• Journal of Korean Academy of Nursing
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• v.53 no.5
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• pp.525-537
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• 2023

Purpose: This study aimed to develop and test a reward scale for hospital nurses. Methods: The initial items were identified through a literature review and focus group interviews with ten hospital nurses. The content validity of the items was evaluated by ten experts. Fifty-one items were derived from the pilot survey. Four hundred eighty-eight nurses participated in the study: 248 for exploratory factor analysis (EFA) and 240 confirmatory factor analysis (CFA). Data were analyzed using item analysis, EFA, CFA, convergent validity, known-group validity, and internal consistency using IBM SPSS Statistics 29.0 and IBM SPSS AMOS 29.0. Results: The final scale consisted of 31 items and eight factors (decent wage, opportunity to grow and develop, support for special situations, various benefits, flexibility of work, job-related achievement, reflecting career and performance, and recognition), which explained 67.3% of the total variance. The eight-subscale model was validated by CFA. Convergent validity was evaluated by analyzing correlation with intention to leave (r = - .63, p < .001) and job satisfaction (r = .54, p < .001). The known-group validity was evaluated by comparing the reward scales according to age, clinical career, income level and hospital type. The scale was found to be reliable with a Cronbach's α of .89. Conclusion: Both the validity and reliability of the reward scale for hospital nurses are verified, which can enhance the understanding of the range of rewards and may assist nurse managers in establishing an effective reward system.

• Journal of Agricultural Extension & Community Development
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• v.1 no.2
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• pp.147-163
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• 1994

Agricultural extension programs in Korea had focused mainly on increased production, and the biggest pride of extension was the achievement of rice self-sufficency in 1970s and abundant vegetable and animal production in 1980s. Farming in Korea has changed rapidly in recent years and extension system on commercialized crops have not been satisfactorily developed to mete farmers` demands. Facing the emerging challenges of international competition and trade liberalization for agricultural commodities, the goals of extension should be focused on increased income and the welfare of coral communities. The transfering of agricultural extension educator from central government jobs to local ones has emerged recently under the trends of localization which resulted unstable job environment of extension educator. Intensive pre-service and in-service training of extension workers on current and advanced techologies are essential to upgrade the quality of extension services, and the future directions for professional development of agricultural extension educators in Korea were suggested as follows: 1. Establishing a national network on agricultural extension system to promote exchanges of information among counties and provinces, to conduct meetings and to publish information on agricultural extension. 2. Determining the implications of recent national and global trends on agricultural extension, and strenthening communication at local, national and international levels for an effective extension system in the era of localization, internationalization and globalization; 3. Recognizing the effect of number and quality of extension staff on the impact of extension and providing opportunities development and advancement of extension personnel through education, training, incentives and rewards; 4. Giving a higher priority to agricultural extension in national policies in order to ensure the adequacy of budgetary support and recognition of importance of extension by the ministries concerned and mass communications.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.353-363
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• 2008

A multi-agent system has a longer learning period and larger state-spaces than a sin91e agent system. In this paper, we suggest a new method to reduce the learning time of Nash Q-learning in a multi-agent environment. We apply Macro-actions to Nash Q-learning to improve the teaming speed. In the Nash Q-teaming scheme, when agents select actions, rewards are accumulated like Macro-actions. In the experiments, we compare Nash Q-learning using Macro-actions with general Nash Q-learning. First, we observed how many times the agents achieve their goals. The results of this experiment show that agents using Nash Q-learning and 4 Macro-actions have 9.46% better performance than Nash Q-learning using only 4 primitive actions. Second, when agents use Macro-actions, Q-values are accumulated 2.6 times more. Finally, agents using Macro-actions select less actions about 44%. As a result, agents select fewer actions and Macro-actions improve the Q-value's update. It the agents' learning speeds improve.

• Molecules and Cells
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• v.41 no.7
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• pp.646-652
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• 2018

Neurodegeneration can result in memory loss in the central nervous system (CNS) and impairment of taste and smell in the peripheral nervous system (PNS). The neurodegeneration seen in Parkinson's disease (PD) is characterized by functional loss of dopaminergic neurons. Recent studies have also found a role for dopaminergic neurons in regulating taste memory rewards in insects. To investigate how taste memories and sugar sensitivity can be affected in PD, we utilized the $DJ-1{\beta}$ mutant fruit fly, $DJ-1{\beta}^{ex54}$, as a PD model. We performed binary choice feeding assays, electrophysiology and taste-mediated memory tests to explore the function of the $DJ-1{\beta}$ gene in terms of sugar sensitivity as well as associative taste memory. We found that PD flies exhibited an impaired ability to discriminate sucrose across a range of sugar concentrations, with normal responses at only very high concentrations of sugar. They also showed an impairment in associative taste memory. We highlight that the taste impairment and memory defect in $DJ-1{\beta}^{ex54}$ can be recovered by the expression of wild-type $DJ-1{\beta}$ gene in the dopaminergic neurons. We also emphasized the role of dopaminergic neurons in restoring taste memory function. This impaired memory property of $DJ-1{\beta}^{ex54}$ flies also allows them to be used as a model system for finding supplementary dietary foods that can improve memory function. Here we provide evidence that the associative taste memory of both control and $DJ-1{\beta}^{ex54}$ flies can be enhanced with dietary supplementation of the medicinal plant, omija.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1095-1100
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• 2013

Carbon dioxide is a major cause for which accelerates Global Warming. Therefore several countries are working on the project recommended to use a bicycle instead of the car when you move to the nearby destination in an effort to reduce the emissions of carbon dioxide. In this paper, It was developed to measure the greenhouse gas reduction using Bluetooth Sensor Node by riding a bicycle instead of a car and management system in order to authenticate the riding record. The developed application provides various information such as individual bicycle mileage, greenhouse gas reductions, bicycle riding path, the number of planted ginkgo trees. This proposed system is expected to be helpful to green house gas emission reduction because the usage rate of bicycle will increase if government combine ways to offer people rewards such as pin money or tax breaks for people who take advantage of the bicycle with the project.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.763-777
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• 2021

Information security started as an IT operation process and is now recognized as an important issue of information technology, and each international organization is newly defining the concept. Information security itself is a new combination of IT technologies, a set of technologies and a technology area. As IT outsourcing becomes common in many public sectors, SLAs are introduced to evaluate the level of IT services. In the area of information security, many studies have been conducted on the derivation and selection of SLA performance indicators, but it is difficult to find a way to apply the performance indicators to service level evaluation and performance systems. This thesis conducted a study on the application of a service evaluation system for information security performance indicators based on the public sector and a performance system including compensation regulations. It presents standards and rewards(incentive and penalty) that define expectation and targets of performance indicators that take into account the environment and characteristics of a specific public sector, and defines appropriate SLA costs. It proposes a change plan for the organizational structure for practical SLA application and service level improvement.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.151-175
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• 2013

This study investigates the potential components for academic research collaboration, and the factors that make it possible to achieve higher academic productivity. The components include collaboration factors and a collaboration model. We use two major collaboration factors to develop a framework for understanding the mechanisms that influence academic research collaborations: motivational factors and mediating factors. Motivational factors include self-motivation and trust whereas mediating factors are collaboration orientation and peer support. We analyze the effect for use of e-collaboration with research performance, reward, and satisfaction with e-research output. A survey of academicians was conducted, and by using the factor analysis and the structural equation model with SPSS 20 AMOS, we illustrate the possible influence of these factors on research performance and satisfaction. We discovered that both motivational and mediating factors play important roles on the success of academic research. This study offers several implications for academicians. We develop a parsimonious research model, which is related to e-collaboration in academic research. This unique model offers academicians to achieve good publication output from the research team. The motivational factor, self-motivation and trust, are important factors which has received positive impact of mediating factor collaboration orientation and peer support. Our research sheds light on the crucial factors for use of e-collaboration which offer the ultimate effect on performance and satisfaction with e-research output. Satisfaction motivates people to work more and more on the field of their interest, thereby influencing the performance of academicians. Rewards should be distributed according to performance of the individual, which will motivate the person to become more enthusiastic for his work of interest. Our evidence suggests that in understating the collaborative process, one must account for the context in which the collaboration occurs, the motivation of the collaborators, the scope and nature of the project, the roles and activities undertaken, and interpersonal processes such as trust. Researchers' motivations for engaging in collaboration were both instrumental and intrinsic.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.229-234
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• 2019

This study is an empirical study to examine how the family-friendly corporate culture affects organizational commitment and job performance for ICT companies in Korea. Therefore, the purpose of the study is to investigate the effects of family-friendly culture of ICT companies on the organizational commitment and job performance of their employees. To this end, the impacts of internal factors of family-friendly corporate culture on their organizational commitment and job performance of the employees of ICT companies in South Korean are empirically analyzed. And the findings of the empirical investigation are as follows: Family-friendly Organizational culture and Family-Friendly Welfare System have positive effects on the organizational commitment, and Organizational commitment, in return, has positive effects on the job performance. But the Family-friendly working environment is found to have NO significant effects on the Organizational commitment. These results confirm the characteristics of workers who prefer family-friendly welfare systems with economic rewards rather than formal family-friendly programs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.