, the accidents of elderly pedestrian and pedestrian safety are becoming very important issues. In terms of smartphone technologies, older people are increasingly looking for useful and friendly ICT services that which can add a value on their silver life. This paper introduced a new IT-based service for elderly walking assist using a smart-phone accompanied by a wearable watch. We describe the functional requirements and a systems architecture model with an interface between a smart-phone and wearable watch. Moreover, this study attempted to verify what services are needed and to estimate elderly pedestrians' WTP (willingness to pay) for IT-based walking assistance device. A total of 189 elderly pedestrians were randomly surveyed through face-to-face interviews. The questionnaire consisted of 3 categories: (1) questions pertaining to socio-economic status, (2) 12 questions regarding walking attitudes, and (3) a question to measure WTP. With this gathered data, factor analysis and path model estimating were conducted. The results identified the elderly user requirements and the use-value of new innovative products for IT-based walking assistance services by two groups(latent elderly and elderly). The modeling result shows that elderly's service preference would increase the possibilities for the commercialization of IT-based walking device with improving their walking safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.95-111
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• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Genomics & Informatics
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• v.9 no.3
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• pp.121-126
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• 2011

Osteoarthritis (OA) is the most common degenerative joint disorder in the elderly population. To identify OA-associated genetic variants and candidate genes, we conducted a genome-wide association study (GWAS). A total 3,793 samples (476 cases: wrist + knee and 3317 controls) from a community-based epidemiological study were genotyped using the Affymetrix SNP 5.0. An intronic SNP (rs4789934) in the TIMP2 (tissue inhibitor of metalloproteinase-2) showed the most significance with OA (odd ratio [OR] = 2.06, 95% confidence interval [CI] = 1.52-2.81, p = $4.01{\times}10^{-6}$). Furthermore, a poly-morphism (rs1352677) in the NKAIN2 ($Na^+/K^+$ transporting ATPase interacting 2) was suggestively associated with OA (OR = 1.43, CI = 1.22-1.66, p = $7.01{\times}10^{-6}$). The present study provides new insights into the identification of genetic predisposing factors for OA.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.5
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• pp.261-275
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• 2024

In response to increasing economic uncertainty and the challenges posed by low birth rates and an aging population, the rapid growth of startups has become a crucial strategy for fostering economic development. In 2023, the Korean government introduced the "Startup Korea" initiative, aiming to attract top talent and capital into the domestic startup ecosystem and shift away from traditional government subsidies toward encouraging private capital investment. However, current national startup policies are limited by their concentration on the capital region and specific industries, raising concerns about the need for more regionally-tailored and sustainable policy approaches. This study seeks to analyze both national and regional entrepreneurial ecosystems, with a specific focus on Seoul, to propose long-term strategies for developing a sustainable and globally competitive entrepreneurial environment. Utilizing the Evidence-Informed Policy Making (EIP) framework, the study first conducted a literature review to analyze national startup policies, Seoul's policies, and the Startup Genome global ecosystem report. Following this, expert interviews and Delphi surveys were conducted with key stakeholders to gather comprehensive evidence. The data was then analyzed to identify key policy areas aligned with the entrepreneurial ecosystem's core components. Finally, policy recommendations were tailored to align with Seoul's unique vision and characteristics, offering sustainable growth strategies for the regional startup ecosystem.

• Management & Information Systems Review
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• v.35 no.2
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• pp.221-254
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• 2016

With increasing interest of health due to population aging, medical device industry is highlighted as a promising industry. However, Korea medical device industry is not enough market competitiveness compared to global company due to a narrow domestic market and a small company structure. In order to retain the national competitiveness, it is necessary that we have to derive a central technology and its trend. This study has predicted a central technology for medical device industrial using patent network analysis. The central technology is defined as a key technology that is connected to most other technologies and that significantly affects them. For the empirical study, we conducted social network analysis using covariance and correlation coefficient between IPC codes extracted from medical device patents, introduced by Jun(2012). A social network is a social structure of diverse items as well as of human beings. In this study, we set each medical device as a node in an SNA and analyze the Degree values between them. Also, Korea health industrial statistics system are utilized for verification of selected central technology. As a result, we found that the central technology is located on the medical device items, which are listed higher the amount of production. The central technology selected through the proposed methodology will provide a inspiration for establishment of R&D policy.

• Korean Journal of Social Welfare Studies
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• v.42 no.3
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• pp.267-290
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• 2011

This research attempts to analyze the effects of demographic factors, socioeconomic factors, health behaviors and social/familial supports on health inequalities among Korean elderly. For this end, this study adopts the multiple linear regression analysis to process data on population aged over 65 contained in 'The Third Korea Welfare Panel Study' published in 2008. The following are the results. First, the less educated they are, the smaller income they earn, the less they drink, the less satisfied with relationships with their family members, the more they turn out to feel depressed. Second, the less educated they are, the smaller income they earn, the less they drink, the less they are satisfied with relationship with family members, the more they benefit from social welfare services, the worse they turn out to rate their health. Based on these findings, three following suggestions could be forwarded. First, vulnerable aged groups including female elderly, low-income elderly, less-educated elderly need customized social supports. Second, new social policy for households is required to enhance elderly people's satisfaction with their family relationships with the rapid trend of a growing number of nuclear families and aging. Third, social welfare service programs need to be reevaluated to enhance their function for the aged.

• 한국체육학회지인문사회과학편
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• v.57 no.4
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• pp.375-386
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• 2018

Due to the rapid increase of the elderly population in Korea, there is a growing interest in 'Healthy Aging.' In this trend, it is important to identify the relationship between their lifestyle factors and quality of life. The purpose of this study was to identify the association of physical activity level, sedentary behavior and health-related quality of life (HRQoL) among Korean older adults. A total of 4,589 older adults at the Sixth and Seventh National Health and Nutrition Examination Survey was analyzed. The results showed that better HRQoL was observed among physically active older female, which was more evident among physically active female with central obesity while no such relationship was observed among older male. On the other hand, higher sedentary time was associated with lower HRQoL in both male and female subjects. Our analyses indicated that central obesity was closely related with HRQoL regardless of their physical activity levels in female subjects. Further analyses investigating association between sub-dimension of HRQoL and sub-domain of physical activity showed that higher transport physical activity was associated with better anxiety/depression score and higher sedentary time was associated with poorer score on mobility, usual activities among male and mobility, self-care, usual activity and anxiety/depression among female. Our finding suggests that physical activity level, sedentary behavior and central obesity associated with HRQoL.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.463-493
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• 2018

As the population structure of Korea changes with the increase of single households and elderly households, this may have effect on domestic energy consumption pattern. Our study analyzes whether the energy consumption of single and elderly households are distinguishable from those of general households. For empirical analysis, Household Energy Standing Survey panel data and regional fixed effect model are employed. The result strongly shows that single households consume more energy than other households. The consumption of single households from 40s to 60s was the highest. On the other hand, the effect of aging was different from energy sources. Electricity consumption of elderly household was more than other age groups, while oil consumption of elderly household was less than others. Gas and total energy consumptions turned out to be not much different among different age groups.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.4
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• pp.21-29
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• 2014

In terms of quality of life, leisure and health have become important issues with increasing incomes and decreasing working hours in Korea. This study empirically investigates the effects of urban open space on outdoor leisure activities, emphasizing that parks, river banks, and physical activity sites can provide opportunities such as walking, jogging, stretching, and cycling, free of charge to all residents. Based on 2010 sample survey data on leisure activities, multiple regression model as well as hierarchical linear model are estimated, taking account of both individual characteristics on demand and environmental/areal factors on supply side, including open space. Major findings include: first, urban open space significantly increases residents' outdoor leisure activities, second, the effect is more significant for the elderly and third, the effect is more valid for those with relatively low incomes and less education. These results imply that urban open space could be available as a local public good to cope with population aging and to realize health city and social welfare, since this space is not only a leisure place but also public health and welfare facilities.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.