• Journal of Fisheries and Marine Sciences Education
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• v.21 no.2
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• pp.306-324
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• 2009

The purpose of this study is to analyze green growth issues such as employment, education and training, social capital and nature's standing right from the complementary perspective between natural environment conservation and economic growth. Green growth can be defined as a growth which lowers an increasing rate of entropy and at the same time improves our living standard. Green growth paradigm requires a quite amount of understanding the laws of thermodynamics and the uncertainty principle as the highest orders which regulate our overall socio-economic behaviors. They suggest that socio-economic growth is a mere transformation process of natural energy from one form to another and they increases natural manmade entropy over time. The most important issue of green growth policy may be a problem concerning employment and/or unemployment since green growth may induce inevitable movement of resources from the existing industries to the green sector. In particular, green industries will demand more highly specialized manpower than the existing ones. Without a well-designed new training education system and social capital accumulation toward environmental concerns, green growth may accompany a substantial amount of structural involuntary frictional unemployment. This may increase not only wealth-distribution disparity but also political instability. In order to achieve harmonious green growth, we should recognize that there are important complementary relationships between green and growth. Our society should also be able to innovate the existing educational system to accumulate social capital, to create a new sharing system, and to admit nature's standing right. Although the 2003 lawsuit case of Korean Salamander in Cheonseong Mountain went against plaintiff, it would provide apparently our society with a way of green development ahead.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1165-1170
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• 2022

In WSNs, a clustering algorithm groups sensor nodes on a unit called cluster and periodically selects a cluster head (CH) that acts as a communication relay on behalf of nodes in each cluster for the purpose of energy conservation and relay efficiency. Meanwhile, attack techniques also have emerged to intervene in the CH election process through compromised nodes (inside attackers) and have a fatal impact on network operation. However, existing countermeasures such as encryption key-based methods against outside attackers have a limitation to defend against such inside attackers. Therefore, we propose a statistical detection method that detects abnormal CH election behaviors occurs in a WSN cluster. We design two attack methods (Selfish and Greedy attacks) and our proposed defense method in WSNs with two clustering algorithms and conduct experiments to validate our proposed defense method works well against those attacks.

• Journal of Korean Academy of Nursing Administration
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• v.6 no.3
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• pp.357-374
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• 2000

The purpose of this study was to validate knowledge outcomes included Nursing Outcomes Classification(NOC) developed by Johnson and Maas at the University of Iowa. A sample of 71 nurse experts working in university affiliated hospitals participated in this study. They were asked to rate indicators that examplified the outcomes on a scale of 1(indicator is not all characteristic) to 5(indicator is very characteristic). A questionnaire with an adaptation of Fehring's methodology was used to establish the content validity of outcomes. The results were as follow: 1. All indicators were considered to be 'supporting' and no indicators were considered to be 'nonsupporting'. 2. 'Knowledge: Treatment Regimen' attained and OCV score of 0.816 and was the highest OCV score among outcomes. 3. 'Knowledge: Energy Conservation' attained an OCV score of 0.748 and was the lowest OCV score among abuse outcomes. 4. 'Knowledge: Breastfeeding' attained an OCV score of 0.790 and was the highest indicator was 'description of benefits of breastfeeding'. 5. 'Knowledge: Child Safety' attained an OCV score of 0.778 and was the highest indicator was 'demonstration of first aids techniques'. 6. 'Knowledge: Diet' attained an OCV score of 0.779 and was the highest indicator was 'performance of self-monitoring activities'. 7. 'Knowledge: Disease Process' attained an OCV score of 0.815 and was the highest indicator was 'description of signs and symptoms'. 8. 'Knowledge: Health Behaviors' attained an OCV score of 0.800 and was the highest indicator was 'description of safe use of prescription drugs'. 9. 'Knowledge: Health Resources' attained an OCV score of 0.794 and was the highest indicator was 'description of need for follow-up care'. 10. 'Knowledge: Infection Control' attained an OCV score of 0.793 and was the highest indicator was 'description of signs and symptoms'. 11. 'Knowledge: Medication' attained an OCV score of 0.789 and was the highest indicator was 'description of correct administration of medication'. 12. 'Knowledge: Personal Safety' attained an OCV score of 0.804 and was the highest indicator was 'description of measures to reduce risk of accidental injury'. 13. 'Knowledge: Prescribed Activity' attained an OCV score of 0.810 and was the highest indicator was 'proper performance of exercise'. 14. 'Knowledge: Substance Use Control' attained an OCV score of 0.809 and was the highest indicator was 'description of signs of dependence during substance withdrawl'. 15. 'Knowledge: Treatment Procedure(s)' attained an OCV score of 0.795 and was the highest indicator was 'description of appropriate action for complications'. 16. 'Knowledge: Treatment Regimen' attained an OCV score of 0.816 and was the highest indicator was 'description of self-care responsibilities for emergency situations'. More outcomes need to be validated and outcomes sensitive to Korean culture need to be developed.