• 가정과삶의질연구
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• 제19권1호
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• pp.253-268
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• 2001

This study is designed to extent the investigation of the Kyongbuk Womens policy the area of family life and womens economic activity. Results indicated that the primary barriers of getting a job for married women was child rearing and the diffency of working information. On the family life, communication patterns were contributed to the problem of the relationship between child and parent, and spouse relationship. And also, school violence was founded the hot problem. The results underscore the importance of child rearing support system, and affirmative action in womens employment enviroment, Family Life Educator and Family Counselor.

• KIEAE Journal
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• 제13권3호
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• pp.3-13
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• 2013

As climate change is increasingly recognised as an important global problem, a wide variety of policies and measures are emerging at global and local level to deal with the challenges from the anthropogenic global warming. While national and inter-national efforts characterized by limiting GHG emissions shows very little progress because of their expanse spatial scale and complicated political situations, local efforts have the potentials to ensure effective implementation, monitoring and continual improvement. In the context of local-scale climate policy, the city of Portland is known as one of the best leading cities for its progress of implementing climate change strategies. This paper will briefly discuss the city's efforts to solve the climate change problem and its achievements. The latest climate action plan is selected for the analysis on the followings; the framework of the action plan, the types of implementation methods, and the coordinating agencies. The progress status of each action plans is also reviewed. The purpose of this paper is to describe the main characteristics of the climate action plans and their implications from the intensive analysis on the city of Portland's case.

• 식품과학과 산업
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• 제49권3호
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• pp.12-16
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• 2016

• 보건행정학회지
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• 제26권1호
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• pp.79-91
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• 2016

'Health in All Policies' is a new strategy for governance for health in 21st century. The evolution of health promotion has affected the creation of the strategy through the efforts to tackle health inequalities by addressing social determinants of health. More concern about health inequalities, involving wider policy areas, and higher level of institutionalization distinguish the strategy from the old intersectoral collaboration such as intersectoral action for health and healthy public policy. Making intersectoral collaboration the mainstream of policy making is important to address integrated policy agendas such as 'Health in All Policies' and 'Sustainable Development Goals.' Political leadership and interpersonal skills are also required to strengthen the capacity of public health sector for implementing 'Health in All Policies' in local, national, and international circumstances.

• 한국공간구조학회논문집
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• 제21권2호
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• pp.41-48
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• 2021

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Journal of Radiation Protection and Research
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• 제49권1호
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• pp.40-49
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• 2024

Background: This study aimed to prioritize policy measures to improve radiation safety management in medical institutions using the analytic hierarchy process. Materials and Methods: It adopted three policy options-engineering, education, and enforcement-to categorize safety management measures, the so-called Harvey's 3Es. Then, the radiation safety management measures obtained from the current system and other studies were organized into action plan categories. Using the derived model, this study surveyed 33 stakeholders of radiation safety management in medical institutions and analyzed the importance of each measure. Results and Discussion: As a result, these stakeholders generally identified enforcement as the most important factor for improving the safety management system. The study also found that radiation safety officers and medical physicists perceived different measures as important, indicating clear differences in opinions among stakeholders, especially in improving quality assurance in radiation therapy. Hence, the process of coordination and consensus is likely to be critical in improving the radiation safety management system. Conclusion: Stakeholders in the medical field consider enforcement as the most critical factor in improving their safety management systems. Specifically, the most crucial among the six specific action plans was the "reinforcement of the organization and workforce for safety management," with a relative importance of 25.7%.

• 산업진흥연구
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• 제1권1호
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• pp.41-49
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• 2016

본 합리적 행동이론(TRA)과 기술수용이론 (TAM)을 기반으로, SMEs가 벤처지원정책을 수용하는 요인이 무엇인지를 밝히고, 정부가 효율적 방법으로 정책 지원하고 있는지를 알아보며, 지속성의 관점에서 SMEs를 위한, 효율적인 벤처정책 지원 방향을 제시하고 있다. 주요 결과를 살펴보면, 첫째, Experience가 Ease of Use에 영향이 있었고, 둘째, EASE of Use가 Usefulness는 영향이 있지만, Intention to Use에 대하여 영향이 없었으며, 셋째, Usefulness가 Intention to Use 에 직접적 매우 강한 영향을 미치고 있을 뿐 아니라, 다른 많은 변수를 매개하고 있다는 것을 알 수 있다. 한편, 정책 수용 의지 (Intention to use)에 영향을 미치는 요인을 분석한 결과, Output Quality가 Usefulness에 영향을 미치고 있음을 알 수 있었다. 이는 정책수행의 결과가 선택하고 수행 할 때는 기업 입장에서 이해득실에 대한 많은 것을 고려 하고 있는 지극히 이성적으로 행동하는 기업이라는 것을 알 수 있다.

• 인터넷정보학회논문지
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• 제22권4호
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• pp.13-28
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• 2021

강화학습은 한 환경에서 에이전트가 정책에 따라 액션을 취하고 보상 함수를 통해 액션을 평가 및 정책 최적화 과정을 반복하는 Closed-Loop 구조로 이루어진 알고리즘이다. 이러한 강화학습의 주요 장점은 액션의 품질을 평가하고 정책을 지속적으로 최적화 하는 것이다. 따라서, 강화학습은 지능형 시스템, 자율제어 시스템 개발에 효과적으로 활용될 수 있다. 기존의 강화학습은, 단일 정책, 단일 보상함수 및 비교적 단순한 정책 업데이트 기법을 제한적인 문제에 대해 제시하고 적용하였다. 본 논문에서는 구성요소의 복수성을 지원하는 확장된 강화학습 모델을 제안한다. 제안되는 확정 강화학습의 주요 구성 요소들을 정의하고, 그들의 컴퓨팅 모델을 포함하는 정형 모델을 제시한다. 또한, 이 정형모델을 기반으로 시스템 개발을 위한 설계 기법을 제시한다. 제안한 모델을 기반으로 자율 최적화 자동차 내비게이터 시스템에 적용 및 실험을 진행한다. 제시된 정형 모델과 설계 기법을 적용한 사례연구로, 복수의 자동차들이 최적 목적지에 단 시간에 도착할 수 있는 진화된 내비게이터 시스템 설계 및 구현을 진행한다.

• 수산해양교육연구
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• 제15권1호
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• pp.81-100
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• 2003

It is undeniable that IUU Fishing are threatening so many legal fishermen' economic livelihood, negatively impact on conservation and protection of the fishery stock and ecosystem itself. Especially, negative impact of IUU Fishing resulted from the increasing fishery activities on the high seas. The Korea case of Coastal and Off-shore Fisheries, difficulties in conserving and controlling the fishery stock was brought about. Simultaneously, it is the fact that there are so many damage such as the reduction of fish Stock management program's effect, dissatisfaction of legal fishermen, over-exploiting of fish stock. Related with this kind of problem, FAO had adopted "International Plan of Action to Prevent, Deter and Eliminate Illegal, Unreported and Unregulated Fishing(2001)". From this reason, Korea also needs to make actual efforts to prevent IUU Fishing. i.e. each nation should develop Korea action plan by Feb. 2004 and impliment it, report on implementation toward FAO. This Paper will review the definition of the IUU stipulated by "International Plan of Action on Illegal, Unreported and Unregulated Fishing" and study Korea cases of the IUU fishing. Finally, the analysis of Korea's implementation will be done, centering around the contents stated on the International Action Plan. The significance of this paper is to grope the political countermeasures against international movement of the IUU fishing prevention.