• Journal of Pharmacopuncture
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• v.25 no.1
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• pp.15-23
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• 2022

Objectives: This study aims to develop a community care model in traditional Korean medicine (TKM) by developing a community care participation model for the health of the elderly and deriving tasks to implement it. Methods: This study implemented a group interview with experts. A fact-finding survey was conducted targeting 16 local governments that are implementing a leading project to identify the status of TKM service provision and welfare service linkage in all regions. An expert group interview (FGI) targeted public and private sector experts for each job role, the former represented by those in charge of the central government's health care policy and administrative delivery system, and the latter by professors majoring in social welfare, professors majoring in health, and local TKM societies. After forming the expert groups, three expert group interviews were conducted. Results: Through collective interviews with experts, a model for providing TKM and welfare services in community integrated care was derived by dividing it into local and central government levels. The strategies and tasks for promoting TKM-oriented health welfare services were derived from 3 strategies, 8 tasks, and 20 detailed tasks. Conclusion: The core direction of the TKM health care model is the region-centered provision of TKM and welfare services. To this end, policy support for the use and linkage of health care service resources is required at the central government level, and linkage and provision of health welfare services centered on TKM are necessary through linkage and convergence between service subjects and between government health care projects.

• Korean Journal of Childcare and Education
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• v.20 no.2
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• pp.169-194
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• 2024

Objective: The purpose of this study is to develop a child-care support policy strategy in response to the decrease in the population of children aged 0-5 years. This will be achieved by collecting opinions from a panel of experts on child-care support policies through a Delphi survey. Methods: To achieve the purpose of this study, a panel of 20 experts in child-care policy was selected, and a Delphi survey was conducted over three sessions. Data collected through the Delphi survey underwent analysis, including frequency analysis, descriptive statistics, content validity ratio, coefficient of variation, agreement, and convergence. Data processing was carried out using Excel 2016 and SPSS 26.0. Results: As a result of the study, a child-care support policy strategy addressing the decrease in the population of children aged 0-5 years was developed, comprising three policy areas, nine policy tasks, and 38 detailed policy tasks. Conclusion/Implications: Based on these results, it is anticipated that the study will not only enable the preparation of a strategy for child-care support policy to address the decrease in the population of children aged 0-5 years but also offer significant implications for shaping the direction of child-care support policy in alignment with the common good.

• The KIPS Transactions:PartA
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• v.10A no.3
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• pp.181-188
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• 2003

We propose a heuristic on-line scheduling algorithm for the IRIS (Increasing Reward with Increasing Service) tasks, which has low computation complexity and produces total reward approximated to that of previous on-line optimal algorithms. The previous on-line optimal algorithms for IRIS tasks perform scheduling on all tasks in a system to maximize total reward. Therefore, the complexities of these algorithms are too high to apply them to practical systems handling many tasks. The proposed algorithm doesn´t perform scheduling on all tasks in a system, but on (constant) W´s tasks selected by a predefined task selection policy. The proposed algorithm is based on task selection policies that define how to select tasks to be scheduled. We suggest two simple and intuitive selection policies and a generalized selection policy that integrates previous two selection policies. By narrowing down scheduling scope to only W´s selected tasks, the computation complexity of proposed algorithm can be reduced to O(Wn). However, simulation results for various cases show that it is closed to O(W) on the average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• 수도
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• s.62
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• pp.3-21
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• 1993

• Korean Journal of Human Ecology
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• v.11 no.1
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• pp.1-11
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• 2002

This paper was written to present the recent trend of juvenile delinquency within the context of family system and to provide the role and tasks of Family Science in the area of Probation and Parole System in Korea. Since Family Science provides knowledges and skills to help for both adolescents and their families by improving interactional functions, the role of Family Science was focusing more on comprehensive and integrated perspectives. The tasks of Family Science, especially, in family life education, family therapy, and family policy, were as follows: 1) to prevent recurrence of misbehavior by family life education. 2) to draw the cooperation with the judicial system. 3) to provide the advanced course for volunteers. 4) to perform crime prevention education for normal adolescents. 5) to join the official education for civil service personnel. 6) to manage group-homes after the completion of the probation period.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.635-641
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• 2022

Although social economy organizations have achieved quantitative growth in various types and fields, they have been mainly promoted by the government, and there is still room for qualitative improvement, such as institutional reorganization, support systems and support methods, compared to advanced countries. In this study, the problems of social economy organizations, the current status and actual analysis of social economy organizations, the policy delivery system, obstacles to the development of social economy organizations, and problems of activation, etc. were reviewed through previous studies. Through this, policy directions and tasks for revitalization of future social economy organizations were presented. As a result, the policy direction for revitalization of social economy organizations requires private and local government initiatives, expansion of fields, customized support for the creation of a growth ecosystem, and various linkage cooperation. Organizational capacity development and education, reinforcement of various linkage cooperation systems, creation of an investment ecosystem, and joint market development are necessary.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.spc1
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• pp.30-44
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• 2024

The DMAIC methodology, which is most familiar to battery production system developers, is partially inadequate in its conformity to utilize battery production system tasks, so it is necessary to improve the function and structure of the methodology, but many battery production system developers use the DMAIC method based on experience, causing side effects such as confusion, delay in tasks, and insufficient performance during tasks. Accordingly, we intend to conduct an empirical study to improve the "efficiency improvement and conformity evaluation method" so that the DMAIC methodology can be used more reasonably and easily. Using the three-stage research model, we derive components that affect conformity through literature and questionnaire surveys in the first stage, use relational characteristics between components in the second stage to confirm the effect on conformity, and use the relational characteristics in the third stage to confirm the possibility of improving efficiency by applying them to the DMAIC methodology in actual cases. Finally, the "Conformity Assessment Index (CAI) equation" based on relational characteristics is established to enable effective conformity evaluation and continuous improvement.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.40-49
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• 2019

Reinforcement learning has been applied to various problems in robotics. However, it was still hard to train complex robotic manipulation tasks since there is a few models which can be applicable to general tasks. Such general models require a lot of training episodes. In these reasons, deep neural networks which have shown to be good function approximators have not been actively used for robot manipulation task. Recently, some of these challenges are solved by a set of methods, such as Guided Policy Search, which guide or limit search directions while training of a deep neural network based policy model. These frameworks are already applied to a humanoid robot, PR2. However, in robotics, it is not trivial to adjust existing algorithms designed for one robot to another robot. In this paper, we present our implementation of Guided Policy Search to the robotic arms of the Baxter Research Robot. To meet the goals and needs of the project, we build on an existing implementation of Baxter Agent class for the Guided Policy Search algorithm code using the built-in Python interface. This work is expected to play an important role in popularizing robot manipulation reinforcement learning methods on cost-effective robot platforms.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.73-83
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• 2013

Effective policy coordination is necessary function for successful policy implementation. Korean government, for effective policy coordination, had developed the policy coordination system in the Prime Minister's Office. The Prime Minister's Office had successfully implemented policy coordination tasks during 35 years. The Prime Minister's Office had systemized policy coordination institutions and developed organizational capacity for effective coordination, and utilized various strategies, such as power, persuasion, and technical strategy. Based on the system, capacity, and various strategies, ]the Prime Minister's Office had achieved 90% of the asked policy conflict problems and completed 85% of coordination tasks within 6 months. The purpose of this study is for reviewing the performance of successful coordination of Prime Minister's Office and searching for some implications. For the study, the author analyzed the 429 policy conflict problems which had been recorded in 8 Policy Coordination White Papers.